Merge branch 'release' into add_params_to_llms

README.md

@@ -13,8 +13,9 @@
 <img alt="Github License" src="https://img.shields.io/github/license/logspace-ai/langflow" />
 </p>
 
+
 <p>
-<a href="https://discord.gg/FUhJnnJ9"><img alt="Discord Server" src="https://dcbadge.vercel.app/api/server/FUhJnnJ9?compact=true&style=flat"/></a>
+<a href="https://discord.gg/EqksyE2EX9"><img alt="Discord Server" src="https://dcbadge.vercel.app/api/server/EqksyE2EX9?compact=true&style=flat"/></a>
 <a href="https://huggingface.co/spaces/Logspace/LangFlow"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg" alt="HuggingFace Spaces"></a>
 </p>
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.1.6"
+version = "0.2.5"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [
@@ -23,14 +23,14 @@ langflow = "langflow.__main__:main"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.12"
-fastapi = "^0.97.0"
+fastapi = "^0.98.0"
 uvicorn = "^0.22.0"
 beautifulsoup4 = "^4.11.2"
 google-search-results = "^2.4.1"
 google-api-python-client = "^2.79.0"
 typer = "^0.9.0"
 gunicorn = "^20.1.0"
-langchain = "^0.0.202"
+langchain = "^0.0.218"
 openai = "^0.27.8"
 types-pyyaml = "^6.0.12.8"
 pandas = "^1.5.3"
@@ -51,12 +51,13 @@ tiktoken = "~0.4.0"
 wikipedia = "^1.4.0"
 langchain-serve = { version = ">0.0.39", optional = true }
 qdrant-client = "^1.2.0"
-websockets = "^11.0.3"
+websockets = "^10.3"
 weaviate-client = "^3.21.0"
 jina = "3.15.2"
 sentence-transformers = "^2.2.2"
 ctransformers = "^0.2.2"
 cohere = "^4.6.0"
+python-multipart = "^0.0.6"
 sqlmodel = "^0.0.8"
 faiss-cpu = "^1.7.4"
 anthropic = "^0.2.10"
@@ -64,9 +65,14 @@ orjson = "^3.9.1"
 multiprocess = "^0.70.14"
 cachetools = "^5.3.1"
 types-cachetools = "^5.3.0.5"
+appdirs = "^1.4.4"
+pinecone-client = "^2.2.2"
+supabase = "^1.0.3"
+pymongo = "^4.4.0"
+certifi = "^2023.5.7"
 
 
-[tool.poetry.group.dev.dependencies]
+[tool.poetry.dev-dependencies]
 black = "^23.1.0"
 ipykernel = "^6.21.2"
 mypy = "^1.1.1"
@@ -78,6 +84,7 @@ requests = "^2.28.0"
 pytest-cov = "^4.0.0"
 pandas-stubs = "^2.0.0.230412"
 types-pillow = "^9.5.0.2"
+types-appdirs = "^1.4.3.5"
 
 
 [tool.poetry.extras]

src/backend/langflow/__main__.py

@@ -1,6 +1,5 @@
 import sys
 import time
-from fastapi import FastAPI
 import httpx
 from multiprocess import Process, cpu_count  # type: ignore
 import platform
@@ -11,9 +10,7 @@ from rich.panel import Panel
 from rich import box
 from rich import print as rprint
 import typer
-from fastapi.staticfiles import StaticFiles
-from fastapi.responses import FileResponse
-from langflow.main import create_app
+from langflow.main import setup_app
 from langflow.settings import settings
 from langflow.utils.logger import configure, logger
 import webbrowser
@@ -30,6 +27,7 @@ def get_number_of_workers(workers=None):
 
 def update_settings(
     config: str,
+    cache: str,
     dev: bool = False,
     database_url: Optional[str] = None,
     remove_api_keys: bool = False,
@@ -41,6 +39,8 @@ def update_settings(
         settings.update_settings(database_url=database_url)
     if remove_api_keys:
         settings.update_settings(remove_api_keys=remove_api_keys)
+    if cache:
+        settings.update_settings(cache=cache)
 
