Merge remote-tracking branch 'origin/dev' into zustand/io/migration

docs/docs/examples/buffer-memory.mdx

@@ -21,7 +21,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
 
 <Admonition type="note" title="LangChain Components 🦜🔗">
 
-- [`ConversationBufferMemory`](https://python.langchain.com/docs/modules/memory/how_to/buffer)
+- [`ConversationBufferMemory`](https://python.langchain.com/docs/modules/memory/types/buffer)
 - [`ConversationChain`](https://python.langchain.com/docs/modules/chains/)
 - [`ChatOpenAI`](https://python.langchain.com/docs/modules/model_io/models/chat/integrations/openai)
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.6.5a13"
+version = "0.6.6"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [
@@ -26,24 +26,24 @@ langflow = "langflow.__main__:main"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
-fastapi = "^0.108.0"
-uvicorn = "^0.25.0"
+fastapi = "^0.109.0"
+uvicorn = "^0.27.0"
 beautifulsoup4 = "^4.12.2"
 google-search-results = "^2.4.1"
 google-api-python-client = "^2.79.0"
 typer = "^0.9.0"
 gunicorn = "^21.2.0"
 langchain = "~0.1.0"
-openai = "^1.10.0"
 duckdb = "^0.9.2"
+openai = "^1.11.0"
 pandas = "2.0.3"
 chromadb = "^0.4.0"
-huggingface-hub = { version = "^0.19.0", extras = ["inference"] }
+huggingface-hub = { version = "^0.20.0", extras = ["inference"] }
 rich = "^13.7.0"
 llama-cpp-python = { version = "~0.2.0", optional = true }
 networkx = "^3.1"
-unstructured = "^0.11.0"
-pypdf = "^3.17.0"
+unstructured = "^0.12.0"
+pypdf = "^4.0.0"
 lxml = "^4.9.2"
 pysrt = "^1.1.2"
 fake-useragent = "^1.4.0"
@@ -55,18 +55,18 @@ wikipedia = "^1.4.0"
 qdrant-client = "^1.7.0"
 weaviate-client = "*"
 jina = "*"
-sentence-transformers = { version = "^2.2.2", optional = true }
+sentence-transformers = { version = "^2.3.1", optional = true }
 ctransformers = { version = "^0.2.10", optional = true }
-cohere = "^4.39.0"
+cohere = "^4.45.0"
 python-multipart = "^0.0.6"
 sqlmodel = "^0.0.14"
 faiss-cpu = "^1.7.4"
-anthropic = "^0.13.0"
+anthropic = "^0.15.0"
 orjson = "3.9.3"
 multiprocess = "^0.70.14"
 cachetools = "^5.3.1"
 types-cachetools = "^5.3.0.5"
-platformdirs = "^4.1.0"
+platformdirs = "^4.2.0"
 pinecone-client = "^2.2.2"
 pymongo = "^4.6.0"
 supabase = "^2.3.0"
@@ -84,12 +84,12 @@ passlib = "^1.7.4"
 bcrypt = "4.0.1"
 python-jose = "^3.3.0"
 metaphor-python = "^0.1.11"
-pydantic = "^2.5.0"
+pydantic = "^2.6.0"
 pydantic-settings = "^2.1.0"
 zep-python = "*"
 pywin32 = { version = "^306", markers = "sys_platform == 'win32'" }
 loguru = "^0.7.1"
-langfuse = "^1.1.11"
+langfuse = "^2.9.0"
 pillow = "^10.0.0"
 metal-sdk = "^2.4.0"
 markupsafe = "^2.1.3"
@@ -101,12 +101,12 @@ numexpr = "^2.8.6"
 qianfan = "0.2.0"
 pgvector = "^0.2.3"
 pyautogen = "^0.2.0"
-langchain-google-genai = "^0.0.2"
+langchain-google-genai = "^0.0.6"
 elasticsearch = "^8.11.1"
 pytube = "^15.0.0"
-llama-index = "^0.9.24"
-langchain-openai = "^0.0.2"
 python-socketio = "^5.11.0"
+llama-index = "^0.9.44"
+langchain-openai = "^0.0.5"
 
 [tool.poetry.group.dev.dependencies]
 pytest-asyncio = "^0.23.1"

