Merge branch 'main' into workflows

Author: pamelafox

.devcontainer/Dockerfile

@@ -3,6 +3,13 @@ FROM mcr.microsoft.com/devcontainers/python:3.12-bookworm
 # Required for cloning agent-framework from GitHub (it uses Git LFS)
 RUN apt-get update && apt-get install -y git-lfs && git lfs install && rm -rf /var/lib/apt/lists/*
 
+# Required for building Rust-based Python packages (e.g. base2048 via pyrit/azure-ai-evaluation[redteam])
+ENV RUSTUP_HOME="/home/vscode/.rustup" CARGO_HOME="/home/vscode/.cargo"
+ENV PATH="/home/vscode/.cargo/bin:${PATH}"
+RUN mkdir -p /home/vscode/.rustup /home/vscode/.cargo \
+    && curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y \
+    && chown -R vscode:vscode /home/vscode/.rustup /home/vscode/.cargo
+
 COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /usr/local/bin/
 
 COPY pyproject.toml uv.lock /tmp/uv-tmp/

.devcontainer/devcontainer.json

@@ -12,7 +12,8 @@
     "customizations": {
         "vscode": {
             "settings": {
-                "python.defaultInterpreterPath": "/usr/local/bin/python",
+                "python.defaultInterpreterPath": "${workspaceFolder}/.venv/bin/python",
+                "python.terminal.activateEnvironment": true,
                 "remote.autoForwardPorts": false,
                 "python.createEnvironment.trigger": "off",
                 "python.analysis.typeCheckingMode": "off"
@@ -23,5 +24,6 @@
             ]
         }
     },
+    "postCreateCommand": "uv sync",
     "remoteUser": "vscode"
 }

.env.sample

@@ -7,10 +7,11 @@ AZURE_OPENAI_CHAT_DEPLOYMENT=YOUR-AZURE-DEPLOYMENT-NAME
 OPENAI_API_KEY=YOUR-OPENAI-KEY
 OPENAI_MODEL=gpt-3.5-turbo
 # Configure for GitHub models: (GITHUB_TOKEN already exists inside Codespaces)
-GITHUB_MODEL=gpt-5-mini
+GITHUB_MODEL=gpt-4.1-mini
 GITHUB_TOKEN=YOUR-GITHUB-PERSONAL-ACCESS-TOKEN
 # Configure for Redis (used by agent_history_redis.py, defaults to dev container Redis):
 REDIS_URL=redis://localhost:6379
+# Configure OTLP exporter (not needed in devcontainer, which sets these via docker-compose):
 OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
 OTEL_EXPORTER_OTLP_PROTOCOL=grpc
 # Or use console exporters instead of OTLP:

README.md

@@ -117,13 +117,13 @@ If you want to run the scripts locally, you need to set up the `GITHUB_TOKEN` en
     export GITHUB_TOKEN=your_personal_access_token
     ```
 
-10. Optionally, you can use a model other than "gpt-5-mini" by setting the `GITHUB_MODEL` environment variable. Use a model that supports function calling, such as: `gpt-5`, `gpt-5-mini`, `gpt-4o`, `gpt-4o-mini`, `o3-mini`, `AI21-Jamba-1.5-Large`, `AI21-Jamba-1.5-Mini`, `Codestral-2501`, `Cohere-command-r`, `Ministral-3B`, `Mistral-Large-2411`, `Mistral-Nemo`, `Mistral-small`
+10. Optionally, you can use a model other than "gpt-4.1-mini" by setting the `GITHUB_MODEL` environment variable. Use a model that supports function calling, such as: `gpt-5`, `gpt-4.1-mini`, `gpt-4o`, `gpt-4o-mini`, `o3-mini`, `AI21-Jamba-1.5-Large`, `AI21-Jamba-1.5-Mini`, `Codestral-2501`, `Cohere-command-r`, `Ministral-3B`, `Mistral-Large-2411`, `Mistral-Nemo`, `Mistral-small`
 
 ## Using Azure AI Foundry models
 
 You can run all examples in this repository using GitHub Models. If you want to run the examples using models from Azure AI Foundry instead, you need to provision the Azure AI resources, which will incur costs.
 