 
 def serve_on_jcloud():
@@ -102,6 +102,11 @@ def serve(
     ),
     log_level: str = typer.Option("critical", help="Logging level."),
     log_file: Path = typer.Option("logs/langflow.log", help="Path to the log file."),
+    cache: str = typer.Argument(
+        envvar="LANGCHAIN_CACHE",
+        help="Type of cache to use. (InMemoryCache, SQLiteCache)",
+        default="SQLiteCache",
+    ),
     jcloud: bool = typer.Option(False, help="Deploy on Jina AI Cloud"),
     dev: bool = typer.Option(False, help="Run in development mode (may contain bugs)"),
     database_url: str = typer.Option(
@@ -130,17 +135,15 @@ def serve(
 
     configure(log_level=log_level, log_file=log_file)
     update_settings(
-        config, dev=dev, database_url=database_url, remove_api_keys=remove_api_keys
+        config,
+        dev=dev,
+        database_url=database_url,
+        remove_api_keys=remove_api_keys,
+        cache=cache,
     )
-    # get the directory of the current file
-    if not path:
-        frontend_path = Path(__file__).parent
-        static_files_dir = frontend_path / "frontend"
-    else:
-        static_files_dir = Path(path)
-
-    app = create_app()
-    setup_static_files(app, static_files_dir)
+    # create path object if path is provided
+    static_files_dir: Optional[Path] = Path(path) if path else None
+    app = setup_app(static_files_dir=static_files_dir)
     # check if port is being used
     if is_port_in_use(port, host):
         port = get_free_port(port)
@@ -188,29 +191,6 @@ def run_on_windows(host, port, log_level, options, app):
     run_langflow(host, port, log_level, options, app)
 
 
-def setup_static_files(app: FastAPI, static_files_dir: Path):
-    """
-    Setup the static files directory.
-
-    Args:
-        app (FastAPI): FastAPI app.
-        path (str): Path to the static files directory.
-    """
-    app.mount(
-        "/",
-        StaticFiles(directory=static_files_dir, html=True),
-        name="static",
-    )
-
-    @app.exception_handler(404)
-    async def custom_404_handler(request, __):
-        path = static_files_dir / "index.html"
-
-        if not path.exists():
-            raise RuntimeError(f"File at path {path} does not exist.")
-        return FileResponse(path)
-
-
 def is_port_in_use(port, host="localhost"):
     """
     Check if a port is in use.

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

@@ -1,12 +1,14 @@
+from typing import Optional
+from langflow.cache.utils import save_uploaded_file
 from langflow.database.models.flow import Flow
 from langflow.processing.process import process_graph_cached, process_tweaks
 from langflow.utils.logger import logger
 
-from fastapi import APIRouter, Depends, HTTPException
+from fastapi import APIRouter, Depends, HTTPException, UploadFile
 
 from langflow.api.v1.schemas import (
-    PredictRequest,
-    PredictResponse,
+    ProcessResponse,
+    UploadFileResponse,
 )
 
 from langflow.interface.types import build_langchain_types_dict
@@ -22,14 +24,17 @@ def get_all():
     return build_langchain_types_dict()
 
 
-@router.post("/predict/{flow_id}", response_model=PredictResponse)
-async def predict_flow(
-    predict_request: PredictRequest,
+# For backwards compatibility we will keep the old endpoint
+@router.post("/predict/{flow_id}", response_model=ProcessResponse)
+@router.post("/process/{flow_id}", response_model=ProcessResponse)
+async def process_flow(
     flow_id: str,
+    inputs: Optional[dict] = None,
+    tweaks: Optional[dict] = None,
     session: Session = Depends(get_session),
 ):
     """
-    Endpoint to process a message using the flow passed in the bearer token.
+    Endpoint to process an input with a given flow_id.
     """
 
     try:
@@ -40,15 +45,14 @@ async def predict_flow(
         if flow.data is None:
             raise ValueError(f"Flow {flow_id} has no data")
         graph_data = flow.data
-        if predict_request.tweaks:
+        if tweaks:
             try:
-                graph_data = process_tweaks(graph_data, predict_request.tweaks)
+                graph_data = process_tweaks(graph_data, tweaks)
             except Exception as exc:
                 logger.error(f"Error processing tweaks: {exc}")
-        response = process_graph_cached(graph_data, predict_request.message)
-        return PredictResponse(
-            result=response.get("result", ""),
-            intermediate_steps=response.get("thought", ""),
+        response = process_graph_cached(graph_data, inputs)
+        return ProcessResponse(
+            result=response,
         )
     except Exception as e:
         # Log stack trace
@@ -56,6 +60,21 @@ async def predict_flow(
         raise HTTPException(status_code=500, detail=str(e)) from e
 
