Merge PR #1874: preserve provider-specific tool-call fields

nanobot/agent/loop.py

@@ -203,14 +203,7 @@ class AgentLoop:
                     await on_progress(self._tool_hint(response.tool_calls), tool_hint=True)
 
                 tool_call_dicts = [
-                    {
-                        "id": tc.id,
-                        "type": "function",
-                        "function": {
-                            "name": tc.name,
-                            "arguments": json.dumps(tc.arguments, ensure_ascii=False)
-                        }
-                    }
+                    tc.to_openai_tool_call()
                     for tc in response.tool_calls
                 ]
                 messages = self.context.add_assistant_message(

nanobot/agent/subagent.py

@@ -126,14 +126,7 @@ class SubagentManager:
 
                 if response.has_tool_calls:
                     tool_call_dicts = [
-                        {
-                            "id": tc.id,
-                            "type": "function",
-                            "function": {
-                                "name": tc.name,
-                                "arguments": json.dumps(tc.arguments, ensure_ascii=False),
-                            },
-                        }
+                        tc.to_openai_tool_call()
                         for tc in response.tool_calls
                     ]
                     messages.append(build_assistant_message(

nanobot/providers/base.py

@@ -1,6 +1,7 @@
 """Base LLM provider interface."""
 
 import asyncio
+import json
 from abc import ABC, abstractmethod
 from dataclasses import dataclass, field
 from typing import Any
@@ -14,6 +15,24 @@ class ToolCallRequest:
     id: str
     name: str
     arguments: dict[str, Any]
+    provider_specific_fields: dict[str, Any] | None = None
+    function_provider_specific_fields: dict[str, Any] | None = None
+
+    def to_openai_tool_call(self) -> dict[str, Any]:
+        """Serialize to an OpenAI-style tool_call payload."""
+        tool_call = {
+            "id": self.id,
+            "type": "function",
+            "function": {
+                "name": self.name,
+                "arguments": json.dumps(self.arguments, ensure_ascii=False),
+            },
+        }
+        if self.provider_specific_fields:
+            tool_call["provider_specific_fields"] = self.provider_specific_fields
+        if self.function_provider_specific_fields:
+            tool_call["function"]["provider_specific_fields"] = self.function_provider_specific_fields
+        return tool_call
 
 
 @dataclass

nanobot/providers/litellm_provider.py

@@ -309,10 +309,17 @@ class LiteLLMProvider(LLMProvider):
             if isinstance(args, str):
                 args = json_repair.loads(args)
 
+            provider_specific_fields = getattr(tc, "provider_specific_fields", None) or None
+            function_provider_specific_fields = (
+                getattr(tc.function, "provider_specific_fields", None) or None
+            )
+
             tool_calls.append(ToolCallRequest(
                 id=_short_tool_id(),
                 name=tc.function.name,
                 arguments=args,
+                provider_specific_fields=provider_specific_fields,
+                function_provider_specific_fields=function_provider_specific_fields,
             ))
 
         usage = {}

tests/test_gemini_thought_signature.py

@@ -0,0 +1,53 @@
+from types import SimpleNamespace
+
+from nanobot.providers.base import ToolCallRequest
+from nanobot.providers.litellm_provider import LiteLLMProvider
+
+
+def test_litellm_parse_response_preserves_tool_call_provider_fields() -> None:
+    provider = LiteLLMProvider(default_model="gemini/gemini-3-flash")
+
+    response = SimpleNamespace(
+        choices=[
+            SimpleNamespace(
+                finish_reason="tool_calls",
+                message=SimpleNamespace(
+                    content=None,
+                    tool_calls=[
+                        SimpleNamespace(
+                            id="call_123",
+                            function=SimpleNamespace(
+                                name="read_file",
+                                arguments='{"path":"todo.md"}',
+                                provider_specific_fields={"inner": "value"},
+                            ),
+                            provider_specific_fields={"thought_signature": "signed-token"},
+                        )
+                    ],
+                ),
+            )
+        ],
+        usage=None,
+    )
+
+    parsed = provider._parse_response(response)
+
+    assert len(parsed.tool_calls) == 1
+    assert parsed.tool_calls[0].provider_specific_fields == {"thought_signature": "signed-token"}
+    assert parsed.tool_calls[0].function_provider_specific_fields == {"inner": "value"}
+
+
+def test_tool_call_request_serializes_provider_fields() -> None:
+    tool_call = ToolCallRequest(
+        id="abc123xyz",
+        name="read_file",
+        arguments={"path": "todo.md"},
+        provider_specific_fields={"thought_signature": "signed-token"},
+        function_provider_specific_fields={"inner": "value"},
+    )
+
+    message = tool_call.to_openai_tool_call()
+
+    assert message["provider_specific_fields"] == {"thought_signature": "signed-token"}
+    assert message["function"]["provider_specific_fields"] == {"inner": "value"}
+    assert message["function"]["arguments"] == '{"path": "todo.md"}'