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import openai
from openai import OpenAI
from Query_Agent import extract_action
class Answering_Agent:
def __init__(self, openai_api_key) -> None:
# TODO: Initialize the Answering_Agent
# openai_api_key = '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'
self.openai_client = openai
openai.api_key = openai_api_key
def get_document_content(self, doc_id):
# This is a placeholder function, you'll need to implement the logic to retrieve the actual content.
# For example, it might query a database or an API with the document ID.
return "Document content for ID " + doc_id
def generate_response(self, query, docs, conv_history, k=5, mode="chatty"):
# TODO: Generate a response to the user's query
# Concatenate the contents of the top k relevant documents
# top_docs = docs[2][:k] # Get the top k documents based on the score
# Retrieve the content for each of the top documents
context_texts = "\n\n".join(
[f"Context {idx + 1}: {result[2]}" for idx, result in enumerate(docs)]) # Assuming result[2] is the text
print(f"context_texts is : {context_texts} \n\n\n")
# docs_content = "\n".join([self.get_document_content(doc["id"]) for doc in docs])
# Optional: Include conversation history in the prompt if provided
if conv_history:
history_str = "\n".join([f"{turn['role']}: {turn['content']}" for turn in conv_history])
prompt = f"""Based on the following documents and conversation history, answer the query:
Documents:
{context_texts}
Conversation:
{history_str}
Query: {query}
ONLY If neither Documents nor Conversation has anything to do with query, you must reply directly: No relevant documents found in the documents. Please ask a relevant question to the book on Machine Learning.
Answer: """
else:
prompt = f"Based on the following documents, answer the query:\nDocuments:\n{context_texts}\nQuery: {query}\n ONLY If Documents has nothing to do with query, you must reply directly: No relevant documents found in the documents.Please ask a relevant question to the book on Machine Learning. \nAnswer: "
# Adjust the prompt, max_tokens, and temperature based on the mode
max_tokens = 4000 if mode == "chatty" else 100
temperature = 0.9 if mode == "chatty" else 0.5
# mode of chatty
if mode == "chatty":
prompt = 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"
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
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