 
+@router.post("/upload/{flow_id}", response_model=UploadFileResponse, status_code=201)
+async def create_upload_file(file: UploadFile, flow_id: str):
+    # Cache file
+    try:
+        file_path = save_uploaded_file(file.file, folder_name=flow_id)
+
+        return UploadFileResponse(
+            flowId=flow_id,
+            file_path=file_path,
+        )
+    except Exception as exc:
+        logger.error(f"Error saving file: {exc}")
+        raise HTTPException(status_code=500, detail=str(exc)) from exc
+
+
 # get endpoint to return version of langflow
 @router.get("/version")
 def get_version():

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

@@ -1,3 +1,4 @@
+from pathlib import Path
 from typing import Any, Dict, List, Optional, Union
 from langflow.database.models.flow import FlowCreate, FlowRead
 from pydantic import BaseModel, Field, validator
@@ -20,34 +21,22 @@ class ExportedFlow(BaseModel):
     data: GraphData
 
 
-class PredictRequest(BaseModel):
-    """Predict request schema."""
+class InputRequest(BaseModel):
+    input: dict
 
-    message: str
+
+class TweaksRequest(BaseModel):
     tweaks: Optional[Dict[str, Dict[str, str]]] = Field(default_factory=dict)
 
-    class Config:
-        schema_extra = {
-            "example": {
-                "message": "Hello, how are you?",
-                "tweaks": {
-                    "dndnode_986363f0-4677-4035-9f38-74b94af5dd78": {
-                        "name": "A tool name",
-                        "description": "A tool description",
-                    },
-                    "dndnode_986363f0-4677-4035-9f38-74b94af57378": {
-                        "template": "A {template}",
-                    },
-                },
-            }
-        }
+
+class UpdateTemplateRequest(BaseModel):
+    template: dict
 
 
-class PredictResponse(BaseModel):
-    """Predict response schema."""
+class ProcessResponse(BaseModel):
+    """Process response schema."""
 
-    result: str
-    intermediate_steps: str = ""
+    result: dict
 
 
 class ChatMessage(BaseModel):
@@ -104,6 +93,13 @@ class BuiltResponse(BaseModel):
     built: bool
 
 
+class UploadFileResponse(BaseModel):
+    """Upload file response schema."""
+
+    flowId: str
+    file_path: Path
+
+
 class StreamData(BaseModel):
     event: str
     data: dict

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

@@ -1,5 +1,3 @@
-import json
-
 from fastapi import APIRouter, HTTPException
 
 from langflow.api.v1.base import (
@@ -9,8 +7,6 @@ from langflow.api.v1.base import (
     PromptValidationResponse,
     validate_prompt,
 )
-from langflow.graph.vertex.types import VectorStoreVertex
-from langflow.graph import Graph
 from langflow.utils.logger import logger
 from langflow.utils.validate import validate_code
 
@@ -37,21 +33,3 @@ def post_validate_prompt(prompt: Prompt):
     except Exception as e:
         logger.exception(e)
         raise HTTPException(status_code=500, detail=str(e)) from e
-
-
-# validate node
-@router.post("/node/{node_id}", status_code=200)
-def post_validate_node(node_id: str, data: dict):
-    try:
-        # build graph
-        graph = Graph.from_payload(data)
-        # validate node
-        node = graph.get_node(node_id)
-        if node is None:
-            raise ValueError(f"Node {node_id} not found")
-        if not isinstance(node, VectorStoreVertex):
-            node.build()
-        return json.dumps({"valid": True, "params": str(node._built_object_repr())})
-    except Exception as e:
-        logger.exception(e)
-        return json.dumps({"valid": False, "params": str(e)})

src/backend/langflow/cache/base.py

@@ -62,9 +62,6 @@ class BaseCache(abc.ABC):
 
