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import { discordWebhook } from "https://esm.town/v/stevekrouse/discordWebhook";
import { Octokit } from "npm:octokit";
import { OpenAI } from "https://esm.town/v/std/openai";
// Environment variables, set them in the left sidebar
 */
async function generateUserFocusedSummary(fullCommitMessage: string, commitType: string): Promise<string> {
  const openai = new OpenAI();
  
  const prompt = `You are writing release notes for a developer tool. Based on this commit message, write a concise one-liner.
  try {
    const completion = await openai.chat.completions.create({
      messages: [{ role: "user", content: prompt }],
      model: "gpt-4o-mini",

Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
### OpenAI
```ts
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
  messages: [
    { role: "user", content: "Say hello in a creative way" },

Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
### OpenAI
```ts
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
  messages: [
    { role: "user", content: "Say hello in a creative way" },

Configure the following variables in your environment: 
- `AGENT_API_KEY` (This is a secure token that you choose to secure the agent.tsx POST endpoint)
- `OPENAI_API_KEY` (An OpenAI API Key)
- `EXA_API_KEY` (Optional, though needed if you use the web search tool)

import { anthropic } from "npm:@ai-sdk/anthropic";
import { openai } from "npm:@ai-sdk/openai";
import { generateText, streamText } from "npm:ai";
import { getSystemPrompt } from "./prompt.tsx";
  const maxSteps = 10;
  const model = Deno.env.get("ANTHROPIC_API_KEY") ? anthropic("claude-3-7-sonnet-latest") : openai("gpt-4.1");
  const options = {

Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
### OpenAI
```ts
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
  messages: [
    { role: "user", content: "Say hello in a creative way" },

Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
### OpenAI
```ts
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
  messages: [
    { role: "user", content: "Say hello in a creative way" },

Note: When changing a SQLite table's schema, change the table's name (e.g., add _2 or _3) to create a fresh table.
### OpenAI
```ts
import { OpenAI } from "https://esm.town/v/std/openai";
const openai = new OpenAI();
const completion = await openai.chat.completions.create({
  messages: [
    { role: "user", content: "Say hello in a creative way" },

// --- Main Request Handler (Server Code - MODIFIED) ---
export default async function(req: Request) {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const { fetch } = await import("https://esm.town/v/std/fetch");
  // PDFExtract is kept if you want to add document features later, but not primary for this use case.
  const action = url.searchParams.get("action"); // New: "loanAssumptionInfo"
  const sourceUrl = import.meta.url.replace("esm.town", "val.town");
  const openai = new OpenAI();
  const MAX_TEXT_LENGTH_ANALYSIS = 10000; // Reduced as input is smaller now
  }
  // callOpenAI function (same as original, but uses gpt-4o by default)
  async function callOpenAI(
    openaiInstance: OpenAI,
    systemPrompt: string,
    userMessage: string, // For this app, userMessage to AI might be empty if all info is in systemPrompt
  ): Promise<object | string> {
    // ... (implementation from original)
    log.push({ agent: agentName, type: "step", message: `Calling OpenAI model ${model}...` });
    try {
      const response = await openaiInstance.chat.completions.create({
        model: model,
        messages: [{ role: "system", content: systemPrompt }, { role: "user", content: userMessage }],
        .replace("%%USER_NAME%%", analysisInput.userName);
      // The %%INPUT_SOURCE_DESCRIPTION%% and %%LEGAL_TASK_QUERY%% are not in the new prompt in this direct way.
      // The userMessage to openAI can be kept minimal or empty as the system prompt is rich.
      const userMessageForAI = ""; // Or analysisInput.documentText if you want to provide more context there.
      const analysisAgentName = "HomeAdvantage AI";
      const aiResponse = await callOpenAI(
        openai,
        finalSystemPrompt,
        userMessageForAI,

}
export default async function(req: Request) {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const { fetch } = await import("https://esm.town/v/std/fetch");
  const { PDFExtract, PDFExtractOptions } = await import("npm:pdf.js-extract");
  const action = url.searchParams.get("action");
  const sourceUrl = import.meta.url.replace("esm.town", "val.town");
  const openai = new OpenAI();
  const MAX_TEXT_LENGTH_SUGGESTION = 20000;
  const MAX_TEXT_LENGTH_ANALYSIS = 30000;
    }
  }
  async function callOpenAI(
    openaiInstance: OpenAI,
    systemPrompt: string,
    userMessage: string,
    agentName: string,
  ): Promise<object | string> {
    log.push({ agent: agentName, type: "step", message: `Calling OpenAI model ${model}...` });
    try {
      const response = await openaiInstance.chat.completions.create({
        model: model,
        messages: [{ role: "system", content: systemPrompt }, { role: "user", content: userMessage }],
    );
    const suggestionAgentName = "Task Suggestion AI";
    const suggestionsResponse = await callOpenAI(
      openai,
      suggestionPrompt,
      "",
      );
      const analysisAgentName = "Legal Analysis AI";
      const aiResponse = await callOpenAI(
        openai,
        finalSystemPrompt,
        documentTextToAnalyze,