Merge branch 'dev' into feat/vectorstore-pgvector

Dockerfile

@@ -11,5 +11,5 @@ WORKDIR $HOME/app
 
 COPY --chown=user . $HOME/app
 
-RUN pip install langflow>==0.0.86 -U --user
+RUN pip install langflow>==0.5.0 -U --user
 CMD ["python", "-m", "langflow", "run", "--host", "0.0.0.0", "--port", "7860"]

Makefile

@@ -74,10 +74,10 @@ backend:
  make install_backend
 ifeq ($(login),1)
  @echo "Running backend without autologin";
- poetry run langflow run --backend-only --port 7860 --host 0.0.0.0 --no-open-browser
+ poetry run langflow run --backend-only --port 7860 --host 0.0.0.0 --no-open-browser --log-level debug --workers 3
 else
  @echo "Running backend with autologin";
- LANGFLOW_AUTO_LOGIN=True poetry run langflow run --backend-only --port 7860 --host 0.0.0.0 --no-open-browser
+ LANGFLOW_AUTO_LOGIN=True poetry run langflow run --backend-only --port 7860 --host 0.0.0.0 --no-open-browser --log-level debug --workers 3
 endif
 
 build_and_run:

docker_example/Dockerfile

@@ -1,14 +1,15 @@
 FROM python:3.10-slim
 
-RUN apt-get update && apt-get install gcc g++ git make -y
+RUN apt-get update && apt-get install gcc g++ git make -y && apt-get clean \
+ && rm -rf /var/lib/apt/lists/*
 RUN useradd -m -u 1000 user
 USER user
 ENV HOME=/home/user \
- PATH=/home/user/.local/bin:$PATH
+ PATH=/home/user/.local/bin:$PATH
 
 WORKDIR $HOME/app
 
 COPY --chown=user . $HOME/app
 
-RUN pip install langflow>==0.0.71 -U --user
-CMD ["langflow", "--host", "0.0.0.0", "--port", "7860"]
+RUN pip install langflow>==0.5.0 -U --user
+CMD ["python", "-m", "langflow", "run", "--host", "0.0.0.0", "--port", "7860"]

docker_example/docker-compose.yml

@@ -7,4 +7,4 @@ services:
  dockerfile: Dockerfile
  ports:
  - "7860:7860"
- command: langflow --host 0.0.0.0
+ command: langflow run --host 0.0.0.0

docs/docs/guidelines/components.mdx

@@ -5,7 +5,7 @@ import ReactPlayer from "react-player";
 
 # Component
 
-Components are the building blocks of the flows. They are made of inputs, outputs, and parameters that define their functionality, providing a convenient and straightforward way to compose LLM-based applications. Learn more about components and how they work in the LangChain [documentation](https://docs.langchain.com/docs/category/components) section.
+Components are the building blocks of the flows. They are made of inputs, outputs, and parameters that define their functionality, providing a convenient and straightforward way to compose LLM-based applications. Learn more about components and how they work in the LangChain [documentation](https://python.langchain.com/docs/integrations/components) section.
 
 ### Component's Features
 

docs/docusaurus.config.js

@@ -31,7 +31,7 @@ module.exports = {
  [
  remarkCodeHike,
  {
- theme: "github-light",
+ theme: "github-dark",
  showCopyButton: true,
  lineNumbers: true,
  },
@@ -112,8 +112,10 @@ module.exports = {
  },
  colorMode: {
  defaultMode: "light",
- disableSwitch: true,
- respectPrefersColorScheme: false,
+ /* Allow users to chose light or dark mode. */
+ disableSwitch: false,
+ /* Respect user preferences, such as low light mode in the evening */
+ respectPrefersColorScheme: true,
  },
  announcementBar: {
  content:

