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https://github.com/khoaliber/khoj.git
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918af5e6f8
- Default to using `text-davinci-003' if conversation model not explicitly configured by user. Stop using the older `davinci' and `davinci-instruct' models - Use `model' instead of `engine' as parameter. Usage of `engine' parameter in OpenAI API is deprecated
92 lines
3.7 KiB
Python
92 lines
3.7 KiB
Python
# 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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from fastapi import APIRouter
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# Internal Packages
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from src.routers.api import search
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from src.processor.conversation.gpt import converse, extract_search_type, message_to_log, message_to_prompt, understand, summarize
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from src.utils.config import SearchType
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from src.utils.helpers import get_absolute_path, get_from_dict
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from src.utils import state
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# Initialize Router
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api_beta = APIRouter()
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logger = logging.getLogger(__name__)
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# Create Routes
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@api_beta.get('/search')
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def search_beta(q: str, n: Optional[int] = 1):
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# Extract Search Type using GPT
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metadata = extract_search_type(q, api_key=state.processor_config.conversation.openai_api_key, verbose=state.verbose)
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search_type = get_from_dict(metadata, "search-type")
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# Search
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search_results = search(q, n=n, t=SearchType(search_type))
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# Return response
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return {'status': 'ok', 'result': search_results, 'type': search_type}
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@api_beta.get('/chat')
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def chat(q: str):
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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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model = state.processor_config.conversation.model
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api_key = state.processor_config.conversation.openai_api_key
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# Converse with OpenAI GPT
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metadata = understand(q, model=model, api_key=api_key, verbose=state.verbose)
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logger.debug(f'Understood: {get_from_dict(metadata, "intent")}')
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if get_from_dict(metadata, "intent", "memory-type") == "notes":
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query = get_from_dict(metadata, "intent", "query")
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result_list = search(query, n=1, t=SearchType.Org, r=True)
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collated_result = "\n".join([item.entry for item in result_list])
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logger.debug(f'Semantically Similar Notes:\n{collated_result}')
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gpt_response = summarize(collated_result, summary_type="notes", user_query=q, model=model, api_key=api_key)
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else:
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gpt_response = converse(q, model, chat_session, api_key=api_key)
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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(q, metadata, gpt_response, meta_log.get('chat', []))
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return {'status': 'ok', 'response': gpt_response}
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@api_beta.on_event('shutdown')
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def shutdown_event():
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# No need to create empty log file
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if not (state.processor_config and state.processor_config.conversation and state.processor_config.conversation.meta_log):
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return
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logger.debug('INFO:\tSaving conversation logs to disk...')
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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 = get_absolute_path(state.processor_config.conversation.conversation_logfile)
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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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logger.info('INFO:\tConversation logs saved to disk.')
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