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// ============================================================================
// OPENAI INTEGRATION (40 lines)
// ============================================================================
async function callOpenAI(prompt: string): Promise<SimpleAnalysisResult> {
  const requestBody = {
    model: 'gpt-4o-mini',
  };
  // Log the full request being sent to OpenAI
  console.log('=== OPENAI REQUEST BEING SENT ===');
  console.log('Model:', requestBody.model);
  console.log('Max completion tokens:', requestBody.max_completion_tokens);
  console.log('Response format:', requestBody.response_format);
  console.log('=== PROMPT BEING SENT TO OPENAI ===');
  console.log(prompt);
  console.log('=== END PROMPT ===');
  console.log('Request body size (chars):', JSON.stringify(requestBody).length);
  console.log('=== END OPENAI REQUEST ===');
  const response = await fetch('https://api.openai.com/v1/chat/completions', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${Deno.env.get('OPENAI_API_KEY')}`,
      'Content-Type': 'application/json'
    },
  if (!response.ok) {
    throw new Error(`OpenAI API error: ${response.status} - ${response.statusText}`);
  }
  const content = data.choices[0].message.content;
  
  // Log the response from OpenAI
  console.log('=== OPENAI RESPONSE RECEIVED ===');
  console.log('Usage:', data.usage);
  console.log('Model used:', data.model);
  console.log('Response content length:', content?.length || 0);
  console.log('=== OPENAI RESPONSE CONTENT ===');
  console.log(content);
  console.log('=== END OPENAI RESPONSE ===');
  
  try {
    return JSON.parse(content);
  } catch (error) {
    console.error('Failed to parse OpenAI response:', content);
    throw new Error('Invalid JSON response from OpenAI');
  }
}
    const prompt = buildAnalysisPrompt(teamStats, roster);
    
    console.log('Calling OpenAI for enhanced analysis...');
    
    // Get AI analysis
    const analysis = await callOpenAI(prompt);
    
    console.log(`Analysis complete. Grade: ${analysis.overall_grade}, Recommendations: ${analysis.waiver_recommendations.length}`);

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" },

export default async function server(request: Request): Promise<Response> {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const openai = new OpenAI();
  if (request.method === "POST" && new URL(request.url).pathname === "/chat") {
      async start(controller) {
        try {
          const chatCompletion = await openai.chat.completions.create({
            model: "gpt-4o",
            messages: [
          }
        } catch (error) {
          console.error("OpenAI Error:", error);
          controller.enqueue(
            new TextEncoder().encode(

export default async function server(request: Request): Promise<Response> {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const openai = new OpenAI();
  if (request.method === "POST" && new URL(request.url).pathname === "/chat") {
      async start(controller) {
        try {
          const chatCompletion = await openai.chat.completions.create({
            model: "gpt-4o",
            messages: [
          }
        } catch (error) {
          console.error("OpenAI Error:", error);
          controller.enqueue(
            new TextEncoder().encode(

export default async function server(request: Request): Promise<Response> {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const openai = new OpenAI();
  if (request.method === "POST" && new URL(request.url).pathname === "/chat") {
      async start(controller) {
        try {
          const chatCompletion = await openai.chat.completions.create({
            model: "gpt-4o",
            messages: [
          }
        } catch (error) {
          console.error("OpenAI Error:", error);
          controller.enqueue(
            new TextEncoder().encode(

export default async function server(request: Request): Promise<Response> {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const openai = new OpenAI();
  if (request.method === "POST" && new URL(request.url).pathname === "/chat") {
      async start(controller) {
        try {
          const chatCompletion = await openai.chat.completions.create({
            model: "gpt-4o",
            messages: [
          }
        } catch (error) {
          console.error("OpenAI Error:", error);
          controller.enqueue(
            new TextEncoder().encode(

export default async function server(request: Request): Promise<Response> {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const openai = new OpenAI();
  if (request.method === "POST" && new URL(request.url).pathname === "/chat") {
      async start(controller) {
        try {
          const chatCompletion = await openai.chat.completions.create({
            model: "gpt-4o",
            messages: [
          }
        } catch (error) {
          console.error("OpenAI Error:", error);
          controller.enqueue(
            new TextEncoder().encode(

export default async function server(request: Request): Promise<Response> {
  const { OpenAI } = await import("https://esm.town/v/std/openai");
  const openai = new OpenAI();
  if (request.method === "POST" && new URL(request.url).pathname === "/chat") {
      async start(controller) {
        try {
          const chatCompletion = await openai.chat.completions.create({
            model: "gpt-4o",
            messages: [
          }
        } catch (error) {
          console.error("OpenAI Error:", error);
          controller.enqueue(
            new TextEncoder().encode(