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

@@ -1,6 +1,6 @@
 import time
 
-from fastapi import APIRouter, Body, Depends, HTTPException, Query, WebSocket, WebSocketException, status
+from fastapi import APIRouter, Body, Depends, HTTPException, WebSocket, WebSocketException, status
 from fastapi.responses import StreamingResponse
 from langflow.api.utils import build_input_keys_response, format_elapsed_time
 from langflow.api.v1.schemas import (
@@ -15,7 +15,7 @@ from langflow.api.v1.schemas import (
 from langflow.graph.graph.base import Graph
 from langflow.graph.vertex.base import StatelessVertex
 from langflow.processing.process import process_tweaks_on_graph
-from langflow.services.auth.utils import get_current_active_user, get_current_user_by_jwt
+from langflow.services.auth.utils import get_current_active_user, get_current_user_for_websocket
 from langflow.services.cache.service import BaseCacheService
 from langflow.services.cache.utils import update_build_status
 from langflow.services.chat.service import ChatService
@@ -32,17 +32,16 @@ router = APIRouter(tags=["Chat"])
 async def chat(
     client_id: str,
     websocket: WebSocket,
-    token: str = Query(...),
     db: Session = Depends(get_session),
     chat_service: "ChatService" = Depends(get_chat_service),
 ):
     """Websocket endpoint for chat."""
     try:
-        user = await get_current_user_by_jwt(token, db)
+        user = await get_current_user_for_websocket(websocket, db)
         await websocket.accept()
         if not user:
             await websocket.close(code=status.WS_1008_POLICY_VIOLATION, reason="Unauthorized")
-        if not user.is_active:
+        elif not user.is_active:
             await websocket.close(code=status.WS_1008_POLICY_VIOLATION, reason="Unauthorized")
 
         if client_id in chat_service.cache_service:

src/backend/langflow/components/agents/AgentInitializer.py

@@ -41,12 +41,11 @@ class AgentInitializerComponent(CustomComponent):
                 handle_parsing_errors=True,
                 max_iterations=max_iterations,
             )
-        else:
-            return initialize_agent(
-                tools=tools,
-                llm=llm,
-                agent=agent,
-                return_intermediate_steps=True,
-                handle_parsing_errors=True,
-                max_iterations=max_iterations,
-            )
+        return initialize_agent(
+            tools=tools,
+            llm=llm,
+            agent=agent,
+            return_intermediate_steps=True,
+            handle_parsing_errors=True,
+            max_iterations=max_iterations,
+        )

src/backend/langflow/components/agents/OpenAIConversationalAgent.py

@@ -3,13 +3,12 @@ from typing import List, Optional
 from langchain.agents.agent import AgentExecutor
 from langchain.agents.agent_toolkits.conversational_retrieval.openai_functions import _get_default_system_message
 from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
-from langchain_community.chat_models import ChatOpenAI
 from langchain.memory.token_buffer import ConversationTokenBufferMemory
 from langchain.prompts import SystemMessagePromptTemplate
 from langchain.prompts.chat import MessagesPlaceholder
 from langchain.schema.memory import BaseMemory
 from langchain.tools import Tool
-
+from langchain_community.chat_models import ChatOpenAI
 from langflow import CustomComponent
 from langflow.field_typing.range_spec import RangeSpec
 
@@ -20,11 +19,12 @@ class ConversationalAgent(CustomComponent):
 
     def build_config(self):
         openai_function_models = [
+            "gpt-4-turbo-preview",
+            "gpt-4-0125-preview",
             "gpt-4-1106-preview",
-            "gpt-3.5-turbo",
-            "gpt-3.5-turbo-16k",
-            "gpt-4",
-            "gpt-4-32k",
+            "gpt-4-vision-preview",
+            "gpt-3.5-turbo-0125",
+            "gpt-3.5-turbo-1106",
         ]
         return {
             "tools": {"display_name": "Tools"},

src/backend/langflow/components/chains/PromptRunner.py

@@ -1,7 +1,6 @@
 from langchain.llms.base import BaseLLM
 from langchain.prompts import PromptTemplate
 from langchain_core.messages import BaseMessage
-
 from langflow import CustomComponent
 from langflow.field_typing import Text
 

src/backend/langflow/components/documentloaders/FileLoader.py

@@ -1,5 +1,4 @@
-from langchain.schema import Document
-
+from langchain_core.documents import Document
 from langflow import CustomComponent
 from langflow.utils.constants import LOADERS_INFO
 

src/backend/langflow/components/documentloaders/UrlLoader.py

@@ -1,7 +1,8 @@
 from typing import List
 
 from langchain import document_loaders
-from langchain.schema import Document
+from langchain_core.documents import Document
+
 from langflow import CustomComponent
 
