merge

src/backend/base/langflow/alembic/script.py.mako

@@ -11,6 +11,7 @@ from alembic import op
 import sqlalchemy as sa
 import sqlmodel
 from sqlalchemy.engine.reflection import Inspector
+from langflow.utils import migration
 ${imports if imports else ""}
 
 # revision identifiers, used by Alembic.
@@ -22,13 +23,9 @@ depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
 
 def upgrade() -> None:
     conn = op.get_bind()
-    inspector = Inspector.from_engine(conn)  # type: ignore
-    table_names = inspector.get_table_names()
     ${upgrades if upgrades else "pass"}
 
 
 def downgrade() -> None:
     conn = op.get_bind()
-    inspector = Inspector.from_engine(conn)  # type: ignore
-    table_names = inspector.get_table_names()
     ${downgrades if downgrades else "pass"}

src/backend/base/langflow/alembic/versions/012fb73ac359_add_folder_table.py

@@ -48,10 +48,12 @@ def upgrade() -> None:
         with op.batch_alter_table("folder", schema=None) as batch_op:
             batch_op.create_index(batch_op.f("ix_folder_name"), ["name"], unique=False)
 
-    if "folder_id" not in inspector.get_columns("flow"):
-        with op.batch_alter_table("flow", schema=None) as batch_op:
+    column_names = [column["name"] for column in inspector.get_columns("flow")]
+    with op.batch_alter_table("flow", schema=None) as batch_op:
+        if "folder_id" not in column_names:
             batch_op.add_column(sa.Column("folder_id", sqlmodel.sql.sqltypes.GUID(), nullable=True))
             batch_op.create_foreign_key("flow_folder_id_fkey", "folder", ["folder_id"], ["id"])
+        if "folder" in column_names:
             batch_op.drop_column("folder")
 
     # ### end Alembic commands ###
@@ -62,11 +64,13 @@ def downgrade() -> None:
     inspector = Inspector.from_engine(conn)  # type: ignore
     table_names = inspector.get_table_names()
     # ### commands auto generated by Alembic - please adjust! ###
-    if "folder_id" in inspector.get_columns("flow"):
-        with op.batch_alter_table("flow", schema=None) as batch_op:
+    column_names = [column["name"] for column in inspector.get_columns("flow")]
+    with op.batch_alter_table("flow", schema=None) as batch_op:
+        if "folder" not in column_names:
             batch_op.add_column(sa.Column("folder", sa.VARCHAR(), nullable=True))
-            batch_op.drop_constraint("flow_folder_id_fkey", type_="foreignkey")
+        if "folder_id" in column_names:
             batch_op.drop_column("folder_id")
+            batch_op.drop_constraint("flow_folder_id_fkey", type_="foreignkey")
 
     indexes = inspector.get_indexes("folder")
     if "ix_folder_name" in [index["name"] for index in indexes]:

src/backend/base/langflow/alembic/versions/1c79524817ed_add_unique_constraints_per_user_in_.py

@@ -0,0 +1,42 @@
+"""Add unique constraints per user in folder table
+
+Revision ID: 1c79524817ed
+Revises: 3bb0ddf32dfb
+Create Date: 2024-05-29 23:12:09.146880
+
+"""
+
+from typing import Sequence, Union
+
+from alembic import op
+from sqlalchemy.engine.reflection import Inspector
+
+# revision identifiers, used by Alembic.
+revision: str = "1c79524817ed"
+down_revision: Union[str, None] = "3bb0ddf32dfb"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    constraints_names = [constraint["name"] for constraint in inspector.get_unique_constraints("folder")]
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table("folder", schema=None) as batch_op:
+        if "unique_folder_name" not in constraints_names:
+            batch_op.create_unique_constraint("unique_folder_name", ["user_id", "name"])
+
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    constraints_names = [constraint["name"] for constraint in inspector.get_unique_constraints("folder")]
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table("folder", schema=None) as batch_op:
+        if "unique_folder_name" in constraints_names:
+            batch_op.drop_constraint("unique_folder_name", type_="unique")
+
+    # ### end Alembic commands ###

src/backend/base/langflow/alembic/versions/3bb0ddf32dfb_add_unique_constraints_per_user_in_flow_.py

@@ -0,0 +1,54 @@
+"""Add unique constraints per user in flow table
+
+Revision ID: 3bb0ddf32dfb
+Revises: a72f5cf9c2f9
+Create Date: 2024-05-29 23:08:43.935040
+
+"""
+
+from typing import Sequence, Union
+
+from alembic import op
+from sqlalchemy.engine.reflection import Inspector
+
+# revision identifiers, used by Alembic.
+revision: str = "3bb0ddf32dfb"
+down_revision: Union[str, None] = "a72f5cf9c2f9"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    # ### commands auto generated by Alembic - please adjust! ###
+    indexes_names = [index["name"] for index in inspector.get_indexes("flow")]
+    constraints_names = [constraint["name"] for constraint in inspector.get_unique_constraints("flow")]
+    with op.batch_alter_table("flow", schema=None) as batch_op:
+        if "ix_flow_endpoint_name" in indexes_names:
+            batch_op.drop_index("ix_flow_endpoint_name")
+            batch_op.create_index(batch_op.f("ix_flow_endpoint_name"), ["endpoint_name"], unique=False)
+        if "unique_flow_endpoint_name" not in constraints_names:
+            batch_op.create_unique_constraint("unique_flow_endpoint_name", ["user_id", "endpoint_name"])
+        if "unique_flow_name" not in constraints_names:
+            batch_op.create_unique_constraint("unique_flow_name", ["user_id", "name"])
+
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    # ### commands auto generated by Alembic - please adjust! ###
+    indexes_names = [index["name"] for index in inspector.get_indexes("flow")]
+    constraints_names = [constraint["name"] for constraint in inspector.get_unique_constraints("flow")]
+    with op.batch_alter_table("flow", schema=None) as batch_op:
+        if "unique_flow_name" in constraints_names:
+            batch_op.drop_constraint("unique_flow_name", type_="unique")
+        if "unique_flow_endpoint_name" in constraints_names:
+            batch_op.drop_constraint("unique_flow_endpoint_name", type_="unique")
+        if "ix_flow_endpoint_name" in indexes_names:
+            batch_op.drop_index(batch_op.f("ix_flow_endpoint_name"))
+            batch_op.create_index("ix_flow_endpoint_name", ["endpoint_name"], unique=1)
+
+    # ### end Alembic commands ###

src/backend/base/langflow/alembic/versions/631faacf5da2_add_webhook_columns.py

@@ -0,0 +1,45 @@
+"""Add webhook columns
+
+Revision ID: 631faacf5da2
+Revises: 1c79524817ed
+Create Date: 2024-04-22 15:14:43.454784
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.engine.reflection import Inspector
+
+# revision identifiers, used by Alembic.
+revision: str = "631faacf5da2"
+down_revision: Union[str, None] = "1c79524817ed"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    table_names = inspector.get_table_names()
+    # ### commands auto generated by Alembic - please adjust! ###
+    column_names = [column["name"] for column in inspector.get_columns("flow")]
+    with op.batch_alter_table("flow", schema=None) as batch_op:
+        if "flow" in table_names and "webhook" not in column_names:
+            batch_op.add_column(sa.Column("webhook", sa.Boolean(), nullable=True))
+
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    table_names = inspector.get_table_names()
+    # ### commands auto generated by Alembic - please adjust! ###
+    column_names = [column["name"] for column in inspector.get_columns("flow")]
+    with op.batch_alter_table("flow", schema=None) as batch_op:
+        if "flow" in table_names and "webhook" in column_names:
+            batch_op.drop_column("webhook")
+
+    # ### end Alembic commands ###

src/backend/base/langflow/alembic/versions/7d2162acc8b2_adds_updated_at_and_folder_cols.py

@@ -52,9 +52,14 @@ def upgrade() -> None:
 def downgrade() -> None:
     # ### commands auto generated by Alembic - please adjust! ###
     try:
+        conn = op.get_bind()
+        inspector = Inspector.from_engine(conn)  # type: ignore
+        column_names = [column["name"] for column in inspector.get_columns("flow")]
         with op.batch_alter_table("flow", schema=None) as batch_op:
-            batch_op.drop_column("folder")
-            batch_op.drop_column("updated_at")
+            if "folder" in column_names:
+                batch_op.drop_column("folder")
+            if "updated_at" in column_names:
+                batch_op.drop_column("updated_at")
     except Exception as e:
         print(e)
         pass

src/backend/base/langflow/alembic/versions/a72f5cf9c2f9_add_endpoint_name_col.py

@@ -0,0 +1,52 @@
+"""Add endpoint name col
+
+Revision ID: a72f5cf9c2f9
+Revises: 29fe8f1f806b
+Create Date: 2024-05-29 21:44:04.240816
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+import sqlmodel
+from alembic import op
+from sqlalchemy.engine.reflection import Inspector
+
+# revision identifiers, used by Alembic.
+revision: str = "a72f5cf9c2f9"
+down_revision: Union[str, None] = "29fe8f1f806b"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    # ### commands auto generated by Alembic - please adjust! ###
+    column_names = [column["name"] for column in inspector.get_columns("flow")]
+    indexes = inspector.get_indexes("flow")
+    index_names = [index["name"] for index in indexes]
+    with op.batch_alter_table("flow", schema=None) as batch_op:
+        if "endpoint_name" not in column_names:
+            batch_op.add_column(sa.Column("endpoint_name", sqlmodel.sql.sqltypes.AutoString(), nullable=True))
+        if "ix_flow_endpoint_name" not in index_names:
+            batch_op.create_index(batch_op.f("ix_flow_endpoint_name"), ["endpoint_name"], unique=True)
+
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+    inspector = Inspector.from_engine(conn)  # type: ignore
+    # ### commands auto generated by Alembic - please adjust! ###
+    column_names = [column["name"] for column in inspector.get_columns("flow")]
+    indexes = inspector.get_indexes("flow")
+    index_names = [index["name"] for index in indexes]
+    with op.batch_alter_table("flow", schema=None) as batch_op:
+        if "ix_flow_endpoint_name" in index_names:
+            batch_op.drop_index(batch_op.f("ix_flow_endpoint_name"))
+        if "endpoint_name" in column_names:
+            batch_op.drop_column("endpoint_name")
+
+    # ### end Alembic commands ###

src/backend/base/langflow/api/utils.py

@@ -286,7 +286,7 @@ async def get_next_runnable_vertices(
         for v_id in set(next_runnable_vertices):  # Use set to avoid duplicates
             graph.vertices_to_run.remove(v_id)
             graph.remove_from_predecessors(v_id)
-        await chat_service.set_cache(flow_id=flow_id, data=graph, lock=lock)
+        await chat_service.set_cache(key=flow_id, data=graph, lock=lock)
     return next_runnable_vertices
 
 

src/backend/base/langflow/api/v1/chat.py

@@ -1,6 +1,5 @@
 import time
 import uuid
-from functools import partial
 from typing import TYPE_CHECKING, Annotated, Optional
 
 from fastapi import APIRouter, BackgroundTasks, Body, Depends, HTTPException
@@ -164,7 +163,6 @@ async def build_vertex(
         vertex = graph.get_vertex(vertex_id)
         try:
             lock = chat_service._cache_locks[flow_id_str]
-            set_cache_coro = partial(chat_service.set_cache, flow_id=flow_id_str)
             (
                 next_runnable_vertices,
                 top_level_vertices,
@@ -175,7 +173,7 @@ async def build_vertex(
                 vertex,
             ) = await graph.build_vertex(
                 lock=lock,
-                set_cache_coro=set_cache_coro,
+                chat_service=chat_service,
                 vertex_id=vertex_id,
                 user_id=current_user.id,
                 inputs_dict=inputs.model_dump() if inputs else {},

src/backend/base/langflow/api/v1/endpoints.py

@@ -3,7 +3,7 @@ from typing import TYPE_CHECKING, Annotated, List, Optional, Union
 from uuid import UUID
 
 import sqlalchemy as sa
-from fastapi import APIRouter, Body, Depends, HTTPException, UploadFile, status
+from fastapi import APIRouter, BackgroundTasks, Body, Depends, HTTPException, Request, UploadFile, status
 from loguru import logger
 from sqlmodel import Session, select
 
@@ -22,11 +22,14 @@ from langflow.api.v1.schemas import (
 from langflow.custom import CustomComponent
 from langflow.custom.utils import build_custom_component_template
 from langflow.graph.graph.base import Graph
+from langflow.graph.schema import RunOutputs
+from langflow.helpers.flow import get_flow_by_id_or_endpoint_name
 from langflow.processing.process import process_tweaks, run_graph_internal
 from langflow.schema.graph import Tweaks
 from langflow.services.auth.utils import api_key_security, get_current_active_user
 from langflow.services.cache.utils import save_uploaded_file
 from langflow.services.database.models.flow import Flow
+from langflow.services.database.models.flow.utils import get_all_webhook_components_in_flow, get_flow_by_id
 from langflow.services.database.models.user.model import User
 from langflow.services.deps import get_session, get_session_service, get_settings_service, get_task_service
 from langflow.services.session.service import SessionService
@@ -53,10 +56,70 @@ def get_all(
         raise HTTPException(status_code=500, detail=str(exc)) from exc
 
 
-@router.post("/run/{flow_id}", response_model=RunResponse, response_model_exclude_none=True)
+async def simple_run_flow(
+    db: Session,
+    flow: Flow,
+    input_request: SimplifiedAPIRequest,
+    session_service: SessionService,
+    stream: bool = False,
+    api_key_user: Optional[User] = None,
+):
+    try:
+        task_result: List[RunOutputs] = []
+        artifacts = {}
+        user_id = api_key_user.id if api_key_user else None
+        flow_id_str = str(flow.id)
+        if input_request.session_id:
+            session_data = await session_service.load_session(input_request.session_id, flow_id=flow_id_str)
+            graph, artifacts = session_data if session_data else (None, None)
+            if graph is None:
+                raise ValueError(f"Session {input_request.session_id} not found")
+        else:
+            if flow.data is None:
+                raise ValueError(f"Flow {flow_id_str} has no data")
+            graph_data = flow.data
+            graph_data = process_tweaks(graph_data, input_request.tweaks or {}, stream=stream)
+            graph = Graph.from_payload(graph_data, flow_id=flow_id_str, user_id=str(user_id))
+        inputs = [
+            InputValueRequest(components=[], input_value=input_request.input_value, type=input_request.input_type)
+        ]
+        if input_request.output_component:
+            outputs = [input_request.output_component]
+        else:
+            outputs = [
+                vertex.id
+                for vertex in graph.vertices
+                if input_request.output_type == "debug"
+                or (
+                    vertex.is_output
+                    and (input_request.output_type == "any" or input_request.output_type in vertex.id.lower())
+                )
+            ]
+        task_result, session_id = await run_graph_internal(
+            graph=graph,
+            flow_id=flow_id_str,
+            session_id=input_request.session_id,
+            inputs=inputs,
+            outputs=outputs,
+            artifacts=artifacts,
+            session_service=session_service,
+            stream=stream,
+        )
+
+        return RunResponse(outputs=task_result, session_id=session_id)
+
+    except sa.exc.StatementError as exc:
+        # StatementError('(builtins.ValueError) badly formed hexadecimal UUID string')
+        if "badly formed hexadecimal UUID string" in str(exc):
+            logger.error(f"Flow ID {flow_id_str} is not a valid UUID")
+            # This means the Flow ID is not a valid UUID which means it can't find the flow
+            raise ValueError(str(exc)) from exc
+
+
+@router.post("/run/{flow_id_or_name}", response_model=RunResponse, response_model_exclude_none=True)
 async def simplified_run_flow(
     db: Annotated[Session, Depends(get_session)],
-    flow_id: UUID,
+    flow: Annotated[Flow, Depends(get_flow_by_id_or_endpoint_name)],
     input_request: SimplifiedAPIRequest = SimplifiedAPIRequest(),
     stream: bool = False,
     api_key_user: User = Depends(api_key_security),
@@ -67,7 +130,7 @@ async def simplified_run_flow(
 
     ### Parameters:
     - `db` (Session): Database session for executing queries.
-    - `flow_id` (str): Unique identifier of the flow to be executed.
+    - `flow_id_or_name` (str): ID or endpoint name of the flow to run.
     - `input_request` (SimplifiedAPIRequest): Request object containing input values, types, output selection, tweaks, and session ID.
     - `api_key_user` (User): User object derived from the provided API key, used for authentication.
     - `session_service` (SessionService): Service for managing flow sessions, essential for session reuse and caching.
@@ -110,73 +173,21 @@ async def simplified_run_flow(
 
     This endpoint provides a powerful interface for executing flows with enhanced flexibility and efficiency, supporting a wide range of applications by allowing for dynamic input and output configuration along with performance optimizations through session management and caching.
     """
-    session_id = input_request.session_id
-
     try:
-        flow_id_str = str(flow_id)
-        artifacts = {}
-        if input_request.session_id:
-            session_data = await session_service.load_session(input_request.session_id, flow_id=flow_id_str)
-            graph, artifacts = session_data if session_data else (None, None)
-            if graph is None:
-                raise ValueError(f"Session {input_request.session_id} not found")
-        else:
-            # Get the flow that matches the flow_id and belongs to the user
-            # flow = session.query(Flow).filter(Flow.id == flow_id).filter(Flow.user_id == api_key_user.id).first()
-            flow = db.exec(select(Flow).where(Flow.id == flow_id_str).where(Flow.user_id == api_key_user.id)).first()
-            if flow is None:
-                raise ValueError(f"Flow {flow_id_str} not found")
-
-            if flow.data is None:
-                raise ValueError(f"Flow {flow_id_str} has no data")
-            graph_data = flow.data
-
-            graph_data = process_tweaks(graph_data, input_request.tweaks or {}, stream=stream)
-            graph = Graph.from_payload(graph_data, flow_id=flow_id_str, user_id=str(api_key_user.id))
-        inputs = [
-            InputValueRequest(components=[], input_value=input_request.input_value, type=input_request.input_type)
-        ]
-        # outputs is a list of all components that should return output
-        # we need to get them by checking their type
-        # if the output type is debug, we return all outputs
-        # if the output type is any, we return all outputs that are either chat or text
-        # if the output type is chat or text, we return only the outputs that match the type
-        if input_request.output_component:
-            outputs = [input_request.output_component]
-        else:
-            outputs = [
-                vertex.id
-                for vertex in graph.vertices
-                if input_request.output_type == "debug"
-                or (
-                    vertex.is_output
-                    and (input_request.output_type == "any" or input_request.output_type in vertex.id.lower())
-                )
-            ]
-        task_result, session_id = await run_graph_internal(
-            graph=graph,
-            flow_id=flow_id_str,
-            session_id=input_request.session_id,
-            inputs=inputs,
-            outputs=outputs,
-            artifacts=artifacts,
+        return await simple_run_flow(
+            db=db,
+            flow=flow,
+            input_request=input_request,
             session_service=session_service,
             stream=stream,
+            api_key_user=api_key_user,
         )
 
