diff --git a/agent.py b/agent.py index 769e0c9d..dca61c9c 100644 --- a/agent.py +++ b/agent.py @@ -8,9 +8,9 @@ import threading import traceback from typing import Any +import time from datetime import date import time as record_time -import time from bs4 import BeautifulSoup from langchain.llms import OpenAI @@ -94,8 +94,8 @@ def get_chain(store, llm): return chain async def docQA(docpath, query_message, persist_db_path="db", model = "gpt-3.5-turbo"): - chatllm = ChatOpenAI(temperature=0.5, openai_api_base=os.environ.get('API_URL', None).split("chat")[0], model_name=model, openai_api_key=config.API) - embeddings = OpenAIEmbeddings(openai_api_base=os.environ.get('API_URL', None).split("chat")[0], openai_api_key=config.API) + chatllm = ChatOpenAI(temperature=0.5, openai_api_base=config.API_URL.split("chat")[0], model_name=model, openai_api_key=config.API) + embeddings = OpenAIEmbeddings(openai_api_base=config.API_URL.split("chat")[0], openai_api_key=config.API) sitemap = "sitemap.xml" match = re.match(r'^(https?|ftp)://[^\s/$.?#].[^\s]*$', docpath) @@ -134,7 +134,7 @@ def get_doc_from_url(url): return filename def persist_emdedding_pdf(docurl, persist_db_path): - embeddings = OpenAIEmbeddings(openai_api_base=os.environ.get('API_URL', None).split("chat")[0], openai_api_key=os.environ.get('API', None)) + embeddings = OpenAIEmbeddings(openai_api_base=config.API_URL.split("chat")[0], openai_api_key=os.environ.get('API', None)) filename = get_doc_from_url(docurl) docpath = os.getcwd() + "/" + filename loader = UnstructuredPDFLoader(docpath) @@ -149,8 +149,8 @@ def persist_emdedding_pdf(docurl, persist_db_path): return vector_store async def pdfQA(docurl, docpath, query_message, model="gpt-3.5-turbo"): - chatllm = ChatOpenAI(temperature=0.5, openai_api_base=os.environ.get('API_URL', None).split("chat")[0], model_name=model, openai_api_key=os.environ.get('API', None)) - embeddings = OpenAIEmbeddings(openai_api_base=os.environ.get('API_URL', None).split("chat")[0], openai_api_key=os.environ.get('API', None)) + chatllm = ChatOpenAI(temperature=0.5, openai_api_base=config.API_URL.split("chat")[0], model_name=model, openai_api_key=os.environ.get('API', None)) + embeddings = OpenAIEmbeddings(openai_api_base=config.API_URL.split("chat")[0], openai_api_key=os.environ.get('API', None)) persist_db_path = getmd5(docpath) if not os.path.exists(persist_db_path): vector_store = persist_emdedding_pdf(docurl, persist_db_path) @@ -162,8 +162,8 @@ async def pdfQA(docurl, docpath, query_message, model="gpt-3.5-turbo"): return result['result'] def pdf_search(docurl, query_message, model="gpt-3.5-turbo"): - chatllm = ChatOpenAI(temperature=0.5, openai_api_base=os.environ.get('API_URL', None).split("chat")[0], model_name=model, openai_api_key=os.environ.get('API', None)) - embeddings = OpenAIEmbeddings(openai_api_base=os.environ.get('API_URL', None).split("chat")[0], openai_api_key=os.environ.get('API', None)) + chatllm = ChatOpenAI(temperature=0.5, openai_api_base=config.API_URL.split("chat")[0], model_name=model, openai_api_key=os.environ.get('API', None)) + embeddings = OpenAIEmbeddings(openai_api_base=config.API_URL.split("chat")[0], openai_api_key=os.environ.get('API', None)) filename = get_doc_from_url(docurl) docpath = os.getcwd() + "/" + filename loader = UnstructuredPDFLoader(docpath) @@ -280,8 +280,8 @@ def search_summary(result, model=config.DEFAULT_SEARCH_MODEL, temperature=config search_thread.start() chainStreamHandler = ChainStreamHandler() - chatllm = ChatOpenAI(streaming=True, callback_manager=CallbackManager([chainStreamHandler]), temperature=temperature, openai_api_base=os.environ.get('API_URL', None).split("chat")[0], model_name=model, openai_api_key=config.API) - chainllm = ChatOpenAI(temperature=temperature, openai_api_base=os.environ.get('API_URL', None).split("chat")[0], model_name=model, openai_api_key=config.API) + chatllm = ChatOpenAI(streaming=True, callback_manager=CallbackManager([chainStreamHandler]), temperature=temperature, openai_api_base=config.API_URL.split("chat")[0], model_name=model, openai_api_key=config.API) + chainllm = ChatOpenAI(temperature=temperature, openai_api_base=config.API_URL.split("chat")[0], model_name=model, openai_api_key=config.API) if use_gpt: gpt_search_thread = ThreadWithReturnValue(target=gptsearch, args=(result, chainllm,)) @@ -426,17 +426,17 @@ def search_summary(result, model=config.DEFAULT_SEARCH_MODEL, temperature=config # # for i in search_summary("2022年俄乌战争为什么发生？"): # # for i in search_summary("卡罗尔与星期二讲的啥？"): # # for i in search_summary("金砖国家会议有哪些决定？"): - # # for i in search_summary("iphone15有哪些新功能？"): + # for i in search_summary("iphone15有哪些新功能？"): # # for i in search_summary("python函数开头：def time(text: str) -> str:每个部分有什么用？"): - # print(i, end="") + # print(i, end="") # 问答 # result = asyncio.run(docQA("/Users/yanyuming/Downloads/GitHub/wiki/docs", "ubuntu 版本号怎么看？")) # result = asyncio.run(docQA("https://yym68686.top", "说一下HSTL pipeline")) - # result = asyncio.run(docQA("https://wiki.yym68686.top", "PyTorch to MindSpore翻译思路是什么？")) - # print(result['answer']) - result = asyncio.run(pdfQA("https://api.telegram.org/file/bot5569497961:AAHobhUuydAwD8SPkXZiVFybvZJOmGrST_w/documents/file_1.pdf", "HSTL的pipeline详细讲一下")) - print(result) + result = asyncio.run(docQA("https://wiki.yym68686.top", "PyTorch to MindSpore翻译思路是什么？")) + print(result['answer']) + # result = asyncio.run(pdfQA("https://api.telegram.org/file/bot5569497961:AAHobhUuydAwD8SPkXZiVFybvZJOmGrST_w/documents/file_1.pdf", "HSTL的pipeline详细讲一下")) + # print(result) # source_url = set([i.metadata['source'] for i in result["source_documents"]]) # source_url = "\n".join(source_url) # message = ( diff --git a/config.py b/config.py index f8228379..b76ed35d 100644 --- a/config.py +++ b/config.py @@ -1,6 +1,6 @@ import os -WEB_HOOK = os.environ["WEB_HOOK"] -BOT_TOKEN = os.environ["BOT_TOKEN"] +WEB_HOOK = os.environ.get('WEB_HOOK', None) +BOT_TOKEN = os.environ.get('BOT_TOKEN', None) PORT = int(os.environ.get('PORT', '8080')) NICK = os.environ.get('NICK', None) API = os.environ.get('API', None)