pyproject.toml

@@ -26,15 +26,15 @@ langflow = "langflow.__main__:main"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
-fastapi = "^0.103.0"
+fastapi = "^0.104.0"
 uvicorn = "^0.23.0"
 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 = "^0.0.312"
-openai = "^0.27.8"
+openai = "^1.0.1"
 pandas = "2.0.3"
 chromadb = "^0.3.21"
 huggingface-hub = { version = "^0.16.0", extras = ["inference"] }
@@ -48,7 +48,7 @@ pysrt = "^1.1.2"
 fake-useragent = "^1.2.1"
 docstring-parser = "^0.15"
 psycopg2-binary = "^2.9.6"
-pyarrow = "^12.0.0"
+pyarrow = "^14.0.0"
 tiktoken = "~0.5.0"
 wikipedia = "^1.4.0"
 qdrant-client = "^1.4.0"
@@ -66,12 +66,12 @@ orjson = "3.9.3"
 multiprocess = "^0.70.14"
 cachetools = "^5.3.1"
 types-cachetools = "^5.3.0.5"
-appdirs = "^1.4.4"
+platformdirs = "^3.11.0"
 pinecone-client = "^2.2.2"
-supabase = "^1.0.3"
+supabase = "^2.0.3"
 pymongo = "^4.4.0"
 certifi = "^2023.5.7"
-google-cloud-aiplatform = "^1.26.1"
+google-cloud-aiplatform = "^1.36.0"
 psycopg = "^3.1.9"
 psycopg-binary = "^3.1.9"
 fastavro = "^1.8.0"
@@ -108,7 +108,6 @@ 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"
 types-pyyaml = "^6.0.12.8"
 types-python-jose = "^3.3.4.8"
 types-passlib = "^1.7.7.13"

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

@@ -12,7 +12,10 @@
 from langflow.api.v1.schemas import BuildStatus, BuiltResponse, InitResponse, StreamData
 
 from langflow.graph.graph.base import Graph
-from langflow.services.auth.utils import get_current_active_user, get_current_user
+from langflow.services.auth.utils import (
+ get_current_active_user,
+ get_current_user_by_jwt,
+)
 from langflow.services.cache.utils import update_build_status
 from loguru import logger
 from langflow.services.getters import get_chat_service, get_session, get_cache_service
@@ -34,8 +37,8 @@ async def chat(
 ):
  """Websocket endpoint for chat."""
  try:
+ user = await get_current_user_by_jwt(token, db)
  await websocket.accept()
- user = await get_current_user(token, db)
  if not user:
  await websocket.close(
  code=status.WS_1008_POLICY_VIOLATION, reason="Unauthorized"

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

@@ -20,10 +20,11 @@ class ConversationalAgent(CustomComponent):
 
  def build_config(self):
  openai_function_models = [
- "gpt-3.5-turbo-0613",
- "gpt-3.5-turbo-16k-0613",
- "gpt-4-0613",
- "gpt-4-32k-0613",
+ "gpt-4-1106-preview",
+ "gpt-3.5-turbo",
+ "gpt-3.5-turbo-16k",
+ "gpt-4",
+ "gpt-4-32k",
  ]
  return {
  "tools": {"is_list": True, "display_name": "Tools"},

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

@@ -0,0 +1,64 @@
+from typing import Optional
+from langflow import CustomComponent
+
+from langchain.vectorstores.redis import Redis
+from langchain.schema import Document
+from langchain.vectorstores.base import VectorStore
+from langchain.embeddings.base import Embeddings
+
+
+class RedisComponent(CustomComponent):
+ """
+ A custom component for implementing a Vector Store using Redis.
+ """
+
+ display_name: str = "Redis"
+ description: str = "Implementation of Vector Store using Redis"
+ documentation = "https://python.langchain.com/docs/integrations/vectorstores/redis"
+ beta = True
+
+ def build_config(self):
+ """
+ Builds the configuration for the component.
+
+ Returns:
+ - dict: A dictionary containing the configuration options for the component.
+ """
+ return {
+ "index_name": {"display_name": "Index Name", "value": "your_index"},
+ "code": {"show": False, "display_name": "Code"},
+ "documents": {"display_name": "Documents", "is_list": True},
+ "embedding": {"display_name": "Embedding"},
+ "redis_server_url": {
+ "display_name": "Redis Server Connection String",
+ "advanced": False,
+ },
+ "redis_index_name": {"display_name": "Redis Index", "advanced": False},
+ }
+
+ def build(
+ self,
+ embedding: Embeddings,
+ redis_server_url: str,
+ redis_index_name: str,
+ documents: Optional[Document] = None,
+ ) -> VectorStore:
+ """
+ Builds the Vector Store or BaseRetriever object.
+
+ Args:
+ - embedding (Embeddings): The embeddings to use for the Vector Store.
+ - documents (Optional[Document]): The documents to use for the Vector Store.
+ - redis_index_name (str): The name of the Redis index.
+ - redis_server_url (str): The URL for the Redis server.
+
+ 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,
+ )

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

@@ -15,7 +15,7 @@
 from langflow.services.getters import get_session, get_settings_service
 from sqlmodel import Session
 