-This project includes infrastructure as code (IaC) to provision Azure OpenAI deployments of "gpt-5-mini" and "text-embedding-3-large" via Azure AI Foundry. The IaC is defined in the `infra` directory and uses the Azure Developer CLI to provision the resources.
+This project includes infrastructure as code (IaC) to provision Azure OpenAI deployments of "gpt-4.1-mini" and "text-embedding-3-large" via Azure AI Foundry. The IaC is defined in the `infra` directory and uses the Azure Developer CLI to provision the resources.
 
 1. Make sure the [Azure Developer CLI (azd)](https://aka.ms/install-azd) is installed.
 
@@ -194,8 +194,6 @@ You can run the examples in this repository by executing the scripts in the `exa
 | [agent_with_subagent.py](examples/agent_with_subagent.py) | Context isolation with sub-agents to keep prompts focused on relevant tools. |
 | [agent_without_subagent.py](examples/agent_without_subagent.py) | Context bloat example where one agent carries all tool schemas in a single prompt. |
 | [agent_summarization.py](examples/agent_summarization.py) | Context compaction via summarization middleware to reduce token usage in long conversations. |
-| [workflow_magenticone.py](examples/workflow_magenticone.py) | A MagenticOne multi-agent workflow. |
-| [workflow_hitl.py](examples/workflow_hitl.py) | Human-in-the-loop (HITL) for tool-enabled agents with human feedback. |
 | [agent_middleware.py](examples/agent_middleware.py) | Agent, chat, and function middleware for logging, timing, and blocking. |
 | [agent_knowledge_aisearch.py](examples/agent_knowledge_aisearch.py) | Knowledge retrieval (RAG) using Azure AI Search with AgentFrameworkAzureAISearchRAG. |
 | [agent_knowledge_sqlite.py](examples/agent_knowledge_sqlite.py) | Knowledge retrieval (RAG) using a custom context provider with SQLite FTS5. |

chat_history.db

@@ -24,11 +24,11 @@
     client = OpenAIChatClient(
         base_url="https://models.github.ai/inference",
         api_key=os.environ["GITHUB_TOKEN"],
-        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-5-mini"),
+        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4.1-mini"),
     )
 else:
     client = OpenAIChatClient(
-        api_key=os.environ["OPENAI_API_KEY"], model_id=os.environ.get("OPENAI_MODEL", "gpt-5-mini")
+        api_key=os.environ["OPENAI_API_KEY"], model_id=os.environ.get("OPENAI_MODEL", "gpt-4.1-mini")
     )
 
 agent = Agent(client=client, instructions="You're an informational agent. Answer questions cheerfully.")

examples/agent_basic.py

@@ -48,22 +48,22 @@
     client = OpenAIChatClient(
         base_url="https://models.github.ai/inference",
         api_key=os.environ["GITHUB_TOKEN"],
-        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-5-mini"),
+        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4.1-mini"),
     )
     eval_model_config = OpenAIModelConfiguration(
         type="openai",
         base_url="https://models.github.ai/inference",
         api_key=os.environ["GITHUB_TOKEN"],
-        model="openai/gpt-5-mini",
+        model="openai/gpt-4.1-mini",
     )
 else:
     client = OpenAIChatClient(
-        api_key=os.environ["OPENAI_API_KEY"], model_id=os.environ.get("OPENAI_MODEL", "gpt-5-mini")
+        api_key=os.environ["OPENAI_API_KEY"], model_id=os.environ.get("OPENAI_MODEL", "gpt-4.1-mini")
     )
     eval_model_config = OpenAIModelConfiguration(
         type="openai",
         api_key=os.environ["OPENAI_API_KEY"],
-        model=os.environ.get("OPENAI_MODEL", "gpt-5-mini"),
+        model=os.environ.get("OPENAI_MODEL", "gpt-4.1-mini"),
     )
 
