diff --git a/.azure-pipelines/hosted-agent-tests/python/agent-framework/invocations/02-content-safety-guardrail/test-spec.yml b/.azure-pipelines/hosted-agent-tests/python/agent-framework/invocations/02-content-safety-guardrail/test-spec.yml new file mode 100644 index 000000000..c23ac7edb --- /dev/null +++ b/.azure-pipelines/hosted-agent-tests/python/agent-framework/invocations/02-content-safety-guardrail/test-spec.yml @@ -0,0 +1,19 @@ +version: 1 + +sample: + owner: amitbhave + experiences: [azd, vscode] + +tests: + # The guardrail's blocking behavior can't be asserted here: it needs a real RAI + # policy, and the sample ships a placeholder policy ID that fails open. What is + # deterministic — and what regresses if the moderation wiring is wrong — is that + # benign traffic still flows through both the input and output gates untouched. + - name: invocations-guardrail-allows-benign-traffic + turns: + - input: + message: Reply briefly and include the exact marker INVOCATIONS-GUARDRAIL-OK. + assertions: + - source: raw + type: contains + value: INVOCATIONS-GUARDRAIL-OK diff --git a/samples/python/hosted-agents/README.md b/samples/python/hosted-agents/README.md index 14d83b04b..6b83b6760 100644 --- a/samples/python/hosted-agents/README.md +++ b/samples/python/hosted-agents/README.md @@ -136,6 +136,7 @@ Full control over the HTTP request/response cycle. You define the payload schema | Sample | What it shows | | ---------------------------------------------------------------------- | --------------------------------------------------------------------------------------- | | **[Basic Invocations Agent](./agent-framework/invocations/01-basic/)** | Minimal invocations agent — shows the invocations handler pattern with Agent Framework. | +| **[Content safety guardrail (Invocations)](./agent-framework/invocations/02-content-safety-guardrail/)** | Attach a content safety guardrail to an invocations agent, declaring where prompt and response text live with `invocationsModeration`. | --- diff --git a/samples/python/hosted-agents/agent-framework/README.md b/samples/python/hosted-agents/agent-framework/README.md index 580b3fd05..352630fd7 100644 --- a/samples/python/hosted-agents/agent-framework/README.md +++ b/samples/python/hosted-agents/agent-framework/README.md @@ -41,6 +41,7 @@ This directory contains samples that demonstrate how to use the [Agent Framework | # | Sample | Description | | --- | ------------------------------ | ------------------------------------------------------------------------------------------------------------- | | 1 | [Basic](invocations/01-basic/) | A minimal agent demonstrating session state management via `agent_session_id` in URL params/response headers. | +| 2 | [Content Safety Guardrail](invocations/02-content-safety-guardrail/) | An agent with a Responsible AI content safety guardrail, including the `invocationsModeration` settings that tell the platform where prompt and response text live in an agent-defined payload. | ### A2A protocol diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/AGENTS.md b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/AGENTS.md new file mode 100644 index 000000000..cd7212b25 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/AGENTS.md @@ -0,0 +1,40 @@ +# Coding Agent Instructions + +This project is a **Microsoft Foundry hosted agent** — a containerized AI agent that runs in [Foundry Agent Service](https://learn.microsoft.com/en-us/azure/foundry/agents/concepts/hosted-agents). The platform handles containerization, hosting, security, scaling, and observability so you can focus on agent logic. + +## Key files + +- `Dockerfile` — container definition + +## Development workflow + +The **Azure Developer CLI (`azd`)** manages the full lifecycle: + +```bash +azd ai agent run # Run locally on http://localhost:8088 +azd ai agent invoke --local '{"message": "your message"}' # Test the local agent +azd deploy # Deploy to Foundry +azd ai agent invoke '{"message": "your message"}' # Invoke the deployed agent +``` + +## Microsoft Foundry Skill + +Install the **Microsoft Foundry Skill** for guided deployment, evaluation, and troubleshooting workflows. + +Direct install (preferred, works with any coding agent): + +```bash +npx skills add https://github.com/microsoft/azure-skills --skill microsoft-foundry +``` + +Or install the Azure Skills Plugin: + +- **Copilot CLI**: `/plugin marketplace add microsoft/azure-skills` then `/plugin install azure@azure-skills` +- **Claude Code**: `/plugin install azure@claude-plugins-official` + +Then ask naturally, e.g. `Use the Microsoft Foundry Skill to deploy this agent.