# Genkit Python SDK
Genkit is a framework for building AI-powered applications with type-safe flows, structured outputs, and integrated observability. This is the Python implementation that maintains feature parity with the JavaScript/TypeScript SDK.
## Directory Structure
```
py/
├── packages/genkit/ # Core Genkit framework package
├── plugins/ # Official plugins
│ ├── amazon-bedrock/ # Amazon Bedrock models + X-Ray telemetry (community)
│ ├── anthropic/ # Claude models
│ ├── azure/ # Azure AI telemetry (community)
│ ├── cloudflare-workers-ai/ # Cloudflare Workers AI + OTLP telemetry (community)
│ ├── checks/ # Safety guardrails
│ ├── compat-oai/ # OpenAI-compatible APIs
│ ├── deepseek/ # DeepSeek models
│ ├── dev-local-vectorstore/# Local development vector store
│ ├── evaluators/ # RAGAS and custom evaluators
│ ├── firebase/ # Firebase integration + telemetry
│ ├── flask/ # Flask HTTP endpoints
│ ├── google-cloud/ # GCP telemetry (Cloud Trace, Logging)
│ ├── google-genai/ # Gemini, Imagen, Veo, Lyria, TTS
│ ├── huggingface/ # HuggingFace Inference API
│ ├── mcp/ # Model Context Protocol
│ ├── mistral/ # Mistral models
│ ├── microsoft-foundry/ # Azure AI Foundry (11,000+ models) (community)
│ ├── observability/ # 3rd party telemetry (Sentry, Datadog, etc.)
│ ├── ollama/ # Local Ollama models
│ ├── vertex-ai/ # Model Garden + Vector Search
│ └── xai/ # Grok models
├── samples/ # Sample applications
└── testapps/ # Test applications
```
## Setup Instructions
1. Install `uv` from https://docs.astral.sh/uv/getting-started/installation/
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
2. Install required tools using `uv`
```bash
uv tool install httpie
uv tool install mypy
uv tool install ruff
```
3. If you are using VSCode, install the `Ruff` extension from the marketplace to add linter support.
## Quick Start
```python
from genkit import Genkit
from genkit.plugins.google_genai import GoogleGenAI, gemini_2_0_flash
ai = Genkit(
plugins=[GoogleGenAI()],
model=gemini_2_0_flash,
)
response = await ai.generate(prompt="Tell me a joke")
print(response.text)
```
## Plugin Categories
| Category | Plugins | Purpose |
|----------|---------|---------|
| **Model Providers** | google-genai, anthropic, amazon-bedrock, ollama, compat-oai, deepseek, xai, mistral, huggingface, microsoft-foundry, cloudflare-workers-ai | AI model access |
| **Telemetry** | google-cloud, amazon-bedrock, azure, firebase, cloudflare-workers-ai, observability | Distributed tracing & logging |
| **Vector Stores** | firebase, vertex-ai, dev-local-vectorstore | Embeddings storage & retrieval |
| **Safety** | checks, evaluators | Guardrails & evaluation |
| **Integrations** | flask, mcp | HTTP endpoints, tool protocols |
## Community Plugins
Some plugins are community-maintained and supported on a best-effort basis:
- **amazon-bedrock** - Amazon Bedrock models + AWS X-Ray telemetry
- **azure** - Azure Monitor / Application Insights telemetry
- **cloudflare-workers-ai** - Cloudflare Workers AI models + OTLP telemetry
- **microsoft-foundry** - Azure AI Foundry (11,000+ models)
- **observability** - Third-party backends (Sentry, Honeycomb, Datadog, etc.)
## Running Tests
Run all unit tests:
```bash
uv run pytest .
```
Run tests for a specific plugin:
```bash
uv run pytest plugins/amazon-bedrock/
```
## Running Samples
See the [samples/README.md](samples/README.md) for instructions on running individual samples.
Quick start:
```bash
cd samples/provider-google-genai-hello
./run.sh
```
## Development
See [GEMINI.md](GEMINI.md) for detailed development guidelines, including:
- Code quality and linting requirements
- Type checking configuration
- Testing conventions
- Documentation standards
## License
Apache 2.0