-        return RunResponse(outputs=task_result, session_id=session_id)
-    except sa.exc.StatementError as exc:
-        # StatementError('(builtins.ValueError) badly formed hexadecimal UUID string')
-        if "badly formed hexadecimal UUID string" in str(exc):
-            logger.error(f"Flow ID {flow_id_str} is not a valid UUID")
-            # This means the Flow ID is not a valid UUID which means it can't find the flow
-            raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
     except ValueError as exc:
-        if f"Flow {flow_id_str} not found" in str(exc):
-            logger.error(f"Flow {flow_id_str} not found")
-            raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
-        elif f"Session {session_id} not found" in str(exc):
-            logger.error(f"Session {session_id} not found")
+        if "badly formed hexadecimal UUID string" in str(exc):
+            # This means the Flow ID is not a valid UUID which means it can't find the flow
+            raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(exc)) from exc
+        if "not found" in str(exc):
             raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
         else:
             logger.exception(exc)
@@ -186,6 +197,68 @@ async def simplified_run_flow(
         raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(exc)) from exc
 
 
+@router.post("/webhook/{flow_id}", response_model=dict, status_code=HTTPStatus.ACCEPTED)
+async def webhook_run_flow(
+    db: Annotated[Session, Depends(get_session)],
+    flow: Annotated[Flow, Depends(get_flow_by_id)],
+    request: Request,
+    background_tasks: BackgroundTasks,
+    session_service: SessionService = Depends(get_session_service),
+):
+    """
+    Run a flow using a webhook request.
+
+    Args:
+        db (Session): The database session.
+        request (Request): The incoming HTTP request.
+        background_tasks (BackgroundTasks): The background tasks manager.
+        session_service (SessionService, optional): The session service. Defaults to Depends(get_session_service).
+        flow (Flow, optional): The flow to be executed. Defaults to Depends(get_flow_by_id).
+
+    Returns:
+        dict: A dictionary containing the status of the task.
+
+    Raises:
+        HTTPException: If the flow is not found or if there is an error processing the request.
+    """
+    try:
+        logger.debug("Received webhook request")
+        data = await request.body()
+        if not data:
+            logger.error("Request body is empty")
+            raise ValueError(
+                "Request body is empty. You should provide a JSON payload containing the flow ID.",
+            )
+
+        # get all webhook components in the flow
+        webhook_components = get_all_webhook_components_in_flow(flow.data)
+        tweaks = {}
+        data_dict = await request.json()
+        for component in webhook_components:
+            tweaks[component["id"]] = {"data": data.decode() if isinstance(data, bytes) else data}
+        input_request = SimplifiedAPIRequest(
+            input_value=data_dict.get("input_value", ""),
+            input_type=data_dict.get("input_type", "chat"),
+            output_type=data_dict.get("output_type", "chat"),
+            tweaks=tweaks,
+            session_id=data_dict.get("session_id"),
+        )
+        logger.debug("Starting background task")
+        background_tasks.add_task(
+            simple_run_flow,
+            db=db,
+            flow=flow,
+            input_request=input_request,
+            session_service=session_service,
+        )
+        return {"message": "Task started in the background", "status": "in progress"}
+    except Exception as exc:
+        if "Flow ID is required" in str(exc) or "Request body is empty" in str(exc):
+            raise HTTPException(status_code=400, detail=str(exc)) from exc
+        logger.exception(exc)
+        raise HTTPException(status_code=500, detail=str(exc)) from exc
+
+
 @router.post("/run/advanced/{flow_id}", response_model=RunResponse, response_model_exclude_none=True)
 async def experimental_run_flow(
     session: Annotated[Session, Depends(get_session)],

src/backend/base/langflow/api/v1/flows.py

@@ -13,6 +13,7 @@ from langflow.api.v1.schemas import FlowListCreate, FlowListIds, FlowListRead
 from langflow.initial_setup.setup import STARTER_FOLDER_NAME
 from langflow.services.auth.utils import get_current_active_user
 from langflow.services.database.models.flow import Flow, FlowCreate, FlowRead, FlowUpdate
+from langflow.services.database.models.flow.utils import get_webhook_component_in_flow
 from langflow.services.database.models.folder.constants import DEFAULT_FOLDER_NAME
 from langflow.services.database.models.folder.model import Folder
 from langflow.services.database.models.user.model import User
@@ -57,8 +58,22 @@ def read_flows(
     current_user: User = Depends(get_current_active_user),
     session: Session = Depends(get_session),
     settings_service: "SettingsService" = Depends(get_settings_service),
+    remove_example_flows: bool = False,
 ):
-    """Read all flows."""
+    """
+    Retrieve a list of flows.
+
+    Args:
+        current_user (User): The current authenticated user.
+        session (Session): The database session.
+        settings_service (SettingsService): The settings service.
+        remove_example_flows (bool, optional): Whether to remove example flows. Defaults to False.
+
+
+    Returns:
+        List[Dict]: A list of flows in JSON format.
+    """
+
     try:
         auth_settings = settings_service.auth_settings
         if auth_settings.AUTO_LOGIN:
@@ -73,15 +88,16 @@ def read_flows(
         flows = validate_is_component(flows)  # type: ignore
         flow_ids = [flow.id for flow in flows]
         # with the session get the flows that DO NOT have a user_id
-        try:
-            folder = session.exec(select(Folder).where(Folder.name == STARTER_FOLDER_NAME)).first()
+        if not remove_example_flows:
+            try:
+                folder = session.exec(select(Folder).where(Folder.name == STARTER_FOLDER_NAME)).first()
 
-            example_flows = folder.flows if folder else []
-            for example_flow in example_flows:
-                if example_flow.id not in flow_ids:
-                    flows.append(example_flow)  # type: ignore
-        except Exception as e:
-            logger.error(e)
+                example_flows = folder.flows if folder else []
+                for example_flow in example_flows:
+                    if example_flow.id not in flow_ids:
+                        flows.append(example_flow)  # type: ignore
+            except Exception as e:
+                logger.error(e)
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e)) from e
     return [jsonable_encoder(flow) for flow in flows]
@@ -120,30 +136,51 @@ def update_flow(
     settings_service=Depends(get_settings_service),
 ):
     """Update a flow."""
+    try:
+        db_flow = read_flow(
+            session=session,
+            flow_id=flow_id,
+            current_user=current_user,
+            settings_service=settings_service,
+        )
+        if not db_flow:
+            raise HTTPException(status_code=404, detail="Flow not found")
+        flow_data = flow.model_dump(exclude_unset=True)
+        if settings_service.settings.remove_api_keys:
+            flow_data = remove_api_keys(flow_data)
+        for key, value in flow_data.items():
+            if value is not None:
+                setattr(db_flow, key, value)
+        webhook_component = get_webhook_component_in_flow(db_flow.data)
+        db_flow.webhook = webhook_component is not None
+        db_flow.updated_at = datetime.now(timezone.utc)
+        if db_flow.folder_id is None:
+            default_folder = session.exec(select(Folder).where(Folder.name == DEFAULT_FOLDER_NAME)).first()
+            if default_folder:
+                db_flow.folder_id = default_folder.id
+        session.add(db_flow)
+        session.commit()
+        session.refresh(db_flow)
+        return db_flow
+    except Exception as e:
+        # If it is a validation error, return the error message
+        if hasattr(e, "errors"):
+            raise HTTPException(status_code=400, detail=str(e)) from e
+        elif "UNIQUE constraint failed" in str(e):
+            # Get the name of the column that failed
+            columns = str(e).split("UNIQUE constraint failed: ")[1].split(".")[1].split("\n")[0]
+            # UNIQUE constraint failed: flow.user_id, flow.name
+            # or UNIQUE constraint failed: flow.name
+            # if the column has id in it, we want the other column
+            column = columns.split(",")[1] if "id" in columns.split(",")[0] else columns.split(",")[0]
 
-    db_flow = read_flow(
-        session=session,
-        flow_id=flow_id,
-        current_user=current_user,
-        settings_service=settings_service,
-    )
-    if not db_flow:
-        raise HTTPException(status_code=404, detail="Flow not found")
-    flow_data = flow.model_dump(exclude_unset=True)
-    if settings_service.settings.remove_api_keys:
-        flow_data = remove_api_keys(flow_data)
-    for key, value in flow_data.items():
-        if value is not None:
-            setattr(db_flow, key, value)
-    db_flow.updated_at = datetime.now(timezone.utc)
-    if db_flow.folder_id is None:
-        default_folder = session.exec(select(Folder).where(Folder.name == DEFAULT_FOLDER_NAME)).first()
-        if default_folder:
-            db_flow.folder_id = default_folder.id
-    session.add(db_flow)
-    session.commit()
-    session.refresh(db_flow)
-    return db_flow
+            raise HTTPException(
+                status_code=400, detail=f"{column.capitalize().replace('_', ' ')} must be unique"
+            ) from e
+        elif isinstance(e, HTTPException):
+            raise e
+        else:
+            raise HTTPException(status_code=500, detail=str(e)) from e
 
 
 @router.delete("/{flow_id}", status_code=200)

src/backend/base/langflow/api/v1/folders.py

@@ -1,5 +1,4 @@
 from typing import List
-from uuid import UUID
 
 import orjson
 from fastapi import APIRouter, Depends, File, HTTPException, Response, UploadFile, status
@@ -88,7 +87,7 @@ def read_folders(
 def read_folder(
     *,
     session: Session = Depends(get_session),
-    folder_id: UUID,
+    folder_id: str,
     current_user: User = Depends(get_current_active_user),
 ):
     try:
@@ -106,7 +105,7 @@ def read_folder(
 def update_folder(
     *,
     session: Session = Depends(get_session),
-    folder_id: UUID,
+    folder_id: str,
     folder: FolderUpdate,  # Assuming FolderUpdate is a Pydantic model defining updatable fields
     current_user: User = Depends(get_current_active_user),
 ):
@@ -155,7 +154,7 @@ def update_folder(
 def delete_folder(
     *,
     session: Session = Depends(get_session),
-    folder_id: UUID,
+    folder_id: str,
     current_user: User = Depends(get_current_active_user),
 ):
     try:
@@ -177,7 +176,7 @@ def delete_folder(
 async def download_file(
     *,
     session: Session = Depends(get_session),
-    folder_id: UUID,
+    folder_id: str,
     current_user: User = Depends(get_current_active_user),
 ):
     """Download all flows from folder."""

src/backend/base/langflow/api/v1/login.py

@@ -46,6 +46,7 @@ async def login_to_get_access_token(
             samesite=auth_settings.REFRESH_SAME_SITE,
             secure=auth_settings.REFRESH_SECURE,
             expires=auth_settings.REFRESH_TOKEN_EXPIRE_SECONDS,
+            domain=auth_settings.COOKIE_DOMAIN,
         )
         response.set_cookie(
             "access_token_lf",
@@ -54,6 +55,7 @@ async def login_to_get_access_token(
             samesite=auth_settings.ACCESS_SAME_SITE,
             secure=auth_settings.ACCESS_SECURE,
             expires=auth_settings.ACCESS_TOKEN_EXPIRE_SECONDS,
+            domain=auth_settings.COOKIE_DOMAIN,
         )
         variable_service.initialize_user_variables(user.id, db)
         # Create default folder for user if it doesn't exist
@@ -71,8 +73,7 @@ async def login_to_get_access_token(
 async def auto_login(
     response: Response,
     db: Session = Depends(get_session),
-    settings_service=Depends(get_settings_service),
-    variable_service: VariableService = Depends(get_variable_service),
+    settings_service=Depends(get_settings_service)
 ):
     auth_settings = settings_service.auth_settings
     if settings_service.auth_settings.AUTO_LOGIN:
@@ -84,9 +85,9 @@ async def auto_login(
             samesite=auth_settings.ACCESS_SAME_SITE,
             secure=auth_settings.ACCESS_SECURE,
             expires=None,  # Set to None to make it a session cookie
+            domain=auth_settings.COOKIE_DOMAIN,
         )
-        variable_service.initialize_user_variables(user_id, db)
-        create_default_folder_if_it_doesnt_exist(db, user_id)
+
         return tokens
 
     raise HTTPException(
@@ -117,6 +118,7 @@ async def refresh_token(
             samesite=auth_settings.REFRESH_SAME_SITE,
             secure=auth_settings.REFRESH_SECURE,
             expires=auth_settings.REFRESH_TOKEN_EXPIRE_SECONDS,
+            domain=auth_settings.COOKIE_DOMAIN,
         )
         response.set_cookie(
             "access_token_lf",
@@ -125,6 +127,7 @@ async def refresh_token(
             samesite=auth_settings.ACCESS_SAME_SITE,
             secure=auth_settings.ACCESS_SECURE,
             expires=auth_settings.ACCESS_TOKEN_EXPIRE_SECONDS,
+            domain=auth_settings.COOKIE_DOMAIN,
         )
         return tokens
     else:

src/backend/base/langflow/api/v1/schemas.py

@@ -256,6 +256,7 @@ class ResultDataResponse(BaseModel):
     messages: List[ChatOutputResponse | None] = Field(default_factory=list)
     timedelta: Optional[float] = None
     duration: Optional[str] = None
+    used_frozen_result: Optional[bool] = False
 
 
 class VertexBuildResponse(BaseModel):

src/backend/base/langflow/base/curl/parse.py

@@ -0,0 +1,89 @@
+"""
+This file contains a fix for the implementation of the `uncurl` library, which is available at https://github.com/spulec/uncurl.git.
+
+The `uncurl` library provides a way to parse and convert cURL commands into Python requests. However, there are some issues with the original implementation that this file aims to fix.
+
+The `parse_context` function in this file takes a cURL command as input and returns a `ParsedContext` object, which contains the parsed information from the cURL command, such as the HTTP method, URL, headers, cookies, etc.
+
+The `normalize_newlines` function is a helper function that replaces the line continuation character ("\") followed by a newline with a space.
+
+
+"""
+
+import re
+import shlex
+from collections import OrderedDict, namedtuple
+from http.cookies import SimpleCookie
+
+from uncurl.api import parser  # type: ignore
+
+parser.add_argument("-x", "--proxy", default={})
+parser.add_argument("-U", "--proxy-user", default="")
+
+ParsedContext = namedtuple("ParsedContext", ["method", "url", "data", "headers", "cookies", "verify", "auth", "proxy"])
+
+
+def normalize_newlines(multiline_text):
+    return multiline_text.replace(" \\\n", " ")
+
+
+def parse_context(curl_command):
+    method = "get"
+
+    tokens = shlex.split(normalize_newlines(curl_command))
+    tokens = [token for token in tokens if token and token != " "]
+    parsed_args = parser.parse_args(tokens)
+
+    post_data = parsed_args.data or parsed_args.data_binary
+    if post_data:
+        method = "post"
+
+    if parsed_args.X:
+        method = parsed_args.X.lower()
+
+    cookie_dict = OrderedDict()
+    quoted_headers = OrderedDict()
+
+    for curl_header in parsed_args.header:
+        if curl_header.startswith(":"):
+            occurrence = [m.start() for m in re.finditer(":", curl_header)]
+            header_key, header_value = curl_header[: occurrence[1]], curl_header[occurrence[1] + 1 :]
+        else:
+            header_key, header_value = curl_header.split(":", 1)
+
+        if header_key.lower().strip("$") == "cookie":
+            cookie = SimpleCookie(bytes(header_value, "ascii").decode("unicode-escape"))
+            for key in cookie:
+                cookie_dict[key] = cookie[key].value
+        else:
+            quoted_headers[header_key] = header_value.strip()
+
+    # add auth
+    user = parsed_args.user
+    if parsed_args.user:
+        user = tuple(user.split(":"))
+
+    # add proxy and its authentication if it's available.
+    proxies = parsed_args.proxy
+    # proxy_auth = parsed_args.proxy_user
+    if parsed_args.proxy and parsed_args.proxy_user:
+        proxies = {
+            "http": "http://{}@{}/".format(parsed_args.proxy_user, parsed_args.proxy),
+            "https": "http://{}@{}/".format(parsed_args.proxy_user, parsed_args.proxy),
+        }
+    elif parsed_args.proxy:
+        proxies = {
+            "http": "http://{}/".format(parsed_args.proxy),
+            "https": "http://{}/".format(parsed_args.proxy),
+        }
+
+    return ParsedContext(
+        method=method,
+        url=parsed_args.url,
+        data=post_data,
+        headers=quoted_headers,
+        cookies=cookie_dict,
+        verify=parsed_args.insecure,
+        auth=user,
+        proxy=proxies,
+    )

src/backend/base/langflow/components/data/APIRequest.py

@@ -1,11 +1,15 @@
 import asyncio
 import json
-from typing import List, Optional
+from typing import Any, List, Optional
 
 import httpx
+from loguru import logger
 
+from langflow.base.curl.parse import parse_context
 from langflow.custom import CustomComponent
+from langflow.field_typing import NestedDict
 from langflow.schema import Record
+from langflow.schema.dotdict import dotdict
 
 
 class APIRequest(CustomComponent):
@@ -17,10 +21,15 @@ class APIRequest(CustomComponent):
 
     field_config = {
         "urls": {"display_name": "URLs", "info": "URLs to make requests to."},
+        "curl": {
+            "display_name": "Curl",
+            "info": "Paste a curl command to populate the fields.",
+            "refresh_button": True,
+            "refresh_button_text": "",
+        },
         "method": {
             "display_name": "Method",
             "info": "The HTTP method to use.",
-            "field_type": "str",
             "options": ["GET", "POST", "PATCH", "PUT"],
             "value": "GET",
         },
@@ -36,12 +45,33 @@ class APIRequest(CustomComponent):
         },
         "timeout": {
             "display_name": "Timeout",
-            "field_type": "int",
             "info": "The timeout to use for the request.",
             "value": 5,
         },
     }
 