 

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

@@ -42,7 +42,11 @@ class OpenAIEmbeddingsComponent(CustomComponent):
                 "advanced": True,
             },
             "max_retries": {"display_name": "Max Retries", "advanced": True},
-            "model": {"display_name": "Model", "advanced": True},
+            "model": {
+                "display_name": "Model",
+                "advanced": False,
+                "options": ["text-embedding-3-small", "text-embedding-3-large", "text-embedding-ada-002"],
+            },
             "model_kwargs": {"display_name": "Model Kwargs", "advanced": True},
             "openai_api_base": {"display_name": "OpenAI API Base", "password": True, "advanced": True},
             "openai_api_key": {"display_name": "OpenAI API Key", "password": True},
@@ -74,10 +78,10 @@ class OpenAIEmbeddingsComponent(CustomComponent):
         disallowed_special: List[str] = ["all"],
         chunk_size: int = 1000,
         client: Optional[Any] = None,
-        deployment: str = "text-embedding-ada-002",
+        deployment: str = "text-embedding-3-small",
         embedding_ctx_length: int = 8191,
         max_retries: int = 6,
-        model: str = "text-embedding-ada-002",
+        model: str = "text-embedding-3-small",
         model_kwargs: NestedDict = {},
         openai_api_base: Optional[str] = None,
         openai_api_key: Optional[str] = "",

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

@@ -2,6 +2,7 @@ from typing import Optional, Union
 
 from langchain.llms import BaseLLM
 from langchain_community.chat_models.openai import ChatOpenAI
+
 from langflow import CustomComponent
 from langflow.field_typing import BaseLanguageModel, NestedDict
 
@@ -30,11 +31,12 @@ class ChatOpenAIComponent(CustomComponent):
                 "advanced": False,
                 "required": False,
                 "options": [
+                    "gpt-4-turbo-preview",
+                    "gpt-4-0125-preview",
                     "gpt-4-1106-preview",
-                    "gpt-4",
-                    "gpt-4-32k",
-                    "gpt-3.5-turbo",
-                    "gpt-3.5-turbo-16k",
+                    "gpt-4-vision-preview",
+                    "gpt-3.5-turbo-0125",
+                    "gpt-3.5-turbo-1106",
                 ],
             },
             "openai_api_base": {

src/backend/langflow/components/textsplitters/LanguageRecursiveTextSplitter.py

@@ -1,7 +1,7 @@
 from typing import Optional
 
-from langchain.schema import Document
 from langchain.text_splitter import Language
+from langchain_core.documents import Document
 
 from langflow import CustomComponent
 

src/backend/langflow/components/textsplitters/RecursiveCharacterTextSplitter.py

@@ -1,7 +1,10 @@
 from typing import Optional
+
+from langchain_core.documents import Document
+
 from langflow import CustomComponent
-from langchain.schema import Document
 from langflow.utils.util import build_loader_repr_from_documents
+from langchain.text_splitter import RecursiveCharacterTextSplitter
 
 
 class RecursiveCharacterTextSplitterComponent(CustomComponent):
@@ -54,7 +57,6 @@ class RecursiveCharacterTextSplitterComponent(CustomComponent):
         Returns:
             list[str]: The chunks of text.
         """
-        from langchain.text_splitter import RecursiveCharacterTextSplitter
 
         if separators == "":
             separators = None

src/backend/langflow/components/utilities/GetRequest.py

@@ -1,9 +1,10 @@
-from langflow import CustomComponent
-from langchain.schema import Document
-from langflow.services.database.models.base import orjson_dumps
-import requests
 from typing import Optional
 