` + +## References + +- [Hosted agents overview](https://learn.microsoft.com/en-us/azure/foundry/agents/concepts/hosted-agents) +- [Microsoft Foundry Skill](https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/use-microsoft-foundry-skill) \ No newline at end of file diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/CLAUDE.md b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/CLAUDE.md new file mode 100644 index 000000000..e727d7d95 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/CLAUDE.md @@ -0,0 +1,5 @@ +# CLAUDE.md + +This project uses [AGENTS.md](./AGENTS.md) as the single source of truth for coding agent instructions. The import below loads it into Claude Code's context. + +@AGENTS.md \ No newline at end of file diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/README.md b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/README.md new file mode 100644 index 000000000..8c9aeef64 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/README.md @@ -0,0 +1,253 @@ +# Content safety guardrail (Invocations protocol) + +An [Agent Framework](https://github.com/microsoft/agent-framework) agent hosted on Microsoft Foundry using the **Invocations protocol**, with a Responsible AI (RAI) **content safety guardrail** attached. The guardrail screens the prompts the agent receives and the responses it returns against an RAI policy, so harmful content is filtered according to your safety configuration. + +## How it works + +The guardrail is **not** code; it's a definition-level setting. The agent declares a `policies` list with a `rai_policy` entry that points to an RAI policy by its full Azure Resource Manager (ARM) resource ID. + +The invocations protocol adds one requirement that the [Responses protocol sample](../../responses/16-content-safety-guardrail/) doesn't have. On the Responses protocol the platform knows the message shape, so it can find the text on its own. **The invocations protocol carries a request and response body that your agent defines**, so the platform can't guess which fields hold model text. You tell it, with `invocationsModeration`: + +```yaml +policies: + - type: rai_policy + raiPolicyName: /subscriptions//.../raiPolicies/ + invocationsModeration: + responseMode: both + inputContentType: json + outputContentType: json + inputPaths: + - $.message + outputPaths: + - $.response + streamSelectors: + - eventType: message.delta + textField: text +``` + +Those values match this agent's wire shape in [main.py](src/agent-framework-content-safety-guardrail-invocations/main.py): + +| Traffic | Shape | Screened by | +| --- | --- | --- | +| Request | `{"message": "...", "stream": false}` | `inputPaths: [$.message]` | +| Buffered response | `{"response": "..."}` | `outputPaths: [$.response]` | +| Streamed response frame | `{"type": "message.delta", "text": "..."}` | `streamSelectors: [{eventType: message.delta, textField: text}]` | + +### Settings + +| Setting | Required | Description | +| --- | --- | --- | +| `responseMode` | Always | `non_streaming`, `streaming`, or `both`. Declares the response shapes your agent can return. | +| `inputContentType` | Defaults to `json` | `json` or `text`. | +| `outputContentType` | Defaults to `json` | `json` or `text`. | +| `inputPaths` | When `inputContentType` is `json` | Selector expressions locating prompt text in the request body. | +| `outputPaths` | When `responseMode` includes non-streaming and `outputContentType` is `json` | Selector expressions locating text in a buffered response body. | +| `streamSelectors` | When `responseMode` includes streaming and `outputContentType` is `json` | Pairs of `eventType` and `textField` that locate text in streamed events. | + +#### Selectors and field names + +`inputPaths` and `outputPaths` are **selector expressions**, not a full JSONPath +implementation. They support `$` for the document root, dotted members, array indexes, +and `[*]` wildcards — for example `$.messages[*].content`. Constructs outside that +subset, such as filters or recursive descent, are not supported. + +`textField` is **not** a selector: it is the plain **name of a field** on the streamed +frame, so this sample uses `text` rather than `$.text`. A `$`-prefixed value matches +nothing, which silently leaves streamed output unscreened. + +`responseMode: both` declares a **capability**, not "input and output". At runtime the platform inspects the response's actual `Content-Type` and runs exactly one output gate. If the response shape contradicts what the agent declared, the request fails closed with `HTTP 502` — an agent can't disable its own guardrail