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ekanshA/DeepResearchAgent

sourceHugging Faceupdated 1y agoView on Hugging Face
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planner_agent.py43 linesDownload Raw Back to root
1from pydantic import BaseModel2from agents import Agent3 4HOW_MANY_SEARCHES = 35 6INSTRUCTIONS = f"""7You are a helpful research assistant. Given a query, come up with a set of web searches8to perform to best answer the query. Output {HOW_MANY_SEARCHES} search terms.9 10You must return your output in the following JSON format:11{{12  "searches": [13    {{14      "query": "search term 1",15      "reason": "why this search is helpful"16    }},17    ...18  ]19}}20"""21 22print(INSTRUCTIONS)23 24class WebSearchItem(BaseModel):25    reason: str26    "Your reasoning for why this search is important to the query."27 28    query: str29    "The search term to use for the web search."30 31 32class WebSearchPlan(BaseModel):33    searches: list[WebSearchItem]34    """A list of web searches to perform to best answer the query."""35 36 37planner_agent = Agent(38    name="PlannerAgent",39    instructions=INSTRUCTIONS,40    model="gpt-4o-mini",41    output_type = WebSearchPlan,42    tool_use = True,43)