+import requests
+from langchain_core.documents import Document
+from langflow import CustomComponent
+from langflow.services.database.models.base import orjson_dumps
+
 
 class GetRequest(CustomComponent):
     display_name: str = "GET Request"

src/backend/langflow/components/utilities/JSONDocumentBuilder.py

@@ -11,7 +11,7 @@
 
 # - **Document:** The Document containing the JSON object.
 
-from langchain.schema import Document
+from langchain_core.documents import Document
 from langflow import CustomComponent
 from langflow.services.database.models.base import orjson_dumps
 

src/backend/langflow/components/utilities/PostRequest.py

@@ -1,9 +1,10 @@
-from langflow import CustomComponent
-from langchain.schema import Document
-from langflow.services.database.models.base import orjson_dumps
-import requests
 from typing import Optional
 
+import requests
+from langchain_core.documents import Document
+from langflow import CustomComponent
+from langflow.services.database.models.base import orjson_dumps
+
 
 class PostRequest(CustomComponent):
     display_name: str = "POST Request"

src/backend/langflow/components/utilities/UpdateRequest.py

@@ -1,7 +1,8 @@
 from typing import List, Optional
+
 import requests
+from langchain_core.documents import Document
 from langflow import CustomComponent
-from langchain.schema import Document
 from langflow.services.database.models.base import orjson_dumps
 
 

src/backend/langflow/components/vectorstores/Redis.py

@@ -1,9 +1,11 @@
-from typing import Optional
+from typing import Optional, Union
 
 from langchain.embeddings.base import Embeddings
-from langchain.schema import Document
 from langchain_community.vectorstores import VectorStore
 from langchain_community.vectorstores.redis import Redis
+from langchain_core.documents import Document
+from langchain_core.retrievers import BaseRetriever
+
 from langflow import CustomComponent
 
 
@@ -42,7 +44,7 @@ class RedisComponent(CustomComponent):
         redis_server_url: str,
         redis_index_name: str,
         documents: Optional[Document] = None,
-    ) -> VectorStore:
+    ) -> Union[VectorStore, BaseRetriever]:
         """
         Builds the Vector Store or BaseRetriever object.
 
@@ -55,10 +57,19 @@ class RedisComponent(CustomComponent):
         Returns:
         - VectorStore: The Vector Store object.
         """
-
-        return Redis.from_documents(
-            documents=documents,  # type: ignore
-            embedding=embedding,
-            redis_url=redis_server_url,
-            index_name=redis_index_name,
-        )
+        if documents is None:
+            redis_vs = Redis.from_existing_index(
+                embedding=embedding,
+                index_name=redis_index_name,
+                schema=None,
+                key_prefix=None,
+                redis_url=redis_server_url,
+            )
+        else:
+            redis_vs = Redis.from_documents(
+                documents=documents,  # type: ignore
+                embedding=embedding,
+                redis_url=redis_server_url,
+                index_name=redis_index_name,
+            )
+        return redis_vs

src/backend/langflow/components/vectorstores/Vectara.py

@@ -3,11 +3,12 @@ import urllib
 import urllib.request
 from typing import List, Optional, Union
 
-from langchain.embeddings import FakeEmbeddings
-from langchain.schema import BaseRetriever, Document
-from langchain_community.vectorstores import Vectara, VectorStore
+from langchain_community.embeddings import FakeEmbeddings
+from langchain_community.vectorstores.vectara import Vectara
+from langchain_core.vectorstores import VectorStore
 
 from langflow import CustomComponent
+from langflow.field_typing import BaseRetriever, Document
 
 
 class VectaraComponent(CustomComponent):
@@ -18,25 +19,18 @@ class VectaraComponent(CustomComponent):
     field_config = {
         "vectara_customer_id": {
             "display_name": "Vectara Customer ID",
-            "required": True,
         },
         "vectara_corpus_id": {
             "display_name": "Vectara Corpus ID",
-            "required": True,
         },
         "vectara_api_key": {
             "display_name": "Vectara API Key",
             "password": True,
-            "required": True,
-        },
-        "code": {"show": False},
-        "documents": {
-            "display_name": "Documents",
-            "info": "Pass in either for Self Query Retriever or for making a Vectara Object",
         },
+        "documents": {"display_name": "Documents", "info": "If provided, will be upserted to corpus (optional)"},
         "files_url": {
             "display_name": "Files Url",
-            "info": "Make vectara object using url of files(documents not needed)",
+            "info": "Make vectara object using url of files (optional)",
         },
     }
 