by flipping `Content-Type`. + +### Why this sample streams structured frames + +The [basic invocations sample](../01-basic/) streams bare text chunks. This one wraps each chunk in a JSON object with a `type`, because `streamSelectors` matches on the `type` field of each frame. If your agent streams bare text, set `outputContentType: text` instead and omit `streamSelectors` — the platform then screens the raw stream. + +> [!IMPORTANT] +> `textField` is a **field name** on the event payload, not a path expression. Use `text`, not +> `$.text`. `eventType` and `textField` are exact, case-sensitive matches against top-level +> properties of the frame; you can't select a nested field. A selector that matches nothing +> contributes no text to moderation, so a mistyped `textField` silently leaves streamed output +> unscreened while the agent still reports the policy as attached. + +For a conceptual overview, see [Add a content safety guardrail to a hosted agent](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/add-hosted-agent-guardrails). + +> [!WARNING] +> Guardrails on this path fail **open**, and there are three independent ways to end up with an +> agent that reports `active` with no filtering: +> +> 1. `raiPolicyName` points at a policy that doesn't exist — including the `` +> placeholder that ships in [azure.yaml](azure.yaml). +> 1. The `invocationsModeration` block is missing. The policy attaches, but nothing on the +> invocations path is screened. +> 1. A path or selector matches nothing — a wrong `inputPaths` entry, or a `textField` that +> isn't a real field on your frames. +> +> Always run [Verify the guardrail](#verify-the-guardrail) before you rely on this agent's +> content safety. + +## Prerequisites + +1. An RAI policy created on your Foundry resource, and its full ARM resource ID. To create one, see [Configure guardrails and controls](https://learn.microsoft.com/en-us/azure/foundry/guardrails/how-to-create-guardrails). The ARM resource ID has this form: + + ```text + /subscriptions//resourceGroups//providers/Microsoft.CognitiveServices/accounts//raiPolicies/ + ``` + +1. **Azure Developer CLI (`azd`)** — [Install azd](https://learn.microsoft.com/en-us/azure/developer/azure-developer-cli/install-azd), then install the AI agent extension and authenticate: + + ```bash + azd ext install azure.ai.agents + azd auth login + ``` + + `invocationsModeration` requires **azure.ai.agents 1.0.0-beta.12 or later**. Earlier versions reject the block as an unknown field. + +## Configure the guardrail + +Set `raiPolicyName` to your RAI policy's full ARM resource ID in [azure.yaml](azure.yaml). Use the full ARM resource ID, not the bare policy name. + +If you change the agent's request or response shape, update `inputPaths`, `outputPaths`, and `streamSelectors` to match. `azd` validates the block's structure when it packages the agent, but it can't know your agent's field names — a well-formed block that points at the wrong fields deploys cleanly and screens nothing. + +## Option 1: Azure Developer CLI (`azd`) + +### Initialize the agent project + +No cloning required. Create a new folder and initialize from the manifest: + +```bash +mkdir my-guardrail-agent && cd my-guardrail-agent + +azd ai agent init -m https://github.com/microsoft-foundry/foundry-samples/blob/main/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/azure.yaml +``` + +Follow the prompts to configure your Foundry project and model deployment. If you don't have an existing Foundry project, `azd ai agent init` guides you through creating one. + +> [!NOTE] +> After init, confirm that `raiPolicyName` in the generated `azure.yaml` holds your policy's full ARM resource ID. + +### Provision Azure resources (if needed) + +If you don't already have a Foundry project and model deployment: + +```bash +azd provision +``` + +> [!IMPORTANT] +> If you provisioned a new Foundry project, it doesn't have your RAI policy yet. Before you deploy, [create an RAI policy](https://learn.microsoft.com/en-us/azure/foundry/guardrails/how-to-create-guardrails) on the provisioned account, then set `raiPolicyName` in the generated `azure.yaml` to that policy's full ARM resource ID. + +### Deploy to Foundry + +```bash +azd deploy +``` + +The platform applies the guardrail when it creates the agent version. For the full deployment guide, see [Deploy a hosted agent](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/deploy-hosted-agent). + +### Invoke the deployed agent + +The Invocations protocol uses a `{"message": "..."}` payload: + +```bash +azd ai agent invoke '{"message": "Write a short friendly hello message."