deep_research/planner_agent_JD.py

from pydantic import BaseModel, Field
from agents import Agent
from openai import AsyncOpenAI

client = AsyncOpenAI()

HOW_MANY_SEARCHES = 1

INSTRUCTIONS = f"You are a helpful research assistant. Given a query, come up with a set of web searches " \
               f"to perform to best answer the query. Output {HOW_MANY_SEARCHES} terms to query for. Start by coming up " \
               f"with up to 3 clarifying questions, if the search intent is not clear, to ask the user to help you better understand the query."


class WebSearchItem(BaseModel):
    reason: str = Field(description="Your reasoning for why this search is important to the query.")
    query: str = Field(description="The search term to use for the web search.")


class WebSearchPlan(BaseModel):
    searches: list[WebSearchItem] = Field(description="A list of web searches to perform to best answer the query.")


planner_agent = Agent(
    name="PlannerAgent",
    instructions=INSTRUCTIONS,
    model="gpt-4o-mini",
    output_type=WebSearchPlan,
)


async def get_clarification_questions(query: str) -> str:
    """Ask up to 3 clarification questions about the user's query."""
    response = await client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "system", "content": "You are an assistant that detects ambiguity in requests and asks up to 3 clarifying questions."},
            {"role": "user", "content": f"The user said: '{query}'. Ask your clarification questions if needed. If not, say: 'No clarification needed.'"}
        ]
    )
    return response.choices[0].message.content


async def refine_query_with_user_input(original: str, clarification_answer: str) -> str:
    """Refine the original query using the user's clarification answer."""
    response = await client.chat.completions.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": "You are an assistant that improves the original request using the user's clarification."},
            {"role": "user", "content": f"Original request: '{original}'\nClarification answer: '{clarification_answer}'\nRefined query:"}
        ]
    )
    return response.choices[0].message.content


## async def process_query(initial_query: str) -> WebSearchPlan:
##    """Full pipeline from initial user input to executing the planner agent."""
##    clarifications = await get_clarification_questions(initial_query)
##    if clarifications.strip().lower() != "no clarification needed.":
##        print("Clarifying questions:\n", clarifications)
##        user_answer = input("Your answer to the above: ")
##        refined_query = await refine_query_with_user_input(initial_query, user_answer)
##    else:
##        refined_query = initial_query
##
##    search_plan = await planner_agent.run(refined_query)
##    return search_plan