4.3강의: Bad Request 오류 발생

llm.py 코드도 올려드립니다 import streamlit as stfrom dotenv import load_dotenv#환경 변수 로드from langchain_upstage import ChatUpstage from langchain_upstage import UpstageEmbeddings #vector 공간 활용from langchain_pinecone import PineconeVectorStore # pinecone 데이터베이스from pinecone import Pinecone, ServerlessSpecfrom langchain.chains import RetrievalQA #답변 생성을 위해 LLM에 전달from langchain_core.output_parsers import StrOutputParserfrom langchain_core.prompts import ChatPromptTemplatefrom langchain.chains import create_history_aware_retrieverfrom langchain_core.prompts import MessagesPlaceholderfrom langchain.chains import create_retrieval_chainfrom langchain.chains.combine_documents import create_stuff_documents_chainfrom langchain_community.chat_message_histories import ChatMessageHistoryfrom langchain_core.chat_history import BaseChatMessageHistoryfrom langchain_core.runnables.history import RunnableWithMessageHistorystore = {}def get_session_history(session_id: str) -> BaseChatMessageHistory: if session_id not in store: store[session_id] = ChatMessageHistory() return store[session_id]def get_retriever(): embedding = UpstageEmbeddings(model='solar-embedding-1-large')#OpenAI에서 제공하는 Embedding Model을 활용해서 chunk를 vector화 index_name = "tax-markdown" database = PineconeVectorStore.from_existing_index(index_name=index_name, embedding=embedding)# 이미 생성된 데이터베이스를 사용할때 #retriever = database.similarity_search(query, k=3) retriever = database.as_retriever(search_kwargs={'k':4}) return retrieverdef get_llm(model='solar-embedding-1-large'): llm = ChatUpstage(model=model) return llm def get_dictionary_chain(): dictionary = ["사람을 나타내는 표현 -> 거주자"] llm = get_llm() prompt = ChatPromptTemplate.from_template(f""" 사용자의 질문을 보고, 우리의 사전을 참고해서 사용자의 질문을 변경해주세요. 만약 변경할 필요가 없다고 판단된다면, 사용자의 질문을 변경하지 않아도 됩니다. 그런 경우에는 질문만 리턴해주세요 사전: {dictionary} 질문: {{question}} """) dictionary_chain = prompt | llm | StrOutputParser() return dictionary_chaindef get_rag_chain(): llm=get_llm() retriever=get_retriever() contextualize_q_system_prompt = ( "Given a chat history and the latest user question " "which might reference context in the chat history, " "formulate a standalone question which can be understood " "without the chat history. Do NOT answer the question, " "just reformulate it if needed and otherwise return it as is." ) contextualize_q_prompt = ChatPromptTemplate.from_messages( [ ("system", contextualize_q_system_prompt), MessagesPlaceholder("chat_history"), ("human", "{input}"), ] ) history_aware_retriever = create_history_aware_retriever( llm, retriever, contextualize_q_prompt ) system_prompt = ( "You are an assistant for question-answering tasks. " "Use the following pieces of retrieved context to answer " "the question. If you don't know the answer, say that you " "don't know. Use three sentences maximum and keep the " "answer concise." "\n\n" "{context}" ) qa_prompt = ChatPromptTemplate.from_messages( [ ("system", system_prompt), MessagesPlaceholder("chat_history"), ("human", "{input}"), ] ) question_answer_chain = create_stuff_documents_chain(llm, qa_prompt) rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain) conversational_rag_chain = RunnableWithMessageHistory( rag_chain, get_session_history, input_messages_key="input", history_messages_key="chat_history", output_messages_key="answer", ).pick('answer') return conversational_rag_chaindef get_ai_response(user_message): dictionary_chain = get_dictionary_chain() rag_chain = get_rag_chain() tax_chain = {"input": dictionary_chain} | rag_chain ai_response = tax_chain.stream( { "question": user_message }, config={ "configurable": {"session_id": "abc123"} }, ) return ai_response #return ai_message["answer"]

4.3강의: Bad Request 오류 발생

BadRequestError: Bad RequestTraceback:File "C:\Users\leehonggi\anaconda3\Lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 542, in _run_script exec(code, module.__dict__)File "C:\Users\leehonggi\pythonwin\2024\chat.py", line 37, in ai_message = st.write_stream(ai_response) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\streamlit\runtime\metrics_util.py", line 397, in wrapped_func result = non_optional_func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\streamlit\elements\write.py", line 159, in write_stream for chunk in stream: # type: ignoreFile "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 3262, in stream yield from self.transform(iter([input]), config, **kwargs)File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 3249, in transform yield from self._transform_stream_with_config(File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 2054, in _transform_stream_with_config chunk: Output = context.run(next, iterator) # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 3211, in _transform for output in final_pipeline:File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\passthrough.py", line 765, in transform yield from self._transform_stream_with_config(File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 2018, in _transform_stream_with_config final_input: Optional[Input] = next(input_for_tracing, None) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 5301, in transform yield from self.bound.transform(File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 5301, in transform yield from self.bound.transform(File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 3249, in transform yield from self._transform_stream_with_config(File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 2018, in _transform_stream_with_config final_input: Optional[Input] = next(input_for_tracing, None) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 3700, in transform yield from self._transform_stream_with_config(File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 2054, in _transform_stream_with_config chunk: Output = context.run(next, iterator) # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 3685, in _transform chunk = AddableDict({step_name: future.result()}) ^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\concurrent\futures\_base.py", line 449, in result return self.__get_result() ^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\concurrent\futures\_base.py", line 401, in __get_result raise self._exceptionFile "C:\Users\leehonggi\anaconda3\Lib\concurrent\futures\thread.py", line 58, in run result = self.fn(*self.args, **self.kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 3249, in transform yield from self._transform_stream_with_config(File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 2054, in _transform_stream_with_config chunk: Output = context.run(next, iterator) # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 3211, in _transform for output in final_pipeline:File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\output_parsers\transform.py", line 65, in transform yield from self._transform_stream_with_config(File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 2018, in _transform_stream_with_config final_input: Optional[Input] = next(input_for_tracing, None) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\runnables\base.py", line 1290, in transform yield from self.stream(final, config, **kwargs)File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\language_models\chat_models.py", line 425, in stream raise eFile "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_core\language_models\chat_models.py", line 405, in stream for chunk in self._stream(messages, stop=stop, **kwargs):File "C:\Users\leehonggi\anaconda3\Lib\site-packages\langchain_openai\chat_models\base.py", line 558, in _stream response = self.client.create(**payload) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\openai\_utils\_utils.py", line 274, in wrapper return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\openai\resources\chat\completions.py", line 668, in create return self._post( ^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\openai\_base_client.py", line 1259, in post return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\openai\_base_client.py", line 936, in request return self._request( ^^^^^^^^^^^^^^File "C:\Users\leehonggi\anaconda3\Lib\site-packages\openai\_base_client.py", line 1040, in _request raise self._make_status_error_from_response(err.response) from None

덧글 결과가 20개만 출력이 되는데요

해결하셨나용??