 

examples/agent_evaluation.py

@@ -46,13 +46,13 @@
         type="openai",
         base_url="https://models.github.ai/inference",
         api_key=os.environ["GITHUB_TOKEN"],
-        model="openai/gpt-5-mini",
+        model="openai/gpt-4.1-mini",
     )
 else:
     model_config = OpenAIModelConfiguration(
         type="openai",
         api_key=os.environ["OPENAI_API_KEY"],
-        model=os.environ.get("OPENAI_MODEL", "gpt-5-mini"),
+        model=os.environ.get("OPENAI_MODEL", "gpt-4.1-mini"),
     )
 
 # Optional: Set AZURE_AI_PROJECT in .env to log results to Azure AI Foundry.

examples/agent_evaluation_batch.py

@@ -45,11 +45,11 @@
     client = OpenAIChatClient(
         base_url="https://models.github.ai/inference",
         api_key=os.environ["GITHUB_TOKEN"],
-        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-5-mini"),
+        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4.1-mini"),
     )
 else:
     client = OpenAIChatClient(
-        api_key=os.environ["OPENAI_API_KEY"], model_id=os.environ.get("OPENAI_MODEL", "gpt-5-mini")
+        api_key=os.environ["OPENAI_API_KEY"], model_id=os.environ.get("OPENAI_MODEL", "gpt-4.1-mini")
     )
 
 

examples/agent_evaluation_generate.py

@@ -38,11 +38,11 @@
     client = OpenAIChatClient(
         base_url="https://models.github.ai/inference",
         api_key=os.environ["GITHUB_TOKEN"],
-        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-5-mini"),
+        model_id=os.getenv("GITHUB_MODEL", "openai/gpt-4.1-mini"),
     )
 else:
     client = OpenAIChatClient(
-        api_key=os.environ["OPENAI_API_KEY"], model_id=os.environ.get("OPENAI_MODEL", "gpt-5-mini")
+        api_key=os.environ["OPENAI_API_KEY"], model_id=os.environ.get("OPENAI_MODEL", "gpt-4.1-mini")
     )
 
 
@@ -63,7 +63,7 @@ async def example_persistent_session() -> None:
     session_id = str(uuid.uuid4())
 
     # Phase 1: Start a conversation with a Redis-backed history provider
-    print("[dim]--- Phase 1: Starting conversation ---[/dim]")
+    print("[bold]--- Phase 1: Starting conversation ---[/bold]")
     redis_provider = RedisHistoryProvider(source_id="redis_chat", redis_url=REDIS_URL)
 
     agent = Agent(
@@ -84,7 +84,7 @@ async def example_persistent_session() -> None:
     print(f"[green]Agent:[/green] {response.text}")
 
     # Phase 2: Simulate an application restart — reconnect using the same session ID in Redis
-    print("\n[dim]--- Phase 2: Resuming after 'restart' ---[/dim]")
+    print("\n[bold]--- Phase 2: Resuming after 'restart' ---[/bold]")
     redis_provider2 = RedisHistoryProvider(source_id="redis_chat", redis_url=REDIS_URL)
 
     agent2 = Agent(
@@ -99,7 +99,6 @@ async def example_persistent_session() -> None:
     print("[blue]User:[/blue] Which of the cities I asked about had better weather?")
     response = await agent2.run("Which of the cities I asked about had better weather?", session=session2)
     print(f"[green]Agent:[/green] {response.text}")
-    print("[dim]Note: The agent remembered the conversation from Phase 1 via Redis persistence.[/dim]")
 
 
 async def main() -> None:
@@ -111,17 +110,15 @@ async def main() -> None:
     try:
         r.ping()
     except Exception as e:
-        print(f"[red]Cannot connect to Redis at {REDIS_URL}: {e}[/red]")
-        print(
-            "[red]Ensure Redis is running (e.g. via the dev container"
-            " or 'docker run -p 6379:6379 redis:7-alpine').[/red]"
+        logger.error(f"Cannot connect to Redis at {REDIS_URL}: {e}")
+        logger.error(
+            "Ensure Redis is running (e.g. via the dev container"
+            " or 'docker run -p 6379:6379 redis:7-alpine')."
         )
         return
     finally:
         r.close()
 
-    print("[dim]Redis connection verified.[/dim]")
-
     await example_persistent_session()
 
     if async_credential: