mirror of
https://github.com/khoj-ai/khoj.git
synced 2024-11-23 15:38:55 +01:00
Move the chat API out of beta. Save chat sessions at 15min intervals
This commit is contained in:
Debanjum Singh Solanky
parent
e16d0b6d7e
commit
a71f168273
4 changed files with 78 additions and 82 deletions
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@ -9,6 +9,7 @@ import schedule
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from fastapi.staticfiles import StaticFiles
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# Internal Packages
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from khoj.processor.conversation.gpt import summarize
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from khoj.processor.ledger.beancount_to_jsonl import BeancountToJsonl
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from khoj.processor.jsonl.jsonl_to_jsonl import JsonlToJsonl
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from khoj.processor.markdown.markdown_to_jsonl import MarkdownToJsonl
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@ -186,3 +187,39 @@ def configure_conversation_processor(conversation_processor_config):
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conversation_processor.chat_session = ""
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return conversation_processor
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@schedule.repeat(schedule.every(15).minutes)
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def save_chat_session():
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# No need to create empty log file
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if not (
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state.processor_config
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and state.processor_config.conversation
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and state.processor_config.conversation.meta_log
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and state.processor_config.conversation.chat_session
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):
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return
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# Summarize Conversation Logs for this Session
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chat_session = state.processor_config.conversation.chat_session
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openai_api_key = state.processor_config.conversation.openai_api_key
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conversation_log = state.processor_config.conversation.meta_log
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model = state.processor_config.conversation.model
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session = {
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"summary": summarize(chat_session, summary_type="chat", model=model, api_key=openai_api_key),
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"session-start": conversation_log.get("session", [{"session-end": 0}])[-1]["session-end"],
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"session-end": len(conversation_log["chat"]),
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}
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if "session" in conversation_log:
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conversation_log["session"].append(session)
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else:
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conversation_log["session"] = [session]
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# Save Conversation Metadata Logs to Disk
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conversation_logfile = resolve_absolute_path(state.processor_config.conversation.conversation_logfile)
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conversation_logfile.parent.mkdir(parents=True, exist_ok=True) # create conversation directory if doesn't exist
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with open(conversation_logfile, "w+", encoding="utf-8") as logfile:
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json.dump(conversation_log, logfile)
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state.processor_config.conversation.chat_session = None
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logger.info("📩 Saved current chat session to conversation logs")
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@ -48,7 +48,7 @@
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document.getElementById("chat-input").value = "";
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// Generate backend API URL to execute query
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let url = `/api/beta/chat?q=${encodeURIComponent(query)}`;
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let url = `/api/chat?q=${encodeURIComponent(query)}`;
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// Call specified Khoj API
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fetch(url)
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@ -78,7 +78,7 @@
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}
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window.onload = function () {
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fetch('/api/beta/chat')
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fetch('/api/chat')
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.then(response => response.json())
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.then(data => data.response)
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.then(chat_logs => {
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@ -10,6 +10,7 @@ from fastapi import HTTPException
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# Internal Packages
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from khoj.configure import configure_processor, configure_search
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from khoj.processor.conversation.gpt import converse, message_to_log, message_to_prompt
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from khoj.search_type import image_search, text_search
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from khoj.utils.helpers import timer
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from khoj.utils.rawconfig import FullConfig, SearchResponse
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@ -183,3 +184,40 @@ def update(t: Optional[SearchType] = None, force: Optional[bool] = False):
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logger.info("📬 Processor reconfigured via API")
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return {"status": "ok", "message": "khoj reloaded"}
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@api.get("/chat")
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def chat(q: Optional[str] = None):
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# Initialize Variables
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api_key = state.processor_config.conversation.openai_api_key
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# Load Conversation History
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chat_session = state.processor_config.conversation.chat_session
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meta_log = state.processor_config.conversation.meta_log
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# If user query is empty, return chat history
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if not q:
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if meta_log.get("chat"):
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return {"status": "ok", "response": meta_log["chat"]}
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else:
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return {"status": "ok", "response": []}
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# Collate context for GPT
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result_list = search(q, n=2, r=True, score_threshold=0, dedupe=False)
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collated_result = "\n\n".join([f"# {item.additional['compiled']}" for item in result_list])
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logger.debug(f"Reference Context:\n{collated_result}")
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try:
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gpt_response = converse(collated_result, q, meta_log, api_key=api_key)
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status = "ok"
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except Exception as e:
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gpt_response = str(e)