+    def parse_curl(self, curl: str, build_config: dotdict) -> dotdict:
+        try:
+            parsed = parse_context(curl)
+            build_config["urls"]["value"] = [parsed.url]
+            build_config["method"]["value"] = parsed.method.upper()
+            build_config["headers"]["value"] = dict(parsed.headers)
+
+            try:
+                json_data = json.loads(parsed.data)
+                build_config["body"]["value"] = json_data
+            except json.JSONDecodeError as e:
+                print(e)
+        except Exception as exc:
+            logger.error(f"Error parsing curl: {exc}")
+            raise ValueError(f"Error parsing curl: {exc}")
+        return build_config
+
+    def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None):
+        if field_name == "curl" and field_value is not None:
+            build_config = self.parse_curl(field_value, build_config)
+        return build_config
+
     async def make_request(
         self,
         client: httpx.AsyncClient,
@@ -94,21 +124,25 @@ class APIRequest(CustomComponent):
         self,
         method: str,
         urls: List[str],
-        headers: Optional[Record] = None,
-        body: Optional[Record] = None,
+        curl: Optional[str] = None,
+        headers: Optional[NestedDict] = {},
+        body: Optional[NestedDict] = {},
         timeout: int = 5,
     ) -> List[Record]:
         if headers is None:
             headers_dict = {}
-        else:
+        elif isinstance(headers, Record):
             headers_dict = headers.data
+        else:
+            headers_dict = headers
 
         bodies = []
         if body:
-            if isinstance(body, list):
-                bodies = [b.data for b in body]
+            if not isinstance(body, list):
+                bodies = [body]
             else:
-                bodies = [body.data]
+                bodies = body
+            bodies = [b.data if isinstance(b, Record) else b for b in bodies]  # type: ignore
 
         if len(urls) != len(bodies):
             # add bodies with None

src/backend/base/langflow/components/data/Webhook.py

@@ -0,0 +1,39 @@
+import json
+import uuid
+from typing import Any, Optional
+
+from langflow.custom import CustomComponent
+from langflow.schema.dotdict import dotdict
+from langflow.schema.schema import Record
+
+
+class WebhookComponent(CustomComponent):
+    display_name = "Webhook Input"
+    description = "Defines a webhook input for the flow."
+
+    def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None):
+        if field_name == "webhook_id":
+            build_config["webhook_id"]["value"] = uuid.uuid4().hex
+        return build_config
+
+    def build_config(self):
+        return {
+            "data": {
+                "display_name": "Data",
+                "info": "Use this field to quickly test the webhook component by providing a JSON payload.",
+                "multiline": True,
+            }
+        }
+
+    def build(self, data: Optional[str] = "") -> Record:
+        message = ""
+        try:
+            body = json.loads(data or "{}")
+        except json.JSONDecodeError:
+            body = {"payload": data}
+            message = f"Invalid JSON payload. Please check the format.\n\n{data}"
+        record = Record(data=body)
+        if not message:
+            message = json.dumps(body, indent=2)
+        self.status = message
+        return record

src/backend/base/langflow/components/data/__init__.py

@@ -1,7 +1,8 @@
 from .APIRequest import APIRequest
 from .Directory import DirectoryComponent
 from .File import FileComponent
+from .Webhook import WebhookComponent
 
 from .URL import URLComponent
 
-__all__ = ["APIRequest", "DirectoryComponent", "FileComponent", "URLComponent"]
+__all__ = ["APIRequest", "DirectoryComponent", "FileComponent", "URLComponent", "WebhookComponent"]

src/backend/base/langflow/components/experimental/SplitText.py

@@ -43,7 +43,7 @@ class SplitTextComponent(CustomComponent):
                 chunks = [chunk[:truncate_size] for chunk in chunks]
 
             for chunk in chunks:
-                outputs.append(Record(text=chunk, data={"parent": text}))
+                outputs.append(Record(data={"parent": text, "text": chunk}))
 
         self.status = outputs
         return outputs

src/backend/base/langflow/components/models/OllamaModel.py

@@ -1,21 +1,11 @@
-
-from typing import Any, Dict, List, Optional, Union
-
-
-
-from langchain_community.chat_models.ollama import ChatOllama
-from langflow.base.constants import STREAM_INFO_TEXT
-from langflow.base.models.model import LCModelComponent
-from langchain_core.caches import BaseCache
-
-from langflow.field_typing import Text
-
-
-import asyncio
-import json
+from typing import Any, Dict, List, Optional
 
 import httpx
+from langchain_community.chat_models.ollama import ChatOllama
 
+from langflow.base.constants import STREAM_INFO_TEXT
+from langflow.base.models.model import LCModelComponent
+from langflow.field_typing import Text
 
 
 class ChatOllamaComponent(LCModelComponent):
@@ -26,18 +16,12 @@ class ChatOllamaComponent(LCModelComponent):
     field_order = [
         "base_url",
         "headers",
-
         "keep_alive_flag",
         "keep_alive",
-
         "metadata",
         "model",
-
-
         "temperature",
         "cache",
-
-
         "format",
         "metadata",
         "mirostat",
@@ -67,10 +51,7 @@ class ChatOllamaComponent(LCModelComponent):
             "base_url": {
                 "display_name": "Base URL",
                 "info": "Endpoint of the Ollama API. Defaults to 'http://localhost:11434' if not specified.",
-
             },
-
-
             "format": {
                 "display_name": "Format",
                 "info": "Specify the format of the output (e.g., json)",
@@ -79,13 +60,10 @@ class ChatOllamaComponent(LCModelComponent):
             "headers": {
                 "display_name": "Headers",
                 "advanced": True,
-
-
             },
-
             "keep_alive_flag": {
                 "display_name": "Unload interval",
-                "options": ["Keep", "Immediately","Minute", "Hour", "sec" ],
+                "options": ["Keep", "Immediately", "Minute", "Hour", "sec"],
                 "real_time_refresh": True,
                 "refresh_button": True,
             },
@@ -93,9 +71,6 @@ class ChatOllamaComponent(LCModelComponent):
                 "display_name": "interval",
                 "info": "How long the model will stay loaded into memory.",
             },
-
-
-
             "model": {
                 "display_name": "Model Name",
                 "options": [],
@@ -109,14 +84,6 @@ class ChatOllamaComponent(LCModelComponent):
                 "value": 0.8,
                 "info": "Controls the creativity of model responses.",
             },
-
-
-            "format": {
-                "display_name": "Format",
-                "field_type": "str",
-                "info": "Specify the format of the output (e.g., json).",
-                "advanced": True,
-            },
             "metadata": {
                 "display_name": "Metadata",
                 "info": "Metadata to add to the run trace.",
@@ -129,7 +96,6 @@ class ChatOllamaComponent(LCModelComponent):
                 "advanced": False,
                 "real_time_refresh": True,
                 "refresh_button": True,
-
             },
             "mirostat_eta": {
                 "display_name": "Mirostat Eta",
@@ -260,10 +226,14 @@ class ChatOllamaComponent(LCModelComponent):
                     build_config["mirostat_tau"]["value"] = 5
 
         if field_name == "model":
-            base_url = build_config.get("base_url", {}).get(
-                "value", "http://localhost:11434")
-            build_config["model"]["options"] = self.get_model(
-                base_url + "/api/tags")
+            base_url_dict = build_config.get("base_url", {})
+            base_url_load_from_db = base_url_dict.get("load_from_db", False)
+            base_url_value = base_url_dict.get("value")
+            if base_url_load_from_db:
+                base_url_value = self.variables(base_url_value)
+            elif not base_url_value:
+                base_url_value = "http://localhost:11434"
+            build_config["model"]["options"] = self.get_model(base_url_value + "/api/tags")
 
         if field_name == "keep_alive_flag":
             if field_value == "Keep":
@@ -276,9 +246,6 @@ class ChatOllamaComponent(LCModelComponent):
                 build_config["keep_alive"]["advanced"] = False
 
         return build_config
-    
-
-    
 
     def get_model(self, url: str) -> List[str]:
         try:
@@ -287,8 +254,7 @@ class ChatOllamaComponent(LCModelComponent):
                 response.raise_for_status()
                 data = response.json()
 
-                model_names = [model['name']
-                               for model in data.get("models", [])]
+                model_names = [model["name"] for model in data.get("models", [])]
                 return model_names
         except Exception as e:
             raise ValueError("Could not retrieve models") from e
@@ -299,15 +265,13 @@ class ChatOllamaComponent(LCModelComponent):
         base_url: Optional[str],
         model: str,
         input_value: Text,
-
-        mirostat: Optional[str],        
+        mirostat: Optional[str] = "Disabled",
         mirostat_eta: Optional[float] = None,
         mirostat_tau: Optional[float] = None,
-        
         repeat_last_n: Optional[int] = None,
         verbose: Optional[bool] = None,
         keep_alive: Optional[int] = None,
-        keep_alive_flag: Optional[str] = None,
+        keep_alive_flag: Optional[str] = "Keep",
         num_ctx: Optional[int] = None,
         num_gpu: Optional[int] = None,
         format: Optional[str] = None,
@@ -326,12 +290,9 @@ class ChatOllamaComponent(LCModelComponent):
         stream: bool = False,
         system_message: Optional[str] = None,
     ) -> Text:
-
         if not base_url:
             base_url = "http://localhost:11434"
 
-
-
         if keep_alive_flag == "Minute":
             keep_alive_instance = f"{keep_alive}m"
         elif keep_alive_flag == "Hour":

src/backend/base/langflow/components/models/OpenAIModel.py

@@ -78,7 +78,7 @@ class OpenAIModelComponent(LCModelComponent):
         self,
         input_value: Text,
         openai_api_key: str,
-        temperature: float,
+        temperature: float = 0.1,
         model_name: str = "gpt-4o",
         max_tokens: Optional[int] = 256,
         model_kwargs: NestedDict = {},

src/backend/base/langflow/components/vectorsearch/UpstashSearch.py

@@ -0,0 +1,79 @@
+from typing import List, Optional
+
+from langchain_core.embeddings import Embeddings
+
+from langflow.components.vectorstores.base.model import LCVectorStoreComponent
+from langflow.components.vectorstores.Upstash import UpstashVectorStoreComponent
+from langflow.field_typing import Text
+from langflow.schema import Record
+
+
+class UpstashSearchComponent(UpstashVectorStoreComponent, LCVectorStoreComponent):
+    """
+    A custom component for implementing a Vector Store using Upstash.
+    """
+
+    display_name: str = "Upstash Search"
+    description: str = "Search an Upstash Vector Store for similar documents."
+
+    def build_config(self):
+        """
+        Builds the configuration for the component.
+
+        Returns:
+        - dict: A dictionary containing the configuration options for the component.
+        """
+        return {
+            "search_type": {
+                "display_name": "Search Type",
+                "options": ["Similarity", "MMR"],
+            },
+            "input_value": {"display_name": "Input"},
+            "inputs": {"display_name": "Input", "input_types": ["Document", "Record"]},
+            "embedding": {
+                "display_name": "Embedding",
+                "input_types": ["Embeddings"],
+                "info": "To use Upstash's embeddings, don't provide an embedding.",
+            },
+            "index_url": {
+                "display_name": "Index URL",
+                "info": "The URL of the Upstash index.",
+            },
+            "index_token": {
+                "display_name": "Index Token",
+                "info": "The token for the Upstash index.",
+            },
+            "number_of_results": {
+                "display_name": "Number of Results",
+                "info": "Number of results to return.",
+                "advanced": True,
+            },
+            "text_key": {
+                "display_name": "Text Key",
+                "info": "The key in the record to use as text.",
+                "advanced": True,
+            },
+        }
+
+    def build(  # type: ignore[override]
+        self,
+        input_value: Text,
+        search_type: str,
+        text_key: str = "text",
+        index_url: Optional[str] = None,
+        index_token: Optional[str] = None,
+        embedding: Optional[Embeddings] = None,
+        number_of_results: int = 4,
+    ) -> List[Record]:
+        vector_store = super().build(
+            embedding=embedding,
+            text_key=text_key,
+            index_url=index_url,
+            index_token=index_token,
+        )
+        if not vector_store:
+            raise ValueError("Failed to load the Upstash Vector Store.")
+
+        return self.search_with_vector_store(
+            input_value=input_value, search_type=search_type, vector_store=vector_store, k=number_of_results
+        )

src/backend/base/langflow/components/vectorstores/Qdrant.py

@@ -67,22 +67,19 @@ class QdrantComponent(CustomComponent):
                 documents.append(_input.to_lc_document())
             else:
                 documents.append(_input)
-        if documents is None:
+        if not documents:
             from qdrant_client import QdrantClient
 
             client = QdrantClient(
                 location=location,
-                url=host,
+                url=url,
                 port=port,
                 grpc_port=grpc_port,
                 https=https,
                 prefix=prefix,
                 timeout=timeout,
                 prefer_grpc=prefer_grpc,
-                metadata_payload_key=metadata_payload_key,
-                content_payload_key=content_payload_key,
                 api_key=api_key,
-                collection_name=collection_name,
                 host=host,
                 path=path,
             )
@@ -90,6 +87,8 @@ class QdrantComponent(CustomComponent):
                 client=client,
                 collection_name=collection_name,
                 embeddings=embedding,
+                content_payload_key=content_payload_key,
+                metadata_payload_key=metadata_payload_key,
             )
             return vs
         else:

src/backend/base/langflow/components/vectorstores/Upstash.py

@@ -0,0 +1,89 @@
+from typing import List, Optional, Union
+
+from langchain_community.vectorstores.upstash import UpstashVectorStore
+from langchain_core.embeddings import Embeddings
+from langchain_core.retrievers import BaseRetriever
+from langchain_core.vectorstores import VectorStore
+
+from langflow.custom import CustomComponent
+from langflow.schema.schema import Record
+
+
+class UpstashVectorStoreComponent(CustomComponent):
+    """
+    A custom component for implementing a Vector Store using Upstash.
+    """
+
+    display_name: str = "Upstash"
+    description: str = "Create and Utilize an Upstash Vector Store"
+
+    def build_config(self):
+        """
+        Builds the configuration for the component.
+
+        Returns:
+        - dict: A dictionary containing the configuration options for the component.
+        """
+        return {
+            "inputs": {"display_name": "Input", "input_types": ["Document", "Record"]},
+            "embedding": {
+                "display_name": "Embedding",
+                "input_types": ["Embeddings"],
+                "info": "To use Upstash's embeddings, don't provide an embedding.",
+            },
+            "index_url": {
+                "display_name": "Index URL",
+                "info": "The URL of the Upstash index.",
+            },
+            "index_token": {
+                "display_name": "Index Token",
+                "info": "The token for the Upstash index.",
+            },
+            "text_key": {
+                "display_name": "Text Key",
+                "info": "The key in the record to use as text.",
+                "advanced": True,
+            },
+        }
+
+    def build(
+        self,
+        inputs: Optional[List[Record]] = None,
+        text_key: str = "text",
+        index_url: Optional[str] = None,
+        index_token: Optional[str] = None,
+        embedding: Optional[Embeddings] = None,
+    ) -> Union[VectorStore, BaseRetriever]:
+        documents = []
+        for _input in inputs or []:
+            if isinstance(_input, Record):
+                documents.append(_input.to_lc_document())
+            else:
+                documents.append(_input)
+
+        use_upstash_embedding = embedding is None
+        if not documents:
+            upstash_vs = UpstashVectorStore(
+                embedding=embedding or use_upstash_embedding,
+                text_key=text_key,
+                index_url=index_url,
+                index_token=index_token,
+            )
+        else:
+            if use_upstash_embedding:
+                upstash_vs = UpstashVectorStore(
+                    embedding=use_upstash_embedding,
+                    text_key=text_key,
+                    index_url=index_url,
+                    index_token=index_token,
+                )
+                upstash_vs.add_documents(documents)
+            elif embedding:
+                upstash_vs = UpstashVectorStore.from_documents(
+                    documents=documents,  # type: ignore
+                    embedding=embedding,
+                    text_key=text_key,
+                    index_url=index_url,
+                    index_token=index_token,
+                )
+        return upstash_vs

src/backend/base/langflow/custom/utils.py

@@ -159,6 +159,11 @@ def add_new_custom_field(
     if field_type == "bool" and field_value is None:
         field_value = False
 
+    if field_type == "SecretStr":
+        field_config["password"] = True
+        field_config["load_from_db"] = True
+        field_config["input_types"] = ["Text"]
+
     # If options is a list, then it's a dropdown
     # If options is None, then it's a list of strings
     is_list = isinstance(field_config.get("options"), list)

src/backend/base/langflow/graph/graph/base.py

@@ -17,7 +17,10 @@ from langflow.graph.vertex.base import Vertex
 from langflow.graph.vertex.types import InterfaceVertex, StateVertex
 from langflow.schema import Record
 from langflow.schema.schema import INPUT_FIELD_NAME, InputType
+from langflow.services.cache.utils import CacheMiss
+from langflow.services.chat.service import ChatService
 from langflow.services.deps import get_chat_service
+from langflow.services.monitor.utils import log_transaction
 
 if TYPE_CHECKING:
     from langflow.graph.schema import ResultData
@@ -704,7 +707,7 @@ class Graph:
     async def build_vertex(
         self,
         lock: asyncio.Lock,
-        set_cache_coro: Callable[["Graph", asyncio.Lock], Coroutine],
+        chat_service: ChatService,
         vertex_id: str,
         inputs_dict: Optional[Dict[str, str]] = None,
         files: Optional[list[str]] = None,
@@ -740,13 +743,14 @@ class Graph:
                 result_dict = vertex.result
             else:
                 raise ValueError(f"No result found for vertex {vertex_id}")
-
+            set_cache_coro = partial(chat_service.set_cache, key=self.flow_id)
             next_runnable_vertices, top_level_vertices = await self.get_next_and_top_level_vertices(
                 lock, set_cache_coro, vertex
             )
             return next_runnable_vertices, top_level_vertices, result_dict, params, valid, log_type, vertex
         except Exception as exc:
             logger.exception(f"Error building vertex: {exc}")
+            log_transaction(vertex, status="failure", error=str(exc))
             raise exc
 
     async def get_next_and_top_level_vertices(
@@ -811,11 +815,10 @@ class Graph:
             for vertex_id in current_batch:
                 vertex = self.get_vertex(vertex_id)
                 lock = chat_service._cache_locks[self.run_id]
-                set_cache_coro = partial(chat_service.set_cache, flow_id=self.run_id)
                 task = asyncio.create_task(
                     self.build_vertex(
                         lock=lock,
-                        set_cache_coro=set_cache_coro,
+                        chat_service=chat_service,
                         vertex_id=vertex_id,
                         user_id=self.user_id,
                         inputs_dict={},

src/backend/base/langflow/graph/schema.py

@@ -15,6 +15,7 @@ class ResultData(BaseModel):
     duration: Optional[str] = None
     component_display_name: Optional[str] = None
     component_id: Optional[str] = None
+    used_frozen_result: Optional[bool] = False
 
