Agentic Loop Hook

Build a CustomLogger callback that intercepts a model response, fulfills tool calls server-side, and reruns the model — transparently to the caller.

Supported call types

• async only (sync calls do not trigger the hook)
• Non-streaming only (streaming responses cannot be inspected for tool calls)
• Works on both /v1/messages and /v1/chat/completions

Implement the callback

Override two methods on CustomLogger:

from litellm.integrations.custom_logger import CustomLogger
from litellm.types.integrations.custom_logger import AgenticLoopPlan, AgenticLoopRequestPatch

MY_TOOL = "my_tool"

class MyToolCallback(CustomLogger):

    async def async_should_run_agentic_loop(
        self, response, model, messages, tools, stream, custom_llm_provider, kwargs
    ):
        # Return (True, context_dict) if there are tool calls to handle
        content = getattr(response, "content", None) or []
        calls = [b for b in content if isinstance(b, dict)
                 and b.get("type") == "tool_use" and b.get("name") == MY_TOOL]
        if not calls:
            return False, {}
        return True, {"tool_calls": calls}

    async def async_build_agentic_loop_plan(
        self, tools, model, messages, response,
        anthropic_messages_provider_config,
        anthropic_messages_optional_request_params,
        logging_obj, stream, kwargs,
    ):
        calls = tools["tool_calls"]
        results = [f"result for {c['input']}" for c in calls]  # your logic here

        follow_up = messages + [
            {"role": "assistant", "content": [
                {"type": "tool_use", "id": c["id"], "name": c["name"], "input": c["input"]}
                for c in calls
            ]},
            {"role": "user", "content": [
                {"type": "tool_result", "tool_use_id": c["id"], "content": results[i]}
                for i, c in enumerate(calls)
            ]},
        ]
        return AgenticLoopPlan(
            run_agentic_loop=True,
            request_patch=AgenticLoopRequestPatch(messages=follow_up),
        )

For /v1/chat/completions, override async_build_chat_completion_agentic_loop_plan instead — same idea, optional_params replaces anthropic_messages_optional_request_params.

Register it

import litellm
litellm.callbacks = [MyToolCallback()]

Or in config.yaml:

litellm_settings:
  callbacks: ["my_module.MyToolCallback"]

AgenticLoopPlan fields

Field	Effect
run_agentic_loop=True + request_patch	Reruns the model with the patched request
response_override	Returns this value directly to the caller (no rerun)
terminate=True	Stops the loop, returns the current response
run_agentic_loop=False (default)	Skips; next callback is checked

AgenticLoopRequestPatch accepts: model, messages, tools, max_tokens, optional_params, kwargs.

Loop safety

• Default max reruns: 3 — override per-request with kwargs["max_agentic_loops"]
• Identical tool-call fingerprints abort the loop automatically
• Current depth is in kwargs["_agentic_loop_depth"]

Examples in this repo

• litellm/integrations/compression_interception/handler.py
• litellm/integrations/websearch_interception/handler.py