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agent-framework/python/samples/02-agents/devui
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Eduard van Valkenburg 1e350ea22f Python: [BREAKING] PR2 — Wire context provider pipeline, remove old types, update all consumers (#3850)
* PR2: Wire context provider pipeline and update all internal consumers

- Replace AgentThread with AgentSession across all packages
- Replace ContextProvider with BaseContextProvider across all packages
- Replace context_provider param with context_providers (Sequence)
- Replace thread= with session= in run() signatures
- Replace get_new_thread() with create_session()
- Add get_session(service_session_id) to agent interface
- DurableAgentThread -> DurableAgentSession
- Remove _notify_thread_of_new_messages from WorkflowAgent
- Wire before_run/after_run context provider pipeline in RawAgent
- Auto-inject InMemoryHistoryProvider when no providers configured

* fix: update all tests for context provider pipeline, fix lazy-loaders, remove old test files

* refactor: update all sample files for context provider pipeline (AgentThread→AgentSession, ContextProvider→BaseContextProvider)

* fix: update remaining ag-ui references (client docstring, getting_started sample)

* fix: make get_session service_session_id keyword-only to avoid confusion with session_id

* refactor: rename _RunContext.thread_messages to session_messages

* refactor: remove _threads.py, _memory.py, and old provider files; migrate devui to use plain message lists

* rename: remove _new_ prefix from test files

* refactor: rewrite SlidingWindowChatMessageStore as SlidingWindowHistoryProvider(InMemoryHistoryProvider)

* fix: read full history from session state directly instead of reaching into provider internals

* fix: update stale .pyi stubs, sample imports, and README references for new provider types

* fix: remove stale message_store, _notify_thread_of_new_messages, and session_id.key references in samples

* refactor: merge context_providers and sessions sample folders into sessions, remove aggregate_context_provider

* refactor: UserInfoMemory stores state in session.state instead of instance attributes

* feat: add Pydantic BaseModel support to session state serialization

Pydantic models stored in session.state are now automatically serialized
via model_dump() and restored via model_validate() during to_dict()/from_dict()
round-trips. Models are auto-registered on first serialization; use
register_state_type() for cold-start deserialization.

Also export register_state_type as a public API.

* fix mem0

* Update sample README links and descriptions for session terminology

- Replace 'thread' with 'session' in sample descriptions across all READMEs
- Update file links for renamed samples (mem0_sessions, redis_sessions, etc.)
- Fix Threads section → Sessions section in main samples/README.md
- Update tools, middleware, workflows, durabletask, azure_functions READMEs
- Update architecture diagrams in concepts/tools/README.md
- Update migration guides (autogen, semantic-kernel)

* Fix broken Redis README link to renamed sample

* Fix Mem0 OSS client search: pass scoping params as direct kwargs

AsyncMemory (OSS) expects user_id/agent_id/run_id as direct kwargs,
while AsyncMemoryClient (Platform) expects them in a filters dict.
Adds tests for both client types.

Port of fix from #3844 to new Mem0ContextProvider.

* Fix rebase issues: restore missing _conversation_state.py and checkpoint decode logic

- Add back _conversation_state.py (encode/decode_chat_messages) lost in rebase
- Fix on_checkpoint_restore to decode cache/conversation with decode_chat_messages
- Fix on_checkpoint_restore to use decode_checkpoint_value for pending requests
- Add tests/workflow/__init__.py for relative import support
- Fix test_agent_executor checkpoint selection (checkpoints[1] not superstep)

* Add STORES_BY_DEFAULT ClassVar to skip redundant InMemoryHistoryProvider injection

Chat clients that store history server-side by default (OpenAI Responses API,
Azure AI Agent) now declare STORES_BY_DEFAULT = True. The agent checks this
during auto-injection and skips InMemoryHistoryProvider unless the user
explicitly sets store=False.

* Fix broken markdown links in azure_ai and redis READMEs

* Fix getting-started samples to use session API instead of removed thread/ContextProvider API

* updates to workflow as agent

* fix group chat import

* Rename Thread→Session throughout, fix service_session_id propagation, remove stale AGUIThread

- Fix: Propagate conversation_id from ChatResponse back to session.service_session_id
  in both streaming and non-streaming paths in _agents.py
- Rename AgentThreadException → AgentSessionException
- Remove stale AGUIThread from ag_ui lazy-loader
- Rename use_service_thread → use_service_session in ag-ui package
- Rename test functions from *_thread_* to *_session_*
- Rename sample files from *_thread* to *_session*
- Update docstrings and comments: thread → session
- Update _mcp.py kwargs filter: add 'session' alongside 'thread'
- Fix ContinuationToken docstring example: thread=thread → session=session
- Fix _clients.py docstring: 'Agent threads' → 'Agent sessions'

* Fix broken markdown links after thread→session file renames

* fix azure ai test
1e350ea22f · 2026-02-12 21:00:32 +00:00
History
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DevUI Samples

This folder contains sample agents and workflows designed to work with the Agent Framework DevUI - a lightweight web interface for running and testing agents interactively.

