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| import chainlit as cl | |
| from llama_index.llms import MonsterLLM | |
| from llama_index import VectorStoreIndex,SimpleDirectoryReader, ServiceContext | |
| def indexing(llm,path=None): | |
| if path==None: | |
| path="data.txt" | |
| documents = SimpleDirectoryReader(input_files=[path]).load_data() | |
| print("loading done") | |
| service_context = ServiceContext.from_defaults( | |
| chunk_size=1024, llm=llm, embed_model="local:BAAI/bge-small-en-v1.5" | |
| ) | |
| print("indexing") | |
| index = VectorStoreIndex.from_documents(documents, service_context=service_context, use_async=True) | |
| query_engine = index.as_query_engine() | |
| print("all done") | |
| print(query_engine) | |
| return query_engine | |
| def qa(sp,engine,message): | |
| message=message.content | |
| ques=sp+" "+message | |
| response=engine.query(ques) | |
| return response | |
| async def factory(): | |
| url = await cl.AskUserMessage(author="Beast",content="Enter url").send() | |
| print(url) | |
| if url['output'][-1]=="/": | |
| url['output']=url['output'].replace(".ai/",".ai") | |
| auth = await cl.AskUserMessage(author="Beast",content="Enter auth token").send() | |
| print(auth) | |
| model = 'deploy-llm' | |
| llm = MonsterLLM(model=model,base_url=url['output'],monster_api_key=auth['output'],temperature=0.75, context_window=1024) | |
| cl.user_session.set("llm", llm) | |
| # files = None | |
| # while files is None: | |
| # files = await cl.AskFileMessage(author="Beast", | |
| # content="Please upload a PDF file to begin!", | |
| # accept=["application/pdf"], | |
| # max_size_mb=20, | |
| # timeout=180, | |
| # ).send() | |
| # pdf = files[0] | |
| # print(pdf) | |
| res = await cl.AskActionMessage(author="Beast", | |
| content="Do you want to enter system prompt?", | |
| actions=[ | |
| cl.Action(name="yes", value="yes", label="✅ Yes"), | |
| cl.Action(name="no", value="no", label="❌ No"), | |
| ], | |
| ).send() | |
| query_engine = await cl.make_async(indexing)(llm) | |
| if res and res.get("value") == "yes": | |
| sp = await cl.AskUserMessage(author="Beast",content="Enter system prompt").send() | |
| await cl.Message(author="Beast",content="Noted. Go ahead as your questions!!").send() | |
| cl.user_session.set("sp", sp["output"]) | |
| else: | |
| await cl.Message(author="Beast",content="Okay, then you can start asking your questions!!").send() | |
| cl.user_session.set("engine", query_engine) | |
| async def main(message: cl.Message): | |
| engine = cl.user_session.get("engine") | |
| llm=cl.user_session.get("llm") | |
| sp=cl.user_session.get("sp") | |
| if sp==None: | |
| sp="" | |
| if not message.elements: | |
| msg = cl.Message(author="Beast",content=f"Processing...", disable_feedback=False) | |
| await msg.send() | |
| response =await cl.make_async(qa)(sp,engine,message) | |
| print(response) | |
| msg.content = str(response) | |
| await msg.update() | |
| elif message.elements: | |
| go=True | |
| for file in message.elements: | |
| if "pdf" in file.mime: | |
| pdf=file | |
| else: | |
| await cl.Message(author="Beast",content="We only support PDF for now").send() | |
| go=False | |
| break | |
| if go: | |
| msg = cl.Message(author="Beast",content=f"Processing `{pdf.name}`...") | |
| await msg.send() | |
| query_engine = await cl.make_async(indexing)(llm,pdf.path) | |
| msg.content = f"`{pdf.name}` processed." | |
| await msg.update() | |
| response =await cl.make_async(qa)(sp,query_engine,message) | |
| print(response) | |
| msg.content = str(response) | |
| msg.author="Beast" | |
| await msg.send() | |