answer_question.py

from utils import get_embedding
from flask import jsonify
from config import *

import openai
import pdb

from config import *

TOP_K = 10


def get_answer_from_files(question,  botName, pinecone_index):
    logging.info(f"Getting answer for question: {question}")
    # pdb.set_trace()
    search_query_embedding = get_embedding(question, EMBEDDINGS_MODEL)
    try:
        query_response = pinecone_index.query(
            namespace=botName,
            top_k=TOP_K,
            include_values=True,
            include_metadata=True,
            vector=search_query_embedding
        )
        logging.info(
            f"[get_answer_from_files] received query response from Pinecone: {query_response}")

        files_string = ""
        # file_text_dict = current_app.config["file_text_dict"]

        for i in range(len(query_response.matches)):
            result = query_response.matches[i]
            # pdb.set_trace()
            file_chunk_id = result.id
            score = result.score
            filename = result.metadata["filename"]
            # file_text = file_text_dict.get(file_chunk_id)
            file_text = result.metadata["text_chunk"]
            COSINE_SIM_THRESHOLD = 0.9
            file_string = f"###\n\"{filename}\"\n{file_text}\n"
            # pdb.set_trace()
            if score < COSINE_SIM_THRESHOLD and i > 0:
                logging.info(
                    f"[get_answer_from_files] score {score} is below threshold {COSINE_SIM_THRESHOLD} and i is {i}, breaking")
                break
            files_string += file_string
        prompt = f"Given a question, try to answer it using the content of the file extracts below, and if you cannot answer, or find " \
            f"a relevant file, just output \"I couldn't find the answer to that question in your files.\".\n\n" \
            f"If the answer is not contained in the files or if there are no file extracts, respond with \"I couldn't find the answer " \
            f"to that question in your files.\" If the question is not actually a question, respond with \"That's not a valid question.\"\n\n" \
            f"In the cases where you can find the answer, first give the answer." \
            f"Give the answer in markdown format." \
            f"Use the following format:\n\nQuestion: <question>\n\nFiles:\n<###\n\"filename 1\"\nfile text>\n<###\n\"filename 2\"\nfile text>...\n\n"\
            f"Answer: <answer or \"I couldn't find the answer to that question in your files\" or \"That's not a valid question.\">\n\n" \
            f"Question: {question}\n\n" \
            f"Files:\n{files_string}\n" \
            f"Answer:"
        # pdb.set_trace()
        logging.info(f"[get_answer_from_files] prompt: {prompt}")

        response = openai.Completion.create(
            prompt=prompt,
            temperature=0,
            max_tokens=800,
            top_p=1,
            frequency_penalty=0,
            presence_penalty=0,
            engine=GENERATIVE_MODEL,
        )

        answer = response.choices[0].text.strip()

        logging.info(f"[get_answer_from_files] answer: {answer}")

        return jsonify({"answer": answer})

    except Exception as e:
        logging.info(f"[get_answer_from_files] error: {e}")
        return str(e)