         Args:
             key: The key of the item to retrieve.
-
-        Returns:
-            The value associated with the key, or None if the key is not found.
         """
 
     @abc.abstractmethod

src/backend/langflow/cache/utils.py

@@ -8,15 +8,17 @@ import tempfile
 from collections import OrderedDict
 from pathlib import Path
 from typing import Any, Dict
-
+from appdirs import user_cache_dir
 
 CACHE: Dict[str, Any] = {}
 
+CACHE_DIR = user_cache_dir("langflow", "langflow")
+
 
 def create_cache_folder(func):
     def wrapper(*args, **kwargs):
         # Get the destination folder
-        cache_path = Path(tempfile.gettempdir()) / PREFIX
+        cache_path = Path(CACHE_DIR) / PREFIX
 
         # Create the destination folder if it doesn't exist
         os.makedirs(cache_path, exist_ok=True)
@@ -118,7 +120,7 @@ def save_binary_file(content: str, file_name: str, accepted_types: list[str]) ->
         raise ValueError(f"File {file_name} is not accepted")
 
     # Get the destination folder
-    cache_path = Path(tempfile.gettempdir()) / PREFIX
+    cache_path = Path(CACHE_DIR) / PREFIX
     if not content:
         raise ValueError("Please, reload the file in the loader.")
     data = content.split(",")[1]
@@ -132,3 +134,46 @@ def save_binary_file(content: str, file_name: str, accepted_types: list[str]) ->
         file.write(decoded_bytes)
 
     return file_path
+
+
+@create_cache_folder
+def save_uploaded_file(file, folder_name):
+    """
+    Save an uploaded file to the specified folder with a hash of its content as the file name.
+
+    Args:
+        file: The uploaded file object.
+        folder_name: The name of the folder to save the file in.
+
+    Returns:
+        The path to the saved file.
+    """
+    cache_path = Path(CACHE_DIR)
+    folder_path = cache_path / folder_name
+
+    # Create the folder if it doesn't exist
+    if not folder_path.exists():
+        folder_path.mkdir()
+
+    # Create a hash of the file content
+    sha256_hash = hashlib.sha256()
+    # Reset the file cursor to the beginning of the file
+    file.seek(0)
+    # Iterate over the uploaded file in small chunks to conserve memory
+    while chunk := file.read(8192):  # Read 8KB at a time (adjust as needed)
+        sha256_hash.update(chunk)
+
+    # Use the hex digest of the hash as the file name
+    hex_dig = sha256_hash.hexdigest()
+    file_name = hex_dig
+
+    # Reset the file cursor to the beginning of the file
+    file.seek(0)
+
+    # Save the file with the hash as its name
+    file_path = folder_path / file_name
+    with open(file_path, "wb") as new_file:
+        while chunk := file.read(8192):
+            new_file.write(chunk)
+
+    return file_path

src/backend/langflow/chat/config.py

@@ -0,0 +1,2 @@
+class ChatConfig:
+    streaming: bool = True

src/backend/langflow/chat/manager.py

@@ -144,6 +144,8 @@ class ChatManager:
                 if isinstance(msg, FileResponse):
                     if msg.data_type == "image":
                         # Base64 encode the image
+                        if isinstance(msg.data, str):
+                            continue
                         msg.data = pil_to_base64(msg.data)
                     file_responses.append(msg)
                 if msg.type == "start":

