Tool calling in relay mode

The gateway supports tool (function) calling on Chat Completions, the Responses API, and Messages. Declare your tools in the request; if the model decides to use one, the gateway streams the tool call back to you.

Relay mode

The gateway runs tools in relay mode — it never executes them. It declares your tool definitions to the model, returns the call the model wants to make, and stops. You run the tool and send the result back on the next turn. A typical loop:

Send a request with tools (and optionally tool_choice).
The model responds with one or more tool calls and a tool-call finish reason instead of final text.
Run each tool yourself and append the result to the conversation.
Send the updated conversation back; the model continues (more tool calls, or a final text answer).

Because the gateway speaks each provider’s native wire format, the official SDKs’ tool-calling helpers work unchanged — point them at the gateway base URL and key.

Chat Completions

Request — tools[] are function definitions; tool_choice is auto (default), none, required, or { "type": "function", "function": { "name": "..." } }.

curl https://api.impossibl.com/v1/chat/completions \
  -H "Authorization: Bearer imp-rt-..." \
  -H 'content-type: application/json' \
  -d '{
    "model": "openai/gpt-4o-mini",
    "messages": [{"role":"user","content":"What is the weather in Paris?"}],
    "tools": [{
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get the current weather for a city",
        "parameters": {
          "type": "object",
          "properties": { "city": { "type": "string" } },
          "required": ["city"]
        }
      }
    }]
  }'

Response — the assistant message carries tool_calls and finish_reason is tool_calls. Each call’s function.arguments is a JSON-encoded string.

{
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": null,
      "tool_calls": [{
        "id": "call_abc",
        "type": "function",
        "function": { "name": "get_weather", "arguments": "{\"city\":\"Paris\"}" }
      }]
    },
    "finish_reason": "tool_calls"
  }]
}

Returning the result — append the assistant message and a tool message whose tool_call_id matches, then send the conversation again:

{ "role": "tool", "tool_call_id": "call_abc", "content": "{\"tempC\":18}" }

Streaming — tool calls arrive as delta.tool_calls[] fragments. The first fragment for a call carries id, type, and function.name; later fragments stream function.arguments text. The index field correlates fragments of the same call.

Responses API

Request — Responses flattens the function fields onto each tool. tool_choice is auto / none / required / { "type": "function", "name": "..." }.

curl https://api.impossibl.com/v1/responses \
  -H "Authorization: Bearer imp-rt-..." \
  -H 'content-type: application/json' \
  -d '{
    "model": "openai/gpt-4o-mini",
    "input": "What is the weather in Paris?",
    "tools": [{
      "type": "function",
      "name": "get_weather",
      "description": "Get the current weather for a city",
      "parameters": {
        "type": "object",
        "properties": { "city": { "type": "string" } },
        "required": ["city"]
      }
    }]
  }'

Response — the model emits a function_call output item with a call_id and a JSON-string arguments:

{ "type": "function_call", "id": "fc_1", "call_id": "call_abc",
  "name": "get_weather", "arguments": "{\"city\":\"Paris\"}", "status": "completed" }

Returning the result — add a function_call_output input item referencing the same call_id:

{ "type": "function_call_output", "call_id": "call_abc", "output": "{\"tempC\":18}" }

Streaming — a response.output_item.added event opens the function_call item, response.function_call_arguments.delta events stream the argument text, and response.function_call_arguments.done closes it.

Messages (Anthropic)

Request — tools[] use input_schema; tool_choice is { "type": "auto" }, { "type": "any" }, { "type": "tool", "name": "..." }, or { "type": "none" }. (A bare claude-... model id routes to Anthropic; any provider/model id also works here — see SDKs & integrations.)

curl https://api.impossibl.com/v1/messages \
  -H "x-api-key: imp-rt-..." \
  -H 'content-type: application/json' \
  -d '{
    "model": "claude-haiku-4-5",
    "max_tokens": 256,
    "messages": [{"role":"user","content":"What is the weather in Paris?"}],
    "tools": [{
      "name": "get_weather",
      "description": "Get the current weather for a city",
      "input_schema": {
        "type": "object",
        "properties": { "city": { "type": "string" } },
        "required": ["city"]
      }
    }]
  }'

Response — a tool_use content block (with a parsed input object) and stop_reason: "tool_use":

{ "type": "tool_use", "id": "toolu_1", "name": "get_weather",
  "input": { "city": "Paris" } }

Returning the result — send a user turn containing a tool_result block referencing the tool_use_id:

{ "role": "user", "content": [
  { "type": "tool_result", "tool_use_id": "toolu_1", "content": "{\"tempC\":18}" }
]}

Streaming — the tool_use block opens with a content_block_start, its input streams as content_block_delta events of type input_json_delta (partial_json), and closes with content_block_stop.

Across all three surfaces, arguments arrive as JSON text (a string for OpenAI-style calls, streamed partial_json for Anthropic). Parse them yourself before running the tool, and tolerate empty/partial fragments while streaming.

Gemini thought signatures

Gemini 3 models attach an opaque signature to the first function call of each step and reject the tool-result turn unless it comes back verbatim. The gateway round-trips it for you: on Chat Completions the tool call carries extra_content.google.thought_signature (Google’s OpenAI-compat mapping — in streaming it rides a tool_calls fragment), and on the Responses API the function_call item carries the same extra_content field. Send the tool call back exactly as you received it — clients that echo the assistant message unchanged (the OpenAI SDK and Vercel AI SDK loops already do) need no extra code. The Gemini-native endpoint uses Google’s own Part.thoughtSignature unchanged.

Get started

Core concepts

Using the API

Relay mode

Chat Completions

Responses API

Messages (Anthropic)

Gemini thought signatures

​Relay mode

​Chat Completions

​Responses API

​Messages (Anthropic)

​Gemini thought signatures

Relay mode

Chat Completions

Responses API

Messages (Anthropic)

Gemini thought signatures