Merge remote-tracking branch 'origin/dev' into update_lc

Makefile

@@ -45,6 +45,13 @@ run_frontend:
 	@-kill -9 `lsof -t -i:3000`
 	cd src/frontend && npm start
 
+tests_frontend:
+ifeq ($(UI), true)
+		cd src/frontend && ./run-tests.sh --ui
+else
+		cd src/frontend && ./run-tests.sh
+endif
+
 run_cli:
 	poetry run langflow run --path src/frontend/build
 

docs/docs/components/embeddings.mdx

@@ -1,10 +1,12 @@
-import Admonition from '@theme/Admonition';
+import Admonition from "@theme/Admonition";
 
 # Embeddings
 
 <Admonition type="caution" icon="🚧" title="ZONE UNDER CONSTRUCTION">
   <p>
-        We appreciate your understanding as we polish our documentation – it may contain some rough edges. Share your feedback or report issues to help us improve! 🛠️📝
+    We appreciate your understanding as we polish our documentation – it may
+    contain some rough edges. Share your feedback or report issues to help us
+    improve! 🛠️📝
   </p>
 </Admonition>
 
@@ -111,3 +113,11 @@ Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP).
 - **top_p:** Tokens are selected from most probable to least until the sum of their – defaults to `0.95`.
 - **tuned_model_name:** The name of a tuned model. If provided, model_name is ignored.
 - **verbose:** This parameter is used to control the level of detail in the output of the chain. When set to True, it will print out some internal states of the chain while it is being run, which can help debug and understand the chain's behavior. If set to False, it will suppress the verbose output – defaults to `False`.
+
+### OllamaEmbeddings
+
+Used to load [Ollama’s](https://ollama.ai/) embedding models. Wrapper around LangChain's [Ollama API](https://python.langchain.com/docs/integrations/text_embedding/ollama).
+
+- **model** The name of the Ollama model to use – defaults to `llama2`.
+- **base_url** The base URL for the Ollama API – defaults to `http://localhost:11434`.
+- **temperature** Tunes the degree of randomness in text generations. Should be a non-negative value – defaults to `0`.

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.6.4"
+version = "0.6.5a9"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [
@@ -55,7 +55,7 @@ tiktoken = "~0.5.0"
 wikipedia = "^1.4.0"
 qdrant-client = "^1.7.0"
 websockets = "^10.3"
-weaviate-client = "^3.26.0"
+weaviate-client = { version = "^4.4b6", allow-prereleases = true }
 jina = "*"
 sentence-transformers = { version = "^2.2.2", optional = true }
 ctransformers = { version = "^0.2.10", optional = true }

src/backend/langflow/__main__.py

@@ -1,15 +1,12 @@
 import platform
 import socket
 import sys
-import time
-import webbrowser
 from pathlib import Path
 from typing import Optional
 
-import httpx
 import typer
 from dotenv import load_dotenv
-from multiprocess import Process, cpu_count  # type: ignore
+from multiprocess import cpu_count  # type: ignore
 from rich import box
 from rich import print as rprint
 from rich.console import Console
@@ -212,23 +209,12 @@ def run(
         run_on_windows(host, port, log_level, options, app)
     else:
         # Run using gunicorn on Linux
-        run_on_mac_or_linux(host, port, log_level, options, app, open_browser)
+        run_on_mac_or_linux(host, port, log_level, options, app)
 
 
-def run_on_mac_or_linux(host, port, log_level, options, app, open_browser=True):
+def run_on_mac_or_linux(host, port, log_level, options, app):
-    webapp_process = Process(target=run_langflow, args=(host, port, log_level, options, app))
-    webapp_process.start()
-    status_code = 0
-    while status_code != 200:
-        try:
-            status_code = httpx.get(f"http://{host}:{port}/health").status_code
-
-        except Exception:
-            time.sleep(1)
-
     print_banner(host, port)
-    if open_browser:
+    run_langflow(host, port, log_level, options, app)
-        webbrowser.open(f"http://{host}:{port}")
 
 
 def run_on_windows(host, port, log_level, options, app):
@@ -303,19 +289,26 @@ def run_langflow(host, port, log_level, options, app):
     Run Langflow server on localhost
     """
     try:
-        if platform.system() in ["Windows"]:
+        if platform.system() in ["Windows", "Darwin"]:
             # Run using uvicorn on MacOS and Windows
             # Windows doesn't support gunicorn
             # MacOS requires an env variable to be set to use gunicorn
+
             import uvicorn
 
-            uvicorn.run(app, host=host, port=port, log_level=log_level)
+            uvicorn.run(
+                app,
+                host=host,
+                port=port,
+                log_level=log_level,
+            )
         else:
             from langflow.server import LangflowApplication
 
             LangflowApplication(app, options).run()
     except KeyboardInterrupt:
-        pass
+        logger.info("Shutting down server")
+        sys.exit(0)
     except Exception as e:
         logger.exception(e)
         sys.exit(1)

src/backend/langflow/alembic/versions/006b3990db50_add_unique_constraints.py

@@ -27,7 +27,8 @@ def upgrade() -> None:
 
         with op.batch_alter_table('user', schema=None) as batch_op:
             batch_op.create_unique_constraint('uq_user_id', ['id'])
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
 
     # ### end Alembic commands ###
@@ -44,6 +45,7 @@ def downgrade() -> None:
 
         with op.batch_alter_table('apikey', schema=None) as batch_op:
             batch_op.drop_constraint('uq_apikey_id', type_='unique')
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
     # ### end Alembic commands ###