}' +``` + +## Option 2: VS Code (Foundry Toolkit) + +### Prerequisites + +1. **VS Code** with the **[Foundry Toolkit](https://marketplace.visualstudio.com/items?itemName=ms-windows-ai-studio.windows-ai-studio)** extension installed. +2. For debugging Python in VS Code, install the **[Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python)** extension pack. + +### Set up the Python virtual environment + +- With Python 3.13 or later and [pipx](https://pipx.pypa.io/stable/installation/), install uv outside the project environment, then let uv create and synchronize the locked environment: + + ```bash + pipx install uv==0.11.7 + uv sync --frozen --python 3.13 + ``` +- Open the Command Palette (`Ctrl+Shift+P`), run **Python: Select Interpreter**, and select the `.venv` created by uv. + +### Run and debug the agent + +Press **F5** to start the agent. The agent starts and the **Agent Inspector** opens automatically. Chat with the agent in the Inspector. + +### Or run manually, then open the Inspector + +1. Set the required environment variables and sign in to Azure with the Azure CLI (`az login`). +2. Start the agent: `uv run --no-sync python main.py` (listens on `http://localhost:8088`). +3. Command Palette (`Ctrl+Shift+P`) → **Foundry Toolkit: Open Agent Inspector**, then send a message to test. + +### Deploy to Foundry + +1. Set `raiPolicyName` in `azure.yaml` to your policy's full ARM resource ID. +2. Run **Foundry Toolkit: Deploy Hosted Agent** and follow the wizard to deploy. + +## Verify the guardrail + +The guardrail runs as two independent gates. Check both — a working input gate says nothing about the output gate, which depends on different settings. + +### Input stage + +Send a prompt that violates your policy. The platform screens it before the agent runs and returns `HTTP 400`: + +```json +{ + "error": { + "code": "content_filter", + "message": "The request was blocked due to content safety policy violation at input stage. [Request ID: ]", + "type": "content_safety_error" + } +} +``` + +A prompt that passes the policy returns `HTTP 200` with the agent's response. + +To confirm that screening is scoped to the fields you declared, send the same violating text in a field that **isn't** listed in `inputPaths`. It returns `HTTP 200` — the platform screens only what you declared, not the whole request body. + +### Output stage + +A blocked **buffered** response also returns `HTTP 400`, with a message naming the output stage: + +```json +{ + "error": { + "code": "content_filter", + "message": "The response was blocked due to content safety policy violation at output stage.", + "type": "content_safety_error" + } +} +``` + +A blocked **streamed** response is different. Response headers are already sent before the agent's output is screened, so the status stays `HTTP 200`. The platform discards the events it was holding, sends a single error event, and ends the stream: + +```text +event: error +data: {"type":"error","code":"content_filter","message":"The response was blocked due to content safety policy violation."} +``` + +Handle this event in your client and treat it as terminal. **A `200` status alone doesn't mean the response passed the policy.** + +### If nothing is blocked + +Check in this order: + +1. `raiPolicyName` names a policy that **actually exists** on your account. List the policies and confirm the final segment matches one of them: + + ```bash + az rest --method get \ + --url "https://management.azure.com/subscriptions//resourceGroups//providers/Microsoft.CognitiveServices/accounts//raiPolicies?api-version=2024-10-01" \ + --query "value[].name" -o tsv + ``` + +1. The deployed agent version actually carries `invocationsModeration`. Fetch the agent version and confirm the block round-trips. +1. Your policy filters the category and severity you're testing, at the severity threshold you expect. Content that's detected but scores below the threshold isn't blocked. +1. `inputPaths` and `outputPaths` match your agent's real field names, and each `eventType` matches the `type` value your agent sends. `textField` is a bare field name such as `text`, not `$.text`. + +## Next steps + +- [Add a content safety guardrail to a hosted agent](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/add-hosted-agent-guardrails) — set a guardrail with `azd`, the Python SDK, or REST +- [Guardrails and controls overview](https://learn.microsoft.com/en-us/azure/foundry/guardrails/guardrails-overview) — what guardrails are and the risks they detect +- [Content safety guardrail (Responses protocol)](../../responses/16-content-safety-guardrail/) — the