     @field_serializer("results")
     def serialize_results(self, value):

src/backend/base/langflow/graph/vertex/base.py

@@ -708,7 +708,8 @@ class Vertex:
 
             self._finalize_build()
 
-        return await self.get_requester_result(requester)
+        result = await self.get_requester_result(requester)
+        return result
 
     async def get_requester_result(self, requester: Optional["Vertex"]):
         # If the requester is None, this means that

src/backend/base/langflow/helpers/flow.py

@@ -1,13 +1,14 @@
 from typing import TYPE_CHECKING, Any, Awaitable, Callable, List, Optional, Tuple, Type, Union, cast
 from uuid import UUID
 
+from fastapi import Depends, HTTPException
 from pydantic.v1 import BaseModel, Field, create_model
-from sqlmodel import select
+from sqlmodel import Session, select
 
 from langflow.graph.schema import RunOutputs
 from langflow.schema.schema import INPUT_FIELD_NAME, Record
-from langflow.services.database.models.flow.model import Flow
-from langflow.services.deps import session_scope
+from langflow.services.database.models.flow import Flow
+from langflow.services.deps import get_session, session_scope
 
 if TYPE_CHECKING:
     from langflow.graph.graph.base import Graph
@@ -235,3 +236,22 @@ def get_arg_names(inputs: List["Vertex"]) -> List[dict[str, str]]:
         {"component_name": input_.display_name, "arg_name": input_.display_name.lower().replace(" ", "_")}
         for input_ in inputs
     ]
+
+
+def get_flow_by_id_or_endpoint_name(
+    flow_id_or_name: str, db: Session = Depends(get_session), user_id: Optional[UUID] = None
+) -> Flow:
+    endpoint_name = None
+    try:
+        flow_id = UUID(flow_id_or_name)
+        flow = db.get(Flow, flow_id)
+    except ValueError:
+        endpoint_name = flow_id_or_name
+        stmt = select(Flow).where(Flow.name == endpoint_name)
+        if user_id:
+            stmt = stmt.where(Flow.user_id == user_id)
+        flow = db.exec(stmt).first()
+    if flow is None:
+        raise HTTPException(status_code=404, detail=f"Flow identifier {flow_id_or_name} not found")
+
+    return flow

src/backend/base/langflow/initial_setup/setup.py

@@ -1,7 +1,10 @@
+import logging
+import os
 from collections import defaultdict
 from copy import deepcopy
 from datetime import datetime, timezone
 from pathlib import Path
+from uuid import UUID
 
 import orjson
 from emoji import demojize, purely_emoji  # type: ignore
@@ -10,10 +13,16 @@ from sqlmodel import select
 
 from langflow.base.constants import FIELD_FORMAT_ATTRIBUTES, NODE_FORMAT_ATTRIBUTES
 from langflow.interface.types import get_all_components
+from langflow.services.auth.utils import create_super_user
 from langflow.services.database.models.flow.model import Flow, FlowCreate
 from langflow.services.database.models.folder.model import Folder, FolderCreate
+from langflow.services.database.models.user.crud import get_user_by_username
 from langflow.services.deps import get_settings_service, session_scope
 
+from langflow.services.database.models.folder.utils import create_default_folder_if_it_doesnt_exist
+from langflow.services.deps import get_settings_service, session_scope, get_variable_service
+
+
 STARTER_FOLDER_NAME = "Starter Projects"
 STARTER_FOLDER_DESCRIPTION = "Starter projects to help you get started in Langflow."
 
@@ -205,6 +214,63 @@ def create_starter_folder(session):
         return session.exec(select(Folder).where(Folder.name == STARTER_FOLDER_NAME)).first()
 
 
+def _is_valid_uuid(val):
+    try:
+        uuid_obj = UUID(val)
+    except ValueError:
+        return False
+    return str(uuid_obj) == val
+
+def load_flows_from_directory():
+    settings_service = get_settings_service()
+    flows_path = settings_service.settings.load_flows_path
+    if not flows_path:
+        return
+    if not settings_service.auth_settings.AUTO_LOGIN:
+        logging.warning("AUTO_LOGIN is disabled, not loading flows from directory")
+        return
+
+    with session_scope() as session:
+        user_id = get_user_by_username(session, settings_service.auth_settings.SUPERUSER).id
+        files = [f for f in os.listdir(flows_path) if os.path.isfile(os.path.join(flows_path, f))]
+        for filename in files:
+            if not filename.endswith(".json"):
+                continue
+            logger.info(f"Loading flow from file: {filename}")
+            with open(os.path.join(flows_path, filename), "r", encoding="utf-8") as file:
+                flow = orjson.loads(file.read())
+                no_json_name = filename.replace(".json", "")
+                flow_endpoint_name = flow.get("endpoint_name")
+                if _is_valid_uuid(no_json_name):
+                    flow["id"] = no_json_name
+                flow_id = flow.get("id")
+
+                existing = find_existing_flow(session, flow_id, flow_endpoint_name)
+                if existing:
+                    logger.info(f"Updating existing flow: {flow_id} with endpoint name {flow_endpoint_name}")
+                    for key, value in flow.items():
+                        setattr(existing, key, value)
+                    existing.updated_at = datetime.utcnow()
+                    existing.user_id = user_id
+                    session.add(existing)
+                    session.commit()
+                else:
+                    logger.info(f"Creating new flow: {flow_id} with endpoint name {flow_endpoint_name}")
+                    flow["user_id"] = user_id
+                    flow = Flow.model_validate(flow, from_attributes=True)
+                    flow.updated_at = datetime.utcnow()
+                    session.add(flow)
+                session.commit()
+
+def find_existing_flow(session, flow_id, flow_endpoint_name):
+    if flow_endpoint_name:
+        stmt = select(Flow).where(Flow.endpoint_name == flow_endpoint_name)
+        if existing := session.exec(stmt).first():
+            return existing
+    stmt = select(Flow).where(Flow.id == flow_id)
+    if existing := session.exec(stmt).first():
+        return existing
+    return None
 def create_or_update_starter_projects():
     components_paths = get_settings_service().settings.components_path
     try:
@@ -249,3 +315,20 @@ def create_or_update_starter_projects():
                     project_icon_bg_color,
                     new_folder.id,
                 )
+
+
+def initialize_super_user_if_needed():
+    settings_service = get_settings_service()
+    if not settings_service.auth_settings.AUTO_LOGIN:
+        return
+    username = settings_service.auth_settings.SUPERUSER
+    password = settings_service.auth_settings.SUPERUSER_PASSWORD
+    if not username or not password:
+        raise ValueError("SUPERUSER and SUPERUSER_PASSWORD must be set in the settings if AUTO_LOGIN is true.")
+
+    with session_scope() as session:
+        super_user = create_super_user(db=session, username=username, password=password)
+        get_variable_service().initialize_user_variables(super_user.id, session)
+        create_default_folder_if_it_doesnt_exist(session, super_user.id)
+        session.commit()
+        logger.info("Super user initialized")

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, world!).json

@@ -45,7 +45,9 @@
                 "name": "template",
                 "display_name": "Template",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -84,14 +86,22 @@
             "is_input": null,
             "is_output": null,
             "is_composition": null,
-            "base_classes": ["object", "str", "Text"],
+            "base_classes": [
+              "object",
+              "str",
+              "Text"
+            ],
             "name": "",
             "display_name": "Prompt",
             "documentation": "",
             "custom_fields": {
-              "template": ["user_input"]
+              "template": [
+                "user_input"
+              ]
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "full_path": null,
             "field_formatters": {},
             "frozen": false,
@@ -140,7 +150,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "code": {
                 "type": "code",
@@ -149,7 +161,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float = 0.1,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -223,7 +235,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_base": {
                 "type": "str",
@@ -242,7 +256,9 @@
                 "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_key": {
                 "type": "str",
@@ -261,7 +277,9 @@
                 "info": "The OpenAI API Key to use for the OpenAI model.",
                 "load_from_db": true,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": "OPENAI_API_KEY"
               },
               "stream": {
@@ -300,11 +318,13 @@
                 "info": "System message to pass to the model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "temperature": {
                 "type": "float",
-                "required": true,
+                "required": false,
                 "placeholder": "",
                 "list": false,
                 "show": true,
@@ -331,7 +351,11 @@
             },
             "description": "Generates text using OpenAI LLMs.",
             "icon": "OpenAI",
-            "base_classes": ["object", "Text", "str"],
+            "base_classes": [
+              "object",
+              "Text",
+              "str"
+            ],
             "display_name": "OpenAI",
             "documentation": "",
             "custom_fields": {
@@ -345,7 +369,9 @@
               "stream": null,
               "system_message": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [
@@ -416,7 +442,9 @@
                 "name": "input_value",
                 "display_name": "Message",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -440,7 +468,9 @@
                 "info": "In case of Message being a Record, this template will be used to convert it to text.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "return_record": {
                 "type": "bool",
@@ -472,7 +502,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -480,7 +513,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -500,7 +535,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -519,13 +556,20 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
-            "base_classes": ["Record", "Text", "str", "object"],
+            "base_classes": [
+              "Record",
+              "Text",
+              "str",
+              "object"
+            ],
             "display_name": "Chat Output",
             "documentation": "",
             "custom_fields": {
@@ -536,7 +580,10 @@
               "return_record": null,
               "record_template": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -632,7 +679,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -640,7 +690,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -660,7 +712,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -679,13 +733,20 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Get chat inputs from the Playground.",
             "icon": "ChatInput",
-            "base_classes": ["object", "Record", "str", "Text"],
+            "base_classes": [
+              "object",
+              "Record",
+              "str",
+              "Text"
+            ],
             "display_name": "Chat Input",
             "documentation": "",
             "custom_fields": {
@@ -695,7 +756,10 @@
               "session_id": null,
               "return_record": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -716,18 +780,24 @@
     "edges": [
       {
         "source": "OpenAIModel-k39HS",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153Text\u0153,\u0153str\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-k39HS\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-k39HSœ}",
         "target": "ChatOutput-njtka",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-njtka\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-njtkaœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-njtka",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "Text", "str"],
+            "baseClasses": [
+              "object",
+              "Text",
+              "str"
+            ],
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-k39HS"
           }
@@ -736,22 +806,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-OpenAIModel-k39HS{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153Text\u0153,\u0153str\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-k39HS\u0153}-ChatOutput-njtka{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-njtka\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-OpenAIModel-k39HS{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-k39HSœ}-ChatOutput-njtka{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-njtkaœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "Prompt-uxBqP",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-uxBqP\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-uxBqPœ}",
         "target": "OpenAIModel-k39HS",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-k39HS\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-k39HSœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-k39HS",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "str", "Text"],
+            "baseClasses": [
+              "object",
+              "str",
+              "Text"
+            ],
             "dataType": "Prompt",
             "id": "Prompt-uxBqP"
           }
@@ -760,22 +836,32 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-Prompt-uxBqP{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-uxBqP\u0153}-OpenAIModel-k39HS{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-k39HS\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-Prompt-uxBqP{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-uxBqPœ}-OpenAIModel-k39HS{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-k39HSœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "ChatInput-P3fgL",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153Record\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153ChatInput\u0153,\u0153id\u0153:\u0153ChatInput-P3fgL\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-P3fgLœ}",
         "target": "Prompt-uxBqP",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153user_input\u0153,\u0153id\u0153:\u0153Prompt-uxBqP\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-uxBqPœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "user_input",
             "id": "Prompt-uxBqP",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "Record", "str", "Text"],
+            "baseClasses": [
+              "object",
+              "Record",
+              "str",
+              "Text"
+            ],
             "dataType": "ChatInput",
             "id": "ChatInput-P3fgL"
           }
@@ -784,7 +870,7 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-ChatInput-P3fgL{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153Record\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153ChatInput\u0153,\u0153id\u0153:\u0153ChatInput-P3fgL\u0153}-Prompt-uxBqP{\u0153fieldName\u0153:\u0153user_input\u0153,\u0153id\u0153:\u0153Prompt-uxBqP\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-ChatInput-P3fgL{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-P3fgLœ}-Prompt-uxBqP{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-uxBqPœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
       }
     ],
     "viewport": {
@@ -797,4 +883,4 @@
   "name": "Basic Prompting (Hello, World)",
   "last_tested_version": "1.0.0a4",
   "is_component": false
-}
+}

src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json

@@ -45,7 +45,9 @@
                 "name": "template",
                 "display_name": "Template",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -136,14 +138,24 @@
             "is_input": null,
             "is_output": null,
             "is_composition": null,
-            "base_classes": ["object", "Text", "str"],
+            "base_classes": [
+              "object",
+              "Text",
+              "str"
+            ],
             "name": "",
             "display_name": "Prompt",
             "documentation": "",
             "custom_fields": {
-              "template": ["reference_1", "reference_2", "instructions"]
+              "template": [
+                "reference_1",
+                "reference_2",
+                "instructions"
+              ]
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "full_path": null,
             "field_formatters": {},
             "frozen": false,
@@ -210,7 +222,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": [
                   "https://www.promptingguide.ai/techniques/prompt_chaining"
                 ]
@@ -219,13 +233,17 @@
             },
             "description": "Fetch content from one or more URLs.",
             "icon": "layout-template",
-            "base_classes": ["Record"],
+            "base_classes": [
+              "Record"
+            ],
             "display_name": "URL",
             "documentation": "",
             "custom_fields": {
               "urls": null
             },
-            "output_types": ["Record"],
+            "output_types": [
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -284,7 +302,9 @@
                 "name": "input_value",
                 "display_name": "Message",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -308,7 +328,9 @@
                 "info": "In case of Message being a Record, this template will be used to convert it to text.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "return_record": {
                 "type": "bool",
@@ -340,7 +362,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -348,7 +373,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -368,7 +395,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -387,13 +416,20 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
-            "base_classes": ["Text", "Record", "object", "str"],
+            "base_classes": [
+              "Text",
+              "Record",
+              "object",
+              "str"
+            ],
             "display_name": "Chat Output",
             "documentation": "",
             "custom_fields": {
@@ -404,7 +440,10 @@
               "return_record": null,
               "record_template": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -444,7 +483,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "code": {
                 "type": "code",
@@ -453,7 +494,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float = 0.1,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -527,7 +568,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_base": {
                 "type": "str",
@@ -546,7 +589,9 @@
                 "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_key": {
                 "type": "str",
@@ -565,7 +610,9 @@
                 "info": "The OpenAI API Key to use for the OpenAI model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": "OPENAI_API_KEY"
               },
               "stream": {
@@ -604,11 +651,13 @@
                 "info": "System message to pass to the model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "temperature": {
                 "type": "float",
-                "required": true,
+                "required": false,
                 "placeholder": "",
                 "list": false,
                 "show": true,
@@ -635,7 +684,11 @@
             },
             "description": "Generates text using OpenAI LLMs.",
             "icon": "OpenAI",
-            "base_classes": ["str", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Text",
+              "object"
+            ],
             "display_name": "OpenAI",
             "documentation": "",
             "custom_fields": {
@@ -649,7 +702,9 @@
               "stream": null,
               "system_message": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [
@@ -722,20 +777,28 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
-                "value": ["https://www.promptingguide.ai/introduction/basics"]
+                "input_types": [
+                  "Text"
+                ],
+                "value": [
+                  "https://www.promptingguide.ai/introduction/basics"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Fetch content from one or more URLs.",
             "icon": "layout-template",
-            "base_classes": ["Record"],
+            "base_classes": [
+              "Record"
+            ],
             "display_name": "URL",
             "documentation": "",
             "custom_fields": {
               "urls": null
             },
-            "output_types": ["Record"],
+            "output_types": [
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -795,7 +858,10 @@
                 "name": "input_value",
                 "display_name": "Value",
                 "advanced": false,
-                "input_types": ["Record", "Text"],
+                "input_types": [
+                  "Record",
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "Text or Record to be passed as input.",
                 "load_from_db": false,
@@ -819,20 +885,28 @@
                 "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Get text inputs from the Playground.",
             "icon": "type",
-            "base_classes": ["object", "Text", "str"],
+            "base_classes": [
+              "object",
+              "Text",
+              "str"
+            ],
             "display_name": "Instructions",
             "documentation": "",
             "custom_fields": {
               "input_value": null,
               "record_template": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -854,18 +928,25 @@
       {
         "source": "URL-HYPkR",
         "target": "Prompt-Rse03",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153Record\u0153],\u0153dataType\u0153:\u0153URL\u0153,\u0153id\u0153:\u0153URL-HYPkR\u0153}",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153reference_2\u0153,\u0153id\u0153:\u0153Prompt-Rse03\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
-        "id": "reactflow__edge-URL-HYPkR{\u0153baseClasses\u0153:[\u0153Record\u0153],\u0153dataType\u0153:\u0153URL\u0153,\u0153id\u0153:\u0153URL-HYPkR\u0153}-Prompt-Rse03{\u0153fieldName\u0153:\u0153reference_2\u0153,\u0153id\u0153:\u0153Prompt-Rse03\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œRecordœ],œdataTypeœ:œURLœ,œidœ:œURL-HYPkRœ}",
+        "targetHandle": "{œfieldNameœ:œreference_2œ,œidœ:œPrompt-Rse03œ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
+        "id": "reactflow__edge-URL-HYPkR{œbaseClassesœ:[œRecordœ],œdataTypeœ:œURLœ,œidœ:œURL-HYPkRœ}-Prompt-Rse03{œfieldNameœ:œreference_2œ,œidœ:œPrompt-Rse03œ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "reference_2",
             "id": "Prompt-Rse03",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["Record"],
+            "baseClasses": [
+              "Record"
+            ],
             "dataType": "URL",
             "id": "URL-HYPkR"
           }
@@ -878,18 +959,24 @@
       },
       {
         "source": "OpenAIModel-gi29P",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-gi29P\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-gi29Pœ}",
         "target": "ChatOutput-JPlxl",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-JPlxl\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-JPlxlœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-JPlxl",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["str", "Text", "object"],
+            "baseClasses": [
+              "str",
+              "Text",
+              "object"
+            ],
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-gi29P"
           }
@@ -898,22 +985,29 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-OpenAIModel-gi29P{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-gi29P\u0153}-ChatOutput-JPlxl{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-JPlxl\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-OpenAIModel-gi29P{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-gi29Pœ}-ChatOutput-JPlxl{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-JPlxlœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "URL-2cX90",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153Record\u0153],\u0153dataType\u0153:\u0153URL\u0153,\u0153id\u0153:\u0153URL-2cX90\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œRecordœ],œdataTypeœ:œURLœ,œidœ:œURL-2cX90œ}",
         "target": "Prompt-Rse03",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153reference_1\u0153,\u0153id\u0153:\u0153Prompt-Rse03\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œreference_1œ,œidœ:œPrompt-Rse03œ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "reference_1",
             "id": "Prompt-Rse03",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["Record"],
+            "baseClasses": [
+              "Record"
+            ],
             "dataType": "URL",
             "id": "URL-2cX90"
           }
@@ -922,22 +1016,31 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-URL-2cX90{\u0153baseClasses\u0153:[\u0153Record\u0153],\u0153dataType\u0153:\u0153URL\u0153,\u0153id\u0153:\u0153URL-2cX90\u0153}-Prompt-Rse03{\u0153fieldName\u0153:\u0153reference_1\u0153,\u0153id\u0153:\u0153Prompt-Rse03\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-URL-2cX90{œbaseClassesœ:[œRecordœ],œdataTypeœ:œURLœ,œidœ:œURL-2cX90œ}-Prompt-Rse03{œfieldNameœ:œreference_1œ,œidœ:œPrompt-Rse03œ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "TextInput-og8Or",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153Text\u0153,\u0153str\u0153],\u0153dataType\u0153:\u0153TextInput\u0153,\u0153id\u0153:\u0153TextInput-og8Or\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-og8Orœ}",
         "target": "Prompt-Rse03",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153instructions\u0153,\u0153id\u0153:\u0153Prompt-Rse03\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-Rse03œ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "instructions",
             "id": "Prompt-Rse03",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "Text", "str"],
+            "baseClasses": [
+              "object",
+              "Text",
+              "str"
+            ],
             "dataType": "TextInput",
             "id": "TextInput-og8Or"
           }
@@ -946,22 +1049,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-TextInput-og8Or{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153Text\u0153,\u0153str\u0153],\u0153dataType\u0153:\u0153TextInput\u0153,\u0153id\u0153:\u0153TextInput-og8Or\u0153}-Prompt-Rse03{\u0153fieldName\u0153:\u0153instructions\u0153,\u0153id\u0153:\u0153Prompt-Rse03\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-TextInput-og8Or{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-og8Orœ}-Prompt-Rse03{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-Rse03œ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "Prompt-Rse03",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153Text\u0153,\u0153str\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-Rse03\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-Rse03œ}",
         "target": "OpenAIModel-gi29P",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-gi29P\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-gi29Pœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-gi29P",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "Text", "str"],
+            "baseClasses": [
+              "object",
+              "Text",
+              "str"
+            ],
             "dataType": "Prompt",
             "id": "Prompt-Rse03"
           }
@@ -970,7 +1079,7 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-Prompt-Rse03{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153Text\u0153,\u0153str\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-Rse03\u0153}-OpenAIModel-gi29P{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-gi29P\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "id": "reactflow__edge-Prompt-Rse03{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-Rse03œ}-OpenAIModel-gi29P{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-gi29Pœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "selected": false
       }
     ],
@@ -984,4 +1093,4 @@
   "name": "Blog Writer",
   "last_tested_version": "1.0.0a0",
   "is_component": false
-}
+}