src/backend/langflow/alembic/versions/0b8757876a7c_.py

@@ -0,0 +1,71 @@
+"""empty message
+
+Revision ID: 0b8757876a7c
+Revises: 006b3990db50
+Create Date: 2024-01-17 10:32:56.686287
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = '0b8757876a7c'
+down_revision: Union[str, None] = '006b3990db50'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    # ### commands auto generated by Alembic - please adjust! ###
+    try:
+        with op.batch_alter_table('apikey', schema=None) as batch_op:
+            batch_op.create_index(batch_op.f('ix_apikey_api_key'), ['api_key'], unique=True)
+            batch_op.create_index(batch_op.f('ix_apikey_name'), ['name'], unique=False)
+            batch_op.create_index(batch_op.f('ix_apikey_user_id'), ['user_id'], unique=False)
+    except Exception as e:
+        print(e)
+        pass
+    try:
+        with op.batch_alter_table('flow', schema=None) as batch_op:
+            batch_op.create_index(batch_op.f('ix_flow_description'), ['description'], unique=False)
+            batch_op.create_index(batch_op.f('ix_flow_name'), ['name'], unique=False)
+            batch_op.create_index(batch_op.f('ix_flow_user_id'), ['user_id'], unique=False)
+    except Exception as e:
+        print(e)
+        pass
+
+    try:
+        with op.batch_alter_table('user', schema=None) as batch_op:
+            batch_op.create_index(batch_op.f('ix_user_username'), ['username'], unique=True)
+    except Exception as e:
+        print(e)
+        pass
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    # ### commands auto generated by Alembic - please adjust! ###
+    try:
+        with op.batch_alter_table('user', schema=None) as batch_op:
+            batch_op.drop_index(batch_op.f('ix_user_username'))
+    except Exception as e:
+        print(e)
+        pass
+    try:
+        with op.batch_alter_table('flow', schema=None) as batch_op:
+            batch_op.drop_index(batch_op.f('ix_flow_user_id'))
+            batch_op.drop_index(batch_op.f('ix_flow_name'))
+            batch_op.drop_index(batch_op.f('ix_flow_description'))
+    except Exception as e:
+        print(e)
+        pass
+    try:
+        with op.batch_alter_table('apikey', schema=None) as batch_op:
+            batch_op.drop_index(batch_op.f('ix_apikey_user_id'))
+            batch_op.drop_index(batch_op.f('ix_apikey_name'))
+            batch_op.drop_index(batch_op.f('ix_apikey_api_key'))
+    except Exception as e:
+        print(e)
+        pass
+    # ### end Alembic commands ###

src/backend/langflow/alembic/versions/260dbcc8b680_adds_tables.py

@@ -60,8 +60,8 @@ def upgrade() -> None:
             sa.Column("create_at", sa.DateTime(), nullable=False),
             sa.Column("updated_at", sa.DateTime(), nullable=False),
             sa.Column("last_login_at", sa.DateTime(), nullable=True),
-            sa.PrimaryKeyConstraint("id"),
+            sa.PrimaryKeyConstraint("id", name="pk_user"),
-            sa.UniqueConstraint("id"),
+            sa.UniqueConstraint("id", name="uq_user_id"),
         )
         with op.batch_alter_table("user", schema=None) as batch_op:
             batch_op.create_index(
@@ -83,8 +83,8 @@ def upgrade() -> None:
                 ["user_id"],
                 ["user.id"],
             ),
-            sa.PrimaryKeyConstraint("id"),
+            sa.PrimaryKeyConstraint("id", name="pk_apikey"),
-            sa.UniqueConstraint("id"),
+            sa.UniqueConstraint("id", name="uq_apikey_id"),
         )
         with op.batch_alter_table("apikey", schema=None) as batch_op:
             batch_op.create_index(
@@ -106,8 +106,8 @@ def upgrade() -> None:
                 ["user_id"],
                 ["user.id"],
             ),
-            sa.PrimaryKeyConstraint("id"),
+            sa.PrimaryKeyConstraint("id", name="pk_flow"),
-            sa.UniqueConstraint("id"),
+            sa.UniqueConstraint("id", name="uq_flow_id"),
         )
     # Conditionally create indices for 'flow' table
     # if _alembic_tmp_flow exists, then we need to drop it first

src/backend/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py

@@ -29,9 +29,10 @@ def upgrade() -> None:
         sa.Column('id', sqlmodel.sql.sqltypes.GUID(), nullable=False),
         sa.Column('created_at', sa.DateTime(), nullable=False),
         sa.Column('updated_at', sa.DateTime(), nullable=True),
-        sa.PrimaryKeyConstraint('id')
+        sa.PrimaryKeyConstraint('id'),
         )
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
     # ### end Alembic commands ###
 
@@ -40,6 +41,7 @@ def downgrade() -> None:
     # ### commands auto generated by Alembic - please adjust! ###
     try:
         op.drop_table('credential')
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
     # ### end Alembic commands ###

src/backend/langflow/alembic/versions/7843803a87b5_store_updates.py

@@ -45,6 +45,7 @@ def downgrade() -> None:
 
         with op.batch_alter_table("flow", schema=None) as batch_op:
             batch_op.drop_column("is_component")
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
     # ### end Alembic commands ###

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

@@ -37,7 +37,6 @@ def upgrade() -> None:
     with op.batch_alter_table('flow', schema=None) as batch_op:
         batch_op.add_column(sa.Column('updated_at', sa.DateTime(), nullable=True))
         batch_op.add_column(sa.Column('folder', sqlmodel.sql.sqltypes.AutoString(), nullable=True))
-
     # ### end Alembic commands ###
 
 

src/backend/langflow/alembic/versions/eb5866d51fd2_change_columns_to_be_nullable.py

@@ -29,7 +29,8 @@ def upgrade() -> None:
     except exc.SQLAlchemyError:
         # connection.execute(text("ROLLBACK"))
         pass
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
 
     try:
@@ -37,7 +38,8 @@ def upgrade() -> None:
     except exc.SQLAlchemyError:
         # connection.execute(text("ROLLBACK"))
         pass
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
     # ### end Alembic commands ###
 
@@ -57,14 +59,15 @@ def downgrade() -> None:
             sa.Column("is_read_only", sa.BOOLEAN(), nullable=False),
             sa.Column("create_at", sa.DATETIME(), nullable=False),
             sa.Column("update_at", sa.DATETIME(), nullable=False),
-            sa.PrimaryKeyConstraint("id"),
+            sa.PrimaryKeyConstraint("id", name="pk_component"),
         )
         with op.batch_alter_table("component", schema=None) as batch_op:
             batch_op.create_index("ix_component_name", ["name"], unique=False)
             batch_op.create_index(
                 "ix_component_frontend_node_id", ["frontend_node_id"], unique=False
             )
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
 
     try:
@@ -78,9 +81,10 @@ def downgrade() -> None:
                 ["flow_id"],
                 ["flow.id"],
             ),
-            sa.PrimaryKeyConstraint("id"),
+            sa.PrimaryKeyConstraint("id", name="pk_flowstyle"),
-            sa.UniqueConstraint("id"),
+            sa.UniqueConstraint("id", name="uq_flowstyle_id"),
         )
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
     # ### end Alembic commands ###

src/backend/langflow/alembic/versions/f5ee9749d1a6_user_id_can_be_null_in_flow.py

@@ -7,10 +7,8 @@ Create Date: 2023-10-18 23:12:27.297016
 """
 from typing import Sequence, Union
 
-from alembic import op
 import sqlalchemy as sa
-import sqlmodel
+from alembic import op
-
 
 # revision identifiers, used by Alembic.
 revision: str = "f5ee9749d1a6"
@@ -26,7 +24,8 @@ def upgrade() -> None:
             batch_op.alter_column(
                 "user_id", existing_type=sa.CHAR(length=32), nullable=True
             )
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
 