same guardrail on a protocol where the platform knows the message shape +- [Basic invocations agent](../01-basic/) — the agent this sample builds on +- [Manage hosted agents](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/manage-hosted-agent) — monitor and manage deployed agents diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/azure.yaml b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/azure.yaml new file mode 100644 index 000000000..79c1545fb --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/azure.yaml @@ -0,0 +1,74 @@ +# yaml-language-server: $schema=https://raw.githubusercontent.com/Azure/azure-dev/main/schemas/v1.0/azure.yaml.json + +requiredVersions: + azd: '>=1.27.1' + extensions: + # invocationsModeration requires azure.ai.agents 1.0.0-beta.12 or later. + azure.ai.agents: '>=1.0.0-beta.12' +name: agent-framework-content-safety-guardrail-invocations +services: + ai-project: + host: azure.ai.project + deployments: + - name: gpt-5.4-mini + model: + format: OpenAI + name: gpt-5.4-mini + version: '2026-03-17' + sku: + name: GlobalStandard + capacity: 10 + agent-framework-content-safety-guardrail-invocations: + host: azure.ai.agent + metadata: + tags: + - Agent Framework + - AI Agent Hosting + - Azure AI AgentServer + - Invocations Protocol + - Streaming + - Content Safety + - Guardrails + project: src/agent-framework-content-safety-guardrail-invocations + language: python + codeConfiguration: + runtime: python_3_13 + entryPoint: main.py + uses: + - ai-project + kind: hosted + name: agent-framework-content-safety-guardrail-invocations + displayName: Content safety guardrail (Agent Framework, Invocations) + description: An Agent Framework agent hosted by Foundry on the Invocations protocol with a Responsible AI content safety guardrail. Because the invocations protocol carries an agent-defined request and response shape, the agent also declares where its prompt and response text live so the platform can screen them. + protocols: + - protocol: invocations + version: 2.0.0 + env: + AZURE_AI_MODEL_DEPLOYMENT_NAME: ${AZURE_AI_MODEL_DEPLOYMENT_NAME} + container: + resources: + cpu: '0.5' + memory: 1Gi + policies: + - type: rai_policy + raiPolicyName: /subscriptions//resourceGroups//providers/Microsoft.CognitiveServices/accounts//raiPolicies/ + # Tells the platform where this agent's text lives. Without it the policy is + # attached but nothing on the invocations path is screened. + invocationsModeration: + # This agent answers both buffered and streamed requests. + responseMode: both + inputContentType: json + outputContentType: json + # Request body: {"message": "...", "stream": false} + inputPaths: + - $.message + # Buffered response body: {"response": "..."} + outputPaths: + - $.response + # Streamed response frames: {"type": "message.delta", "text": "..."} + # textField is a field name on the frame, not a path expression. + streamSelectors: + - eventType: message.delta + textField: text +infra: + provider: microsoft.foundry diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.azdignore b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.azdignore new file mode 100644 index 000000000..0c34457b0 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.azdignore @@ -0,0 +1 @@ +.env.example diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.dockerignore b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.dockerignore new file mode 100644 index 000000000..31ed562a7 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.dockerignore @@ -0,0 +1,7 @@ +.venv +__pycache__ +*.pyc +*.pyo +*.pyd +.Python +.env diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.env.example b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.env.example new file mode 100644 index 000000000..4d268b931 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/.env.example @@ -0,0 +1,2 @@ +FOUNDRY_PROJECT_ENDPOINT="..." +AZURE_AI_MODEL_DEPLOYMENT_NAME="..." \ No newline at end of file diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/Dockerfile b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/Dockerfile new file mode 100644 index 000000000..b2a151311 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/Dockerfile @@ -0,0 +1,27 @@ +FROM ghcr.io/astral-sh/uv:0.11.7 AS uv +FROM python:3.13-slim + +COPY --from=uv /uv /uvx /bin/ + +WORKDIR /app/user_agent +COPY pyproject.toml uv.lock uv.toml ./ +RUN uv sync --frozen --no-dev --no-install-project + +COPY . . + +EXPOSE 8088 + +# Precompile Python bytecode at build time so cold starts don't pay for it. +# These base images ship almost none of the standard library