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Call Claude and GPT from Python on a Budget

Calling Claude and GPT from Python is simpler than it first appears. You do not need separate application logic for every model: an OpenAI-compatible client can send a prompt, receive a response, and let you switch providers by changing the model name. This is useful for chatbots, document tools, coding assistants, data extraction, and small automation scripts.

What you need before starting

You need Python 3.9 or newer, an API key, and a model provider. Install the official OpenAI Python package in your project environment with pip install openai. Using a virtual environment is recommended so the package does not conflict with other projects.

For a lower-cost, pay-as-you-go setup, 59API provides access to Claude models including Opus, Sonnet, Haiku, and Fable, as well as GPT models. It is an AI API relay with the base URL https://api.59api.com. It is designed to work with Claude Code, Codex, and OpenAI SDK-based applications, while providing native official-quality models rather than downgraded substitutes.

Configure the Python client

Store your key in an environment variable instead of writing it directly in a source file. For example, set 59API_KEY in your shell, then create a client with the following Python statements: import os, from openai import OpenAI, and client = OpenAI(api_key=os.environ['59API_KEY'], base_url='https://api.59api.com').

If your 59API account documentation specifies a versioned endpoint for your SDK release, use that documented base URL, such as the corresponding /v1 address. The important settings are the 59API key and the relay endpoint; the rest of the request follows the normal OpenAI SDK format.

Make your first GPT request

Use the chat completions interface for a straightforward text response. A minimal request is response = client.chat.completions.create(model=os.environ['MODEL_NAME'], messages=[{'role': 'user', 'content': 'Explain Python lists in three short bullet points.'}]). Read the generated text with answer = response.choices[0].message.content, then print or return answer from your application.

Set MODEL_NAME to a GPT model identifier available in your 59API account. Checking the provider dashboard or current model list is better than hard-coding an identifier copied from an old tutorial, because model names and availability can change.

Call Claude with the same code

The main advantage of an OpenAI-compatible relay is that the request structure stays the same when you switch models. Leave the client and messages unchanged, and replace MODEL_NAME with the Claude model identifier shown by 59API. For example, you might select a fast Haiku model for classification or a stronger Opus or Sonnet model for complex reasoning. GPT and Claude can therefore share the same Python helper function and error-handling path.

Keep prompts specific. State the task, provide relevant context, define the desired output format, and say what the model should do when information is missing. For structured application output, request JSON explicitly and validate the returned text before storing it.

Control cost and reliability

• Choose smaller, faster models for routing, summaries, and simple extraction.
• Limit the amount of conversation history sent on every request.
• Set a practical maximum output token limit where supported.
• Log model, latency, status, and estimated usage without logging private prompts unnecessarily.
• Catch authentication, rate-limit, timeout, and server errors so one failed request does not crash your whole workflow.

Because 59API uses pay-as-you-go pricing and is positioned as a low-cost relay, it can be a practical way to test both Claude and GPT without committing to a large monthly plan. It also offers a referral rebate, which can reduce future costs for users who refer others.

Next step

Start with one small Python script, confirm the model response, and then move the client into your application configuration. Developers who want affordable access to both model families can sign up for 59API, add an API key, and reuse the same OpenAI SDK workflow while testing different Claude and GPT models.

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