ai-ml-integration

AI/ML Integration

Overview

Integrating AI and machine learning capabilities into applications, including LLM APIs, embeddings, and RAG patterns.

LLM Integration

OpenAI API

import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
});

// Chat completion
async function chat(messages: Array<{ role: string; content: string }>) {
  const response = await openai.chat.completions.create({
    model: 'gpt-4o',
    messages,
    temperature: 0.7,
    max_tokens: 1000,
  });

  return response.choices[0].message.content;
}

// Streaming response
async function* streamChat(prompt: string) {
  const stream = await openai.chat.completions.create({
    model: 'gpt-4o',
    messages: [{ role: 'user', content: prompt }],
    stream: true,
  });

  for await (const chunk of stream) {
    const content = chunk.choices[0]?.delta?.content;
    if (content) {
      yield content;
    }
  }
}

// Function calling
async function chatWithTools(message: string) {
  const tools = [
    {
      type: 'function' as const,
      function: {
        name: 'get_weather',
        description: 'Get current weather for a location',
        parameters: {
          type: 'object',
          properties: {
            location: { type: 'string', description: 'City name' },
            unit: { type: 'string', enum: ['celsius', 'fahrenheit'] },
          },
          required: ['location'],
        },
      },
    },
  ];

  const response = await openai.chat.completions.create({
    model: 'gpt-4o',
    messages: [{ role: 'user', content: message }],
    tools,
    tool_choice: 'auto',
  });

  const toolCall = response.choices[0].message.tool_calls?.[0];
  if (toolCall) {
    const args = JSON.parse(toolCall.function.arguments);
    // Execute the function
    const result = await executeFunction(toolCall.function.name, args);

    // Continue conversation with function result
    return openai.chat.completions.create({
      model: 'gpt-4o',
      messages: [
        { role: 'user', content: message },
        response.choices[0].message,
        {
          role: 'tool',
          tool_call_id: toolCall.id,
          content: JSON.stringify(result),
        },
      ],
    });
  }

  return response;
}