src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json

@@ -45,7 +45,9 @@
                 "name": "template",
                 "display_name": "Template",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -110,14 +112,23 @@
             "is_input": null,
             "is_output": null,
             "is_composition": null,
-            "base_classes": ["object", "str", "Text"],
+            "base_classes": [
+              "object",
+              "str",
+              "Text"
+            ],
             "name": "",
             "display_name": "Prompt",
             "documentation": "",
             "custom_fields": {
-              "template": ["Document", "Question"]
+              "template": [
+                "Document",
+                "Question"
+              ]
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "full_path": null,
             "field_formatters": {},
             "frozen": false,
@@ -220,14 +231,18 @@
               "_type": "CustomComponent"
             },
             "description": "A generic file loader.",
-            "base_classes": ["Record"],
+            "base_classes": [
+              "Record"
+            ],
             "display_name": "Files",
             "documentation": "",
             "custom_fields": {
               "path": null,
               "silent_errors": null
             },
-            "output_types": ["Record"],
+            "output_types": [
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -323,7 +338,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -331,7 +349,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -351,7 +371,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -370,13 +392,20 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Get chat inputs from the Playground.",
             "icon": "ChatInput",
-            "base_classes": ["str", "Record", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Record",
+              "Text",
+              "object"
+            ],
             "display_name": "Chat Input",
             "documentation": "",
             "custom_fields": {
@@ -386,7 +415,10 @@
               "session_id": null,
               "return_record": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -445,7 +477,9 @@
                 "name": "input_value",
                 "display_name": "Message",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -481,7 +515,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -489,7 +526,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -509,7 +548,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -528,13 +569,20 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
-            "base_classes": ["str", "Record", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Record",
+              "Text",
+              "object"
+            ],
             "display_name": "Chat Output",
             "documentation": "",
             "custom_fields": {
@@ -544,7 +592,10 @@
               "session_id": null,
               "return_record": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -589,7 +640,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "code": {
                 "type": "code",
@@ -598,7 +651,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float = 0.1,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -672,7 +725,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_base": {
                 "type": "str",
@@ -691,7 +746,9 @@
                 "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_key": {
                 "type": "str",
@@ -710,7 +767,9 @@
                 "info": "The OpenAI API Key to use for the OpenAI model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": "OPENAI_API_KEY"
               },
               "stream": {
@@ -749,11 +808,13 @@
                 "info": "System message to pass to the model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "temperature": {
                 "type": "float",
-                "required": true,
+                "required": false,
                 "placeholder": "",
                 "list": false,
                 "show": true,
@@ -780,7 +841,11 @@
             },
             "description": "Generates text using OpenAI LLMs.",
             "icon": "OpenAI",
-            "base_classes": ["object", "str", "Text"],
+            "base_classes": [
+              "object",
+              "str",
+              "Text"
+            ],
             "display_name": "OpenAI",
             "documentation": "",
             "custom_fields": {
@@ -794,7 +859,9 @@
               "stream": null,
               "system_message": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [
@@ -825,18 +892,28 @@
     "edges": [
       {
         "source": "ChatInput-MsSJ9",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Record\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153ChatInput\u0153,\u0153id\u0153:\u0153ChatInput-MsSJ9\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œRecordœ,œTextœ,œobjectœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-MsSJ9œ}",
         "target": "Prompt-tHwPf",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153Question\u0153,\u0153id\u0153:\u0153Prompt-tHwPf\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œQuestionœ,œidœ:œPrompt-tHwPfœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "Question",
             "id": "Prompt-tHwPf",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["str", "Record", "Text", "object"],
+            "baseClasses": [
+              "str",
+              "Record",
+              "Text",
+              "object"
+            ],
             "dataType": "ChatInput",
             "id": "ChatInput-MsSJ9"
           }
@@ -845,22 +922,29 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-ChatInput-MsSJ9{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Record\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153ChatInput\u0153,\u0153id\u0153:\u0153ChatInput-MsSJ9\u0153}-Prompt-tHwPf{\u0153fieldName\u0153:\u0153Question\u0153,\u0153id\u0153:\u0153Prompt-tHwPf\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-ChatInput-MsSJ9{œbaseClassesœ:[œstrœ,œRecordœ,œTextœ,œobjectœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-MsSJ9œ}-Prompt-tHwPf{œfieldNameœ:œQuestionœ,œidœ:œPrompt-tHwPfœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "File-6TEsD",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153Record\u0153],\u0153dataType\u0153:\u0153File\u0153,\u0153id\u0153:\u0153File-6TEsD\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œRecordœ],œdataTypeœ:œFileœ,œidœ:œFile-6TEsDœ}",
         "target": "Prompt-tHwPf",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153Document\u0153,\u0153id\u0153:\u0153Prompt-tHwPf\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œDocumentœ,œidœ:œPrompt-tHwPfœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "Document",
             "id": "Prompt-tHwPf",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["Record"],
+            "baseClasses": [
+              "Record"
+            ],
             "dataType": "File",
             "id": "File-6TEsD"
           }
@@ -869,22 +953,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-File-6TEsD{\u0153baseClasses\u0153:[\u0153Record\u0153],\u0153dataType\u0153:\u0153File\u0153,\u0153id\u0153:\u0153File-6TEsD\u0153}-Prompt-tHwPf{\u0153fieldName\u0153:\u0153Document\u0153,\u0153id\u0153:\u0153Prompt-tHwPf\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-File-6TEsD{œbaseClassesœ:[œRecordœ],œdataTypeœ:œFileœ,œidœ:œFile-6TEsDœ}-Prompt-tHwPf{œfieldNameœ:œDocumentœ,œidœ:œPrompt-tHwPfœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "Prompt-tHwPf",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-tHwPf\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-tHwPfœ}",
         "target": "OpenAIModel-Bt067",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-Bt067\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Bt067œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-Bt067",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "str", "Text"],
+            "baseClasses": [
+              "object",
+              "str",
+              "Text"
+            ],
             "dataType": "Prompt",
             "id": "Prompt-tHwPf"
           }
@@ -893,22 +983,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-Prompt-tHwPf{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-tHwPf\u0153}-OpenAIModel-Bt067{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-Bt067\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-Prompt-tHwPf{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-tHwPfœ}-OpenAIModel-Bt067{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Bt067œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "OpenAIModel-Bt067",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-Bt067\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Bt067œ}",
         "target": "ChatOutput-F5Awj",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-F5Awj\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-F5Awjœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-F5Awj",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "str", "Text"],
+            "baseClasses": [
+              "object",
+              "str",
+              "Text"
+            ],
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-Bt067"
           }
@@ -917,7 +1013,7 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-OpenAIModel-Bt067{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-Bt067\u0153}-ChatOutput-F5Awj{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-F5Awj\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-OpenAIModel-Bt067{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Bt067œ}-ChatOutput-F5Awj{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-F5Awjœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       }
     ],
     "viewport": {
@@ -930,4 +1026,4 @@
   "name": "Document QA",
   "last_tested_version": "1.0.0a0",
   "is_component": false
-}
+}

src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json

@@ -1,6 +1,6 @@
 {
   "id": "08d5cccf-d098-4367-b14b-1078429c9ed9",
-  "icon": "\ud83e\udd16",
+  "icon": "🤖",
   "icon_bg_color": "#FFD700",
   "data": {
     "nodes": [
@@ -83,7 +83,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -91,7 +94,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -111,7 +116,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -130,14 +137,21 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": "MySessionID"
               },
               "_type": "CustomComponent"
             },
             "description": "Get chat inputs from the Playground.",
             "icon": "ChatInput",
-            "base_classes": ["Text", "object", "Record", "str"],
+            "base_classes": [
+              "Text",
+              "object",
+              "Record",
+              "str"
+            ],
             "display_name": "Chat Input",
             "documentation": "",
             "custom_fields": {
@@ -147,7 +161,10 @@
               "session_id": null,
               "return_record": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -206,7 +223,9 @@
                 "name": "input_value",
                 "display_name": "Message",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -242,7 +261,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -250,7 +272,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -270,7 +294,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -289,14 +315,21 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": "MySessionID"
               },
               "_type": "CustomComponent"
             },
             "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
-            "base_classes": ["Text", "object", "Record", "str"],
+            "base_classes": [
+              "Text",
+              "object",
+              "Record",
+              "str"
+            ],
             "display_name": "Chat Output",
             "documentation": "",
             "custom_fields": {
@@ -306,7 +339,10 @@
               "session_id": null,
               "return_record": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -382,7 +418,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Ascending", "Descending"],
+                "options": [
+                  "Ascending",
+                  "Descending"
+                ],
                 "name": "order",
                 "display_name": "Order",
                 "advanced": true,
@@ -390,7 +429,9 @@
                 "info": "Order of the messages.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "record_template": {
                 "type": "str",
@@ -410,7 +451,9 @@
                 "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender": {
                 "type": "str",
@@ -423,7 +466,11 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User", "Machine and User"],
+                "options": [
+                  "Machine",
+                  "User",
+                  "Machine and User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": false,
@@ -431,7 +478,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -450,7 +499,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -465,7 +516,9 @@
                 "name": "session_id",
                 "display_name": "Session ID",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "Session ID of the chat history.",
                 "load_from_db": false,
@@ -476,7 +529,11 @@
             },
             "description": "Retrieves stored chat messages given a specific Session ID.",
             "icon": "history",
-            "base_classes": ["str", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Text",
+              "object"
+            ],
             "display_name": "Chat Memory",
             "documentation": "",
             "custom_fields": {
@@ -487,7 +544,9 @@
               "order": null,
               "record_template": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -549,7 +608,9 @@
                 "name": "template",
                 "display_name": "Template",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -614,14 +675,23 @@
             "is_input": null,
             "is_output": null,
             "is_composition": null,
-            "base_classes": ["Text", "str", "object"],
+            "base_classes": [
+              "Text",
+              "str",
+              "object"
+            ],
             "name": "",
             "display_name": "Prompt",
             "documentation": "",
             "custom_fields": {
-              "template": ["context", "user_message"]
+              "template": [
+                "context",
+                "user_message"
+              ]
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "full_path": null,
             "field_formatters": {},
             "frozen": false,
@@ -670,7 +740,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "code": {
                 "type": "code",
@@ -679,7 +751,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float = 0.1,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -753,7 +825,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_base": {
                 "type": "str",
@@ -772,7 +846,9 @@
                 "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_key": {
                 "type": "str",
@@ -791,7 +867,9 @@
                 "info": "The OpenAI API Key to use for the OpenAI model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": "OPENAI_API_KEY"
               },
               "stream": {
@@ -830,11 +908,13 @@
                 "info": "System message to pass to the model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "temperature": {
                 "type": "float",
-                "required": true,
+                "required": false,
                 "placeholder": "",
                 "list": false,
                 "show": true,
@@ -861,7 +941,11 @@
             },
             "description": "Generates text using OpenAI LLMs.",
             "icon": "OpenAI",
-            "base_classes": ["str", "object", "Text"],
+            "base_classes": [
+              "str",
+              "object",
+              "Text"
+            ],
             "display_name": "OpenAI",
             "documentation": "",
             "custom_fields": {
@@ -875,7 +959,9 @@
               "stream": null,
               "system_message": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [
@@ -927,7 +1013,10 @@
                 "name": "input_value",
                 "display_name": "Value",
                 "advanced": false,
-                "input_types": ["Record", "Text"],
+                "input_types": [
+                  "Record",
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "Text or Record to be passed as output.",
                 "load_from_db": false,
@@ -969,20 +1058,28 @@
                 "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Display a text output in the Playground.",
             "icon": "type",
-            "base_classes": ["str", "object", "Text"],
+            "base_classes": [
+              "str",
+              "object",
+              "Text"
+            ],
             "display_name": "Inspect Memory",
             "documentation": "",
             "custom_fields": {
               "input_value": null,
               "record_template": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -1003,18 +1100,27 @@
     "edges": [
       {
         "source": "MemoryComponent-cdA1J",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153MemoryComponent\u0153,\u0153id\u0153:\u0153MemoryComponent-cdA1J\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œMemoryComponentœ,œidœ:œMemoryComponent-cdA1Jœ}",
         "target": "Prompt-ODkUx",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153context\u0153,\u0153id\u0153:\u0153Prompt-ODkUx\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œcontextœ,œidœ:œPrompt-ODkUxœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "context",
             "type": "str",
             "id": "Prompt-ODkUx",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"]
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ]
           },
           "sourceHandle": {
-            "baseClasses": ["str", "Text", "object"],
+            "baseClasses": [
+              "str",
+              "Text",
+              "object"
+            ],
             "dataType": "MemoryComponent",
             "id": "MemoryComponent-cdA1J"
           }
@@ -1023,23 +1129,33 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-MemoryComponent-cdA1J{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153MemoryComponent\u0153,\u0153id\u0153:\u0153MemoryComponent-cdA1J\u0153}-Prompt-ODkUx{\u0153fieldName\u0153:\u0153context\u0153,\u0153id\u0153:\u0153Prompt-ODkUx\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "id": "reactflow__edge-MemoryComponent-cdA1J{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œMemoryComponentœ,œidœ:œMemoryComponent-cdA1Jœ}-Prompt-ODkUx{œfieldNameœ:œcontextœ,œidœ:œPrompt-ODkUxœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "selected": false
       },
       {
         "source": "ChatInput-t7F8v",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153Text\u0153,\u0153object\u0153,\u0153Record\u0153,\u0153str\u0153],\u0153dataType\u0153:\u0153ChatInput\u0153,\u0153id\u0153:\u0153ChatInput-t7F8v\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œTextœ,œobjectœ,œRecordœ,œstrœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-t7F8vœ}",
         "target": "Prompt-ODkUx",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153user_message\u0153,\u0153id\u0153:\u0153Prompt-ODkUx\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-ODkUxœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "user_message",
             "type": "str",
             "id": "Prompt-ODkUx",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"]
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ]
           },
           "sourceHandle": {
-            "baseClasses": ["Text", "object", "Record", "str"],
+            "baseClasses": [
+              "Text",
+              "object",
+              "Record",
+              "str"
+            ],
             "dataType": "ChatInput",
             "id": "ChatInput-t7F8v"
           }
@@ -1048,23 +1164,29 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-ChatInput-t7F8v{\u0153baseClasses\u0153:[\u0153Text\u0153,\u0153object\u0153,\u0153Record\u0153,\u0153str\u0153],\u0153dataType\u0153:\u0153ChatInput\u0153,\u0153id\u0153:\u0153ChatInput-t7F8v\u0153}-Prompt-ODkUx{\u0153fieldName\u0153:\u0153user_message\u0153,\u0153id\u0153:\u0153Prompt-ODkUx\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "id": "reactflow__edge-ChatInput-t7F8v{œbaseClassesœ:[œTextœ,œobjectœ,œRecordœ,œstrœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-t7F8vœ}-Prompt-ODkUx{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-ODkUxœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "selected": false
       },
       {
         "source": "Prompt-ODkUx",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153Text\u0153,\u0153str\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-ODkUx\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œTextœ,œstrœ,œobjectœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-ODkUxœ}",
         "target": "OpenAIModel-9RykF",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-9RykF\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-9RykFœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-9RykF",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["Text", "str", "object"],
+            "baseClasses": [
+              "Text",
+              "str",
+              "object"
+            ],
             "dataType": "Prompt",
             "id": "Prompt-ODkUx"
           }
@@ -1073,22 +1195,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-Prompt-ODkUx{\u0153baseClasses\u0153:[\u0153Text\u0153,\u0153str\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-ODkUx\u0153}-OpenAIModel-9RykF{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-9RykF\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-Prompt-ODkUx{œbaseClassesœ:[œTextœ,œstrœ,œobjectœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-ODkUxœ}-OpenAIModel-9RykF{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-9RykFœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "OpenAIModel-9RykF",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153object\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-9RykF\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œobjectœ,œTextœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-9RykFœ}",
         "target": "ChatOutput-P1jEe",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-P1jEe\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-P1jEeœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-P1jEe",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["str", "object", "Text"],
+            "baseClasses": [
+              "str",
+              "object",
+              "Text"
+            ],
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-9RykF"
           }
@@ -1097,22 +1225,29 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-OpenAIModel-9RykF{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153object\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-9RykF\u0153}-ChatOutput-P1jEe{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-P1jEe\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-OpenAIModel-9RykF{œbaseClassesœ:[œstrœ,œobjectœ,œTextœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-9RykFœ}-ChatOutput-P1jEe{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-P1jEeœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "MemoryComponent-cdA1J",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153MemoryComponent\u0153,\u0153id\u0153:\u0153MemoryComponent-cdA1J\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œMemoryComponentœ,œidœ:œMemoryComponent-cdA1Jœ}",
         "target": "TextOutput-vrs6T",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153TextOutput-vrs6T\u0153,\u0153inputTypes\u0153:[\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-vrs6Tœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "TextOutput-vrs6T",
-            "inputTypes": ["Record", "Text"],
+            "inputTypes": [
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["str", "Text", "object"],
+            "baseClasses": [
+              "str",
+              "Text",
+              "object"
+            ],
             "dataType": "MemoryComponent",
             "id": "MemoryComponent-cdA1J"
           }
@@ -1121,7 +1256,7 @@
           "stroke": "#555"
         },
         "className": "stroke-foreground stroke-connection",
-        "id": "reactflow__edge-MemoryComponent-cdA1J{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153MemoryComponent\u0153,\u0153id\u0153:\u0153MemoryComponent-cdA1J\u0153}-TextOutput-vrs6T{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153TextOutput-vrs6T\u0153,\u0153inputTypes\u0153:[\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-MemoryComponent-cdA1J{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œMemoryComponentœ,œidœ:œMemoryComponent-cdA1Jœ}-TextOutput-vrs6T{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-vrs6Tœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}"
       }
     ],
     "viewport": {
@@ -1134,4 +1269,4 @@
   "name": "Memory Chatbot",
   "last_tested_version": "1.0.0a0",
   "is_component": false
-}
+}