@@ -48,6 +42,8 @@ class VectaraComponent(CustomComponent):
         files_url: Optional[List[str]] = None,
         documents: Optional[Document] = None,
     ) -> Union[VectorStore, BaseRetriever]:
+        source = "Langflow"
+
         if documents is not None:
             return Vectara.from_documents(
                 documents=documents,
@@ -55,6 +51,7 @@ class VectaraComponent(CustomComponent):
                 vectara_customer_id=vectara_customer_id,
                 vectara_corpus_id=vectara_corpus_id,
                 vectara_api_key=vectara_api_key,
+                source=source,
             )
 
         if files_url is not None:
@@ -70,10 +67,12 @@ class VectaraComponent(CustomComponent):
                 vectara_customer_id=vectara_customer_id,
                 vectara_corpus_id=vectara_corpus_id,
                 vectara_api_key=vectara_api_key,
+                source=source,
             )
 
         return Vectara(
             vectara_customer_id=vectara_customer_id,
             vectara_corpus_id=vectara_corpus_id,
             vectara_api_key=vectara_api_key,
+            source=source,
         )

src/backend/langflow/components/vectorstores/pgvector.py

@@ -1,13 +1,15 @@
-from typing import List, Optional
+from typing import Optional, Union
 
 from langchain.embeddings.base import Embeddings
-from langchain.schema import Document
 from langchain_community.vectorstores import VectorStore
 from langchain_community.vectorstores.pgvector import PGVector
+from langchain_core.documents import Document
+from langchain_core.retrievers import BaseRetriever
+
 from langflow import CustomComponent
 
 
-class PostgresqlVectorComponent(CustomComponent):
+class PGVectorComponent(CustomComponent):
     """
     A custom component for implementing a Vector Store using PostgreSQL.
     """
@@ -15,7 +17,6 @@ class PostgresqlVectorComponent(CustomComponent):
     display_name: str = "PGVector"
     description: str = "Implementation of Vector Store using PostgreSQL"
     documentation = "https://python.langchain.com/docs/integrations/vectorstores/pgvector"
-    beta = True
 
     def build_config(self):
         """
@@ -25,8 +26,7 @@ class PostgresqlVectorComponent(CustomComponent):
         - dict: A dictionary containing the configuration options for the component.
         """
         return {
-            "index_name": {"display_name": "Index Name", "value": "your_index"},
-            "code": {"show": True, "display_name": "Code"},
+            "code": {"show": False},
             "documents": {"display_name": "Documents", "is_list": True},
             "embedding": {"display_name": "Embedding"},
             "pg_server_url": {
@@ -41,8 +41,8 @@ class PostgresqlVectorComponent(CustomComponent):
         embedding: Embeddings,
         pg_server_url: str,
         collection_name: str,
-        documents: Optional[List[Document]] = None,
-    ) -> VectorStore:
+        documents: Optional[Document] = None,
+    ) -> Union[VectorStore, BaseRetriever]:
         """
         Builds the Vector Store or BaseRetriever object.
 
@@ -58,13 +58,13 @@ class PostgresqlVectorComponent(CustomComponent):
 
         try:
             if documents is None:
-                return PGVector.from_existing_index(
+                vector_store = PGVector.from_existing_index(
                     embedding=embedding,
                     collection_name=collection_name,
                     connection_string=pg_server_url,
                 )
 
-            return PGVector.from_documents(
+            vector_store = PGVector.from_documents(
                 embedding=embedding,
                 documents=documents,
                 collection_name=collection_name,
@@ -72,3 +72,4 @@ class PostgresqlVectorComponent(CustomComponent):
             )
         except Exception as e:
             raise RuntimeError(f"Failed to build PGVector: {e}")
+        return vector_store

src/backend/langflow/config.yaml

@@ -174,6 +174,8 @@ prompts:
 textsplitters:
   CharacterTextSplitter:
     documentation: "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter"
+  RecursiveCharacterTextSplitter:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_transformers/recursive_text_splitter"
 toolkits:
   OpenAPIToolkit:
     documentation: ""

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

@@ -2,6 +2,7 @@ import ast
 import os
 import zlib
 
+from langflow.interface.custom.custom_component import CustomComponent
 from loguru import logger
 
 
@@ -245,9 +246,18 @@ class DirectoryReader:
             else:
                 component_name_camelcase = component_name
 
