Ошибка cannot open header file

qa_chain:

qa_chain          = RetrievalQA.from_chain_type(
            llm=ChatOpenAI(
                model_name   = "gpt-4-1106-preview",               # type: ignore
                streaming    = True,
                callbacks    = [StreamingStdOutCallbackHandler()],
                temperature  = 0.55,
                max_tokens   = 550,
                model_kwargs = model_kwargs,
            ),
            chain_type              = "stuff",
            retriever               = self.get_retriever(f"{self.db_name}_{self.version}"),
            chain_type_kwargs       = chain_type_kwargs,
            return_source_documents = True,
        )

get_retriever:

def get_retriever(self, db_name):
    vectordb = self.databases.get(db_name)
    
    if vectordb:
        return MultiQueryRetriever.from_llm(
            vectordb.as_retriever(
                search_type   = "mmr",
                search_kwargs = {"k": 7, "fetch_k": 60}
            ),
            llm = ChatOpenAI(model_name='gpt-3.5-turbo-1106', temperature=0)) # type: ignore
    else:
        raise ValueError(f"Database {db_name} not found")

при вызове qa_chain получаю ошибку: cannot open header file:

llm_response  = qa_chain(input_data)

где input_data = {"query": "some text..."}

файл, где все это запускаю находится в корневой директории, вот все мои импорты:

    import json
import time
import random
import uuid
import os
import openpyxl
import nltk
import xml.etree.ElementTree as ET
import zipfile

from classes.LDA_themes import LDA_themes
from classes.Utils import Utils
from classes.RateLimiter import RateLimiter

from langchain.prompts import (
    FewShotChatMessagePromptTemplate,
    ChatPromptTemplate,
)
from langchain.embeddings import OpenAIEmbeddings
from langchain.vectorstores import Chroma
from langchain.chains import RetrievalQA
from langchain.chat_models import ChatOpenAI
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
from langchain.document_loaders import TextLoader, DirectoryLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.retrievers.multi_query import MultiQueryRetriever
from langchain.schema.output_parser import StrOutputParser

from nltk.stem import WordNetLemmatizer
from nltk.corpus import stopwords

from data import all_examples
from gensim import corpora, models
from dotenv import load_dotenv

from modules.to_excel import append_to_excel

в чем может быть проблема?


Ответы (0 шт):