mirror of
https://github.com/microsoft/agent-framework.git
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Eduard van Valkenburg
3446eb8d5d
* updates to final deprecated pieces and versions * fix mypy * fix readme links
117 lines
4.7 KiB
Markdown
117 lines
4.7 KiB
Markdown
# Samples Structure & Design Choices — Python
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> This file documents the structure and conventions of the Python samples so that
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> agents (AI or human) can maintain them without rediscovering decisions.
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## Directory layout
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```
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python/samples/
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├── 01-get-started/ # Progressive tutorial (steps 01–06)
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├── 02-agents/ # Deep-dive concept samples
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│ ├── tools/ # Tool patterns (function, approval, schema, etc.)
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│ ├── middleware/ # One file per middleware concept
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│ ├── conversations/ # Thread, storage, suspend/resume
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│ ├── providers/ # One sub-folder per provider (azure_ai/, openai/, etc.)
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│ ├── context_providers/ # Memory & context injection
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│ ├── orchestrations/ # Multi-agent orchestration patterns
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│ ├── observability/ # Tracing, telemetry
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│ ├── declarative/ # Declarative agent definitions
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│ ├── chat_client/ # Raw chat client usage
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│ ├── mcp/ # MCP server/client patterns
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│ ├── multimodal_input/ # Image, audio inputs
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│ └── devui/ # DevUI agent/workflow samples
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├── 03-workflows/ # Workflow samples (preserved from upstream)
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│ ├── _start-here/ # Introductory workflow samples
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│ ├── agents/ # Agents in workflows
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│ ├── checkpoint/ # Checkpointing & resume
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│ ├── composition/ # Sub-workflows
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│ ├── control-flow/ # Edges, conditions, loops
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│ ├── declarative/ # YAML-based workflows
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│ ├── human-in-the-loop/ # HITL patterns
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│ ├── observability/ # Workflow telemetry
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│ ├── parallelism/ # Fan-out, map-reduce
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│ ├── state-management/ # State isolation, kwargs
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│ ├── tool-approval/ # Tool approval in workflows
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│ └── visualization/ # Workflow visualization
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├── 04-hosting/ # Deployment & hosting
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│ ├── a2a/ # Agent-to-Agent protocol
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│ ├── azure-functions/ # Azure Functions samples
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│ └── durabletask/ # Durable task framework
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├── 05-end-to-end/ # Complete applications
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│ ├── chatkit-integration/
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│ ├── evaluation/
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│ ├── hosted_agents/
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│ ├── m365-agent/
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│ ├── purview_agent/
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│ └── workflow_evaluation/
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├── autogen-migration/ # Migration guides (do not restructure)
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├── semantic-kernel-migration/
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└── _to_delete/ # Old samples awaiting review
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```
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## Design principles
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1. **Progressive complexity**: Sections 01→05 build from "hello world" to
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production. Within 01-get-started, files are numbered 01–06 and each step
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adds exactly one concept.
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2. **One concept per file** in 01-get-started and flat files in 02-agents/.
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3. **Workflows preserved**: 03-workflows/ keeps the upstream folder names
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and file names intact. Do not rename or restructure workflow samples.
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4. **Single-file for 01-03**: Only 04-hosting and 05-end-to-end use multi-file
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projects with their own README.
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## Default provider
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All canonical samples (01-get-started) use **Azure AI Foundry project-backed chat** via `FoundryChatClient`
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with an Azure AI Foundry project endpoint:
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```python
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import os
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from agent_framework.foundry import FoundryChatClient
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from azure.identity import AzureCliCredential
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credential = AzureCliCredential()
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client = FoundryChatClient(
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project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
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model=os.environ["FOUNDRY_MODEL"],
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credential=credential,
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)
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agent = client.as_agent(name="...", instructions="...")
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```
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Environment variables:
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- `FOUNDRY_PROJECT_ENDPOINT` — Your Azure AI Foundry project endpoint
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- `FOUNDRY_MODEL` — Model deployment name (e.g. gpt-4o)
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For authentication, run `az login` before running samples.
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## Snippet tags for docs integration
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Samples embed named snippet regions for future `:::code` integration:
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```python
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# <snippet_name>
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code here
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# </snippet_name>
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```
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## Package install
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```bash
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pip install agent-framework
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```
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`agent-framework` is released, so `--pre` is not required here. `openai` is a core dependency.
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## Current API notes
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- `Agent` class renamed from `ChatAgent` (use `from agent_framework import Agent`)
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- `Message` class renamed from `ChatMessage` (use `from agent_framework import Message`)
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- `call_next` in middleware takes NO arguments: `await call_next()` (not `await call_next(context)`)
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- Prefer `client.as_agent(...)` over `Agent(client=client, ...)`
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- Tool methods on hosted tools are now functions, not classes (e.g. `hosted_mcp_tool(...)` not `HostedMCPTool(...)`)
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