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status = "error"
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# Update Conversation History
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state.processor_config.conversation.chat_session = message_to_prompt(q, chat_session, gpt_message=gpt_response)
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state.processor_config.conversation.meta_log["chat"] = message_to_log(
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q, gpt_response, khoj_message_metadata={"context": collated_result}, conversation_log=meta_log.get("chat", [])
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)
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return {"status": status, "response": gpt_response, "context": collated_result}
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@ -1,24 +1,18 @@
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# Standard Packages
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import json
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import logging
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from typing import Optional
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# External Packages
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import schedule
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from fastapi import APIRouter
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# Internal Packages
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from khoj.routers.api import search
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from khoj.processor.conversation.gpt import (
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answer,
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converse,
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extract_search_type,
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message_to_log,
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message_to_prompt,
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summarize,
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)
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from khoj.utils.state import SearchType
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from khoj.utils.helpers import get_from_dict, resolve_absolute_path
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from khoj.utils.helpers import get_from_dict
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from khoj.utils import state
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@ -68,76 +62,3 @@ def answer_beta(q: str):
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status = "error"
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return {"status": status, "response": gpt_response}
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@api_beta.get("/chat")
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def chat(q: Optional[str] = None):
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# Initialize Variables
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api_key = state.processor_config.conversation.openai_api_key
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# Load Conversation History
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chat_session = state.processor_config.conversation.chat_session
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meta_log = state.processor_config.conversation.meta_log
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# If user query is empty, return chat history
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if not q:
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if meta_log.get("chat"):
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return {"status": "ok", "response": meta_log["chat"]}
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else:
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return {"status": "ok", "response": []}
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# Collate context for GPT
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result_list = search(q, n=2, r=True, score_threshold=0, dedupe=False)
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collated_result = "\n\n".join([f"# {item.additional['compiled']}" for item in result_list])
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logger.debug(f"Reference Context:\n{collated_result}")
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try:
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gpt_response = converse(collated_result, q, meta_log, api_key=api_key)
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status = "ok"
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except Exception as e:
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gpt_response = str(e)
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status = "error"
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# Update Conversation History
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state.processor_config.conversation.chat_session = message_to_prompt(q, chat_session, gpt_message=gpt_response)
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state.processor_config.conversation.meta_log["chat"] = message_to_log(
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q, gpt_response, khoj_message_metadata={"context": collated_result}, conversation_log=meta_log.get("chat", [])
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)
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return {"status": status, "response": gpt_response, "context": collated_result}
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@schedule.repeat(schedule.every(5).minutes)
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def save_chat_session():
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# No need to create empty log file
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if not (
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state.processor_config
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and state.processor_config.conversation
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and state.processor_config.conversation.meta_log
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and state.processor_config.conversation.chat_session
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):
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return
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# Summarize Conversation Logs for this Session
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chat_session = state.processor_config.conversation.chat_session
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openai_api_key = state.processor_config.conversation.openai_api_key
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conversation_log = state.processor_config.conversation.meta_log
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model = state.processor_config.conversation.model
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session = {
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"summary": summarize(chat_session, summary_type="chat", model=model, api_key=openai_api_key),
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"session-start": conversation_log.get("session", [{"session-end": 0}])[-1]["session-end"],
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"session-end": len(conversation_log["chat"]),
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}
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if "session" in conversation_log:
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conversation_log["session"].append(session)
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else:
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conversation_log["session"] = [session]
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# Save Conversation Metadata Logs to Disk
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conversation_logfile = resolve_absolute_path(state.processor_config.conversation.conversation_logfile)
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conversation_logfile.parent.mkdir(parents=True, exist_ok=True) # create conversation directory if doesn't exist
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with open(conversation_logfile, "w+", encoding="utf-8") as logfile:
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json.dump(conversation_log, logfile)
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state.processor_config.conversation.chat_session = None
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logger.info("📩 Saved current chat session to conversation logs")
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