Answering_Agent.py

import openai
from openai import OpenAI


class Answering_Agent:
    def __init__(self, openai_api_key) -> None:
        self.openai_client = openai
        openai.api_key = openai_api_key

    def get_document_content(self, doc_id):
        # Placeholder for retrieving document content
        return "Document content for ID " + doc_id

    def is_relevant(self, query, context_texts, history_str):
        # Simple relevance check based on keyword presence
        keywords = query.lower().split()
        context = (context_texts + " " + history_str).lower()
        return any(keyword in context for keyword in keywords)

    def generate_response(self, query, docs, conv_history, k=5, mode="chatty"):
        # Concatenate the contents of the top k relevant documents
        context_texts = "\n\n".join([f"Context {idx + 1}: {result[2]}" for idx, result in enumerate(docs)])
        history_str = "\n".join([f"{turn['role']}: {turn['content']}" for turn in conv_history]) if conv_history else ""

        print("context_texts: " + context_texts)
        # Check relevance of the context and history to the query
        relevant = self.is_relevant(query, context_texts, history_str)

        # If not relevant, return a predefined message
        if not relevant:
            return "No relevant documents found in the documents. Please ask a relevant question to the book on Machine Learning."

        # Formulate the prompt, incorporating conversation history if present
        conversation_history = f'Conversation:\n{history_str}\n' if conv_history else ''
        prompt = f"Based on the following documents{' and conversation history' if conv_history else ''}, answer the query:\nDocuments:\n{context_texts}\n{conversation_history}Query: {query}\nAnswer:"
        if mode == "chatty":
            prompt += " Please provide a detailed and comprehensive response that includes background information, relevant examples, and any important distinctions or perspectives related to the topic. Where possible, include step-by-step explanations or descriptions to ensure clarity and depth in your answer."

        # Configure max_tokens and temperature based on the specified mode
            # a longer response
        max_tokens = 3500 if mode == "chatty" else 1000
        temperature = 0.9 if mode == "chatty" else 0.5

        # generate the response
        client = OpenAI(api_key=openai.api_key)
        message = {"role": "user", "content": prompt}
        response = client.chat.completions.create(
            model="gpt-3.5-turbo",
            messages=[message],
            max_tokens=max_tokens,
            temperature=temperature,
            stop=["\n", "Query:"]
        )
        return response.choices[0].message.content