src/backend/langflow/config.yaml

@@ -1,136 +1,247 @@
----
 agents:
-  - ZeroShotAgent
-  - JsonAgent
-  - CSVAgent
-  - AgentInitializer
-  - VectorStoreAgent
-  - VectorStoreRouterAgent
-  - SQLAgent
+  ZeroShotAgent:
+    documentation: "https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent"
+  JsonAgent:
+    documentation: "https://python.langchain.com/docs/modules/agents/toolkits/openapi"
+  CSVAgent:
+    documentation: "https://python.langchain.com/docs/modules/agents/toolkits/csv"
+  AgentInitializer:
+    documentation: "https://python.langchain.com/docs/modules/agents/agent_types/"
+  VectorStoreAgent:
+    documentation: ""
+  VectorStoreRouterAgent:
+    documentation: ""
+  SQLAgent:
+    documentation: ""
 chains:
-  - LLMChain
-  - LLMMathChain
-  - LLMCheckerChain
-  - ConversationChain
-  - SeriesCharacterChain
-  - MidJourneyPromptChain
-  - TimeTravelGuideChain
-  - SQLDatabaseChain
-  - RetrievalQA
-  - RetrievalQAWithSourcesChain
-  - ConversationalRetrievalChain
-  - CombineDocsChain
+  LLMChain:
+    documentation: "https://python.langchain.com/docs/modules/chains/foundational/llm_chain"
+  LLMMathChain:
+    documentation: "https://python.langchain.com/docs/modules/chains/additional/llm_math"
+  LLMCheckerChain:
+    documentation: "https://python.langchain.com/docs/modules/chains/additional/llm_checker"
+  ConversationChain:
+    documentation: ""
+  SeriesCharacterChain:
+    documentation: ""
+  MidJourneyPromptChain:
+    documentation: ""
+  TimeTravelGuideChain:
+    documentation: ""
+  SQLDatabaseChain:
+    documentation: ""
+  RetrievalQA:
+    documentation: "https://python.langchain.com/docs/modules/chains/popular/vector_db_qa"
+  RetrievalQAWithSourcesChain:
+    documentation: ""
+  ConversationalRetrievalChain:
+    documentation: "https://python.langchain.com/docs/modules/chains/popular/chat_vector_db"
+  CombineDocsChain:
+    documentation: ""
 documentloaders:
-  - AirbyteJSONLoader
-  - CoNLLULoader
-  - CSVLoader
-  - UnstructuredEmailLoader
-  - EverNoteLoader
-  - FacebookChatLoader
-  - GutenbergLoader
-  - BSHTMLLoader
-  - UnstructuredHTMLLoader
-  # - UnstructuredImageLoader # Issue with Python 3.11 (https://github.com/Unstructured-IO/unstructured-inference/issues/83)
-  - UnstructuredMarkdownLoader
-  - PyPDFLoader
-  - UnstructuredPowerPointLoader
-  - SRTLoader
-  - TelegramChatLoader
-  - TextLoader
-  - UnstructuredWordDocumentLoader
-  - WebBaseLoader
-  - AZLyricsLoader
-  - CollegeConfidentialLoader
-  - HNLoader
-  - IFixitLoader
-  - IMSDbLoader
-  - GitbookLoader
-  - ReadTheDocsLoader
-  - SlackDirectoryLoader
-  - NotionDirectoryLoader
+  AirbyteJSONLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/airbyte_json"
+  CoNLLULoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/conll-u"
+  CSVLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/csv"
+  UnstructuredEmailLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/email"
+  EverNoteLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/evernote"
+  FacebookChatLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/facebook_chat"
+  GutenbergLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/gutenberg"
+  BSHTMLLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/html"
+  UnstructuredHTMLLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/html"
+  UnstructuredMarkdownLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/markdown"
+  PyPDFLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/pdf"
+  UnstructuredPowerPointLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/microsoft_powerpoint"
+  SRTLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/subtitle"
+  TelegramChatLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/telegram"
+  TextLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/"
+  UnstructuredWordDocumentLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/microsoft_word"
+  WebBaseLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/web_base"
+  AZLyricsLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/azlyrics"
+  CollegeConfidentialLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/college_confidential"
+  HNLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/hacker_news"
+  IFixitLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/ifixit"
+  IMSDbLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/imsdb"
+  GitbookLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/gitbook"
+  ReadTheDocsLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/readthedocs_documentation"
+  SlackDirectoryLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/slack"
+  NotionDirectoryLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/notion"
+  DirectoryLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/file_directory"
+  GitLoader:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/git"
 embeddings:
-  - OpenAIEmbeddings
-  - HuggingFaceEmbeddings
-  - CohereEmbeddings
+  OpenAIEmbeddings:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/openai"
+  HuggingFaceEmbeddings:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/sentence_transformers"
+  CohereEmbeddings:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/cohere"
 llms:
-  - OpenAI
-  # - AzureOpenAI
-  # - AzureChatOpenAI
-  - ChatOpenAI
-  - LlamaCpp 
-  - CTransformers
-  - Cohere
-  - Anthropic
-  - ChatAnthropic
-  - HuggingFaceHub
+  OpenAI:
+    documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai"
