Initial commit

templates/code-interpreter-assistant.ts

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+/**
+ * Code Interpreter Assistant
+ *
+ * Demonstrates:
+ * - Python code execution
+ * - File uploads for data analysis
+ * - Retrieving generated files (charts, CSVs)
+ * - Data visualization
+ */
+
+import OpenAI from 'openai';
+import fs from 'fs';
+
+const openai = new OpenAI({
+  apiKey: process.env.OPENAI_API_KEY,
+});
+
+async function main() {
+  console.log('📊 Creating Data Analyst Assistant...\n');
+
+  // 1. Create assistant with code interpreter
+  const assistant = await openai.beta.assistants.create({
+    name: "Data Analyst",
+    instructions: "You are a data analyst. Analyze data and create visualizations. Always explain your approach and findings.",
+    tools: [{ type: "code_interpreter" }],
+    model: "gpt-4o",
+  });
+
+  console.log(`✅ Assistant created: ${assistant.id}\n`);
+
+  // 2. Upload a data file (CSV example)
+  // For this example, create a sample CSV
+  const csvData = `date,revenue,expenses
+2025-01-01,10000,4000
+2025-01-02,12000,4500
+2025-01-03,9500,4200
+2025-01-04,15000,5000
+2025-01-05,13500,4800`;
+
+  fs.writeFileSync('sample_data.csv', csvData);
+
+  const file = await openai.files.create({
+    file: fs.createReadStream('sample_data.csv'),
+    purpose: 'assistants',
+  });
+
+  console.log(`✅ File uploaded: ${file.id}\n`);
+
+  // 3. Create thread with file attachment
+  const thread = await openai.beta.threads.create({
+    messages: [{
+      role: "user",
+      content: "Analyze this revenue data. Calculate total revenue, average daily revenue, and create a visualization showing revenue and expenses over time.",
+      attachments: [{
+        file_id: file.id,
+        tools: [{ type: "code_interpreter" }],
+      }],
+    }],
+  });
+
+  console.log(`✅ Thread created: ${thread.id}\n`);
+
+  // 4. Run the assistant
+  console.log('🏃 Running analysis...\n');
+  const run = await openai.beta.threads.runs.create(thread.id, {
+    assistant_id: assistant.id,
+  });
+
+  // 5. Poll for completion
+  let runStatus = await openai.beta.threads.runs.retrieve(thread.id, run.id);
+
+  while (!['completed', 'failed', 'cancelled'].includes(runStatus.status)) {
+    await new Promise(resolve => setTimeout(resolve, 1000));
+    runStatus = await openai.beta.threads.runs.retrieve(thread.id, run.id);
+    console.log(`   Status: ${runStatus.status}`);
+  }
+
+  if (runStatus.status !== 'completed') {
+    console.error(`❌ Run ${runStatus.status}:`, runStatus.last_error);
+    process.exit(1);
+  }
+
+  console.log('\n✅ Analysis completed!\n');
+
+  // 6. Retrieve the response
+  const messages = await openai.beta.threads.messages.list(thread.id);
+  const responseMessage = messages.data[0];
+
+  console.log('💬 Analysis Results:\n');
+
+  for (const content of responseMessage.content) {
+    if (content.type === 'text') {
+      console.log(content.text.value);
+      console.log('\n---\n');
+    }
+
+    // Download generated image files (charts)
+    if (content.type === 'image_file') {
+      const imageFileId = content.image_file.file_id;
+      console.log(`📈 Chart generated: ${imageFileId}`);
+
+      // Download the image
+      const imageData = await openai.files.content(imageFileId);
+      const imageBuffer = Buffer.from(await imageData.arrayBuffer());
+
+      fs.writeFileSync(`chart_${imageFileId}.png`, imageBuffer);
+      console.log(`   Saved as: chart_${imageFileId}.png\n`);
+    }
+  }
+
+  // 7. Check run steps to see code that was executed
+  const runSteps = await openai.beta.threads.runs.steps.list(thread.id, run.id);
+
+  console.log('🔍 Execution Steps:\n');
+  for (const step of runSteps.data) {
+    if (step.step_details.type === 'tool_calls') {
+      for (const toolCall of step.step_details.tool_calls) {
+        if (toolCall.type === 'code_interpreter') {
+          console.log('Python code executed:');
+          console.log(toolCall.code_interpreter.input);
+          console.log('\nOutput:');
+          console.log(toolCall.code_interpreter.outputs);
+          console.log('\n---\n');
+        }
+      }
+    }
+  }
+
+  // Cleanup
+  fs.unlinkSync('sample_data.csv');
+
+  console.log('\n📊 Usage:');
+  console.log(`   Total tokens: ${runStatus.usage?.total_tokens}`);
+}
+
+main().catch(console.error);