     # ### end Alembic commands ###
@@ -39,7 +38,8 @@ def downgrade() -> None:
             batch_op.alter_column(
                 "user_id", existing_type=sa.CHAR(length=32), nullable=False
             )
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
 
     # ### end Alembic commands ###

src/backend/langflow/alembic/versions/fd531f8868b1_fix_credential_table.py

@@ -21,7 +21,8 @@ def upgrade() -> None:
     try:
         with op.batch_alter_table('credential', schema=None) as batch_op:
             batch_op.create_foreign_key("fk_credential_user_id", 'user', ['user_id'], ['id'])
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
 
     # ### end Alembic commands ###
@@ -32,7 +33,8 @@ def downgrade() -> None:
     try:
         with op.batch_alter_table('credential', schema=None) as batch_op:
             batch_op.drop_constraint("fk_credential_user_id", type_='foreignkey')
-    except Exception:
+    except Exception as e:
+        print(e)
         pass
 
     # ### end Alembic commands ###

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

@@ -3,12 +3,10 @@ from typing import Annotated, Any, List, Optional, Union
 
 import sqlalchemy as sa
 from fastapi import APIRouter, Body, Depends, HTTPException, UploadFile, status
-from loguru import logger
-from sqlmodel import select
-
 from langflow.api.utils import update_frontend_node_with_template_values
 from langflow.api.v1.schemas import (
     CustomComponentCode,
+    PreloadResponse,
     ProcessResponse,
     TaskResponse,
     TaskStatusResponse,
@@ -17,12 +15,15 @@ from langflow.api.v1.schemas import (
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.interface.custom.directory_reader import DirectoryReader
 from langflow.interface.custom.utils import build_custom_component_template
-from langflow.processing.process import process_graph_cached, process_tweaks
+from langflow.processing.process import build_graph_and_generate_result, process_graph_cached, process_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.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
+from loguru import logger
+from sqlmodel import select
 
 try:
     from langflow.worker import process_graph_cached_task
@@ -32,9 +33,8 @@ except ImportError:
         raise NotImplementedError("Celery is not installed")
 
 
-from sqlmodel import Session
-
 from langflow.services.task.service import TaskService
+from sqlmodel import Session
 
 # build router
 router = APIRouter(tags=["Base"])
@@ -148,6 +148,55 @@ async def process_json(
         raise HTTPException(status_code=500, detail=str(exc)) from exc
 
 
+# Endpoint to preload a graph
+@router.post("/process/preload/{flow_id}", response_model=PreloadResponse)
+async def preload_flow(
+    session: Annotated[Session, Depends(get_session)],
+    flow_id: str,
+    session_id: Optional[str] = None,
+    session_service: SessionService = Depends(get_session_service),
+    api_key_user: User = Depends(api_key_security),
+    clear_session: Annotated[bool, Body(embed=True)] = False,  # noqa: F821
+):
+    try:
+        # 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()
+        if clear_session:
+            session_service.clear_session(session_id)
+            # Check if the session exists
+            session_data = await session_service.load_session(session_id)
+            # Session data is a tuple of (graph, artifacts)
+            # or (None, None) if the session is empty
+            if isinstance(session_data, tuple):
+                graph, artifacts = session_data
+                is_clear = graph is None and artifacts is None
+            else:
+                is_clear = session_data is None
+            return PreloadResponse(session_id=session_id, is_clear=is_clear)
+        else:
+            if session_id is None:
+                session_id = flow_id
+            flow = session.exec(select(Flow).where(Flow.id == flow_id).where(Flow.user_id == api_key_user.id)).first()
+            if flow is None:
+                raise ValueError(f"Flow {flow_id} not found")
+
+            if flow.data is None:
+                raise ValueError(f"Flow {flow_id} has no data")
+            graph_data = flow.data
+            session_service.clear_session(session_id)
+            # Load the graph using SessionService
+            session_data = await session_service.load_session(session_id, graph_data)
+            graph, artifacts = session_data if session_data else (None, None)
+            if not graph:
+                raise ValueError("Graph not found in the session")
+            _ = await graph.build()
+            session_service.update_session(session_id, (graph, artifacts))
+            return PreloadResponse(session_id=session_id)
+    except Exception as exc:
+        logger.exception(exc)
+        raise HTTPException(status_code=500, detail=str(exc)) from exc
+
+
 @router.post(
     "/predict/{flow_id}",
     response_model=ProcessResponse,
@@ -167,12 +216,51 @@ async def process(
     task_service: "TaskService" = Depends(get_task_service),
     api_key_user: User = Depends(api_key_security),
     sync: Annotated[bool, Body(embed=True)] = True,  # noqa: F821
+    session_service: SessionService = Depends(get_session_service),
 ):
     """
     Endpoint to process an input with a given flow_id.
     """
 
     try:
+        if session_id:
+            session_data = await session_service.load_session(session_id)
+            graph, artifacts = session_data if session_data else (None, None)
+            task_result: Any = None
+            task_status = None
+            task_id = None
+            if not graph:
+                raise ValueError("Graph not found in the session")
+            result = await build_graph_and_generate_result(
+                graph=graph,
+                inputs=inputs,
+                artifacts=artifacts,
+                session_id=session_id,
+                session_service=session_service,
+            )
+            task_id = str(id(result))
+            if isinstance(result, dict) and "result" in result:
+                task_result = result["result"]
+                session_id = result["session_id"]
+            elif hasattr(result, "result") and hasattr(result, "session_id"):
+                task_result = result.result
+
+                session_id = result.session_id
+            else:
+                task_result = result
+            if task_id:
+                task_response = TaskResponse(id=task_id, href=f"api/v1/task/{task_id}")
+            else:
+                task_response = None
+            return ProcessResponse(
+                result=task_result,
+                status=task_status,
+                task=task_response,
+                session_id=session_id,
+                backend=task_service.backend_name,
+            )
+
+        else:
             if api_key_user is None:
                 raise HTTPException(
                     status_code=status.HTTP_401_UNAUTHORIZED,

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

@@ -64,6 +64,13 @@ class ProcessResponse(BaseModel):
     backend: Optional[str] = None
 
 
+class PreloadResponse(BaseModel):
+    """Preload response schema."""
+
+    session_id: Optional[str] = None
+    is_clear: Optional[bool] = None
+
+
 # TaskStatusResponse(
 #         status=task.status, result=task.result if task.ready() else None
 #     )

src/backend/langflow/components/embeddings/AzureOpenAIEmbeddings.py

@@ -0,0 +1,64 @@
+from langflow import CustomComponent
+from langchain.embeddings.base import Embeddings
+from langchain_community.embeddings import AzureOpenAIEmbeddings
+
+
+class AzureOpenAIEmbeddingsComponent(CustomComponent):
+    display_name: str = "AzureOpenAIEmbeddings"
+    description: str = "Embeddings model from Azure OpenAI."
+    documentation: str = "https://python.langchain.com/docs/integrations/text_embedding/azureopenai"
+    beta = False
+
+    API_VERSION_OPTIONS = [
+        "2022-12-01",
+        "2023-03-15-preview",
+        "2023-05-15",
+        "2023-06-01-preview",
+        "2023-07-01-preview",
+        "2023-08-01-preview",
+    ]
+
+    def build_config(self):
+        return {
+            "azure_endpoint": {
+                "display_name": "Azure Endpoint",
+                "required": True,
+                "info": "Your Azure endpoint, including the resource.. Example: `https://example-resource.azure.openai.com/`",
+            },
+            "azure_deployment": {
+                "display_name": "Deployment Name",
+                "required": True,
+            },
+            "api_version": {
+                "display_name": "API Version",
+                "options": self.API_VERSION_OPTIONS,
+                "value": self.API_VERSION_OPTIONS[-1],
+                "advanced": True,
+            },
+            "api_key": {
+                "display_name": "API Key",
+                "required": True,
+                "password": True,
+            },
+            "code": {"show": False},
+        }
+
+    def build(
+        self,
+        azure_endpoint: str,
+        azure_deployment: str,
+        api_version: str,
+        api_key: str,
+    ) -> Embeddings:
+        try:
+            embeddings = AzureOpenAIEmbeddings(
+                azure_endpoint=azure_endpoint,
+                deployment=azure_deployment,
+                openai_api_version=api_version,
+                openai_api_key=api_key,
+            )
+
+        except Exception as e:
+            raise ValueError("Could not connect to AzureOpenAIEmbeddings API.") from e
+
+        return embeddings

src/backend/langflow/components/embeddings/OllamaEmbeddings.py

@@ -0,0 +1,38 @@
+from typing import Optional
+
+from langflow import CustomComponent
+from langchain.embeddings.base import Embeddings
+from langchain_community.embeddings import OllamaEmbeddings
+
+
+class OllamaEmbeddingsComponent(CustomComponent):
+    """
+    A custom component for implementing an Embeddings Model using Ollama.
+    """
+
+    display_name: str = "Ollama Embeddings"
+    description: str = "Embeddings model from Ollama."
+    documentation = "https://python.langchain.com/docs/integrations/text_embedding/ollama"
+    beta = True
+
+    def build_config(self):
+        return {
+            "model": {
+                "display_name": "Ollama Model",
+            },
+            "base_url": {"display_name": "Ollama Base URL"},
+            "temperature": {"display_name": "Model Temperature"},
+            "code": {"show": False},
+        }
+
+    def build(
+        self,
+        model: str = "llama2",
+        base_url: str = "http://localhost:11434",
+        temperature: Optional[float] = None,
+    ) -> Embeddings:
+        try:
+            output = OllamaEmbeddings(model=model, base_url=base_url, temperature=temperature)  # type: ignore
+        except Exception as e:
+            raise ValueError("Could not connect to Ollama API.") from e
+        return output

src/backend/langflow/components/llms/AzureChatOpenAI.py

@@ -8,6 +8,7 @@ class AzureChatOpenAIComponent(CustomComponent):
     display_name: str = "AzureChatOpenAI"
     description: str = "LLM model from Azure OpenAI."
     documentation: str = "https://python.langchain.com/docs/integrations/llms/azure_openai"
+    beta = False
 
     AZURE_OPENAI_MODELS = [
         "gpt-35-turbo",
@@ -18,11 +19,21 @@ class AzureChatOpenAIComponent(CustomComponent):
         "gpt-4-vision",
     ]
 
+    AZURE_OPENAI_API_VERSIONS = [
+        "2023-03-15-preview",
+        "2023-05-15",
+        "2023-06-01-preview",
+        "2023-07-01-preview",
+        "2023-08-01-preview",
+        "2023-09-01-preview",
+        "2023-12-01-preview"
+    ]
+
     def build_config(self):
         return {
             "model": {
                 "display_name": "Model Name",
-                "value": "gpt-35-turbo",
+                "value": self.AZURE_OPENAI_MODELS[0],
                 "options": self.AZURE_OPENAI_MODELS,
                 "required": True,
             },
@@ -37,7 +48,8 @@ class AzureChatOpenAIComponent(CustomComponent):
             },
             "api_version": {
                 "display_name": "API Version",
-                "value": "2023-05-15",
+                "options": self.AZURE_OPENAI_API_VERSIONS,
+                "value": self.AZURE_OPENAI_API_VERSIONS[-1],
                 "required": True,
                 "advanced": True,
             },
@@ -54,6 +66,7 @@ class AzureChatOpenAIComponent(CustomComponent):
                 "required": False,
                 "field_type": "int",
                 "advanced": True,
+                "info": "Maximum number of tokens to generate.",
             },
             "code": {"show": False},
         }
@@ -64,11 +77,12 @@ class AzureChatOpenAIComponent(CustomComponent):
         azure_endpoint: str,
         azure_deployment: str,
         api_key: str,
-        api_version: str = "2023-05-15",
+        api_version: str,
         temperature: float = 0.7,
         max_tokens: Optional[int] = 1000,
     ) -> BaseLanguageModel:
-        return AzureChatOpenAI(
+        try:
+            llm = AzureChatOpenAI(
                 model=model,
                 azure_endpoint=azure_endpoint,
                 azure_deployment=azure_deployment,
@@ -77,3 +91,6 @@ class AzureChatOpenAIComponent(CustomComponent):
                 temperature=temperature,
                 max_tokens=max_tokens,
             )
+        except Exception as e:
+            raise ValueError("Could not connect to AzureOpenAI API.") from e
+        return llm

src/backend/langflow/config.yaml

@@ -106,6 +106,8 @@ embeddings:
     documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/google_vertex_ai_palm"
   AmazonBedrockEmbeddings:
     documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/bedrock"
+  OllamaEmbeddings:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/ollama"
 
 llms:
   OpenAI:

src/backend/langflow/interface/chains/custom.py

@@ -67,7 +67,9 @@ Human: {input}
 class MidJourneyPromptChain(BaseCustomConversationChain):
     """MidJourneyPromptChain is a chain you can use to generate new MidJourney prompts."""
 
-    template: Optional[str] = """I want you to act as a prompt generator for Midjourney's artificial intelligence program.
+    template: Optional[
+        str
+    ] = """I want you to act as a prompt generator for Midjourney's artificial intelligence program.
     Your job is to provide detailed and creative descriptions that will inspire unique and interesting images from the AI.
     Keep in mind that the AI is capable of understanding a wide range of language and can interpret abstract concepts, so feel free to be as imaginative and descriptive as possible.
     For example, you could describe a scene from a futuristic city, or a surreal landscape filled with strange creatures.
@@ -81,7 +83,9 @@ class MidJourneyPromptChain(BaseCustomConversationChain):
 
 
 class TimeTravelGuideChain(BaseCustomConversationChain):
-    template: Optional[str] = """I want you to act as my time travel guide. You are helpful and creative. I will provide you with the historical period or future time I want to visit and you will suggest the best events, sights, or people to experience. Provide the suggestions and any necessary information.
+    template: Optional[
+        str
+    ] = """I want you to act as my time travel guide. You are helpful and creative. I will provide you with the historical period or future time I want to visit and you will suggest the best events, sights, or people to experience. Provide the suggestions and any necessary information.
     Current conversation:
     {history}
     Human: {input}

src/backend/langflow/main.py

@@ -7,6 +7,7 @@ from fastapi import FastAPI, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import FileResponse
 from fastapi.staticfiles import StaticFiles
+
 from langflow.api import router
 from langflow.interface.utils import setup_llm_caching
 from langflow.services.plugins.langfuse_plugin import LangfuseInstance
@@ -102,11 +103,12 @@ def setup_app(static_files_dir: Optional[Path] = None, backend_only: bool = Fals
 
 if __name__ == "__main__":
     import uvicorn
+
     from langflow.__main__ import get_number_of_workers
 
     configure()
     uvicorn.run(
-        create_app,
+        "langflow.main:create_app",
         host="127.0.0.1",
         port=7860,
         workers=get_number_of_workers(),

src/backend/langflow/processing/process.py

@@ -7,9 +7,11 @@ from langchain.schema import AgentAction, Document
 from langchain.vectorstores.base import VectorStore
 from langchain_core.messages import AIMessage
 from langchain_core.runnables.base import Runnable
+from langflow.graph.graph.base import Graph
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.interface.run import build_sorted_vertices, get_memory_key, update_memory_keys
 from langflow.services.deps import get_session_service
+from langflow.services.session.service import SessionService
 from loguru import logger
 from pydantic import BaseModel
 
@@ -220,13 +222,29 @@ async def process_graph_cached(
     graph, artifacts = session if session else (None, None)
     if not graph:
         raise ValueError("Graph not found in the session")
+
+    result = await build_graph_and_generate_result(
+        graph=graph, session_id=session_id, inputs=inputs, artifacts=artifacts, session_service=session_service
+    )
+
+    return result
+
+
+async def build_graph_and_generate_result(
+    graph: "Graph",
+    session_id: str,
+    inputs: Optional[Union[dict, List[dict]]] = None,
+    artifacts: Optional[Dict[str, Any]] = None,
+    session_service: Optional[SessionService] = None,
+):
+    """Build the graph and generate the result"""
     built_object = await graph.build()
     processed_inputs = process_inputs(inputs, artifacts or {})
     result = await generate_result(built_object, processed_inputs)
     # langchain_object is now updated with the new memory
     # we need to update the cache with the updated langchain_object
+    if session_id and session_service:
         session_service.update_session(session_id, (graph, artifacts))
-
     return Result(result=result, session_id=session_id)
 
 

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

@@ -5,17 +5,16 @@ from typing import TYPE_CHECKING
 import sqlalchemy as sa
 from alembic import command, util
 from alembic.config import Config
-from loguru import logger
-from sqlalchemy import inspect
-from sqlalchemy.exc import OperationalError
-from sqlmodel import Session, SQLModel, create_engine, select, text
-
 from langflow.services.base import Service
 from langflow.services.database import models  # noqa
 from langflow.services.database.models.user.crud import get_user_by_username
 from langflow.services.database.utils import Result, TableResults
 from langflow.services.deps import get_settings_service
 from langflow.services.utils import teardown_superuser
+from loguru import logger
+from sqlalchemy import inspect
+from sqlalchemy.exc import OperationalError
+from sqlmodel import Session, SQLModel, create_engine, select, text
 
 if TYPE_CHECKING:
     from sqlalchemy.engine import Engine
@@ -40,7 +39,7 @@ 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, max_overflow=-1)
 
     def __enter__(self):
         self._session = Session(self.engine)

src/backend/langflow/services/session/service.py

@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Optional
 
 from langflow.interface.run import build_sorted_vertices
 from langflow.services.base import Service
@@ -14,14 +14,15 @@ class SessionService(Service):
     def __init__(self, cache_service):
         self.cache_service: "BaseCacheService" = cache_service
 
-    async def load_session(self, key, data_graph):
+    async def load_session(self, key, data_graph: Optional[dict] = None):
         # Check if the data is cached
         if key in self.cache_service:
             return self.cache_service.get(key)
 
         if key is None:
             key = self.generate_key(session_id=None, data_graph=data_graph)
-
+        if data_graph is None:
+            return (None, None)
         # If not cached, build the graph and cache it
         graph, artifacts = await build_sorted_vertices(data_graph)
 

src/frontend/src/App.tsx

@@ -23,7 +23,6 @@ import useFlowsManagerStore from "./stores/flowsManagerStore";
 import { useTypesStore } from "./stores/typesStore";
 
 export default function App() {
-
   const errorData = useAlertStore((state) => state.errorData);
   const errorOpen = useAlertStore((state) => state.errorOpen);
   const setErrorOpen = useAlertStore((state) => state.setErrorOpen);

src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx

@@ -57,6 +57,7 @@ export default function ParameterComponent({
   proxy,
   showNode,
   index = "",
+  isMinimized,
 }: ParameterComponentType): JSX.Element {
   const ref = useRef<HTMLDivElement>(null);
   const refHtml = useRef<HTMLDivElement & ReactNode>(null);
@@ -132,7 +133,6 @@ export default function ParameterComponent({
       takeSnapshot();
     }
 
-    
     setNode(data.id, (oldNode) => {
       let newNode = cloneDeep(oldNode);
 
@@ -273,9 +273,11 @@ export default function ParameterComponent({
             <Handle
               type={left ? "target" : "source"}
               position={left ? Position.Left : Position.Right}
-              key={proxy
+              key={
+                proxy
                   ? scapedJSONStringfy({ ...id, proxy })
-                : scapedJSONStringfy(id)}
+                  : scapedJSONStringfy(id)
+              }
               id={
                 proxy
                   ? scapedJSONStringfy({ ...id, proxy })
@@ -286,7 +288,8 @@ export default function ParameterComponent({
               }
               className={classNames(
                 left ? "my-12 -ml-0.5 " : " my-12 -mr-0.5 ",
-                "h-3 w-3 rounded-full border-2 bg-background"
+                "h-3 w-3 rounded-full border-2 bg-background",
+                isMinimized ? "mt-0" : ""
               )}
               style={{
                 borderColor: color,
@@ -348,9 +351,11 @@ export default function ParameterComponent({
                 <Handle
                   type={left ? "target" : "source"}
                   position={left ? Position.Left : Position.Right}
-                  key={proxy
+                  key={
+                    proxy
                       ? scapedJSONStringfy({ ...id, proxy })
-                    : scapedJSONStringfy(id)}
+                      : scapedJSONStringfy(id)
+                  }
                   id={
                     proxy
                       ? scapedJSONStringfy({ ...id, proxy })
@@ -395,8 +400,8 @@ export default function ParameterComponent({
                 disabled={disabled}
                 value={data.node.template[name].value ?? ""}
                 onChange={handleOnNewValue}
-                id={"textarea-" + index}
+                id={"textarea-" + data.node.template[name].name}
-                data-testid={"textarea-" + index}
+                data-testid={"textarea-" + data.node.template[name].name}
               />
             ) : (
               <InputComponent

src/frontend/src/CustomNodes/GenericNode/index.tsx

@@ -1,5 +1,5 @@
 import { useEffect, useState } from "react";
-import { NodeToolbar } from "reactflow";
+import { NodeToolbar, useUpdateNodeInternals } from "reactflow";
 import ShadTooltip from "../../components/ShadTooltipComponent";
 import Tooltip from "../../components/TooltipComponent";
 import IconComponent from "../../components/genericIconComponent";
@@ -41,7 +41,9 @@ export default function GenericNode({
   const [validationStatus, setValidationStatus] =
     useState<validationStatusType | null>(null);
   const [handles, setHandles] = useState<boolean[] | []>([]);
+  const [isMinimized, setIsMinimized] = useState<boolean>(false);
   let numberOfInputs: boolean[] = [];
+  const updateNodeInternals = useUpdateNodeInternals();
 
   const takeSnapshot = useFlowsManagerStore((state) => state.takeSnapshot);
 
@@ -105,6 +107,10 @@ export default function GenericNode({
 
   const nameEditable = data.node?.flow || data.type === "CustomComponent";
 
+  useEffect(() => {
+    updateNodeInternals(data.id);
+  }, [isMinimized]);
+
   return (
     <>
       <NodeToolbar>
@@ -123,6 +129,7 @@ export default function GenericNode({
           }}
           numberOfHandles={handles}
           showNode={showNode}
+          setIsMinimized={setIsMinimized}
         ></NodeToolbarComponent>
       </NodeToolbar>
 
@@ -276,6 +283,7 @@ export default function GenericNode({
                             }
                             proxy={data.node?.template[templateField].proxy}
                             showNode={showNode}
+                            isMinimized={isMinimized}
                           />
                         )
                     )}
@@ -302,6 +310,7 @@ export default function GenericNode({
                     type={data.node?.base_classes.join("|")}
                     left={false}
                     showNode={showNode}
+                    isMinimized={isMinimized}
                   />
                 </>
               )}
@@ -506,6 +515,7 @@ export default function GenericNode({
                         }
                         proxy={data.node?.template[templateField].proxy}
                         showNode={showNode}
+                        isMinimized={isMinimized}
                       />
                     ) : (
                       <></>
@@ -549,6 +559,7 @@ export default function GenericNode({
                   type={data.node?.base_classes.join("|")}
                   left={false}
                   showNode={showNode}
+                  isMinimized={isMinimized}
                 />
               )}
             </>

src/frontend/src/components/chatComponent/index.tsx

@@ -5,7 +5,6 @@ import BuildTrigger from "./buildTrigger";
 import ChatTrigger from "./chatTrigger";
 
 import * as _ from "lodash";
-import { getBuildStatus } from "../../controllers/API";
 import FormModal from "../../modals/formModal";
 import useFlowStore from "../../stores/flowStore";
 import { NodeType } from "../../types/flow";
@@ -32,17 +31,6 @@ export default function Chat({ flow }: ChatType): JSX.Element {
     };
   }, [isBuilt]);
 
-  useEffect(() => {
-    // Define an async function within the useEffect hook
-    const fetchBuildStatus = async () => {
-      const response = await getBuildStatus(flow.id);
-      setIsBuilt(response.data.built);
-    };
-
-    // Call the async function
-    fetchBuildStatus();
-  }, [flow]);
-
   const prevNodesRef = useRef<any[] | undefined>();
   const nodes: NodeType[] = useNodes();
   useEffect(() => {

src/frontend/src/components/codeTabsComponent/index.tsx

@@ -35,7 +35,6 @@ import {
   convertObjToArray,
   convertValuesToNumbers,
   hasDuplicateKeys,
-  unselectAllNodes,
 } from "../../utils/reactflowUtils";
 import { classNames } from "../../utils/utils";
 import DictComponent from "../dictComponent";
@@ -54,6 +53,7 @@ export default function CodeTabsComponent({
   const [data, setData] = useState(flow ? flow["data"]!["nodes"] : null);
   const [openAccordion, setOpenAccordion] = useState<string[]>([]);
   const dark = useDarkStore((state) => state.dark);
+  const unselectAll = useFlowStore((state) => state.unselectAll);
 
   const setNodes = useFlowStore((state) => state.setNodes);
 
@@ -67,12 +67,7 @@ export default function CodeTabsComponent({
 
   useEffect(() => {
     if (tweaks && data) {
-      unselectAllNodes({
+      unselectAll();
-        data,
-        updateNodes: (nodes) => {
-          setNodes(nodes);
-        },
-      });
     }
   }, []);
 
@@ -593,14 +588,7 @@ export default function CodeTabsComponent({
                                               ].type === "prompt" ? (
                                               <div className="mx-auto">
                                                 <PromptAreaComponent
-                                                  readonly={
+                                                  readonly={true}
-                                                    node.data.node?.flow &&
-                                                    node.data.node.template[
-                                                      templateField
-                                                    ].dynamic
-                                                      ? true
-                                                      : false
-                                                  }
                                                   editNode={true}
                                                   disabled={false}
                                                   value={
@@ -643,14 +631,7 @@ export default function CodeTabsComponent({
                                                 <CodeAreaComponent
                                                   disabled={false}
                                                   editNode={true}
-                                                  readonly={
+                                                  readonly={true}
-                                                    node.data.node?.flow &&
-                                                    node.data.node.template[
-                                                      templateField
-                                                    ].dynamic
-                                                      ? true
-                                                      : false
-                                                  }
                                                   value={
                                                     !node.data.node.template[
                                                       templateField

src/frontend/src/modals/EditNodeModal/index.tsx

@@ -216,8 +216,16 @@ const EditNodeModal = forwardRef(
                                     ) : myData.node.template[templateParam]
                                         .multiline ? (
                                       <TextAreaComponent
-                                        id={"textarea-edit-" + index}
+                                        id={
-                                        data-testid={"textarea-edit-" + index}
+                                          "textarea-edit-" +
+                                          myData.node.template[templateParam]
+                                            .name
+                                        }
+                                        data-testid={
+                                          "textarea-edit-" +
+                                          myData.node.template[templateParam]
+                                            .name
+                                        }
                                         disabled={disabled}
                                         editNode={true}
                                         value={
@@ -448,9 +456,13 @@ const EditNodeModal = forwardRef(
                                       onChange={(value: string | string[]) => {
                                         handleOnNewValue(value, templateParam);
                                       }}
-                                      id={"prompt-area-edit" + index}
+                                      id={
+                                        "prompt-area-edit-" +
+                                        myData.node.template[templateParam].name
+                                      }
                                       data-testid={
-                                        "modal-prompt-input-" + index
+                                        "modal-prompt-input-" +
+                                        myData.node.template[templateParam].name
                                       }
                                     />
                                   </div>

src/frontend/src/modals/genericModal/index.tsx

@@ -126,7 +126,8 @@ export default function GenericModal({
           if (
             JSON.stringify(apiReturn.data?.frontend_node) !== JSON.stringify({})
           ) {
-            setNodeClass!(apiReturn.data?.frontend_node, inputValue);
+            if (setNodeClass)
+              setNodeClass(apiReturn.data?.frontend_node, inputValue);
             setModalOpen(closeModal);
             setIsEdit(false);
           }

src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx

@@ -9,7 +9,6 @@ import ReactFlow, {
   OnMove,
   OnSelectionChangeParams,
   SelectionDragHandler,
-  addEdge,
   updateEdge,
 } from "reactflow";
 import GenericNode from "../../../../CustomNodes/GenericNode";
@@ -19,13 +18,12 @@ import useFlowStore from "../../../../stores/flowStore";
 import useFlowsManagerStore from "../../../../stores/flowsManagerStore";
 import { useTypesStore } from "../../../../stores/typesStore";
 import { APIClassType } from "../../../../types/api";
-import { FlowType, NodeType, targetHandleType } from "../../../../types/flow";
+import { FlowType, NodeType } from "../../../../types/flow";
 import {
   generateFlow,
   generateNodeFromFlow,
   getNodeId,
   isValidConnection,
-  scapeJSONParse,
   validateSelection,
 } from "../../../../utils/reactflowUtils";
 import { getRandomName, isWrappedWithClass } from "../../../../utils/utils";
@@ -175,8 +173,8 @@ export default function Page({
   useEffect(() => {
     return () => {
       cleanFlow();
-    }
+    };
-  }, [])
+  }, []);
 
   const onConnectMod = useCallback(
     (params: Connection) => {

src/frontend/src/pages/FlowPage/components/extraSidebarComponent/sideBarDraggableComponent/index.tsx

@@ -4,7 +4,7 @@ import {
   Select,
   SelectContent,
   SelectItem,
-  SelectTrigger
+  SelectTrigger,
 } from "../../../../../components/ui/select-custom";
 import { useDarkStore } from "../../../../../stores/darkStore";
 import useFlowsManagerStore from "../../../../../stores/flowsManagerStore";

src/frontend/src/pages/FlowPage/components/nodeToolbarComponent/index.tsx

@@ -32,6 +32,7 @@ export default function NodeToolbarComponent({
   setShowNode,
   numberOfHandles,
   showNode,
+  setIsMinimized,
 }: nodeToolbarPropsType): JSX.Element {
   const nodeLength = Object.keys(data.node!.template).filter(
     (templateField) =>
@@ -97,6 +98,10 @@ export default function NodeToolbarComponent({
     showconfirmShare,
   ]);
 
+  useEffect(() => {
+    setIsMinimized(!showNode);
+  }, [showNode]);
+
   const handleSelectChange = (event) => {
     switch (event) {
       case "advanced":

src/frontend/src/stores/flowStore.ts

@@ -201,7 +201,7 @@ const useFlowStore = create<FlowStoreType>((set, get) => ({
         .map((node) => ({ ...node, selected: false }))
         .concat({ ...newNode, selected: false });
     });
-    set({ nodes: newNodes });
+    get().setNodes(newNodes);
 
     selection.edges.forEach((edge: Edge) => {
       let source = idsMap[edge.source];
@@ -245,7 +245,7 @@ const useFlowStore = create<FlowStoreType>((set, get) => ({
         newEdges.map((edge) => ({ ...edge, selected: false }))
       );
     });
-    set({ edges: newEdges });
+    get().setEdges(newEdges);
   },
   setLastCopiedSelection: (newSelection) => {
     set({ lastCopiedSelection: newSelection });
@@ -265,7 +265,7 @@ const useFlowStore = create<FlowStoreType>((set, get) => ({
   },
   getFilterEdge: [],
   onConnect: (connection) => {
-    let newEdges: Edge[] = []
+    let newEdges: Edge[] = [];
     get().setEdges((oldEdges) => {
       newEdges = addEdge(
         {
@@ -287,8 +287,7 @@ const useFlowStore = create<FlowStoreType>((set, get) => ({
         oldEdges
       );
       return newEdges;
-
+    });
-    })
     useFlowsManagerStore
       .getState()
       .autoSaveCurrentFlow(
@@ -297,6 +296,17 @@ const useFlowStore = create<FlowStoreType>((set, get) => ({
         get().reactFlowInstance?.getViewport() ?? { x: 0, y: 0, zoom: 1 }
       );
   },
+  unselectAll: () => {
+    let newNodes = cloneDeep(get().nodes);
+    newNodes.forEach((node) => {
+      node.selected = false;
+      let newEdges = cleanEdges(newNodes, get().edges);
+      set({
+        nodes: newNodes,
+        edges: newEdges,
+      });
+    });
+  },
 }));
 
 export default useFlowStore;

src/frontend/src/stores/typesStore.ts

@@ -43,5 +43,4 @@ export const useTypesStore = create<TypesStoreType>((set, get) => ({
     let newChange = typeof change === "function" ? change(get().data) : change;
     set({ data: newChange });
   },
-
 }));

