wehub-resource-sync
137 lines
4.8 KiB
Python
137 lines
4.8 KiB
Python
import os
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from typing import Type
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from dotenv import load_dotenv
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from pydantic import BaseModel, Field
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from linkup import LinkupClient
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from crewai import Agent, Task, Crew, Process, LLM
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from crewai.tools import BaseTool
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# Load environment variables (for non-LinkUp settings)
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load_dotenv()
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def get_llm_client():
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"""Initialize and return the LLM client"""
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return LLM(
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model="ollama/deepseek-r1:7b",
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base_url="http://localhost:11434"
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)
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# Define LinkUp Search Tool
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class LinkUpSearchInput(BaseModel):
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"""Input schema for LinkUp Search Tool."""
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query: str = Field(description="The search query to perform")
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depth: str = Field(default="standard",
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description="Depth of search: 'standard' or 'deep'")
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output_type: str = Field(
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default="searchResults", description="Output type: 'searchResults', 'sourcedAnswer', or 'structured'")
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class LinkUpSearchTool(BaseTool):
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name: str = "LinkUp Search"
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description: str = "Search the web for information using LinkUp and return comprehensive results"
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args_schema: Type[BaseModel] = LinkUpSearchInput
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def __init__(self):
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super().__init__()
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def _run(self, query: str, depth: str = "standard", output_type: str = "searchResults") -> str:
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"""Execute LinkUp search and return results."""
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try:
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# Initialize LinkUp client with API key from environment variables
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linkup_client = LinkupClient(api_key=os.getenv("LINKUP_API_KEY"))
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# Perform search
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search_response = linkup_client.search(
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query=query,
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depth=depth,
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output_type=output_type
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)
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return str(search_response)
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except Exception as e:
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return f"Error occurred while searching: {str(e)}"
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def create_research_crew(query: str):
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"""Create and configure the research crew with all agents and tasks"""
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# Initialize tools
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linkup_search_tool = LinkUpSearchTool()
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# Get LLM client
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client = get_llm_client()
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web_searcher = Agent(
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role="Web Searcher",
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goal="Find the most relevant information on the web, along with source links (urls).",
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backstory="An expert at formulating search queries and retrieving relevant information. Passes the results to the 'Research Analyst' only.",
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verbose=True,
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allow_delegation=True,
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tools=[linkup_search_tool],
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llm=client,
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)
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# Define the research analyst
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research_analyst = Agent(
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role="Research Analyst",
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goal="Analyze and synthesize raw information into structured insights, along with source links (urls) as citations.",
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backstory="An expert at analyzing information, identifying patterns, and extracting key insights. If required, can delagate the task of fact checking/verification to 'Web Searcher' only. Passes the final results to the 'Technical Writer' only.",
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verbose=True,
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allow_delegation=True,
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llm=client,
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)
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# Define the technical writer
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technical_writer = Agent(
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role="Technical Writer",
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goal="Create well-structured, clear, and comprehensive responses in markdown format, with citations/source links (urls).",
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backstory="An expert at communicating complex information in an accessible way.",
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verbose=True,
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allow_delegation=False,
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llm=client,
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)
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# Define tasks
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search_task = Task(
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description=f"Search for comprehensive information about: {query}.",
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agent=web_searcher,
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expected_output="Detailed raw search results including sources (urls).",
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tools=[linkup_search_tool]
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)
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analysis_task = Task(
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description="Analyze the raw search results, identify key information, verify facts and prepare a structured analysis.",
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agent=research_analyst,
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expected_output="A structured analysis of the information with verified facts and key insights, along with source links",
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context=[search_task]
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)
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writing_task = Task(
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description="Create a comprehensive, well-organized response based on the research analysis.",
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agent=technical_writer,
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expected_output="A clear, comprehensive response that directly answers the query with proper citations/source links (urls).",
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context=[analysis_task]
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)
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# Create the crew
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crew = Crew(
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agents=[web_searcher, research_analyst, technical_writer],
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tasks=[search_task, analysis_task, writing_task],
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verbose=True,
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process=Process.sequential
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)
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return crew
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def run_research(query: str):
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"""Run the research process and return results"""
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try:
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crew = create_research_crew(query)
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result = crew.kickoff()
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return result.raw
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except Exception as e:
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return f"Error: {str(e)}"
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