Azure Bing Grounding

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://\x3Cyour-resource>.ai.azure.com/api/projects/\x3Cyour-project>"
   
   # The ID of the Bing Grounding connection in your Azure AI Foundry Project
   BING_PROJECT_CONNECTION_ID="\x3Cyour-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="\x3Ctenant-id>"
   AZURE_CLIENT_ID="\x3Cclient-id>"
   AZURE_CLIENT_SECRET="\x3Cclient-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.