src/frontend/src/types/components/index.ts

@@ -53,6 +53,7 @@ export type ParameterComponentType = {
   showNode?: boolean;
   index?: string;
   onCloseModal?: (close: boolean) => void;
+  isMinimized?: boolean;
 };
 export type InputListComponentType = {
   value: string[];
@@ -479,6 +480,7 @@ export type nodeToolbarPropsType = {
   setShowNode: (boolean: any) => void;
   numberOfHandles: boolean[] | [];
   showNode: boolean;
+  setIsMinimized: (boolean: boolean) => void;
 };
 
 export type parsedDataType = {

src/frontend/src/types/zustand/flow/index.ts

@@ -54,4 +54,5 @@ export type FlowStoreType = {
   setFilterEdge: (newState) => void;
   getFilterEdge: any[];
   onConnect: (connection: Connection) => void;
+  unselectAll: () => void;
 };

src/frontend/tests/end-to-end/promptModalComponent.spec.ts

@@ -44,7 +44,7 @@ test("PromptTemplateComponent", async ({ page }) => {
 
   await page.getByTestId("genericModalBtnSave").click();
 
-  await page.getByTestId("div-textarea-5").click();
+  await page.getByTestId("div-textarea-prompt").click();
   await page.getByTestId("text-area-modal").fill("prompt_value_!@#!@#");
 
   value = await page.getByTestId("text-area-modal").inputValue();
@@ -55,7 +55,7 @@ test("PromptTemplateComponent", async ({ page }) => {
 
   await page.getByTestId("genericModalBtnSave").click();
 
-  await page.getByTestId("div-textarea-6").click();
+  await page.getByTestId("div-textarea-prompt1").click();
   await page
     .getByTestId("text-area-modal")
     .fill("prompt_name_test_123123!@#!@#");
@@ -77,29 +77,31 @@ test("PromptTemplateComponent", async ({ page }) => {
   await page.getByTestId("more-options-modal").click();
   await page.getByTestId("edit-button-modal").click();
 
-  value = await page.locator('//*[@id="textarea-edit-1"]').inputValue();
+  value = await page.locator('//*[@id="textarea-edit-prompt"]').inputValue();
 
   if (value != "prompt_value_!@#!@#") {
     expect(false).toBeTruthy();
   }
 
-  value = await page.locator('//*[@id="textarea-edit-2"]').inputValue();
+  value = await page.locator('//*[@id="textarea-edit-prompt1"]').inputValue();
 
   if (value != "prompt_name_test_123123!@#!@#") {
     expect(false).toBeTruthy();
   }
 
-  value = await page.locator('//*[@id="prompt-area-edit0"]').innerText();
+  value = await page
+    .locator('//*[@id="prompt-area-edit-template"]')
+    .innerText();
 
   if (value != "{prompt} example {prompt1}") {
     expect(false).toBeTruthy();
   }
 
   await page
-    .locator('//*[@id="textarea-edit-2"]')
+    .locator('//*[@id="textarea-edit-prompt1"]')
     .fill("prompt_edit_test_12312312321!@#$");
   await page
-    .locator('//*[@id="textarea-edit-1"]')
+    .locator('//*[@id="textarea-edit-prompt"]')
     .fill("prompt_edit_test_44444444444!@#$");
 
   await page.locator('//*[@id="showtemplate"]').click();
@@ -141,35 +143,29 @@ test("PromptTemplateComponent", async ({ page }) => {
 
   await page.locator('//*[@id="saveChangesBtn"]').click();
 
-  const plusButtonLocator = page.locator('//*[@id="textarea-8"]');
-  const elementCount = await plusButtonLocator.count();
-  if (elementCount === 0) {
-    expect(true).toBeTruthy();
-
   await page.getByTestId("more-options-modal").click();
   await page.getByTestId("edit-button-modal").click();
 
   await page.locator('//*[@id="showprompt1"]').click();
-    expect(
+  expect(await page.locator('//*[@id="showprompt1"]').isChecked()).toBeTruthy();
-      await page.locator('//*[@id="showprompt1"]').isChecked()
-    ).toBeTruthy();
 
-    value = await page.locator('//*[@id="textarea-edit-1"]').inputValue();
+  value = await page.locator('//*[@id="textarea-edit-prompt"]').inputValue();
 
   if (value != "prompt_edit_test_44444444444!@#$") {
     expect(false).toBeTruthy();
   }
 
-    value = await page.locator('//*[@id="textarea-edit-2"]').inputValue();
+  value = await page.locator('//*[@id="textarea-edit-prompt1"]').inputValue();
 
   if (value != "prompt_edit_test_12312312321!@#$") {
     expect(false).toBeTruthy();
   }
 
-    value = await page.locator('//*[@id="prompt-area-edit0"]').innerText();
+  value = await page
+    .locator('//*[@id="prompt-area-edit-template"]')
+    .innerText();
 
   if (value != "{prompt} example {prompt1}") {
     expect(false).toBeTruthy();
   }
-  }
 });

src/frontend/tests/onlyFront/group.spec.ts

@@ -67,7 +67,7 @@ test.describe("group node test", () => {
 
     await page.getByRole("button", { name: "Group" }).click();
 
-    const textArea = page.getByTestId("div-textarea-2");
+    const textArea = page.getByTestId("div-textarea-description");
     const elementCountText = await textArea.count();
     if (elementCountText > 0) {
       expect(true).toBeTruthy();

src/frontend/tests/onlyFront/nestedComponent.spec.ts

@@ -26,8 +26,7 @@ test("NestedComponent", async ({ page }) => {
     .getByTestId("vectorstoresPinecone")
     .first()
     .dragTo(page.locator('//*[@id="react-flow-id"]'));
-  await page.mouse.up();
+  await page.click('//*[@id="react-flow-id"]');
-  await page.mouse.down();
 
   await page.getByTestId("more-options-modal").click();
   await page.getByTestId("edit-button-modal").click();

src/frontend/tests/onlyFront/saveComponents.spec.ts

@@ -74,7 +74,7 @@ test.describe("save component tests", () => {
 
     await page.getByRole("button", { name: "Group" }).click();
 
-    let textArea = page.getByTestId("div-textarea-2");
+    let textArea = page.getByTestId("div-textarea-description");
     let elementCountText = await textArea.count();
     if (elementCountText > 0) {
       expect(true).toBeTruthy();
@@ -102,7 +102,7 @@ test.describe("save component tests", () => {
     await page.mouse.up();
     await page.mouse.down();
 
-    textArea = page.getByTestId("div-textarea-2");
+    textArea = page.getByTestId("div-textarea-description");
     elementCountText = await textArea.count();
     if (elementCountText > 0) {
       expect(true).toBeTruthy();