🔥 refactor(chat/manager.py): remove unused imports and code
🚀 feat(chat/manager.py): add import for pil_to_base64 function to support image encoding in chat messages
This commit is contained in:
Gabriel Luiz Freitas Almeida
parent
e74fc00442
commit
ba9d57fa78
2 changed files with 1 additions and 222 deletions
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@ -1,222 +0,0 @@
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from collections import defaultdict
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from fastapi import WebSocket, status
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from langflow.api.v1.schemas import ChatMessage, ChatResponse, FileResponse
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from langflow.cache import cache_manager
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from langflow.cache.manager import Subject
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from langflow.chat.utils import process_graph
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from langflow.interface.utils import pil_to_base64
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from langflow.utils.logger import logger
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import asyncio
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import json
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from typing import Any, Dict, List
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from langflow.cache.flow import InMemoryCache
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class ChatHistory(Subject):
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def __init__(self):
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super().__init__()
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self.history: Dict[str, List[ChatMessage]] = defaultdict(list)
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def add_message(self, client_id: str, message: ChatMessage):
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"""Add a message to the chat history."""
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self.history[client_id].append(message)
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if not isinstance(message, FileResponse):
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self.notify()
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def get_history(self, client_id: str, filter_messages=True) -> List[ChatMessage]:
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"""Get the chat history for a client."""
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if history := self.history.get(client_id, []):
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if filter_messages:
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return [msg for msg in history if msg.type not in ["start", "stream"]]
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return history
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else:
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return []
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def empty_history(self, client_id: str):
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"""Empty the chat history for a client."""
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self.history[client_id] = []
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class ChatManager:
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def __init__(self):
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self.active_connections: Dict[str, WebSocket] = {}
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self.chat_history = ChatHistory()
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self.cache_manager = cache_manager
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self.cache_manager.attach(self.update)
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self.in_memory_cache = InMemoryCache()
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def on_chat_history_update(self):
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"""Send the last chat message to the client."""
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client_id = self.cache_manager.current_client_id
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if client_id in self.active_connections:
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chat_response = self.chat_history.get_history(
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client_id, filter_messages=False
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)[-1]
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if chat_response.is_bot:
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# Process FileResponse
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if isinstance(chat_response, FileResponse):
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# If data_type is pandas, convert to csv
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if chat_response.data_type == "pandas":
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chat_response.data = chat_response.data.to_csv()
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elif chat_response.data_type == "image":
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# Base64 encode the image
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chat_response.data = pil_to_base64(chat_response.data)
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# get event loop
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loop = asyncio.get_event_loop()
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coroutine = self.send_json(client_id, chat_response)
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asyncio.run_coroutine_threadsafe(coroutine, loop)
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def update(self):
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if self.cache_manager.current_client_id in self.active_connections:
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self.last_cached_object_dict = self.cache_manager.get_last()
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# Add a new ChatResponse with the data
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chat_response = FileResponse(
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message=None,
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type="file",
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data=self.last_cached_object_dict["obj"],
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data_type=self.last_cached_object_dict["type"],
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)
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self.chat_history.add_message(
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self.cache_manager.current_client_id, chat_response
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)
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async def connect(self, client_id: str, websocket: WebSocket):
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await websocket.accept()
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self.active_connections[client_id] = websocket
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def disconnect(self, client_id: str):
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self.active_connections.pop(client_id, None)
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async def send_message(self, client_id: str, message: str):
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websocket = self.active_connections[client_id]
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await websocket.send_text(message)
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async def send_json(self, client_id: str, message: ChatMessage):
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websocket = self.active_connections[client_id]
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await websocket.send_json(message.dict())
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async def close_connection(self, client_id: str, code: int, reason: str):
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if websocket := self.active_connections[client_id]:
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try:
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await websocket.close(code=code, reason=reason)
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self.disconnect(client_id)
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except RuntimeError as exc:
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# This is to catch the following error:
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# Unexpected ASGI message 'websocket.close', after sending 'websocket.close'
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if "after sending" in str(exc):
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logger.error(f"Error closing connection: {exc}")
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async def process_message(
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self, client_id: str, payload: Dict, langchain_object: Any
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):
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# Process the graph data and chat message
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chat_inputs = payload.pop("inputs", {})