src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json

@@ -45,7 +45,9 @@
                 "name": "template",
                 "display_name": "Template",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -84,14 +86,22 @@
             "is_input": null,
             "is_output": null,
             "is_composition": null,
-            "base_classes": ["object", "str", "Text"],
+            "base_classes": [
+              "object",
+              "str",
+              "Text"
+            ],
             "name": "",
             "display_name": "Prompt",
             "documentation": "",
             "custom_fields": {
-              "template": ["document"]
+              "template": [
+                "document"
+              ]
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "full_path": null,
             "field_formatters": {},
             "frozen": false,
@@ -155,7 +165,9 @@
                 "name": "template",
                 "display_name": "Template",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -194,14 +206,22 @@
             "is_input": null,
             "is_output": null,
             "is_composition": null,
-            "base_classes": ["object", "str", "Text"],
+            "base_classes": [
+              "object",
+              "str",
+              "Text"
+            ],
             "name": "",
             "display_name": "Prompt",
             "documentation": "",
             "custom_fields": {
-              "template": ["summary"]
+              "template": [
+                "summary"
+              ]
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "full_path": null,
             "field_formatters": {},
             "frozen": false,
@@ -260,7 +280,9 @@
                 "name": "input_value",
                 "display_name": "Message",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -284,7 +306,9 @@
                 "info": "In case of Message being a Record, this template will be used to convert it to text.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "return_record": {
                 "type": "bool",
@@ -316,7 +340,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -324,7 +351,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -344,7 +373,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -363,13 +394,20 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
-            "base_classes": ["object", "Record", "Text", "str"],
+            "base_classes": [
+              "object",
+              "Record",
+              "Text",
+              "str"
+            ],
             "display_name": "Chat Output",
             "documentation": "",
             "custom_fields": {
@@ -380,7 +418,10 @@
               "return_record": null,
               "record_template": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -435,7 +476,9 @@
                 "name": "input_value",
                 "display_name": "Message",
                 "advanced": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "",
                 "load_from_db": false,
@@ -459,7 +502,9 @@
                 "info": "In case of Message being a Record, this template will be used to convert it to text.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "return_record": {
                 "type": "bool",
@@ -491,7 +536,10 @@
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
-                "options": ["Machine", "User"],
+                "options": [
+                  "Machine",
+                  "User"
+                ],
                 "name": "sender",
                 "display_name": "Sender Type",
                 "advanced": true,
@@ -499,7 +547,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "sender_name": {
                 "type": "str",
@@ -519,7 +569,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "session_id": {
                 "type": "str",
@@ -538,13 +590,20 @@
                 "info": "If provided, the message will be stored in the memory.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Display a chat message in the Playground.",
             "icon": "ChatOutput",
-            "base_classes": ["object", "Record", "Text", "str"],
+            "base_classes": [
+              "object",
+              "Record",
+              "Text",
+              "str"
+            ],
             "display_name": "Chat Output",
             "documentation": "",
             "custom_fields": {
@@ -555,7 +614,10 @@
               "return_record": null,
               "record_template": null
             },
-            "output_types": ["Text", "Record"],
+            "output_types": [
+              "Text",
+              "Record"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -610,7 +672,10 @@
                 "name": "input_value",
                 "display_name": "Value",
                 "advanced": false,
-                "input_types": ["Record", "Text"],
+                "input_types": [
+                  "Record",
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "Text or Record to be passed as input.",
                 "load_from_db": false,
@@ -634,20 +699,28 @@
                 "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Get text inputs from the Playground.",
             "icon": "type",
-            "base_classes": ["str", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Text",
+              "object"
+            ],
             "display_name": "Text Input",
             "documentation": "",
             "custom_fields": {
               "input_value": null,
               "record_template": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -689,7 +762,10 @@
                 "name": "input_value",
                 "display_name": "Value",
                 "advanced": false,
-                "input_types": ["Record", "Text"],
+                "input_types": [
+                  "Record",
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "Text or Record to be passed as output.",
                 "load_from_db": false,
@@ -731,20 +807,28 @@
                 "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Display a text output in the Playground.",
             "icon": "type",
-            "base_classes": ["str", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Text",
+              "object"
+            ],
             "display_name": "First Prompt",
             "documentation": "",
             "custom_fields": {
               "input_value": null,
               "record_template": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -789,7 +873,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "code": {
                 "type": "code",
@@ -798,7 +884,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float = 0.1,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -872,7 +958,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_base": {
                 "type": "str",
@@ -891,7 +979,9 @@
                 "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_key": {
                 "type": "str",
@@ -910,7 +1000,9 @@
                 "info": "The OpenAI API Key to use for the OpenAI model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": "OPENAI_API_KEY"
               },
               "stream": {
@@ -949,11 +1041,13 @@
                 "info": "System message to pass to the model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "temperature": {
                 "type": "float",
-                "required": true,
+                "required": false,
                 "placeholder": "",
                 "list": false,
                 "show": true,
@@ -980,7 +1074,11 @@
             },
             "description": "Generates text using OpenAI LLMs.",
             "icon": "OpenAI",
-            "base_classes": ["str", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Text",
+              "object"
+            ],
             "display_name": "OpenAI",
             "documentation": "",
             "custom_fields": {
@@ -994,7 +1092,9 @@
               "stream": null,
               "system_message": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [
@@ -1046,7 +1146,10 @@
                 "name": "input_value",
                 "display_name": "Value",
                 "advanced": false,
-                "input_types": ["Record", "Text"],
+                "input_types": [
+                  "Record",
+                  "Text"
+                ],
                 "dynamic": false,
                 "info": "Text or Record to be passed as output.",
                 "load_from_db": false,
@@ -1088,20 +1191,28 @@
                 "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "_type": "CustomComponent"
             },
             "description": "Display a text output in the Playground.",
             "icon": "type",
-            "base_classes": ["str", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Text",
+              "object"
+            ],
             "display_name": "Second Prompt",
             "documentation": "",
             "custom_fields": {
               "input_value": null,
               "record_template": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [],
@@ -1146,7 +1257,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "code": {
                 "type": "code",
@@ -1155,7 +1268,7 @@
                 "list": false,
                 "show": true,
                 "multiline": true,
-                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
+                "value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n\n    field_order = [\n        \"max_tokens\",\n        \"model_kwargs\",\n        \"model_name\",\n        \"openai_api_base\",\n        \"openai_api_key\",\n        \"temperature\",\n        \"input_value\",\n        \"system_message\",\n        \"stream\",\n    ]\n\n    def build_config(self):\n        return {\n            \"input_value\": {\"display_name\": \"Input\"},\n            \"max_tokens\": {\n                \"display_name\": \"Max Tokens\",\n                \"advanced\": True,\n                \"info\": \"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            },\n            \"model_kwargs\": {\n                \"display_name\": \"Model Kwargs\",\n                \"advanced\": True,\n            },\n            \"model_name\": {\n                \"display_name\": \"Model Name\",\n                \"advanced\": False,\n                \"options\": MODEL_NAMES,\n            },\n            \"openai_api_base\": {\n                \"display_name\": \"OpenAI API Base\",\n                \"advanced\": True,\n                \"info\": (\n                    \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n                    \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n                ),\n            },\n            \"openai_api_key\": {\n                \"display_name\": \"OpenAI API Key\",\n                \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n                \"advanced\": False,\n                \"password\": True,\n            },\n            \"temperature\": {\n                \"display_name\": \"Temperature\",\n                \"advanced\": False,\n                \"value\": 0.1,\n            },\n            \"stream\": {\n                \"display_name\": \"Stream\",\n                \"info\": STREAM_INFO_TEXT,\n                \"advanced\": True,\n            },\n            \"system_message\": {\n                \"display_name\": \"System Message\",\n                \"info\": \"System message to pass to the model.\",\n                \"advanced\": True,\n            },\n        }\n\n    def build(\n        self,\n        input_value: Text,\n        openai_api_key: str,\n        temperature: float = 0.1,\n        model_name: str = \"gpt-4o\",\n        max_tokens: Optional[int] = 256,\n        model_kwargs: NestedDict = {},\n        openai_api_base: Optional[str] = None,\n        stream: bool = False,\n        system_message: Optional[str] = None,\n    ) -> Text:\n        if not openai_api_base:\n            openai_api_base = \"https://api.openai.com/v1\"\n        if openai_api_key:\n            api_key = SecretStr(openai_api_key)\n        else:\n            api_key = None\n\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature,\n        )\n\n        return self.get_chat_result(output, stream, input_value, system_message)\n",
                 "fileTypes": [],
                 "file_path": "",
                 "password": false,
@@ -1229,7 +1342,9 @@
                 "info": "",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_base": {
                 "type": "str",
@@ -1248,7 +1363,9 @@
                 "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "openai_api_key": {
                 "type": "str",
@@ -1267,7 +1384,9 @@
                 "info": "The OpenAI API Key to use for the OpenAI model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"],
+                "input_types": [
+                  "Text"
+                ],
                 "value": ""
               },
               "stream": {
@@ -1306,11 +1425,13 @@
                 "info": "System message to pass to the model.",
                 "load_from_db": false,
                 "title_case": false,
-                "input_types": ["Text"]
+                "input_types": [
+                  "Text"
+                ]
               },
               "temperature": {
                 "type": "float",
-                "required": true,
+                "required": false,
                 "placeholder": "",
                 "list": false,
                 "show": true,
@@ -1337,7 +1458,11 @@
             },
             "description": "Generates text using OpenAI LLMs.",
             "icon": "OpenAI",
-            "base_classes": ["str", "Text", "object"],
+            "base_classes": [
+              "str",
+              "Text",
+              "object"
+            ],
             "display_name": "OpenAI",
             "documentation": "",
             "custom_fields": {
@@ -1351,7 +1476,9 @@
               "stream": null,
               "system_message": null
             },
-            "output_types": ["Text"],
+            "output_types": [
+              "Text"
+            ],
             "field_formatters": {},
             "frozen": false,
             "field_order": [
@@ -1382,18 +1509,27 @@
     "edges": [
       {
         "source": "TextInput-sptaH",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153TextInput\u0153,\u0153id\u0153:\u0153TextInput-sptaH\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-sptaHœ}",
         "target": "Prompt-amqBu",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153document\u0153,\u0153id\u0153:\u0153Prompt-amqBu\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œdocumentœ,œidœ:œPrompt-amqBuœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "document",
             "id": "Prompt-amqBu",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["str", "Text", "object"],
+            "baseClasses": [
+              "str",
+              "Text",
+              "object"
+            ],
             "dataType": "TextInput",
             "id": "TextInput-sptaH"
           }
@@ -1402,22 +1538,29 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-TextInput-sptaH{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153TextInput\u0153,\u0153id\u0153:\u0153TextInput-sptaH\u0153}-Prompt-amqBu{\u0153fieldName\u0153:\u0153document\u0153,\u0153id\u0153:\u0153Prompt-amqBu\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-TextInput-sptaH{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-sptaHœ}-Prompt-amqBu{œfieldNameœ:œdocumentœ,œidœ:œPrompt-amqBuœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "Prompt-amqBu",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-amqBu\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-amqBuœ}",
         "target": "TextOutput-2MS4a",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153TextOutput-2MS4a\u0153,\u0153inputTypes\u0153:[\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-2MS4aœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "TextOutput-2MS4a",
-            "inputTypes": ["Record", "Text"],
+            "inputTypes": [
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "str", "Text"],
+            "baseClasses": [
+              "object",
+              "str",
+              "Text"
+            ],
             "dataType": "Prompt",
             "id": "Prompt-amqBu"
           }
@@ -1426,22 +1569,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-Prompt-amqBu{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-amqBu\u0153}-TextOutput-2MS4a{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153TextOutput-2MS4a\u0153,\u0153inputTypes\u0153:[\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-Prompt-amqBu{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-amqBuœ}-TextOutput-2MS4a{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-2MS4aœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "Prompt-amqBu",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-amqBu\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-amqBuœ}",
         "target": "OpenAIModel-uYXZJ",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-uYXZJ\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-uYXZJœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-uYXZJ",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "str", "Text"],
+            "baseClasses": [
+              "object",
+              "str",
+              "Text"
+            ],
             "dataType": "Prompt",
             "id": "Prompt-amqBu"
           }
@@ -1450,22 +1599,31 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-Prompt-amqBu{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-amqBu\u0153}-OpenAIModel-uYXZJ{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-uYXZJ\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-Prompt-amqBu{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-amqBuœ}-OpenAIModel-uYXZJ{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-uYXZJœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "OpenAIModel-uYXZJ",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-uYXZJ\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uYXZJœ}",
         "target": "Prompt-gTNiz",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153summary\u0153,\u0153id\u0153:\u0153Prompt-gTNiz\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œsummaryœ,œidœ:œPrompt-gTNizœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "summary",
             "id": "Prompt-gTNiz",
-            "inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
+            "inputTypes": [
+              "Document",
+              "BaseOutputParser",
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["str", "Text", "object"],
+            "baseClasses": [
+              "str",
+              "Text",
+              "object"
+            ],
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-uYXZJ"
           }
@@ -1474,22 +1632,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-OpenAIModel-uYXZJ{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-uYXZJ\u0153}-Prompt-gTNiz{\u0153fieldName\u0153:\u0153summary\u0153,\u0153id\u0153:\u0153Prompt-gTNiz\u0153,\u0153inputTypes\u0153:[\u0153Document\u0153,\u0153BaseOutputParser\u0153,\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-OpenAIModel-uYXZJ{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uYXZJœ}-Prompt-gTNiz{œfieldNameœ:œsummaryœ,œidœ:œPrompt-gTNizœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "OpenAIModel-uYXZJ",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-uYXZJ\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uYXZJœ}",
         "target": "ChatOutput-EJkG3",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-EJkG3\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-EJkG3œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-EJkG3",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["str", "Text", "object"],
+            "baseClasses": [
+              "str",
+              "Text",
+              "object"
+            ],
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-uYXZJ"
           }
@@ -1498,22 +1662,29 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-OpenAIModel-uYXZJ{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-uYXZJ\u0153}-ChatOutput-EJkG3{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-EJkG3\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-OpenAIModel-uYXZJ{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uYXZJœ}-ChatOutput-EJkG3{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-EJkG3œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "Prompt-gTNiz",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-gTNiz\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-gTNizœ}",
         "target": "TextOutput-MUDOR",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153TextOutput-MUDOR\u0153,\u0153inputTypes\u0153:[\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-MUDORœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "TextOutput-MUDOR",
-            "inputTypes": ["Record", "Text"],
+            "inputTypes": [
+              "Record",
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "str", "Text"],
+            "baseClasses": [
+              "object",
+              "str",
+              "Text"
+            ],
             "dataType": "Prompt",
             "id": "Prompt-gTNiz"
           }
@@ -1522,22 +1693,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-Prompt-gTNiz{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-gTNiz\u0153}-TextOutput-MUDOR{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153TextOutput-MUDOR\u0153,\u0153inputTypes\u0153:[\u0153Record\u0153,\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-Prompt-gTNiz{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-gTNizœ}-TextOutput-MUDOR{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-MUDORœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "Prompt-gTNiz",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-gTNiz\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-gTNizœ}",
         "target": "OpenAIModel-XawYB",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-XawYB\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-XawYBœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "OpenAIModel-XawYB",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["object", "str", "Text"],
+            "baseClasses": [
+              "object",
+              "str",
+              "Text"
+            ],
             "dataType": "Prompt",
             "id": "Prompt-gTNiz"
           }
@@ -1546,22 +1723,28 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-Prompt-gTNiz{\u0153baseClasses\u0153:[\u0153object\u0153,\u0153str\u0153,\u0153Text\u0153],\u0153dataType\u0153:\u0153Prompt\u0153,\u0153id\u0153:\u0153Prompt-gTNiz\u0153}-OpenAIModel-XawYB{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153OpenAIModel-XawYB\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-Prompt-gTNiz{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-gTNizœ}-OpenAIModel-XawYB{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-XawYBœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       },
       {
         "source": "OpenAIModel-XawYB",
-        "sourceHandle": "{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-XawYB\u0153}",
+        "sourceHandle": "{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-XawYBœ}",
         "target": "ChatOutput-DNmvg",
-        "targetHandle": "{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-DNmvg\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-DNmvgœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
         "data": {
           "targetHandle": {
             "fieldName": "input_value",
             "id": "ChatOutput-DNmvg",
-            "inputTypes": ["Text"],
+            "inputTypes": [
+              "Text"
+            ],
             "type": "str"
           },
           "sourceHandle": {
-            "baseClasses": ["str", "Text", "object"],
+            "baseClasses": [
+              "str",
+              "Text",
+              "object"
+            ],
             "dataType": "OpenAIModel",
             "id": "OpenAIModel-XawYB"
           }
@@ -1570,7 +1753,7 @@
           "stroke": "#555"
         },
         "className": "stroke-gray-900 stroke-connection",
-        "id": "reactflow__edge-OpenAIModel-XawYB{\u0153baseClasses\u0153:[\u0153str\u0153,\u0153Text\u0153,\u0153object\u0153],\u0153dataType\u0153:\u0153OpenAIModel\u0153,\u0153id\u0153:\u0153OpenAIModel-XawYB\u0153}-ChatOutput-DNmvg{\u0153fieldName\u0153:\u0153input_value\u0153,\u0153id\u0153:\u0153ChatOutput-DNmvg\u0153,\u0153inputTypes\u0153:[\u0153Text\u0153],\u0153type\u0153:\u0153str\u0153}"
+        "id": "reactflow__edge-OpenAIModel-XawYB{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-XawYBœ}-ChatOutput-DNmvg{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-DNmvgœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
       }
     ],
     "viewport": {
@@ -1583,4 +1766,4 @@
   "name": "Prompt Chaining",
   "last_tested_version": "1.0.0a0",
   "is_component": false
-}
+}