precompiled +# (~2% of stdlib .py files, on both Debian-slim and Azure Linux), so without +# this every new container recompiles hundreds of stdlib modules on first +# import. Dependencies are best-effort (`|| true`) so a stray unparsable file +# vendored by a third-party package can't fail the build; application code is +# compiled strictly so a syntax error surfaces at build time rather than at +# container start. +# PYTHONDONTWRITEBYTECODE is cleared for these commands only: it blocks +# bytecode *writes*, not *reads*, so images that set it still benefit. +RUN PYTHONDONTWRITEBYTECODE= .venv/bin/python -m compileall -q $(.venv/bin/python -c "import sysconfig as s; print(s.get_paths()['stdlib'], s.get_paths()['purelib'])") || true; \ + PYTHONDONTWRITEBYTECODE= .venv/bin/python -m compileall -q -x '[.]venv' . + +CMD ["/app/user_agent/.venv/bin/python", "main.py"] \ No newline at end of file diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/main.py b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/main.py new file mode 100644 index 000000000..2eca84b77 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/main.py @@ -0,0 +1,88 @@ +# Copyright (c) Microsoft. All rights reserved. + +import json +import os +from collections.abc import AsyncGenerator + +from agent_framework import Agent, AgentSession +from agent_framework.foundry import FoundryChatClient +from azure.ai.agentserver.invocations import InvocationAgentServerHost +from azure.identity import DefaultAzureCredential +from dotenv import load_dotenv +from starlette.requests import Request +from starlette.responses import JSONResponse, Response, StreamingResponse + +# Load environment variables from .env file +load_dotenv() + + +# In-memory session store — keyed by session ID. +# WARNING: This is lost on restart. Use durable storage in production. +_sessions: dict[str, AgentSession] = {} + +# Create the agent +client = FoundryChatClient( + project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"], + model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"], + credential=DefaultAzureCredential(), +) + +agent = Agent( + client=client, + instructions="You are a friendly assistant. Keep your answers brief.", + # History will be managed by the hosting infrastructure, thus there + # is no need to store history by the service. Learn more at: + # https://developers.openai.com/api/reference/resources/responses/methods/create + default_options={"store": False}, +) + +app = InvocationAgentServerHost() + + +def _sse(payload: dict) -> str: + """Serialize one Server-Sent Events frame. + + The guardrail's `streamSelectors` read the `type` field of each frame to decide + which frames carry model text, so every frame must be a JSON object with a + `type`. See the README for why this sample streams structured frames rather + than bare text. + """ + return f"data: {json.dumps(payload)}\n\n" + + +@app.invoke_handler +async def handle_invoke(request: Request): + """Handle streaming and buffered multi-turn chat over the invocations protocol.""" + data = await request.json() + session_id = request.state.session_id + + stream = data.get("stream", False) + user_message = data.get("message", None) + if user_message is None: + error = "Missing 'message' in request" + if stream: + return StreamingResponse(content=error, status_code=400) + return Response(content=error, status_code=400) + + session = _sessions.setdefault(session_id, AgentSession(session_id=session_id)) + + if stream: + + async def stream_response() -> AsyncGenerator[str]: + async for update in agent.run(user_message, session=session, stream=True): + if update.text: + yield _sse({"type": "message.delta", "text": update.text}) + yield _sse({"type": "message.done"}) + + return StreamingResponse( + stream_response(), + media_type="text/event-stream", + headers={"Cache-Control": "no-cache", "Connection": "keep-alive"}, + ) + + response = await agent.run([user_message], session=session, stream=stream) + return JSONResponse({"response": response.text}) + + +if __name__ == "__main__": + app.run() diff --git a/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/pyproject.toml b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/pyproject.toml new file mode 100644 index 000000000..18a3cbd88 --- /dev/null +++ b/samples/python/hosted-agents/agent-framework/invocations/02-content-safety-guardrail/src/agent-framework-content-safety-guardrail-invocations/pyproject.toml @@ -0,0 +1,10 @@ +[project] +name = "agent-framework-content-safety-guardrail-invocations" +version = "0.1.0" +description = 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