+  ChatOpenAI:
+    documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/integrations/openai"
+  LlamaCpp:
+    documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/llamacpp"
+  CTransformers:
+    documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/ctransformers"
+  Cohere:
+    documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/cohere"
+  Anthropic:
+    documentation: ""
+  ChatAnthropic:
+    documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/integrations/anthropic"
+  HuggingFaceHub:
+    documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/huggingface_hub"
 memories:
-  - ConversationBufferMemory
-  - ConversationSummaryMemory
-  - ConversationKGMemory
+  ConversationBufferMemory:
+    documentation: "https://python.langchain.com/docs/modules/memory/how_to/summary"
+  ConversationSummaryMemory:
+    documentation: "https://python.langchain.com/docs/modules/memory/how_to/summary"
+  ConversationKGMemory:
+    documentation: "https://python.langchain.com/docs/modules/memory/how_to/kg"
+  ConversationBufferWindowMemory:
+    documentation: "https://python.langchain.com/docs/modules/memory/how_to/buffer_window"
+  VectorStoreRetrieverMemory:
+    documentation: "https://python.langchain.com/docs/modules/memory/how_to/vectorstore_retriever_memory"
 prompts:
-  - PromptTemplate
-  - FewShotPromptTemplate
-  - ZeroShotPrompt
+  PromptTemplate:
+    documentation: "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/"
+  ZeroShotPrompt:
+    documentation: "https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent"
 textsplitters:
-  - CharacterTextSplitter
-  - RecursiveCharacterTextSplitter
-  # - LatexTextSplitter
-  # - PythonCodeTextSplitter
+  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/text_splitters/recursive_text_splitter"
 toolkits:
-  - OpenAPIToolkit
-  - JsonToolkit
-  - VectorStoreInfo
-  - VectorStoreRouterToolkit
-  - VectorStoreToolkit
+  OpenAPIToolkit:
+    documentation: ""
+  JsonToolkit:
+    documentation: ""
+  VectorStoreInfo:
+    documentation: ""
+  VectorStoreRouterToolkit:
+    documentation: ""
+  VectorStoreToolkit:
+    documentation: ""
 tools:
-  - Search
-  - PAL-MATH
-  - Calculator
-  - Serper Search
-  - Tool
-  - PythonFunctionTool
-  - PythonFunction
-  - JsonSpec
-  - News API
-  - TMDB API
-  - Podcast API
-  - QuerySQLDataBaseTool
-  - InfoSQLDatabaseTool
-  - ListSQLDatabaseTool
-  # - QueryCheckerTool
-  - BingSearchRun
-  - GoogleSearchRun
-  - GoogleSearchResults
-  - GoogleSerperRun
-  - JsonListKeysTool
-  - JsonGetValueTool
-  - PythonREPLTool
-  - PythonAstREPLTool
-  - RequestsGetTool
-  - RequestsPostTool
-  - RequestsPatchTool
-  - RequestsPutTool
-  - RequestsDeleteTool
-  - WikipediaQueryRun
-  - WolframAlphaQueryRun
+  Search:
+    documentation: ""
+  PAL-MATH:
+    documentation: ""
+  Calculator:
+    documentation: ""
+  Serper Search:
+    documentation: ""
+  Tool:
+    documentation: ""
+  PythonFunctionTool:
+    documentation: ""
+  PythonFunction:
+    documentation: ""
+  JsonSpec:
+    documentation: ""
+  News API:
+    documentation: ""
+  TMDB API:
+    documentation: ""
+  Podcast API:
+    documentation: ""
+  QuerySQLDataBaseTool:
+    documentation: ""
+  InfoSQLDatabaseTool:
+    documentation: ""
+  ListSQLDatabaseTool:
+    documentation: ""
+  BingSearchRun:
+    documentation: ""
+  GoogleSearchRun:
+    documentation: ""
+  GoogleSearchResults:
+    documentation: ""
+  GoogleSerperRun:
+    documentation: ""
+  JsonListKeysTool:
+    documentation: ""
+  JsonGetValueTool:
+    documentation: ""
+  PythonREPLTool:
+    documentation: ""
+  PythonAstREPLTool:
+    documentation: ""
+  RequestsGetTool:
+    documentation: ""
+  RequestsPostTool:
+    documentation: ""
+  RequestsPatchTool:
+    documentation: ""
+  RequestsPutTool:
+    documentation: ""
+  RequestsDeleteTool:
+    documentation: ""
+  WikipediaQueryRun:
+    documentation: ""
+  WolframAlphaQueryRun:
+    documentation: ""
 utilities:
-  - BingSearchAPIWrapper
-  - GoogleSearchAPIWrapper
-  - GoogleSerperAPIWrapper
-  - SearxResults
-  - SearxSearchWrapper
-  - SerpAPIWrapper
-  - WikipediaAPIWrapper
-  - WolframAlphaAPIWrapper
-  # - ZapierNLAWrapper
-  - SQLDatabase
+  BingSearchAPIWrapper:
+    documentation: ""
+  GoogleSearchAPIWrapper:
+    documentation: ""
+  GoogleSerperAPIWrapper:
+    documentation: ""
+  SearxResults:
+    documentation: ""
+  SearxSearchWrapper:
+    documentation: ""
+  SerpAPIWrapper:
+    documentation: ""
+  WikipediaAPIWrapper:
+    documentation: ""
+  WolframAlphaAPIWrapper:
+    documentation: ""
 vectorstores:
-  - Chroma
-  - Qdrant
-  - Weaviate
-  - FAISS
+  Chroma:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/chroma"
+  Qdrant:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/qdrant"
+  Weaviate:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/weaviate"
+  FAISS:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/faiss"
+  Pinecone:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/pinecone"
+  SupabaseVectorStore:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/supabase"
+  MongoDBAtlasVectorSearch:
+    documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/mongodb_atlas_vector_search"
 wrappers:
-  - RequestsWrapper
-  # - ChatPromptTemplate
-  # - SystemMessagePromptTemplate
-  # - HumanMessagePromptTemplate
+  RequestsWrapper:
+    documentation: ""

