Grounding with Bing Search (Microsoft Foundry)

Grounding with Bing Search runs a web search through a model deployment in a Microsoft Foundry project, using the project's Responses API. The model performs the search and returns cited results, so search traffic stays inside your Foundry project and is billed by Azure

There are two modes, chosen by whether you set a Grounding with Bing connection:

• Web search mode (default): the model's built-in web_search tool. It needs no Bing resource and pays no per-search Bing fee, so LiteLLM tracks it at zero cost
• Connection mode: the paid Grounding with Bing (G1) connection, selected with BING_GROUNDING_CONNECTION_ID. LiteLLM tracks it at the bing_grounding/search map price

Both modes call the same model deployment, whose token usage is billed by Azure on your Foundry account

Provider ID	bing_grounding
Project endpoint	BING_GROUNDING_PROJECT_ENDPOINT, or api_base
Model deployment	BING_GROUNDING_MODEL (required)
Auth (Azure API key)	api_key, sent as the api-key header
Auth (Entra token)	BING_GROUNDING_TOKEN, sent as Authorization: Bearer
Auth (azure-identity)	any DefaultAzureCredential source, for scope https://ai.azure.com/.default
Grounding with Bing connection	BING_GROUNDING_CONNECTION_ID (optional, switches to connection mode)

The project endpoint looks like https://<account>.services.ai.azure.com/api/projects/<project>

LiteLLM Python SDK

Grounding with Bing Search

import os
from litellm import search

os.environ["BING_GROUNDING_PROJECT_ENDPOINT"] = "https://<account>.services.ai.azure.com/api/projects/<project>"
os.environ["BING_GROUNDING_MODEL"] = "gpt-4.1"
os.environ["BING_GROUNDING_TOKEN"] = "<entra bearer token>"

response = search(
    query="latest AI developments",
    search_provider="bing_grounding",
    max_results=5
)

for result in response.results:
    print(f"{result.title}: {result.url}")
    print(f"Snippet: {result.snippet}\n")

Authentication

Pass an Azure API key per call, and it rides the api-key header:

Grounding with Bing Search with an Azure API key

response = search(
    query="latest AI developments",
    search_provider="bing_grounding",
    api_key=os.environ["AZURE_AI_API_KEY"]
)

Or omit BING_GROUNDING_TOKEN and api_key to mint an Entra token from the standard azure-identity chain (AZURE_CLIENT_ID / AZURE_CLIENT_SECRET / AZURE_TENANT_ID, a shared profile, managed identity, or any other DefaultAzureCredential source) for scope https://ai.azure.com/.default

Connection mode (paid Grounding with Bing)

Set BING_GROUNDING_CONNECTION_ID to the project connection for a Grounding with Bing (G1) resource. The model then searches through that paid connection instead of the built-in tool, and LiteLLM tracks the bing_grounding/search cost:

Grounding with Bing Search in connection mode

os.environ["BING_GROUNDING_CONNECTION_ID"] = (
    "/subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.CognitiveServices"
    "/accounts/<account>/projects/<project>/connections/<bing-connection>"
)

response = search(
    query="latest AI developments",
    search_provider="bing_grounding",
    max_results=5
)

LiteLLM AI Gateway

1. Setup config.yaml

config.yaml

search_tools:
  - search_tool_name: bing-grounding-search
    litellm_params:
      search_provider: bing_grounding

Set BING_GROUNDING_PROJECT_ENDPOINT, BING_GROUNDING_MODEL, and one of the auth options in the proxy's environment. BING_GROUNDING_CONNECTION_ID is optional and switches to connection mode

2. Start the proxy

litellm --config /path/to/config.yaml

# RUNNING on http://0.0.0.0:4000

3. Test the search endpoint

Test Request

curl http://0.0.0.0:4000/v1/search/bing-grounding-search \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "latest AI developments",
    "max_results": 5
  }'

Web search interception

Grounding with Bing Search is a natural backend for web search interception, which serves a model's native web_search tool from a search provider. Point the interception at the configured tool:

config.yaml

model_list:
  - model_name: gpt-5-mini
    litellm_params:
      model: openai/gpt-5-mini
      api_key: os.environ/OPENAI_API_KEY

search_tools:
  - search_tool_name: bing-grounding-search
    litellm_params:
      search_provider: bing_grounding

litellm_settings:
  callbacks: ["websearch_interception"]
  websearch_interception_params:
    enabled_providers: ["openai"]
    search_tool_name: bing-grounding-search

Unified Parameters

Unified spec parameter	Web search mode	Connection mode
max_results	caps the returned results after the fact (the built-in tool has no count knob)	maps to the search configuration's count
country	maps to the approximate user_location	ignored (the connection's market wants a full locale, which a bare country code cannot fill)
search_domain_filter	ignored (no equivalent)	ignored (no equivalent)
max_tokens_per_page	ignored (no equivalent)	ignored (no equivalent)

Notes

Web search mode is tracked at zero cost because the built-in web_search tool pays no per-search Bing fee. Connection mode is tracked at the bing_grounding/search map price, the Grounding with Bing (G1) per-search fee. The model deployment's token usage is billed separately by Azure on your Foundry account

The Entra token (BING_GROUNDING_TOKEN or one minted via azure-identity) is only sent to the endpoint configured in BING_GROUNDING_PROJECT_ENDPOINT, so a caller-supplied api_base cannot exfiltrate it. A caller-supplied api_key is treated as an Azure API key and sent in the api-key header instead

LiteLLM posts to <project-endpoint>/openai/v1/responses, appending the path automatically if the endpoint does not already end in it

If the grounded search comes back failed or incomplete with no results, LiteLLM raises an error rather than returning an empty success, so a failed search is not logged as a normal zero-result hit