GPT model integration for Amplifier via OpenAI's Responses API.
- Python 3.11+
- UV - Fast Python package manager
# macOS/Linux/WSL
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"Provides access to OpenAI's GPT-5 and GPT-4 models as an LLM provider for Amplifier using the Responses API for enhanced capabilities.
Module Type: Provider
Mount Point: providers
Entry Point: amplifier_module_provider_openai:mount
gpt-5-codex- GPT-5 optimized for code (default)gpt-5- Latest GPT-5 modelgpt-5-mini- Smaller, faster GPT-5gpt-5-codex- Code-optimized GPT-5gpt-5-nano- Smallest GPT-5 variant
[[providers]]
module = "provider-openai"
name = "openai"
config = {
default_model = "gpt-5-codex",
max_tokens = 4096,
temperature = 0.7,
reasoning = "low",
enable_state = false
}export OPENAI_API_KEY="your-api-key-here"# In amplifier configuration
[provider]
name = "openai"
model = "gpt-5-codex"- Reasoning Control - Adjust reasoning effort (minimal, low, medium, high)
- Stateful Conversations - Optional conversation persistence
- Native Tools - Built-in web search, image generation, code interpreter
- Structured Output - JSON schema-based output formatting
- Function Calling - Custom tool use support
- Token Counting - Usage tracking and management
The provider detects OpenAI Responses API function_call / tool_call
blocks automatically, decodes JSON arguments, and returns standard
ToolCall objects to Amplifier. No extra configuration is required—tools
declared in your config or profiles execute as soon as the model requests
them.
amplifier-core>=1.0.0openai>=1.0.0
Note
This project is not currently accepting external contributions, but we're actively working toward opening this up. We value community input and look forward to collaborating in the future. For now, feel free to fork and experiment!
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