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

@@ -146,7 +146,7 @@ class Graph:
     def generator_build(self) -> Generator:
         """Builds each vertex in the graph and yields it."""
         sorted_vertices = self.topological_sort()
-        logger.info("Sorted vertices: %s", sorted_vertices)
+        logger.debug("Sorted vertices: %s", sorted_vertices)
         yield from sorted_vertices
 
     def get_node_neighbors(self, node: Vertex) -> Dict[Vertex, int]:

src/backend/langflow/graph/graph/constants.py

@@ -30,9 +30,6 @@ from langflow.interface.wrappers.base import wrapper_creator
 from typing import Dict, Type
 
 
-DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any", "prompt"]
-
-
 VERTEX_TYPE_MAP: Dict[str, Type[Vertex]] = {
     **{t: PromptVertex for t in prompt_creator.to_list()},
     **{t: AgentVertex for t in agent_creator.to_list()},

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

@@ -1,6 +1,5 @@
-from langflow.cache import utils as cache_utils
-from langflow.graph.vertex.constants import DIRECT_TYPES
-from langflow.interface import loading
+from langflow.utils.constants import DIRECT_TYPES
+from langflow.interface.initialize import loading
 from langflow.interface.listing import ALL_TYPES_DICT
 from langflow.utils.logger import logger
 from langflow.utils.util import sync_to_async
@@ -90,12 +89,7 @@ class Vertex:
                 # Load the type in value.get('suffixes') using
                 # what is inside value.get('content')
                 # value.get('value') is the file name
-                file_name = value.get("value")
-                content = value.get("content")
-                type_to_load = value.get("suffixes")
-                file_path = cache_utils.save_binary_file(
-                    content=content, file_name=file_name, accepted_types=type_to_load
-                )
+                file_path = value.get("file_path")
 
                 params[key] = file_path
 

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

@@ -1 +1 @@
-DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any", "prompt"]
+

