Hosted-TextRag
A hosted agent with Retrieval Augmented Generation (RAG) capabilities using TextSearchProvider. The agent grounds its answers in product documentation by running a search before each model invocation, then citing the source in its response.
This sample demonstrates how to add knowledge grounding to a hosted agent without requiring an external search index — using a mock search function that can be replaced with Azure AI Search or any other provider.
Prerequisites
- .NET 10 SDK
- A Foundry project with a deployed model (e.g.,
gpt-4o) - Azure CLI logged in (
az login)
Configuration
Copy the template and fill in your project endpoint:
cp .env.example .env
Edit .env and set your Foundry project endpoint:
FOUNDRY_PROJECT_ENDPOINT=https://<your-account>.services.ai.azure.com/api/projects/<your-project>
ASPNETCORE_URLS=http://+:8088
ASPNETCORE_ENVIRONMENT=Development
FOUNDRY_MODEL=gpt-4o
AZURE_BEARER_TOKEN=
Note:
.envis gitignored. The.env.exampletemplate is checked in as a reference.
Running directly (contributors)
This project uses ProjectReference to build against the local Agent Framework source.
cd dotnet/samples/04-hosting/FoundryHostedAgents/responses/Hosted-TextRag
AGENT_NAME=hosted-text-rag dotnet run
The agent will start on http://localhost:8088.
Test it
Using the Azure Developer CLI:
azd ai agent invoke --local "What is your return policy?"
azd ai agent invoke --local "How long does shipping take?"
azd ai agent invoke --local "How do I clean my tent?"
Or with curl:
curl -X POST http://localhost:8088/responses \
-H "Content-Type: application/json" \
-d '{"input": "What is your return policy?", "model": "hosted-text-rag"}'
Running with Docker
Since this project uses ProjectReference, use Dockerfile.contributor which takes a pre-published output.
1. Publish for the container runtime (Linux Alpine)
dotnet publish -c Debug -f net10.0 -r linux-musl-x64 --self-contained false -o out
2. Build the Docker image
docker build -f Dockerfile.contributor -t hosted-text-rag .
3. Run the container
Generate a bearer token on your host and pass it to the container:
# Generate token (expires in ~1 hour)
export AZURE_BEARER_TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
# Run with token
docker run --rm -p 8088:8088 \
-e AGENT_NAME=hosted-text-rag \
-e AZURE_BEARER_TOKEN=$AZURE_BEARER_TOKEN \
--env-file .env \
hosted-text-rag
4. Test it
Using the Azure Developer CLI:
azd ai agent invoke --local "What is your return policy?"
How RAG works in this sample
The TextSearchProvider runs a mock search before each model invocation:
| User query contains | Search result injected |
|---|---|
| "return" or "refund" | Contoso Outdoors Return Policy |
| "shipping" | Contoso Outdoors Shipping Guide |
| "tent" or "fabric" | TrailRunner Tent Care Instructions |
The model receives the search results as additional context and cites the source in its response. In production, replace MockSearchAsync with a call to Azure AI Search or your preferred search provider.
Deploying to Foundry (azd spec)
This sample includes an azd manifest (agent.manifest.yaml) and hosted agent spec (agent.yaml) for deployment to Foundry.
Initialize an azd project from this sample's manifest:
mkdir hosted-text-rag && cd hosted-text-rag
azd ai agent init -m https://github.com/microsoft/agent-framework/blob/main/dotnet/samples/04-hosting/FoundryHostedAgents/responses/Hosted-TextRag/agent.manifest.yaml
Then deploy:
azd deploy
If you need to override defaults, set deployment-time environment variables in the azd environment before deploying:
azd env set AGENT_NAME hosted-text-rag
azd env set AZURE_AI_MODEL_DEPLOYMENT_NAME gpt-4o
For end-to-end hosted agent deployment guidance, see the official deployment guide.
NuGet package users
If you are consuming the Agent Framework as a NuGet package (not building from source), use the standard Dockerfile instead of Dockerfile.contributor. See the commented section in HostedTextRag.csproj for the PackageReference alternative.