Merge branch 'dev' into feat/vectorstore-pgvector

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

@@ -12,7 +12,10 @@ from langflow.api.utils import build_input_keys_response
 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.database.models.user.crud import (
 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 @@ import tempfile
 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 @@ OPENAI_MODELS = [
     "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 typing import Optional
 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)