What is DevUI?

DevUI is a sample application that provides:

  • A web interface for testing agents and workflows
  • OpenAI-compatible API endpoints
  • Directory-based entity discovery
  • In-memory entity registration
  • Sample entity gallery

Note

: DevUI is a sample app for development and testing. For production use, build your own custom interface using the Agent Framework SDK.

Quick Start

Option 1: In-Memory Mode (Simplest)

Run a single sample directly. This demonstrates how to wrap agents and workflows programmatically without needing a directory structure:

cd python/samples/02-agents/devui
python in_memory_mode.py

This opens your browser at http://localhost:8090 with pre-configured agents and a basic workflow.

Option 2: Directory Discovery

Launch DevUI to discover all samples in this folder:

cd python/samples/02-agents/devui
devui

This starts the server at http://localhost:8080 with all agents and workflows available.

Sample Structure

Each agent/workflow follows a strict structure required by DevUI's discovery system:

agent_name/
├── __init__.py      # Must export: agent = Agent(...)
├── agent.py         # Agent implementation
└── .env.example     # Example environment variables

Available Samples

Agents

Sample Description Features Required Environment Variables
weather_agent_azure/ Weather agent using Azure OpenAI with API key authentication Azure OpenAI integration, function calling, mock weather tools AZURE_OPENAI_API_KEY, AZURE_OPENAI_CHAT_DEPLOYMENT_NAME, AZURE_OPENAI_ENDPOINT
foundry_agent/ Weather agent using Azure AI Agent (Foundry) with Azure CLI authentication (run az login first) Azure AI Agent integration, Azure CLI authentication, mock weather tools AZURE_AI_PROJECT_ENDPOINT, FOUNDRY_MODEL_DEPLOYMENT_NAME

Workflows

Sample Description Features Required Environment Variables
declarative/ Declarative YAML workflow with conditional branching YAML-based workflow definition, conditional logic, no Python code required None - uses mock data
workflow_agents/ Content review workflow with agents as executors Agents as workflow nodes, conditional routing based on structured outputs, quality-based paths (Writer -> Reviewer -> Editor/Publisher) AZURE_OPENAI_API_KEY, AZURE_OPENAI_CHAT_DEPLOYMENT_NAME, AZURE_OPENAI_ENDPOINT
spam_workflow/ 5-step email spam detection workflow with branching logic Sequential execution, conditional branching (spam vs. legitimate), multiple executors, mock spam detection None - uses mock data
fanout_workflow/ Advanced data processing workflow with parallel execution Fan-out/fan-in patterns, complex state management, multi-stage processing (validation -> transformation -> quality assurance) None - uses mock data

Standalone Examples

Sample Description Features
in_memory_mode.py Demonstrates programmatic entity registration without directory structure In-memory agent and workflow registration, multiple entities served from a single file, includes basic workflow, simplest way to get started

Environment Variables

Each sample that requires API keys includes a .env.example file. To use:

  1. Copy .env.example to .env in the same directory
  2. Fill in your actual API keys
  3. DevUI automatically loads .env files from entity directories

Alternatively, set environment variables globally:

export OPENAI_API_KEY="your-key-here"
export OPENAI_CHAT_MODEL_ID="gpt-4o"

Using DevUI with Your Own Agents

To make your agent discoverable by DevUI:

  1. Create a folder for your agent
  2. Add an __init__.py that exports agent or workflow
  3. (Optional) Add a .env file for environment variables

Example:

# my_agent/__init__.py
from agent_framework import Agent
from agent_framework.openai import OpenAIChatClient

agent = Agent(
    name="MyAgent",
    description="My custom agent",
    client=OpenAIChatClient(),
    # ... your configuration
)

Then run:

devui /path/to/my/agents/folder

API Usage

DevUI exposes OpenAI-compatible endpoints:

curl -X POST http://localhost:8080/v1/responses \
  -H "Content-Type: application/json" \
  -d '{
    "model": "agent-framework",
    "input": "What is the weather in Seattle?",
    "extra_body": {"entity_id": "agent_directory_weather-agent_<uuid>"}
  }'

List available entities:

curl http://localhost:8080/v1/entities

Learn More

Troubleshooting

Missing API keys: Check your .env files or environment variables.

Import errors: Make sure you've installed the devui package:

pip install agent-framework-devui --pre

Port conflicts: DevUI uses ports 8080 (directory mode) and 8090 (in-memory mode) by default. Close other services or specify a different port:

devui --port 8888