+            if validation_result:
+                try:
+                    output_types = self.get_output_types_from_code(result_content)
+                except Exception as exc:
+                    logger.exception(f"Error while getting output types from code: {str(exc)}")
+                    output_types = [component_name_camelcase]
+            else:
+                output_types = [component_name_camelcase]
+
             component_info = {
                 "name": "CustomComponent",
-                "output_types": [component_name_camelcase],
+                "output_types": output_types,
                 "file": filename,
                 "code": result_content if validation_result else "",
                 "error": "" if validation_result else result_content,
@@ -259,3 +269,13 @@ class DirectoryReader:
                 response["menu"].append(menu_result)
         logger.debug("-------------------- Component menu list built --------------------")
         return response
+
+    @staticmethod
+    def get_output_types_from_code(code: str) -> list:
+        """
+        Get the output types from the code.
+        """
+        custom_component = CustomComponent(code=code)
+        types_list = custom_component.get_function_entrypoint_return_type
+        # Get the name of types classes
+        return [type_.__name__ for type_ in types_list if hasattr(type_, "__name__")]

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

@@ -7,8 +7,6 @@ from typing import Any, Dict, List, Optional, Union
 from uuid import UUID
 
 from fastapi import HTTPException
-from loguru import logger
-
 from langflow.field_typing.range_spec import RangeSpec
 from langflow.interface.custom.code_parser.utils import extract_inner_type
 from langflow.interface.custom.custom_component import CustomComponent
@@ -21,6 +19,7 @@ from langflow.interface.importing.utils import eval_custom_component_code
 from langflow.template.field.base import TemplateField
 from langflow.template.frontend_node.custom_components import CustomComponentFrontendNode
 from langflow.utils.util import get_base_classes
+from loguru import logger
 
 
 def add_output_types(frontend_node: CustomComponentFrontendNode, return_types: List[str]):

src/backend/langflow/interface/initialize/loading.py

@@ -9,8 +9,8 @@ from langchain.agents.agent_toolkits.base import BaseToolkit
 from langchain.agents.tools import BaseTool
 from langchain.chains.base import Chain
 from langchain.document_loaders.base import BaseLoader
-from langchain.schema import Document
 from langchain_community.vectorstores import VectorStore
+from langchain_core.documents import Document
 from loguru import logger
 from pydantic import ValidationError
 

src/backend/langflow/interface/initialize/vector_store.py

@@ -2,7 +2,6 @@ import os
 from typing import Any, Callable, Dict, Type
 
 import orjson
-from langchain.schema import Document
 from langchain_community.vectorstores import (
     FAISS,
     Chroma,
@@ -13,6 +12,7 @@ from langchain_community.vectorstores import (
     SupabaseVectorStore,
     Weaviate,
 )
+from langchain_core.documents import Document
 
 
 def docs_in_params(params: dict) -> bool:

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

@@ -7,6 +7,7 @@ from fastapi import Depends, HTTPException, Security, status
 from fastapi.security import APIKeyHeader, APIKeyQuery, OAuth2PasswordBearer
 from jose import JWTError, jwt
 from sqlmodel import Session
+from starlette.websockets import WebSocket
 
 from langflow.services.database.models.api_key.model import ApiKey
 from langflow.services.database.models.api_key.crud import check_key
@@ -130,6 +131,21 @@ async def get_current_user_by_jwt(
     return user
 
 
+async def get_current_user_for_websocket(
+    websocket: WebSocket,
+    db: Session = Depends(get_session),
+    query_param: str = Security(api_key_query),
+) -> Optional[User]:
+    token = websocket.query_params.get("token")
+    api_key = websocket.query_params.get("x-api-key")
+    if token:
+        return await get_current_user_by_jwt(token, db)
+    elif api_key:
+        return await api_key_security(api_key, query_param, db)
+    else:
+        return None
+
+
 def get_current_active_user(current_user: Annotated[User, Depends(get_current_user)]):
     if not current_user.is_active:
         raise HTTPException(status_code=400, detail="Inactive user")

src/backend/langflow/utils/constants.py

@@ -8,12 +8,12 @@ OPENAI_MODELS = [
     "text-ada-001",
 ]
 CHAT_OPENAI_MODELS = [
+    "gpt-4-turbo-preview",
+    "gpt-4-0125-preview",
     "gpt-4-1106-preview",
     "gpt-4-vision-preview",
-    "gpt-4",
-    "gpt-4-32k",
-    "gpt-3.5-turbo",
-    "gpt-3.5-turbo-16k",
+    "gpt-3.5-turbo-0125",
+    "gpt-3.5-turbo-1106",
 ]
 
