Python Examples

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Complete Python guide for GMTech's API using the OpenAI library.

Installation

pip install openai

Basic Setup

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://app.gmtech.com/api/v1",
    api_key=os.getenv("GMTECH_API_KEY")
)

Simple Chat

response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is Python?"}
    ]
)

print(response.choices[0].message.content)

Try Different Models

# OpenAI
response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[{"role": "user", "content": "Hello!"}]
)

# Claude
response = client.chat.completions.create(
    model="claude-3-5-sonnet-20241022",
    messages=[{"role": "user", "content": "Hello!"}]
)

# Gemini
response = client.chat.completions.create(
    model="gemini-1.5-pro",
    messages=[{"role": "user", "content": "Hello!"}]
)

Streaming

stream = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[{"role": "user", "content": "Tell me a story"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Error Handling

from openai import APIError, AuthenticationError, RateLimitError
import time

try:
    response = client.chat.completions.create(
        model="gpt-4-turbo",
        messages=[{"role": "user", "content": "Hello"}]
    )
except AuthenticationError:
    print("Invalid API key")
except RateLimitError:
    print("Rate limit exceeded")
    time.sleep(2)  # Wait and retry
except APIError as e:
    print(f"API error: {e}")

Flask Web App Example

from flask import Flask, request, jsonify
from openai import OpenAI
import os

app = Flask(__name__)
client = OpenAI(
    base_url="https://app.gmtech.com/api/v1",
    api_key=os.getenv("GMTECH_API_KEY")
)

@app.route('/chat', methods=['POST'])
def chat():
    data = request.json

    try:
        response = client.chat.completions.create(
            model=data.get('model', 'gpt-3.5-turbo'),
            messages=data['messages']
        )

        return jsonify({
            'response': response.choices[0].message.content,
            'tokens': response.usage.total_tokens
        })
    except Exception as e:
        return jsonify({'error': str(e)}), 500

if __name__ == '__main__':
    app.run(debug=True)

Image Generation

response = client.images.generate(
    model="dall-e-3",
    prompt="A futuristic city",
    size="1024x1024"
)

print(response.data[0].url)

Async Operations

import asyncio
from openai import AsyncOpenAI

async_client = AsyncOpenAI(
    base_url="https://app.gmtech.com/api/v1",
    api_key=os.getenv("GMTECH_API_KEY")
)

async def async_chat():
    response = await async_client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": "Hello!"}]
    )
    return response.choices[0].message.content

# Run
result = asyncio.run(async_chat())
print(result)

Next Steps

• JavaScript Examples - Frontend and Node.js
• cURL Examples - Command-line testing
• API Overview - Complete API docs

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