-oauth2_login = OAuth2PasswordBearer(tokenUrl="api/v1/login")
+oauth2_login = OAuth2PasswordBearer(tokenUrl="api/v1/login", auto_error=False)
 
 API_KEY_NAME = "x-api-key"
 
@@ -69,6 +69,30 @@ async def api_key_security(
 
 
 async def get_current_user(
+ token: str = Security(oauth2_login),
+ query_param: str = Security(api_key_query),
+ header_param: str = Security(api_key_header),
+ db: Session = Depends(get_session),
+) -> User:
+ if token:
+ return await get_current_user_by_jwt(token, db)
+ else:
+ if not query_param and not header_param:
+ raise HTTPException(
+ status_code=status.HTTP_403_FORBIDDEN,
+ detail="An API key must be passed as query or header",
+ )
+ user = await api_key_security(query_param, header_param, db)
+ if user:
+ return user
+
+ raise HTTPException(
+ status_code=status.HTTP_403_FORBIDDEN,
+ detail="Invalid or missing API key",
+ )
+
+
+async def get_current_user_by_jwt(
  token: Annotated[str, Depends(oauth2_login)],
  db: Session = Depends(get_session),
 ) -> User:

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

@@ -7,7 +7,7 @@
 from collections import OrderedDict
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Dict
-from appdirs import user_cache_dir
+from platformdirs import user_cache_dir
 from fastapi import UploadFile
 from langflow.api.v1.schemas import BuildStatus
 from langflow.services.database.models.base import orjson_dumps

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

@@ -55,14 +55,14 @@ class Settings(BaseSettings):
  @validator("CONFIG_DIR", pre=True, allow_reuse=True)
  def set_langflow_dir(cls, value):
  if not value:
- import appdirs
+ from platformdirs import user_cache_dir
 
  # Define the app name and author
  app_name = "langflow"
  app_author = "logspace"
 
  # Get the cache directory for the application
- cache_dir = appdirs.user_cache_dir(app_name, app_author)
+ cache_dir = user_cache_dir(app_name, app_author)
 
  # Create a .langflow directory inside the cache directory
  value = Path(cache_dir)

src/backend/langflow/utils/constants.py

@@ -6,16 +6,14 @@
  "text-ada-001",
 ]
 CHAT_OPENAI_MODELS = [
- "gpt-3.5-turbo-0613",
- "gpt-3.5-turbo",
- "gpt-3.5-turbo-16k-0613",
- "gpt-3.5-turbo-16k",
- "gpt-4-0613",
- "gpt-4-32k-0613",
+ "gpt-4-1106-preview",
  "gpt-4",
  "gpt-4-32k",
+ "gpt-3.5-turbo",
+ "gpt-3.5-turbo-16k",
 ]
 
+
 ANTHROPIC_MODELS = [
  # largest model, ideal for a wide range of more complex tasks.
  "claude-v1",

src/backend/langflow/utils/logger.py

@@ -2,9 +2,9 @@
 from loguru import logger
 from pathlib import Path
 from rich.logging import RichHandler
+from platformdirs import user_cache_dir
 import os
 import orjson
-import appdirs
 
 
 VALID_LOG_LEVELS = ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
@@ -50,7 +50,7 @@ def configure(log_level: Optional[str] = None, log_file: Optional[Path] = None):
  )
 
  if not log_file:
- cache_dir = Path(appdirs.user_cache_dir("langflow"))
+ cache_dir = Path(user_cache_dir("langflow"))
  log_file = cache_dir / "langflow.log"
 
  log_file = Path(log_file)

tests/test_llms_template.py

@@ -309,17 +309,14 @@ def test_chat_open_ai(client: TestClient, logged_in_headers):
  "placeholder": "",
  "show": True,
  "multiline": False,
- "value": "gpt-3.5-turbo-0613",
+ "value": "gpt-4-1106-preview",
  "password": False,
  "options": [
- "gpt-3.5-turbo-0613",
- "gpt-3.5-turbo",
- "gpt-3.5-turbo-16k-0613",
- "gpt-3.5-turbo-16k",
- "gpt-4-0613",
- "gpt-4-32k-0613",
+ "gpt-4-1106-preview",
  "gpt-4",
  "gpt-4-32k",
+ "gpt-3.5-turbo",
+ "gpt-3.5-turbo-16k",
  ],
  "name": "model_name",
  "type": "str",