 

src/backend/langflow/utils/util.py

@@ -1,14 +1,14 @@
-import re
-import inspect
 import importlib
+import inspect
+import re
 from functools import wraps
-from typing import List, Optional, Dict, Any, Union
+from typing import Any, Dict, List, Optional, Union
 
 from docstring_parser import parse
+from langchain_core.documents import Document
 
 from langflow.template.frontend_node.constants import FORCE_SHOW_FIELDS
 from langflow.utils import constants
-from langchain.schema import Document
 
 
 def remove_ansi_escape_codes(text):

src/frontend/playwright.config.ts

@@ -18,7 +18,7 @@ export default defineConfig({
   /* Retry on CI only */
   retries: process.env.CI ? 2 : 0,
   /* Opt out of parallel tests on CI. */
-  workers: process.env.CI ? 1 : undefined,
+  workers: process.env.CI ? 2 : undefined,
   /* Reporter to use. See https://playwright.dev/docs/test-reporters */
   reporter: [
     ["html", { open: "never", outputFolder: "playwright-report/test-results" }],
@@ -44,10 +44,10 @@ export default defineConfig({
       use: { ...devices["Desktop Firefox"] },
     },
 
-    {
-      name: "webkit",
-      use: { ...devices["Desktop Safari"] },
-    },
+    // {
+    //   name: "webkit",
+    //   use: { ...devices["Desktop Safari"] },
+    // },
 
     /* Test against mobile viewports. */
     // {

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

@@ -297,7 +297,7 @@ export default function GenericNode({
                     title={
                       data.node?.output_types &&
                       data.node.output_types.length > 0
-                        ? data.node.output_types.join("|")
+                        ? data.node.output_types.join(" | ")
                         : data.type
                     }
                     tooltipTitle={data.node?.base_classes.join("\n")}
@@ -580,7 +580,7 @@ export default function GenericNode({
                   }
                   title={
                     data.node?.output_types && data.node.output_types.length > 0
-                      ? data.node.output_types.join("|")
+                      ? data.node.output_types.join(" | ")
                       : data.type
                   }
                   tooltipTitle={data.node?.base_classes.join("\n")}

src/frontend/src/icons/VectaraIcon/index.tsx

@@ -0,0 +1,9 @@
+import React, { forwardRef } from "react";
+import SvgVectara from "./Vectara";
+
+export const VectaraIcon = forwardRef<
+  SVGSVGElement,
+  React.PropsWithChildren<{}>
+>((props, ref) => {
+  return <SvgVectara className="icon" ref={ref} {...props} />;
+});

src/frontend/src/icons/VectaraIcon/vectara.svg

@@ -0,0 +1,252 @@
+<svg xmlns="http://www.w3.org/2000/svg" version="1.1" width="720px" height="627px" style="transform: scale(0.05);; shape-rendering:geometricPrecision; text-rendering:geometricPrecision; image-rendering:optimizeQuality; fill-rule:evenodd; clip-rule:evenodd" xmlns:xlink="http://www.w3.org/1999/xlink">
+<path style="opacity:0.985" fill="#16fed9" d="M 632.5,-0.5 C 643.167,-0.5 653.833,-0.5 664.5,-0.5C 666.679,0.67722 669.013,1.67722 671.5,2.5C 671.291,3.92167 670.791,5.25501 670,6.5C 664.666,13.1805 657.833,17.6805 649.5,20C 643.159,25.3027 635.659,27.4693 627,26.5C 620.18,29.7476 613.18,32.4142 606,34.5C 602.575,33.905 599.075,33.7383 595.5,34C 591.065,30.8012 586.731,27.6346 582.5,24.5C 597.266,12.4502 613.933,4.11689 632.5,-0.5 Z"/>
+<path style="opacity:0.988" fill="#1ffecd" d="M 671.5,2.5 C 680.297,5.89126 687.631,11.2246 693.5,18.5C 690.305,20.3534 687.139,22.3534 684,24.5C 683.586,24.0426 683.086,23.7093 682.5,23.5C 667.582,30.4689 652.916,36.4689 638.5,41.5C 637.914,41.2907 637.414,40.9574 637,40.5C 635.604,42.5268 633.938,42.8602 632,41.5C 625.735,43.4928 619.402,44.1595 613,43.5C 607.252,44.4499 601.585,45.7832 596,47.5C 593.765,46.7607 591.765,46.7607 590,47.5C 583.932,44.1014 578.432,39.9347 573.5,35C 572.552,34.5172 571.552,34.3505 570.5,34.5C 574.183,30.8197 578.183,27.4864 582.5,24.5C 586.731,27.6346 591.065,30.8012 595.5,34C 599.075,33.7383 602.575,33.905 606,34.5C 613.18,32.4142 620.18,29.7476 627,26.5C 635.659,27.4693 643.159,25.3027 649.5,20C 657.833,17.6805 664.666,13.1805 670,6.5C 670.791,5.25501 671.291,3.92167 671.5,2.5 Z"/>
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src/frontend/src/pages/FlowPage/components/nodeToolbarComponent/index.tsx

