Research new signups

def linkup_search(
    query: str,
    output_type: str = "sourcedAnswer",
    max_results: int = 5
) -> str:
    """
    Search the web using Linkup API for fresh, trusted information.

    Args:
        query: The search query string.
        output_type: "sourcedAnswer" for natural language answer with citations.
        max_results: Maximum number of results (default 5).

    Returns:
        JSON string with search results or sourced answer with citations.
    """
    response = linkup_client.search(
        query=query,
        depth="standard",
        output_type=output_type,
        max_results=max_results,
    )
    # Process and return results...

def linkup_fetch(url: str) -> str:
    """
    Fetch and extract content from a web page URL using Linkup API.
    Use this to get detailed content from specific pages.

    Args:
        url: The fully qualified URL to fetch.

    Returns:
        JSON string with the extracted markdown content from the page.
    """
    response = linkup_client.fetch(url=url)
    # Process and return content...

AGENT_INSTRUCTIONS_TEMPLATE = """You are a research analyst who helps sales teams understand new signups.

## YOUR CLIENT'S BUSINESS

You are researching on behalf of a business with the following description:
{business_description}

## RESEARCH PROCESS

1. Search for company info (1-2 searches)
2. Search for the person's role and LinkedIn (1-2 searches)
3. Write the final report DIRECTLY as your response

## REPORT FORMAT

# Research Report: [Person Name] at [Company]

## Executive Summary
2-3 sentence overview of who this person is and what their company does.

## Company Profile
- **Company**: Name and website
- **Industry**: What they do
- **Products/Services**: Key offerings
- **Size/Funding**: If known

## Person Profile
- **Name**: Full name
- **Role**: Current position
- **Background**: Professional experience
- **LinkedIn**: URL if found

## Recommendations for Outreach
- How the client's business (described above) could help them
- Specific use cases based on their industry
- Personalization hooks from research

## Sources
- List URLs consulted
"""

@app.post("/api/research")
async def research(request: ResearchRequest, node: NodeDep):
    agent_name = f"researcher_{secrets.token_hex(4)}"

    instructions = AGENT_INSTRUCTIONS_TEMPLATE.format(
        business_description=request.business_description
    )

    agent = await Agent.start(
        node=node,
        name=agent_name,
        instructions=instructions,
        model=Model("claude-sonnet-4-5"),
        tools=[
            Tool(linkup_search),
            Tool(linkup_fetch),
            FilesystemTools(visibility="conversation"),
        ],
    )

    message = f"""Research this new signup and write a report:

    - **Name**: {request.name}
    - **Email**: {request.email}
    - **Organization**: {request.organization}
    """

    async def stream_response():
        async for response in agent.send_stream(message, timeout=300):
            yield json.dumps(response.snippet, default=json_serializer) + "\n"

    return StreamingResponse(stream_response(), media_type="application/json")

AGENT_INSTRUCTIONS_TEMPLATE = """You are a research analyst focused on technical evaluation.

## RESEARCH PROCESS

1. Search for the company's tech stack and engineering blog
2. Search for the person's technical background and GitHub
3. Identify technical challenges they might face

## REPORT FORMAT

Focus on:
- Technical infrastructure and tools they use
- Engineering team size and structure
- Open source contributions
- Technical pain points your product solves
"""

def check_company_funding(company_name: str) -> str:
    """Check recent funding rounds for a company."""
    # Implement using Crunchbase API or similar
    pass

agent = await Agent.start(
    node=node,
    name=agent_name,
    instructions=instructions,
    model=Model("claude-sonnet-4-5"),
    tools=[
        Tool(linkup_search),
        Tool(linkup_fetch),
        Tool(check_company_funding),  # Add new tool
    ],
)

# For faster responses
model=Model("claude-haiku-3-5")

# For more capable research
model=Model("claude-sonnet-4-5")

{
  "name": "Jane Doe",
  "email": "jane@example.com",
  "organization": "Example Corp",
  "business_description": "We provide cloud-based project management software."
}

{"messages": [...], "type": "conversation_snippet"}

import requests

def on_user_signup(user):
    response = requests.post(
        "https://your-zone.cluster.autonomy.computer/api/research",
        json={
            "name": user.name,
            "email": user.email,
            "organization": user.company,
            "business_description": "We provide cloud-based analytics software."
        },
        stream=True
    )
    
    # Collect the streamed response
    report = ""
    for line in response.iter_lines():
        if line:
            data = json.loads(line)
            for msg in data.get("messages", []):
                if msg.get("content", {}).get("text"):
                    report += msg["content"]["text"]
    
    # Save to your CRM, send to Slack, etc.
    save_research_report(user.id, report)