src/backend/base/langflow/main.py

@@ -14,7 +14,11 @@ from rich import print as rprint
 from starlette.middleware.base import BaseHTTPMiddleware
 
 from langflow.api import router
-from langflow.initial_setup.setup import create_or_update_starter_projects
+from langflow.initial_setup.setup import (
+    create_or_update_starter_projects,
+    initialize_super_user_if_needed,
+    load_flows_from_directory,
+)
 from langflow.interface.utils import setup_llm_caching
 from langflow.services.plugins.langfuse_plugin import LangfuseInstance
 from langflow.services.utils import initialize_services, teardown_services
@@ -33,22 +37,22 @@ class JavaScriptMIMETypeMiddleware(BaseHTTPMiddleware):
         return response
 
 
-def get_lifespan(fix_migration=False, socketio_server=None):
-    from langflow.version import __version__  # type: ignore
-
+def get_lifespan(fix_migration=False, socketio_server=None, version=None):
     @asynccontextmanager
     async def lifespan(app: FastAPI):
         nest_asyncio.apply()
         # Startup message
-        if __version__:
-            rprint(f"[bold green]Starting Langflow v{__version__}...[/bold green]")
+        if version:
+            rprint(f"[bold green]Starting Langflow v{version}...[/bold green]")
         else:
             rprint("[bold green]Starting Langflow...[/bold green]")
         try:
             initialize_services(fix_migration=fix_migration, socketio_server=socketio_server)
             setup_llm_caching()
             LangfuseInstance.update()
+            initialize_super_user_if_needed()
             create_or_update_starter_projects()
+            load_flows_from_directory()
             yield
         except Exception as exc:
             if "langflow migration --fix" not in str(exc):
@@ -63,11 +67,17 @@ def get_lifespan(fix_migration=False, socketio_server=None):
 
 def create_app():
     """Create the FastAPI app and include the router."""
+    try:
+        from langflow.version import __version__  # type: ignore
+    except ImportError:
+        from importlib.metadata import version
+
+        __version__ = version("langflow-base")
 
     configure()
     socketio_server = socketio.AsyncServer(async_mode="asgi", cors_allowed_origins="*", logger=True)
-    lifespan = get_lifespan(socketio_server=socketio_server)
-    app = FastAPI(lifespan=lifespan)
+    lifespan = get_lifespan(socketio_server=socketio_server, version=__version__)
+    app = FastAPI(lifespan=lifespan, title="Langflow", version=__version__)
     origins = ["*"]
 
     app.add_middleware(

src/backend/base/langflow/services/auth/utils.py

@@ -76,11 +76,6 @@ async def get_current_user(
     if token:
         return await get_current_user_by_jwt(token, db)
     else:
-        if not query_param and not header_param:
-            raise HTTPException(
-                status_code=status.HTTP_403_FORBIDDEN,
-                detail="An API key as query or header, or a JWT token must be passed",
-            )
         user = await api_key_security(query_param, header_param, db)
         if user:
             return user
@@ -216,15 +211,14 @@ def create_super_user(
 
 def create_user_longterm_token(db: Session = Depends(get_session)) -> tuple[UUID, dict]:
     settings_service = get_settings_service()
+
     username = settings_service.auth_settings.SUPERUSER
-    password = settings_service.auth_settings.SUPERUSER_PASSWORD
-    if not username or not password:
+    super_user = get_user_by_username(db, username)
+    if not super_user:
         raise HTTPException(
             status_code=status.HTTP_400_BAD_REQUEST,
-            detail="Missing first superuser credentials",
+            detail="Super user hasn't been created"
         )
-    super_user = create_super_user(db=db, username=username, password=password)
-
     access_token_expires_longterm = timedelta(days=365)
     access_token = create_token(
         data={"sub": str(super_user.id)},

src/backend/base/langflow/services/cache/service.py

@@ -9,6 +9,9 @@ from loguru import logger
 
 from langflow.services.base import Service
 from langflow.services.cache.base import AsyncBaseCacheService, CacheService
+from langflow.services.cache.utils import CacheMiss
+
+CACHE_MISS = CacheMiss()
 
 
 class ThreadingInMemoryCache(CacheService, Service):
@@ -341,12 +344,14 @@ class AsyncInMemoryCache(AsyncBaseCacheService, Service):
 
     async def _get(self, key):
         item = self.cache.get(key, None)
-        if item and (time.time() - item["time"] < self.expiration_time):
-            self.cache.move_to_end(key)
-            return pickle.loads(item["value"]) if isinstance(item["value"], bytes) else item["value"]
         if item:
-            await self.delete(key)
-        return None
+            if time.time() - item["time"] < self.expiration_time:
+                self.cache.move_to_end(key)
+                return pickle.loads(item["value"]) if isinstance(item["value"], bytes) else item["value"]
+            else:
+                logger.info(f"Cache item for key '{key}' has expired and will be deleted.")
+                await self.delete(key)  # Log before deleting the expired item
+        return CACHE_MISS
 
     async def set(self, key, value, lock: Optional[asyncio.Lock] = None):
         if not lock:

src/backend/base/langflow/services/cache/utils.py

@@ -19,6 +19,11 @@ CACHE_DIR = user_cache_dir("langflow", "langflow")
 PREFIX = "langflow_cache"
 
 
+class CacheMiss:
+    def __repr__(self):
+        return "<CACHE_MISS>"
+
+
 def create_cache_folder(func):
     def wrapper(*args, **kwargs):
         # Get the destination folder

src/backend/base/langflow/services/chat/service.py

@@ -13,7 +13,7 @@ class ChatService(Service):
         self._cache_locks = defaultdict(asyncio.Lock)
         self.cache_service = get_cache_service()
 
-    async def set_cache(self, flow_id: str, data: Any, lock: Optional[asyncio.Lock] = None) -> bool:
+    async def set_cache(self, key: str, data: Any, lock: Optional[asyncio.Lock] = None) -> bool:
         """
         Set the cache for a client.
         """
@@ -23,17 +23,17 @@ class ChatService(Service):
             "result": data,
             "type": type(data),
         }
-        await self.cache_service.upsert(flow_id, result_dict, lock=lock or self._cache_locks[flow_id])
-        return flow_id in self.cache_service
+        await self.cache_service.upsert(key, result_dict, lock=lock or self._cache_locks[key])
+        return key in self.cache_service
 
-    async def get_cache(self, flow_id: str, lock: Optional[asyncio.Lock] = None) -> Any:
+    async def get_cache(self, key: str, lock: Optional[asyncio.Lock] = None) -> Any:
         """
         Get the cache for a client.
         """
-        return await self.cache_service.get(flow_id, lock=lock or self._cache_locks[flow_id])
+        return await self.cache_service.get(key, lock=lock or self._cache_locks[key])
 
-    async def clear_cache(self, flow_id: str, lock: Optional[asyncio.Lock] = None):
+    async def clear_cache(self, key: str, lock: Optional[asyncio.Lock] = None):
         """
         Clear the cache for a client.
         """
-        await self.cache_service.delete(flow_id, lock=lock or self._cache_locks[flow_id])
+        await self.cache_service.delete(key, lock=lock or self._cache_locks[key])

src/backend/base/langflow/services/database/factory.py

@@ -15,4 +15,4 @@ class DatabaseServiceFactory(ServiceFactory):
         # Here you would have logic to create and configure a DatabaseService
         if not settings_service.settings.database_url:
             raise ValueError("No database URL provided")
-        return DatabaseService(settings_service.settings.database_url)
+        return DatabaseService(settings_service)

src/backend/base/langflow/services/database/models/flow/model.py

@@ -1,5 +1,6 @@
 # Path: src/backend/langflow/services/database/models/flow/model.py
 
+import re
 import warnings
 from datetime import datetime, timezone
 from typing import TYPE_CHECKING, Dict, Optional
@@ -7,7 +8,9 @@ from uuid import UUID, uuid4
 
 import emoji
 from emoji import purely_emoji  # type: ignore
+from fastapi import HTTPException, status
 from pydantic import field_serializer, field_validator
+from sqlalchemy import UniqueConstraint
 from sqlmodel import JSON, Column, Field, Relationship, SQLModel
 
 from langflow.schema.schema import Record
@@ -25,7 +28,26 @@ class FlowBase(SQLModel):
     data: Optional[Dict] = Field(default=None, nullable=True)
     is_component: Optional[bool] = Field(default=False, nullable=True)
     updated_at: Optional[datetime] = Field(default_factory=lambda: datetime.now(timezone.utc), nullable=True)
+    webhook: Optional[bool] = Field(default=False, nullable=True, description="Can be used on the webhook endpoint")
     folder_id: Optional[UUID] = Field(default=None, nullable=True)
+    endpoint_name: Optional[str] = Field(default=None, nullable=True, index=True)
+
+    @field_validator("endpoint_name")
+    @classmethod
+    def validate_endpoint_name(cls, v):
+        # Endpoint name must be a string containing only letters, numbers, hyphens, and underscores
+        if v is not None:
+            if not isinstance(v, str):
+                raise HTTPException(
+                    status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
+                    detail="Endpoint name must be a string",
+                )
+            if not re.match(r"^[a-zA-Z0-9_-]+$", v):
+                raise HTTPException(
+                    status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
+                    detail="Endpoint name must contain only letters, numbers, hyphens, and underscores",
+                )
+        return v
 
     @field_validator("icon_bg_color")
     def validate_icon_bg_color(cls, v):
@@ -93,10 +115,15 @@ class FlowBase(SQLModel):
 
     # updated_at can be serialized to JSON
     @field_serializer("updated_at")
-    def serialize_dt(self, dt: datetime, _info):
-        if dt is None:
-            return None
-        return dt.isoformat()
+    def serialize_datetime(value):
+        if isinstance(value, datetime):
+            # I'm getting 2024-05-29T17:57:17.631346
+            # and I want 2024-05-29T17:57:17-05:00
+            value = value.replace(microsecond=0)
+            if value.tzinfo is None:
+                value = value.replace(tzinfo=timezone.utc)
+            return value.isoformat()
+        return value
 
     @field_validator("updated_at", mode="before")
     def validate_dt(cls, v):
@@ -128,6 +155,11 @@ class Flow(FlowBase, table=True):
         record = Record(data=data)
         return record
 
+    __table_args__ = (
+        UniqueConstraint("user_id", "name", name="unique_flow_name"),
+        UniqueConstraint("user_id", "endpoint_name", name="unique_flow_endpoint_name"),
+    )
+
 
 class FlowCreate(FlowBase):
     user_id: Optional[UUID] = None
@@ -145,3 +177,21 @@ class FlowUpdate(SQLModel):
     description: Optional[str] = None
     data: Optional[Dict] = None
     folder_id: Optional[UUID] = None
+    endpoint_name: Optional[str] = None
+
+    @field_validator("endpoint_name")
+    @classmethod
+    def validate_endpoint_name(cls, v):
+        # Endpoint name must be a string containing only letters, numbers, hyphens, and underscores
+        if v is not None:
+            if not isinstance(v, str):
+                raise HTTPException(
+                    status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
+                    detail="Endpoint name must be a string",
+                )
+            if not re.match(r"^[a-zA-Z0-9_-]+$", v):
+                raise HTTPException(
+                    status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
+                    detail="Endpoint name must contain only letters, numbers, hyphens, and underscores",
+                )
+        return v

src/backend/base/langflow/services/database/models/flow/utils.py

@@ -0,0 +1,33 @@
+from typing import Optional
+
+from fastapi import Depends
+from sqlmodel import Session
+
+from langflow.services.deps import get_session
+
+from .model import Flow
+
+
+def get_flow_by_id(session: Session = Depends(get_session), flow_id: Optional[str] = None) -> Flow | None:
+    """Get flow by id."""
+
+    if flow_id is None:
+        raise ValueError("Flow id is required.")
+
+    return session.get(Flow, flow_id)
+
+
+def get_webhook_component_in_flow(flow_data: dict):
+    """Get webhook component in flow data."""
+
+    for node in flow_data.get("nodes", []):
+        if "Webhook" in node.get("id"):
+            return node
+    return None
+
+
+def get_all_webhook_components_in_flow(flow_data: dict | None):
+    """Get all webhook components in flow data."""
+    if not flow_data:
+        return []
+    return [node for node in flow_data.get("nodes", []) if "Webhook" in node.get("id")]

src/backend/base/langflow/services/database/models/folder/model.py

@@ -1,6 +1,7 @@
 from typing import TYPE_CHECKING, List, Optional
 from uuid import UUID, uuid4
 
+from sqlalchemy import UniqueConstraint
 from sqlmodel import Field, Relationship, SQLModel
 
 from langflow.services.database.models.flow.model import FlowRead
@@ -30,6 +31,8 @@ class Folder(FolderBase, table=True):
         back_populates="folder", sa_relationship_kwargs={"cascade": "all, delete, delete-orphan"}
     )
 
+    __table_args__ = (UniqueConstraint("user_id", "name", name="unique_folder_name"),)
+
 
 class FolderCreate(FolderBase):
     components_list: Optional[List[UUID]] = None

src/backend/base/langflow/services/database/service.py

@@ -21,12 +21,17 @@ from langflow.services.utils import teardown_superuser
 if TYPE_CHECKING:
     from sqlalchemy.engine import Engine
 
+    from langflow.services.settings.service import SettingsService
+
 
 class DatabaseService(Service):
     name = "database_service"
 
-    def __init__(self, database_url: str):
-        self.database_url = database_url
+    def __init__(self, settings_service: "SettingsService"):
+        self.settings_service = settings_service
+        if settings_service.settings.database_url is None:
+            raise ValueError("No database URL provided")
+        self.database_url: str = settings_service.settings.database_url
         # This file is in langflow.services.database.manager.py
         # the ini is in langflow
         langflow_dir = Path(__file__).parent.parent.parent
@@ -41,7 +46,12 @@ class DatabaseService(Service):
             connect_args = {"check_same_thread": False}
         else:
             connect_args = {}
-        return create_engine(self.database_url, connect_args=connect_args)
+        return create_engine(
+            self.database_url,
+            connect_args=connect_args,
+            pool_size=self.settings_service.settings.pool_size,
+            max_overflow=self.settings_service.settings.max_overflow,
+        )
 
     def __enter__(self):
         self._session = Session(self.engine)
@@ -267,3 +277,4 @@ class DatabaseService(Service):
             logger.error(f"Error tearing down database: {exc}")
 
         self.engine.dispose()
+        self.engine.dispose()

src/backend/base/langflow/services/monitor/utils.py

@@ -8,6 +8,7 @@ from langflow.services.deps import get_monitor_service
 
 if TYPE_CHECKING:
     from langflow.api.v1.schemas import ResultDataResponse
+    from langflow.graph.vertex.base import Vertex
 
 
 INDEX_KEY = "index"
@@ -165,3 +166,35 @@ async def log_vertex_build(
         monitor_service.add_row(table_name="vertex_builds", data=row)
     except Exception as e:
         logger.exception(f"Error logging vertex build: {e}")
+
+
+def build_clean_params(target: "Vertex") -> dict:
+    """
+    Cleans the parameters of the target vertex.
+    """
+    # Removes all keys that the values aren't python types like str, int, bool, etc.
+    params = {
+        key: value for key, value in target.params.items() if isinstance(value, (str, int, bool, float, list, dict))
+    }
+    # if it is a list we need to check if the contents are python types
+    for key, value in params.items():
+        if isinstance(value, list):
+            params[key] = [item for item in value if isinstance(item, (str, int, bool, float, list, dict))]
+    return params
+
+
+def log_transaction(vertex: "Vertex", status, error=None):
+    try:
+        monitor_service = get_monitor_service()
+        clean_params = build_clean_params(vertex)
+        data = {
+            "vertex_id": vertex.id,
+            "inputs": clean_params,
+            "output": str(vertex.result),
+            "timestamp": monitor_service.get_timestamp(),
+            "status": status,
+            "error": error,
+        }
+        monitor_service.add_row(table_name="transactions", data=data)
+    except Exception as e:
+        logger.error(f"Error logging transaction: {e}")

src/backend/base/langflow/services/settings/auth.py

@@ -47,6 +47,9 @@ class AuthSettings(BaseSettings):
     ACCESS_HTTPONLY: bool = False
     """The HttpOnly attribute of the access token cookie."""
 
