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93 lines
4.0 KiB
Markdown
93 lines
4.0 KiB
Markdown
# Python Samples
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This directory contains samples demonstrating the capabilities of Microsoft Agent Framework for Python.
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## Structure
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| Folder | Description |
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|--------|-------------|
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| [`01-get-started/`](./01-get-started/) | Progressive tutorial: hello agent → hosting |
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| [`02-agents/`](./02-agents/) | Deep-dive by concept: tools, middleware, providers, orchestrations |
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| [`03-workflows/`](./03-workflows/) | Workflow patterns: sequential, concurrent, state, declarative |
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| [`04-hosting/`](./04-hosting/) | Deployment: Azure Functions, Durable Tasks, A2A |
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| [`05-end-to-end/`](./05-end-to-end/) | Full applications, evaluation, demos |
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## Getting Started
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Start with `01-get-started/` and work through the numbered files:
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1. **[01_hello_agent.py](./01-get-started/01_hello_agent.py)** — Create and run your first agent
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2. **[02_add_tools.py](./01-get-started/02_add_tools.py)** — Add function tools with `@tool`
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3. **[03_multi_turn.py](./01-get-started/03_multi_turn.py)** — Multi-turn conversations with `AgentSession`
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4. **[04_memory.py](./01-get-started/04_memory.py)** — Agent memory with `ContextProvider`
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5. **[05_first_workflow.py](./01-get-started/05_first_workflow.py)** — Build a workflow with executors and edges
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6. **[06_host_your_agent.py](./01-get-started/06_host_your_agent.py)** — Host your agent via Azure Functions
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## Prerequisites
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```bash
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pip install agent-framework --pre
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```
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### Environment Variables
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Samples call `load_dotenv()` to automatically load environment variables from a `.env` file in the `python/` directory. This is a convenience for local development and testing.
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**For local development**, set up your environment using any of these methods:
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**Option 1: Using a `.env` file** (recommended for local development):
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1. Copy `.env.example` to `.env` in the `python/` directory:
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```bash
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cp .env.example .env
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```
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2. Edit `.env` and set your values (API keys, endpoints, etc.)
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**Option 2: Export environment variables directly**:
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```bash
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export FOUNDRY_PROJECT_ENDPOINT="your-foundry-project-endpoint"
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export FOUNDRY_MODEL="gpt-4o"
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```
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**Option 3: Using `env_file_path` parameter** (for per-client configuration):
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All client classes (e.g., `OpenAIChatClient`, `AzureOpenAIResponsesClient`) support an `env_file_path` parameter to load environment variables from a specific file:
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```python
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from agent_framework.openai import OpenAIChatClient
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# Load from a custom .env file
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client = OpenAIChatClient(env_file_path="path/to/custom.env")
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```
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This allows different clients to use different configuration files if needed.
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For the generic OpenAI clients (`OpenAIChatClient` and `OpenAIChatCompletionClient`), routing
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precedence is:
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1. Explicit Azure inputs such as `credential`, `azure_endpoint`, or `api_version`
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2. `OPENAI_API_KEY` / explicit OpenAI API-key parameters
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3. Azure environment fallback such as `AZURE_OPENAI_ENDPOINT` and `AZURE_OPENAI_API_KEY`
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If you keep both OpenAI and Azure variables in your shell, the generic clients stay on OpenAI until
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you pass an explicit Azure input.
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For the getting-started samples, you'll need at minimum:
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```bash
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FOUNDRY_PROJECT_ENDPOINT="your-foundry-project-endpoint"
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FOUNDRY_MODEL="gpt-4o"
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```
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**Note for production**: In production environments, set environment variables through your deployment platform (e.g., Azure App Settings, Kubernetes ConfigMaps/Secrets) rather than using `.env` files. The `load_dotenv()` call in samples will have no effect when a `.env` file is not present, allowing environment variables to be loaded from the system.
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For Azure authentication, run `az login` before running samples.
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## Note on XML tags
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Some sample files include XML-style snippet tags (for example `<snippet_name>` and `</snippet_name>`). These are used by our documentation tooling and can be ignored or removed when you use the samples outside this repository.
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## Additional Resources
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- [Agent Framework Documentation](https://learn.microsoft.com/agent-framework/)
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- [AGENTS.md](./AGENTS.md) — Structure documentation for maintainers
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- [SAMPLE_GUIDELINES.md](./SAMPLE_GUIDELINES.md) — Coding conventions for samples
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