@@ -189,7 +189,7 @@ export default function NodeToolbarComponent({
             </ShadTooltip>
           )}
 
-          <Select onValueChange={handleSelectChange}>
+          <Select onValueChange={handleSelectChange} value="">
             <ShadTooltip content="More" side="top">
               <SelectTrigger>
                 <div>

src/frontend/src/utils/styleUtils.ts

@@ -138,6 +138,7 @@ import { SearxIcon } from "../icons/Searx";
 import { ShareIcon } from "../icons/Share";
 import { Share2Icon } from "../icons/Share2";
 import SvgSlackIcon from "../icons/Slack/SlackIcon";
+import { VectaraIcon } from "../icons/VectaraIcon";
 import { VertexAIIcon } from "../icons/VertexAI";
 import { WeaviateIcon } from "../icons/Weaviate";
 import SvgWikipedia from "../icons/Wikipedia/Wikipedia";
@@ -233,6 +234,7 @@ export const nodeNames: { [char: string]: string } = {
 };
 
 export const nodeIconsLucide: iconsType = {
+  Vectara: VectaraIcon,
   ArrowUpToLine: ArrowUpToLine,
   Chroma: ChromaIcon,
   AirbyteJSONLoader: AirbyteIcon,

src/frontend/tests/custom_component_full.ts

@@ -3,7 +3,7 @@ export const custom = `from langflow import CustomComponent
 from langchain.llms.base import BaseLLM
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.schema import Document
+from langchain_core.documents import Document
 from langflow.field_typing import NestedDict
 
 import requests

tests/test_custom_component.py

@@ -21,7 +21,7 @@ from langflow.interface.custom.custom_component import CustomComponent
 from langchain.llms.base import BaseLLM
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.schema import Document
+from langchain_core.documents import Document
 
 import requests
 
@@ -228,6 +228,7 @@ def test_custom_component_get_function_entrypoint_return_type():
     Test the get_function_entrypoint_return_type
     property of the CustomComponent class.
     """
+
     custom_component = CustomComponent(code=code_default, function_entrypoint_name="build")
     return_type = custom_component.get_function_entrypoint_return_type
     assert return_type == [Document]

tests/test_endpoints.py

@@ -72,11 +72,12 @@ PROMPT_REQUEST = {
                             "text-ada-001",
                         ],
                         "ChatOpenAI": [
+                            "gpt-4-turbo-preview",
+                            "gpt-4-0125-preview",
                             "gpt-4-1106-preview",
-                            "gpt-4",
-                            "gpt-4-32k",
-                            "gpt-3.5-turbo",
-                            "gpt-3.5-turbo-16k",
+                            "gpt-4-vision-preview",
+                            "gpt-3.5-turbo-0125",
+                            "gpt-3.5-turbo-1106",
                         ],
                         "Anthropic": [
                             "claude-v1",

tests/test_template.py

@@ -235,7 +235,7 @@ def test_format_dict():
             "password": False,
             "multiline": False,
             "options": CHAT_OPENAI_MODELS,
-            "value": "gpt-4-1106-preview",
+            "value": "gpt-4-turbo-preview",
         },
     }
     assert format_dict(input_dict, "OpenAI") == expected_output_openai