+    COOKIE_DOMAIN: str | None = None
+    """The domain attribute of the cookies. If None, the domain is not set."""
+
     pwd_context: CryptContext = CryptContext(schemes=["bcrypt"], deprecated="auto")
 
     class Config:

src/backend/base/langflow/services/settings/base.py

@@ -67,10 +67,16 @@ class Settings(BaseSettings):
 
     dev: bool = False
     database_url: Optional[str] = None
+    """Database URL for Langflow. If not provided, Langflow will use a SQLite database."""
+    pool_size: int = 10
+    """The number of connections to keep open in the connection pool. If not provided, the default is 10."""
+    max_overflow: int = 10
+    """The number of connections to allow that can be opened beyond the pool size. If not provided, the default is 10."""
     cache_type: str = "async"
     remove_api_keys: bool = False
     components_path: List[str] = []
     langchain_cache: str = "InMemoryCache"
+    load_flows_path: Optional[str] = None
 
     # Redis
     redis_host: str = "localhost"
@@ -146,7 +152,13 @@ class Settings(BaseSettings):
                 # if there is a database in that location
                 if not info.data["config_dir"]:
                     raise ValueError("config_dir not set, please set it or provide a database_url")
-                from langflow.version import is_pre_release  # type: ignore
+                try:
+                    from langflow.version import is_pre_release  # type: ignore
+                except ImportError:
+                    from importlib import metadata
+
+                    version = metadata.version("langflow-base")
+                    is_pre_release = "a" in version or "b" in version or "rc" in version
 
                 if info.data["save_db_in_config_dir"]:
                     database_dir = info.data["config_dir"]

src/backend/base/langflow/services/settings/constants.py

@@ -17,6 +17,8 @@ VARIABLES_TO_GET_FROM_ENVIRONMENT = [
     "PINECONE_API_KEY",
     "SEARCHAPI_API_KEY",
     "SERPAPI_API_KEY",
+    "UPSTASH_VECTOR_REST_URL",
+    "UPSTASH_VECTOR_REST_TOKEN",
     "VECTARA_CUSTOMER_ID",
     "VECTARA_CORPUS_ID",
     "VECTARA_API_KEY",

src/backend/base/langflow/services/settings/service.py

@@ -1,4 +1,5 @@
 import os
+from typing import Optional
 
 import yaml
 from loguru import logger
@@ -7,7 +8,6 @@ from langflow.services.base import Service
 from langflow.services.settings.auth import AuthSettings
 from langflow.services.settings.base import Settings
 
-
 class SettingsService(Service):
     name = "settings_service"
 
@@ -27,7 +27,6 @@ class SettingsService(Service):
 
         with open(file_path, "r") as f:
             settings_dict = yaml.safe_load(f)
-            settings_dict = {k.upper(): v for k, v in settings_dict.items()}
 
             for key in settings_dict:
                 if key not in Settings.model_fields.keys():

src/backend/base/langflow/utils/migration.py

@@ -0,0 +1,65 @@
+from sqlalchemy.engine.reflection import Inspector
+
+
+def table_exists(name, conn):
+    """
+    Check if a table exists.
+
+    Parameters:
+    name (str): The name of the table to check.
+    conn (sqlalchemy.engine.Engine or sqlalchemy.engine.Connection): The SQLAlchemy engine or connection to use.
+
+    Returns:
+    bool: True if the table exists, False otherwise.
+    """
+    inspector = Inspector.from_engine(conn)
+    return name in inspector.get_table_names()
+
+
+def column_exists(table_name, column_name, conn):
+    """
+    Check if a column exists in a table.
+
+    Parameters:
+    table_name (str): The name of the table to check.
+    column_name (str): The name of the column to check.
+    conn (sqlalchemy.engine.Engine or sqlalchemy.engine.Connection): The SQLAlchemy engine or connection to use.
+
+    Returns:
+    bool: True if the column exists, False otherwise.
+    """
+    inspector = Inspector.from_engine(conn)
+    return column_name in [column["name"] for column in inspector.get_columns(table_name)]
+
+
+def foreign_key_exists(table_name, fk_name, conn):
+    """
+    Check if a foreign key exists in a table.
+
+    Parameters:
+    table_name (str): The name of the table to check.
+    fk_name (str): The name of the foreign key to check.
+    conn (sqlalchemy.engine.Engine or sqlalchemy.engine.Connection): The SQLAlchemy engine or connection to use.
+
+    Returns:
+    bool: True if the foreign key exists, False otherwise.
+    """
+    inspector = Inspector.from_engine(conn)
+    return fk_name in [fk["name"] for fk in inspector.get_foreign_keys(table_name)]
+
+
+def constraint_exists(table_name, constraint_name, conn):
+    """
+    Check if a constraint exists in a table.
+
+    Parameters:
+    table_name (str): The name of the table to check.
+    constraint_name (str): The name of the constraint to check.
+    conn (sqlalchemy.engine.Engine or sqlalchemy.engine.Connection): The SQLAlchemy engine or connection to use.
+
+    Returns:
+    bool: True if the constraint exists, False otherwise.
+    """
+    inspector = Inspector.from_engine(conn)
+    constraints = inspector.get_unique_constraints(table_name)
+    return constraint_name in [constraint["name"] for constraint in constraints]

src/backend/base/poetry.lock

@@ -264,13 +264,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2024.2.2"
+version = "2024.6.2"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
-    {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
+    {file = "certifi-2024.6.2-py3-none-any.whl", hash = "sha256:ddc6c8ce995e6987e7faf5e3f1b02b302836a0e5d98ece18392cb1a36c72ad56"},
+    {file = "certifi-2024.6.2.tar.gz", hash = "sha256:3cd43f1c6fa7dedc5899d69d3ad0398fd018ad1a17fba83ddaf78aa46c747516"},
 ]
 
 [[package]]
@@ -1224,18 +1224,18 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
 
 [[package]]
 name = "langchain-core"
-version = "0.2.1"
+version = "0.2.3"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.2.1-py3-none-any.whl", hash = "sha256:3521e1e573988c47399fca9739270c5d34f8ecec147253ad829eb9ff288f76d5"},
-    {file = "langchain_core-0.2.1.tar.gz", hash = "sha256:49383126168d934559a543ce812c485048d9e6ac9b6798fbf3d4a72b6bba5b0c"},
+    {file = "langchain_core-0.2.3-py3-none-any.whl", hash = "sha256:22189b5a3a30bfd65eb995f95e627f7c2c3acb322feb89f5f5f2fb7df21833a7"},
+    {file = "langchain_core-0.2.3.tar.gz", hash = "sha256:fbc75a64b9c0b7655d96ca57a707df1e6c09efc1539c36adbd73260612549810"},
 ]
 
 [package.dependencies]
 jsonpatch = ">=1.33,<2.0"
-langsmith = ">=0.1.0,<0.2.0"
+langsmith = ">=0.1.65,<0.2.0"
 packaging = ">=23.2,<24.0"
 pydantic = ">=1,<3"
 PyYAML = ">=5.3"
@@ -1281,13 +1281,13 @@ extended-testing = ["beautifulsoup4 (>=4.12.3,<5.0.0)", "lxml (>=4.9.3,<6.0)"]
 
 [[package]]
 name = "langchainhub"
-version = "0.1.16"
+version = "0.1.17"
 description = "The LangChain Hub API client"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchainhub-0.1.16-py3-none-any.whl", hash = "sha256:a4379a1879cc6b441b8d02cc65e28a54f160fba61c9d1d4b0eddc3a276dff99a"},
-    {file = "langchainhub-0.1.16.tar.gz", hash = "sha256:9f11e68fddb575e70ef4b28800eedbd9eeb180ba508def04f7153ea5b246b6fc"},
+    {file = "langchainhub-0.1.17-py3-none-any.whl", hash = "sha256:4c609b3948252c71670f0d98f73413b515cfd2f6701a7b40ce959203e6133e04"},
+    {file = "langchainhub-0.1.17.tar.gz", hash = "sha256:af7df0cb1cebc7a6e0864e8632ae48ecad39ed96568f699c78657b9d04e50b46"},
 ]
 
 [package.dependencies]
@@ -1296,13 +1296,13 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
 
 [[package]]
 name = "langsmith"
-version = "0.1.63"
+version = "0.1.67"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.63-py3-none-any.whl", hash = "sha256:7810afdf5e3f3b472fc581a29371fb96cd843dde2149e048d1b9610325159d1e"},
-    {file = "langsmith-0.1.63.tar.gz", hash = "sha256:a609405b52f6f54df442a142cbf19ab38662d54e532f96028b4c546434d4afdf"},
+    {file = "langsmith-0.1.67-py3-none-any.whl", hash = "sha256:7eb2e1c1b375925ff47700ed8071e10c15e942e9d1d634b4a449a9060364071a"},
+    {file = "langsmith-0.1.67.tar.gz", hash = "sha256:149558669a2ac4f21471cd964e61072687bba23b7c1ccb51f190a8f59b595b39"},
 ]
 
 [package.dependencies]
@@ -2104,18 +2104,18 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.7.1"
+version = "2.7.2"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic-2.7.1-py3-none-any.whl", hash = "sha256:e029badca45266732a9a79898a15ae2e8b14840b1eabbb25844be28f0b33f3d5"},
-    {file = "pydantic-2.7.1.tar.gz", hash = "sha256:e9dbb5eada8abe4d9ae5f46b9939aead650cd2b68f249bb3a8139dbe125803cc"},
+    {file = "pydantic-2.7.2-py3-none-any.whl", hash = "sha256:834ab954175f94e6e68258537dc49402c4a5e9d0409b9f1b86b7e934a8372de7"},
+    {file = "pydantic-2.7.2.tar.gz", hash = "sha256:71b2945998f9c9b7919a45bde9a50397b289937d215ae141c1d0903ba7149fd7"},
 ]
 
 [package.dependencies]
 annotated-types = ">=0.4.0"
-pydantic-core = "2.18.2"
+pydantic-core = "2.18.3"
 typing-extensions = ">=4.6.1"
 
 [package.extras]
@@ -2123,90 +2123,90 @@ email = ["email-validator (>=2.0.0)"]
 
 [[package]]
 name = "pydantic-core"
-version = "2.18.2"
+version = "2.18.3"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic_core-2.18.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:9e08e867b306f525802df7cd16c44ff5ebbe747ff0ca6cf3fde7f36c05a59a81"},
-    {file = "pydantic_core-2.18.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f0a21cbaa69900cbe1a2e7cad2aa74ac3cf21b10c3efb0fa0b80305274c0e8a2"},
-    {file = "pydantic_core-2.18.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0680b1f1f11fda801397de52c36ce38ef1c1dc841a0927a94f226dea29c3ae3d"},
-    {file = "pydantic_core-2.18.2-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:95b9d5e72481d3780ba3442eac863eae92ae43a5f3adb5b4d0a1de89d42bb250"},
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 ]
 
 [package.dependencies]
@@ -2214,17 +2214,17 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pydantic-settings"
-version = "2.2.1"
+version = "2.3.0"
 description = "Settings management using Pydantic"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic_settings-2.2.1-py3-none-any.whl", hash = "sha256:0235391d26db4d2190cb9b31051c4b46882d28a51533f97440867f012d4da091"},
-    {file = "pydantic_settings-2.2.1.tar.gz", hash = "sha256:00b9f6a5e95553590434c0fa01ead0b216c3e10bc54ae02e37f359948643c5ed"},
+    {file = "pydantic_settings-2.3.0-py3-none-any.whl", hash = "sha256:26eeed27370a9c5e3f64e4a7d6602573cbedf05ed940f1d5b11c3f178427af7a"},
+    {file = "pydantic_settings-2.3.0.tar.gz", hash = "sha256:78db28855a71503cfe47f39500a1dece523c640afd5280edb5c5c9c9cfa534c9"},
 ]
 
 [package.dependencies]
-pydantic = ">=2.3.0"
+pydantic = ">=2.7.0"
 python-dotenv = ">=0.21.0"
 
 [package.extras]
@@ -2466,13 +2466,13 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.32.2"
+version = "2.32.3"
 description = "Python HTTP for Humans."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "requests-2.32.2-py3-none-any.whl", hash = "sha256:fc06670dd0ed212426dfeb94fc1b983d917c4f9847c863f313c9dfaaffb7c23c"},
-    {file = "requests-2.32.2.tar.gz", hash = "sha256:dd951ff5ecf3e3b3aa26b40703ba77495dab41da839ae72ef3c8e5d8e2433289"},
+    {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
+    {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
 ]
 
 [package.dependencies]
@@ -2720,13 +2720,13 @@ typing-extensions = ">=3.7.4.3"
 
 [[package]]
 name = "types-requests"
-version = "2.32.0.20240523"
+version = "2.32.0.20240602"
 description = "Typing stubs for requests"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-requests-2.32.0.20240523.tar.gz", hash = "sha256:26b8a6de32d9f561192b9942b41c0ab2d8010df5677ca8aa146289d11d505f57"},
-    {file = "types_requests-2.32.0.20240523-py3-none-any.whl", hash = "sha256:f19ed0e2daa74302069bbbbf9e82902854ffa780bc790742a810a9aaa52f65ec"},
+    {file = "types-requests-2.32.0.20240602.tar.gz", hash = "sha256:3f98d7bbd0dd94ebd10ff43a7fbe20c3b8528acace6d8efafef0b6a184793f06"},
+    {file = "types_requests-2.32.0.20240602-py3-none-any.whl", hash = "sha256:ed3946063ea9fbc6b5fc0c44fa279188bae42d582cb63760be6cb4b9d06c3de8"},
 ]
 
 [package.dependencies]
@@ -2734,13 +2734,13 @@ urllib3 = ">=2"
 
 [[package]]
 name = "typing-extensions"
-version = "4.12.0"
+version = "4.12.1"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "typing_extensions-4.12.0-py3-none-any.whl", hash = "sha256:b349c66bea9016ac22978d800cfff206d5f9816951f12a7d0ec5578b0a819594"},
-    {file = "typing_extensions-4.12.0.tar.gz", hash = "sha256:8cbcdc8606ebcb0d95453ad7dc5065e6237b6aa230a31e81d0f440c30fed5fd8"},
+    {file = "typing_extensions-4.12.1-py3-none-any.whl", hash = "sha256:6024b58b69089e5a89c347397254e35f1bf02a907728ec7fee9bf0fe837d203a"},
+    {file = "typing_extensions-4.12.1.tar.gz", hash = "sha256:915f5e35ff76f56588223f15fdd5938f9a1cf9195c0de25130c627e4d597f6d1"},
 ]
 
 [[package]]
@@ -2856,6 +2856,21 @@ files = [
     {file = "ujson-5.10.0.tar.gz", hash = "sha256:b3cd8f3c5d8c7738257f1018880444f7b7d9b66232c64649f562d7ba86ad4bc1"},
 ]
 
+[[package]]
+name = "uncurl"
+version = "0.0.11"
+description = "A library to convert curl requests to python-requests."
+optional = false
+python-versions = "*"
+files = [
+    {file = "uncurl-0.0.11-py3-none-any.whl", hash = "sha256:5961e93f07a5c9f2ef8ae4245bd92b0a6ce503c851de980f5b70080ae74cdc59"},
+    {file = "uncurl-0.0.11.tar.gz", hash = "sha256:530c9bbd4d118f4cde6194165ff484cc25b0661cd256f19e9d5fcb53fc077790"},
+]
+
+[package.dependencies]
+pyperclip = "*"
+six = "*"
+
 [[package]]
 name = "urllib3"
 version = "2.2.1"
@@ -2875,13 +2890,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.29.0"
+version = "0.30.1"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "uvicorn-0.29.0-py3-none-any.whl", hash = "sha256:2c2aac7ff4f4365c206fd773a39bf4ebd1047c238f8b8268ad996829323473de"},
-    {file = "uvicorn-0.29.0.tar.gz", hash = "sha256:6a69214c0b6a087462412670b3ef21224fa48cae0e452b5883e8e8bdfdd11dd0"},
+    {file = "uvicorn-0.30.1-py3-none-any.whl", hash = "sha256:cd17daa7f3b9d7a24de3617820e634d0933b69eed8e33a516071174427238c81"},
+    {file = "uvicorn-0.30.1.tar.gz", hash = "sha256:d46cd8e0fd80240baffbcd9ec1012a712938754afcf81bce56c024c1656aece8"},
 ]
 
 [package.dependencies]
@@ -3250,4 +3265,4 @@ local = []
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "31d8e5ce045ef7d94e63058559b5f8181e6b51fc923c4904f45481443d59235d"
+content-hash = "48a7355a7096e763b75315d0704bed8f4d8134a33553e62bc305a686b9e72803"

src/backend/base/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow-base"
-version = "0.0.50"
+version = "0.0.55"
 description = "A Python package with a built-in web application"
 authors = ["Langflow <contact@langflow.org>"]
 maintainers = [
@@ -28,7 +28,7 @@ langflow-base = "langflow.__main__:main"
 python = ">=3.10,<3.13"
 fastapi = "^0.111.0"
 httpx = "*"
-uvicorn = "^0.29.0"
+uvicorn = "^0.30.0"
 gunicorn = "^22.0.0"
 langchain = "~0.2.0"
 langchainhub = "~0.1.15"
@@ -62,6 +62,7 @@ emoji = "^2.12.0"
 cryptography = "^42.0.5"
 asyncer = "^0.0.5"
 pyperclip = "^1.8.2"
+uncurl = "^0.0.11"
 
 
 [tool.poetry.extras]