Azure Bing Grounding

Web search grounding via Azure Foundry and Bing Grounding Search tool. Use when the user needs up-to-date information searched from the web via Azure AI Agents. Returns the synthesized answer and URL citations.

Use the bundled Python script to perform grounded searches using Azure Foundry's Agent Service and the Bing Grounding Search Tool.

Requirements

1. Required Python packages:

   pip install azure-identity azure-ai-agents
   

2. Authentication:

   • Ensure Azure CLI is logged in (az login), OR
   • Set Azure Service Principal / Managed Identity credentials compatible with DefaultAzureCredential or ClientSecretCredential.

3. Environment Variables: Add the following to your ~/.openclaw/.env file or export them in your shell:

   # Your Azure AI Foundry project endpoint
   FOUNDRY_PROJECT_ENDPOINT="https://<your-resource>.ai.azure.com/api/projects/<your-project>"
   
   # The ID of the Bing Grounding connection in your Azure AI Foundry Project
   BING_PROJECT_CONNECTION_ID="<your-connection-id>"
   
   # Default model deployment name (optional, defaults to gpt-4o)
   FOUNDRY_MODEL_DEPLOYMENT_NAME="gpt-4o"
   
   # (Optional) Service Principal Credentials if not using DefaultAzureCredential
   AZURE_TENANT_ID="<tenant-id>"
   AZURE_CLIENT_ID="<client-id>"
   AZURE_CLIENT_SECRET="<client-secret>"
   

Commands

Run from the OpenClaw workspace:

# Raw JSON output (default)
python3 {baseDir}/scripts/bing_grounding.py --query "What is the latest AI news today?"

# Markdown human-readable output
python3 {baseDir}/scripts/bing_grounding.py --query "What is the latest AI news today?" --format md

# Use a specific model deployment (default is gpt-4o)
python3 {baseDir}/scripts/bing_grounding.py --query "Weather in Seattle?" --model "gpt-4o-mini"

Output

Returns a generated response synthesized by the Azure AI Agent based on Bing Search results, along with the source URL citations.