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

@@ -106,9 +106,6 @@ class VectorStoreVertex(Vertex):
     def __init__(self, data: Dict):
         super().__init__(data, base_type="vectorstores")
 
-    def _built_object_repr(self):
-        return "Vector stores can take time to build. It will build on the first query."
-
 
 class MemoryVertex(Vertex):
     def __init__(self, data: Dict):

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

@@ -6,6 +6,7 @@ from langchain.agents import (
     Tool,
     ZeroShotAgent,
     initialize_agent,
+    AgentType,
 )
 from langchain.agents.agent_toolkits import (
     SQLDatabaseToolkit,
@@ -192,7 +193,7 @@ class SQLAgent(CustomAgentExecutor):
         from langchain.tools.sql_database.tool import (
             InfoSQLDatabaseTool,
             ListSQLDatabaseTool,
-            QueryCheckerTool,
+            QuerySQLCheckerTool,
             QuerySQLDataBaseTool,
         )
 
@@ -207,7 +208,7 @@ class SQLAgent(CustomAgentExecutor):
             QuerySQLDataBaseTool(db=db),  # type: ignore
             InfoSQLDatabaseTool(db=db),  # type: ignore
             ListSQLDatabaseTool(db=db),  # type: ignore
-            QueryCheckerTool(db=db, llm_chain=llmchain, llm=llm),  # type: ignore
+            QuerySQLCheckerTool(db=db, llm_chain=llmchain, llm=llm),  # type: ignore
         ]
 
         prefix = SQL_PREFIX.format(dialect=toolkit.dialect, top_k=10)
@@ -297,6 +298,9 @@ class InitializeAgent(CustomAgentExecutor):
         agent: str,
         memory: Optional[BaseChatMemory] = None,
     ):
+        # Find which value in the AgentType enum corresponds to the string
+        # passed in as agent
+        agent = AgentType(agent)
         return initialize_agent(
             tools=tools,
             llm=llm,

src/backend/langflow/interface/base.py

@@ -8,6 +8,7 @@ from langflow.template.field.base import TemplateField
 from langflow.template.frontend_node.base import FrontendNode
 from langflow.template.template.base import Template
 from langflow.utils.logger import logger
+from langflow.settings import settings
 
 # Assuming necessary imports for Field, Template, and FrontendNode classes
 
@@ -15,12 +16,29 @@ from langflow.utils.logger import logger
 class LangChainTypeCreator(BaseModel, ABC):
     type_name: str
     type_dict: Optional[Dict] = None
+    name_docs_dict: Optional[Dict[str, str]] = None
 
     @property
     def frontend_node_class(self) -> Type[FrontendNode]:
         """The class type of the FrontendNode created in frontend_node."""
         return FrontendNode
 
+    @property
+    def docs_map(self) -> Dict[str, str]:
+        """A dict with the name of the component as key and the documentation link as value."""
+        if self.name_docs_dict is None:
+            try:
+                type_settings = getattr(settings, self.type_name)
+                self.name_docs_dict = {
+                    name: value_dict["documentation"]
+                    for name, value_dict in type_settings.items()
+                }
+            except AttributeError as exc:
+                logger.error(exc)
+
+                self.name_docs_dict = {}
+        return self.name_docs_dict
+
     @property
     @abstractmethod
     def type_to_loader_dict(self) -> Dict:
@@ -68,7 +86,7 @@ class LangChainTypeCreator(BaseModel, ABC):
                     value=value.get("value", None),
                     suffixes=value.get("suffixes", []),
                     file_types=value.get("fileTypes", []),
-                    content=value.get("content", None),
+                    file_path=value.get("file_path", None),
                 )
                 for key, value in signature["template"].items()
                 if key != "_type"
@@ -83,7 +101,7 @@ class LangChainTypeCreator(BaseModel, ABC):
 
         signature.add_extra_fields()
         signature.add_extra_base_classes()
-
+        signature.set_documentation(self.docs_map.get(name, ""))
         return signature