// deep-research.ts — Runs web search then summarizes
const BASE = "https://www.upivia.com/api/v1";

async function research(topic: string, agentKey: string) {
  // Step 1: Search the web
  const searchRes = await fetch(`${BASE}/service-requests`, {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${agentKey}`,
      "Content-Type": "application/json",
      "Idempotency-Key": crypto.randomUUID(),
    },
    body: JSON.stringify({
      operation: "web_search.search",
      payload: { query: topic },
    }),
  });
  const searchData = await searchRes.json();
  const sources = searchData.result?.results ?? [];

  // Step 2: Summarize with LLM
  const llmRes = await fetch(`${BASE}/service-requests`, {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${agentKey}`,
      "Content-Type": "application/json",
      "Idempotency-Key": crypto.randomUUID(),
    },
    body: JSON.stringify({
      operation: "text_generation.generate",
      payload: {
        model: "openai/gpt-4o-mini",
        messages: [
          { role: "system", content: "Summarize these search results into a structured research report." },
          { role: "user", content: `Topic: ${topic}\n\nSources:\n${JSON.stringify(sources, null, 2)}` },
        ],
      },
    }),
  });
  const llmData = await llmRes.json();
  return llmData.result; // The research report
}

# cold_outreach.py — Research, draft, and send
import os, uuid, requests

BASE = "https://www.upivia.com/api/v1"
KEY = os.environ["AGENT_KEY"]
HEADERS = {"Authorization": f"Bearer {KEY}", "Content-Type": "application/json"}

def dispatch(operation, payload):
    r = requests.post(f"{BASE}/service-requests",
        headers={**HEADERS, "Idempotency-Key": str(uuid.uuid4())},
        json={"operation": operation, "payload": payload}, timeout=30)
    data = r.json()
    assert data["status"] == "executed", data
    return data["result"]

# Step 1: Research the prospect
search = dispatch("web_search.search", {"query": f"{company} {role} recent news"})
# Step 2: Draft a personalized email
email_text = dispatch("text_generation.generate", {
    "model": "openai/gpt-4o-mini",
    "messages": [
        {"role": "system", "content": "Write a concise cold email. Max 150 words."},
        {"role": "user", "content": f"Prospect: {name}, {role} at {company}\nResearch: {search}"},
    ],
})
# Step 3: Send it
dispatch("email.send", {"to": prospect_email, "subject": f"Quick question about {company}", "body": email_text["content"]})

# Schedule the entire pipeline as a workflow
curl -X POST https://www.upivia.com/api/v1/scheduled-tasks \
  -H "Authorization: Bearer upivia_pat_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "agent_id": "agt_pipeline_01...",
    "name": "Daily Sales Insights",
    "operation": "workflow.run",
    "payload": {
      "workflow_id": "wf_daily_insights",
      "input": { "csv_url": "https://api.example.com/sales.csv" }
    },
    "schedule_type": "recurring",
    "cron_expr": "0 6 * * *",
    "timezone": "America/New_York"
  }'

// pr-review.ts — Fetch, analyze, and post review
async function reviewPR(prUrl: string, agentKey: string) {
  // Step 1: Fetch the PR diff
  const diffRes = await fetch("/api/v1/service-requests", {
    method: "POST",
    headers: { "Authorization": `Bearer ${agentKey}`, "Content-Type": "application/json", "Idempotency-Key": crypto.randomUUID() },
    body: JSON.stringify({ operation: "web.fetch_url", payload: { url: `${prUrl}.diff` } }),
  });
  const diff = (await diffRes.json()).result?.content ?? "";

  // Step 2: Analyze with LLM
  const reviewRes = await fetch("/api/v1/service-requests", {
    method: "POST",
    headers: { "Authorization": `Bearer ${agentKey}`, "Content-Type": "application/json", "Idempotency-Key": crypto.randomUUID() },
    body: JSON.stringify({
      operation: "text_generation.generate",
      payload: {
        model: "anthropic/claude-3.5-sonnet",
        messages: [
          { role: "system", content: "You are a senior code reviewer. Analyze this diff for bugs, security issues, and style." },
          { role: "user", content: `PR Diff:\n\n${diff}` },
        ],
      },
    }),
  });
  const review = (await reviewRes.json()).result;

  // Step 3: Post to Slack
  await fetch("/api/v1/service-requests", {
    method: "POST",
    headers: { "Authorization": `Bearer ${agentKey}`, "Content-Type": "application/json", "Idempotency-Key": crypto.randomUUID() },
    body: JSON.stringify({
      operation: "chat.send",
      payload: { channel: "#pr-reviews", text: `*PR Review: ${prUrl}*\n\n${review.content}` },
    }),
  });
}