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chat_inputs = ChatMessage(message=chat_inputs)
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self.chat_history.add_message(client_id, chat_inputs)
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# graph_data = payload
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start_resp = ChatResponse(message=None, type="start", intermediate_steps="")
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await self.send_json(client_id, start_resp)
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# is_first_message = len(self.chat_history.get_history(client_id=client_id)) <= 1
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# Generate result and thought
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try:
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logger.debug("Generating result and thought")
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result, intermediate_steps = await process_graph(
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langchain_object=langchain_object,
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chat_inputs=chat_inputs,
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websocket=self.active_connections[client_id],
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)
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self.cache_manager.set(client_id, langchain_object)
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except Exception as e:
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# Log stack trace
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logger.exception(e)
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self.chat_history.empty_history(client_id)
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raise e
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# Send a response back to the frontend, if needed
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intermediate_steps = intermediate_steps or ""
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history = self.chat_history.get_history(client_id, filter_messages=False)
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file_responses = []
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if history:
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# Iterate backwards through the history
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for msg in reversed(history):
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if isinstance(msg, FileResponse):
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if msg.data_type == "image":
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# Base64 encode the image
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if isinstance(msg.data, str):
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continue
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msg.data = pil_to_base64(msg.data)
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file_responses.append(msg)
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if msg.type == "start":
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break
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response = ChatResponse(
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message=result,
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intermediate_steps=intermediate_steps.strip(),
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type="end",
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files=file_responses,
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)
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await self.send_json(client_id, response)
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self.chat_history.add_message(client_id, response)
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def set_cache(self, client_id: str, langchain_object: Any) -> bool:
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"""
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Set the cache for a client.
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"""
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result_dict = {"result": langchain_object, "type": type(langchain_object)}
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self.cache_manager.upsert(client_id, result_dict)
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return client_id in self.cache_manager
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async def handle_websocket(self, client_id: str, websocket: WebSocket):
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await self.connect(client_id, websocket)
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try:
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chat_history = self.chat_history.get_history(client_id)
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# iterate and make BaseModel into dict
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chat_history = [chat.dict() for chat in chat_history]
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await websocket.send_json(chat_history)
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while True:
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json_payload = await websocket.receive_json()
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try:
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payload = json.loads(json_payload)
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except TypeError:
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payload = json_payload
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if "clear_history" in payload:
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self.chat_history.history[client_id] = []
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continue
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with self.cache_manager.set_client_id(client_id):
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if langchain_object := self.in_memory_cache.get(client_id).get(
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"result"
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):
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await self.process_message(client_id, payload, langchain_object)
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else:
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raise ValueError("No langchain object found in cache")
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except Exception as exc:
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# Handle any exceptions that might occur
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logger.error(f"Error handling websocket: {exc}")
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await self.close_connection(
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client_id=client_id,
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code=status.WS_1011_INTERNAL_ERROR,
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reason=str(exc)[:120],
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)
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finally:
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try:
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await self.close_connection(
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client_id=client_id,
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code=status.WS_1000_NORMAL_CLOSURE,
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reason="Client disconnected",
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)
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except Exception as exc:
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logger.error(f"Error closing connection: {exc}")
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self.disconnect(client_id)
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@ -1,6 +1,7 @@
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from collections import defaultdict
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from collections import defaultdict
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from fastapi import WebSocket, status
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from fastapi import WebSocket, status
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from langflow.api.v1.schemas import ChatMessage, ChatResponse, FileResponse
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from langflow.api.v1.schemas import ChatMessage, ChatResponse, FileResponse
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from langflow.interface.utils import pil_to_base64
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from langflow.services.base import Service
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from langflow.services.base import Service
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from langflow.services.chat.cache import Subject
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from langflow.services.chat.cache import Subject
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from langflow.services.chat.utils import process_graph
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from langflow.services.chat.utils import process_graph
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