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Eduard van Valkenburg
a2856d3b92
* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent → hosting) - 02-agents/: all agent concept samples (tools, middleware, providers, etc.) - 03-workflows/: ALL existing workflow samples preserved as-is - 04-hosting/: azure-functions, durabletask, a2a - 05-end-to-end/: demos, evaluation, hosted agents - Old files moved to _to_delete/ for review - Added AGENTS.md with structure documentation - autogen-migration/ and semantic-kernel-migration/ preserved at root * fix: switch to AzureOpenAI Foundry, fix CI failures - Switch all 01-get-started samples to AzureOpenAIResponsesClient with Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT + AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential) - Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes - Fix test paths in packages/ that referenced old getting_started/ dirs: durabletask conftest + streaming test, azurefunctions conftest, devui conftest + capture_messages + openai_sdk_integration - Fix workflow_as_agent_human_in_the_loop.py import (sibling import) - Update hosting READMEs and tool comment paths - Replace root README.md with new structure overview - Update AGENTS.md to document Azure OpenAI Foundry as default provider * cleanup: remove _to_delete folder, copy resource files to active dirs All files in _to_delete/ were either: - Exact duplicates of files in the new structure (240 files) - Same file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since active samples reference them. * fix: address PR review comments, centralize resources, remove root duplicates - Fix type annotation in 04_memory.py (string union -> proper types) - Fix old sample paths in observability files - Fix grammar/spelling in observability samples - Move sample_assets/ and resources/ to shared/ folder - Remove 8 duplicate observability files from 02-agents root - Update resource path references in multimodal_input and provider samples * fix: update broken links from old getting_started paths to new structure - Update relative paths in READMEs: getting_started/ → 01-get-started/, 02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/ - Fix absolute GitHub URLs in package READMEs - Fix broken link in ollama package README * fix: convert absolute GitHub URLs to relative paths for link checker Absolute URLs to python/samples/ on main branch 404 until PR merges. Converted to relative paths that linkspector can verify locally. * fix: update link for handoff sample moved to orchestrations/ * fix: update chatkit-integration README path from demos/ to 05-end-to-end/ * fix: update broken links in orchestrations README to match flat directory structure
68 lines
6.3 KiB
Markdown
68 lines
6.3 KiB
Markdown
# Orchestration Getting Started Samples
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## Installation
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The orchestrations package is included when you install `agent-framework` (which pulls in all optional packages):
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```bash
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pip install agent-framework
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```
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Or install the orchestrations package directly:
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```bash
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pip install agent-framework-orchestrations
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```
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Orchestration builders are available via the `agent_framework.orchestrations` submodule:
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```python
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from agent_framework.orchestrations import (
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SequentialBuilder,
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ConcurrentBuilder,
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HandoffBuilder,
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GroupChatBuilder,
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MagenticBuilder,
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)
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```
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## Samples Overview
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| Sample | File | Concepts |
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| ------------------------------------------------- | ------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------- |
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| Concurrent Orchestration (Default Aggregator) | [concurrent_agents.py](./concurrent_agents.py) | Fan-out to multiple agents; fan-in with default aggregator returning combined Messages |
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| Concurrent Orchestration (Custom Aggregator) | [concurrent_custom_aggregator.py](./concurrent_custom_aggregator.py) | Override aggregator via callback; summarize results with an LLM |
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| Concurrent Orchestration (Custom Agent Executors) | [concurrent_custom_agent_executors.py](./concurrent_custom_agent_executors.py) | Child executors own Agents; concurrent fan-out/fan-in via ConcurrentBuilder |
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| Group Chat with Agent Manager | [group_chat_agent_manager.py](./group_chat_agent_manager.py) | Agent-based manager using `with_orchestrator(agent=)` to select next speaker |
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| Group Chat Philosophical Debate | [group_chat_philosophical_debate.py](./group_chat_philosophical_debate.py) | Agent manager moderates long-form, multi-round debate across diverse participants |
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| Group Chat with Simple Function Selector | [group_chat_simple_selector.py](./group_chat_simple_selector.py) | Group chat with a simple function selector for next speaker |
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| Handoff (Simple) | [handoff_simple.py](./handoff_simple.py) | Single-tier routing: triage agent routes to specialists, control returns to user after each specialist response |
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| Handoff (Autonomous) | [handoff_autonomous.py](./handoff_autonomous.py) | Autonomous mode: specialists iterate independently until invoking a handoff tool using `.with_autonomous_mode()` |
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| Handoff with Code Interpreter | [handoff_with_code_interpreter_file.py](./handoff_with_code_interpreter_file.py) | Retrieve file IDs from code interpreter output in handoff workflow |
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| Magentic Workflow (Multi-Agent) | [magentic.py](./magentic.py) | Orchestrate multiple agents with Magentic manager and streaming |
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| Magentic + Human Plan Review | [magentic_human_plan_review.py](./magentic_human_plan_review.py) | Human reviews/updates the plan before execution |
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| Magentic + Checkpoint Resume | [magentic_checkpoint.py](./magentic_checkpoint.py) | Resume Magentic orchestration from saved checkpoints |
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| Sequential Orchestration (Agents) | [sequential_agents.py](./sequential_agents.py) | Chain agents sequentially with shared conversation context |
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| Sequential Orchestration (Custom Executor) | [sequential_custom_executors.py](./sequential_custom_executors.py) | Mix agents with a summarizer that appends a compact summary |
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## Tips
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**Magentic checkpointing tip**: Treat `MagenticBuilder.participants` keys as stable identifiers. When resuming from a checkpoint, the rebuilt workflow must reuse the same participant names; otherwise the checkpoint cannot be applied and the run will fail fast.
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**Handoff workflow tip**: Handoff workflows maintain the full conversation history including any `Message.additional_properties` emitted by your agents. This ensures routing metadata remains intact across all agent transitions. For specialist-to-specialist handoffs, use `.add_handoff(source, targets)` to configure which agents can route to which others with a fluent, type-safe API.
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**Sequential orchestration note**: Sequential orchestration uses a few small adapter nodes for plumbing:
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- `input-conversation` normalizes input to `list[Message]`
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- `to-conversation:<participant>` converts agent responses into the shared conversation
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- `complete` publishes the final output event (type='output')
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These may appear in event streams (executor_invoked/executor_completed). They're analogous to concurrent's dispatcher and aggregator and can be ignored if you only care about agent activity.
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## Environment Variables
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- **AzureOpenAIChatClient**: Set Azure OpenAI environment variables as documented [here](https://github.com/microsoft/agent-framework/blob/main/python/samples/02-agents/chat_client/README.md#environment-variables).
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- **OpenAI** (used in some orchestration samples):
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- [OpenAIChatClient env vars](https://github.com/microsoft/agent-framework/blob/main/python/samples/02-agents/providers/openai/README.md)
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- [OpenAIResponsesClient env vars](https://github.com/microsoft/agent-framework/blob/main/python/samples/02-agents/providers/openai/README.md)
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