Fix native tool-calling follow-up round on Gemini and Ollama (#867)

The agent's multi-round (tool-result) follow-up request was rejected with
HTTP 400 on two providers, so tools ran but the agent never produced an answer:

- OpenAI-compatible streaming (Gemini 3) dropped the per-call thought_signature
  and collided parallel tool calls, which arrive with index=None: they all
  landed in slot 0, overwriting the first call's name and corrupting its
  arguments by concatenation, so the follow-up request 400'd. Capture and replay
  each call's extra_content (thought_signature), and give every parallel call
  its own accumulator slot (allocated above the max key, so sparse or mixed
  indices can't collide).
- Native Ollama /api/chat expects object tool-call arguments, but Odysseus
  carries them as a JSON string, which Ollama rejected ("Value looks like
  object, but can't find closing '}' symbol"). Convert them to objects in the
  Ollama payload builder.

Both compose with the no-prose null-content sanitize fix from #862.

Tested: python -m pytest tests/test_llm_core_streaming.py
tests/test_llm_core_ollama.py tests/test_agent_loop.py (53 pass), and
python -m py_compile src/llm_core.py src/agent_loop.py.

src/agent_loop.py

@@ -1123,6 +1123,11 @@ def _append_tool_results(
                     "name": tc.get("name", ""),
                     "arguments": tc.get("arguments", "{}"),
                 },
+                # Gemini 3 requires the opaque thought_signature it returned with
+                # each function call to be echoed back on the follow-up turn, or
+                # the next request 400s. Replay it when present; other providers
+                # never emit it (their payload builders just ignore the field).
+                **({"extra_content": tc["extra_content"]} if tc.get("extra_content") else {}),
             }
             for j, tc in enumerate(native_tool_calls)
         ]

src/llm_core.py

@@ -194,6 +194,43 @@ def _normalize_ollama_url(url: str) -> str:
     return base.rstrip("/") + "/chat"
 
 
+def _ollama_normalize_tool_messages(messages: List[Dict]) -> List[Dict]:
+    """Adapt Odysseus' canonical OpenAI-style messages to native Ollama /api/chat.
+
+    Odysseus carries assistant tool calls in the OpenAI shape, where
+    `function.arguments` is a JSON *string*. Native Ollama expects it to be a
+    JSON *object*; given the string it fails the whole request with HTTP 400
+    "Value looks like object, but can't find closing '}' symbol", which aborts
+    every follow-up (tool-result) round. Parse the arguments back into an object
+    here, on a shallow copy, leaving non-tool messages untouched. The opaque
+    Gemini `extra_content` (thought_signature) is dropped — it is meaningless to
+    Ollama and only matters when the conversation is replayed to Gemini.
+    """
+    out: List[Dict] = []
+    for m in messages or []:
+        tcs = m.get("tool_calls") if isinstance(m, dict) else None
+        if not tcs:
+            out.append(m)
+            continue
+        new_calls = []
+        for tc in tcs:
+            fn = tc.get("function") or {}
+            args = fn.get("arguments")
+            if isinstance(args, str):
+                try:
+                    args = json.loads(args) if args.strip() else {}
+                except (json.JSONDecodeError, TypeError):
+                    args = {}
+            call: Dict = {"function": {"name": fn.get("name", ""), "arguments": args or {}}}
+            if tc.get("id"):
+                call["id"] = tc["id"]
+            new_calls.append(call)
+        nm = dict(m)
+        nm["tool_calls"] = new_calls
+        out.append(nm)
+    return out
+
+
 def _build_ollama_payload(
     model: str,
     messages: List[Dict],
@@ -204,7 +241,7 @@ def _build_ollama_payload(
 ) -> Dict:
     payload: Dict = {
         "model": model,
-        "messages": messages,
+        "messages": _ollama_normalize_tool_messages(messages),
         "stream": stream,
     }
     options: Dict = {}
@@ -1040,6 +1077,7 @@ async def stream_llm(url: str, model: str, messages: List[Dict], temperature: fl
     # ── OpenAI-compatible streaming ──
     # Accumulate native tool_calls across streaming chunks
     _tc_acc: Dict[int, Dict] = {}  # index -> {id, name, arguments}
+    _tc_last_idx = [-1]  # most-recently-touched slot, for providers that omit `index`
     # For thinking models: prepend <think> to first content delta so frontend
     # can detect thinking-in-progress (some models output </think> but no <think>)
     _thinking_model = _supports_thinking(model)
@@ -1105,12 +1143,41 @@ async def stream_llm(url: str, model: str, messages: List[Dict], temperature: fl
                                             yield f'data: {json.dumps({"delta": content})}\n\n'
                                         # Native tool calls — accumulate across chunks
                                         for tc in delta.get("tool_calls") or []:
-                                            idx = tc.get("index", 0)
+                                            func = tc.get("function") or {}
+                                            raw_idx = tc.get("index")
+                                            if raw_idx is None:
+                                                # Gemini's OpenAI-compat layer omits `index` on
+                                                # parallel tool calls (every delta arrives as
+                                                # index=None) and sends each call complete in one
+                                                # delta. Without this, all parallel calls collide
+                                                # into slot 0 — later calls overwrite the first's
+                                                # name and CORRUPT its arguments by concatenation,
+                                                # so only one malformed call survives and the
+                                                # follow-up round 400s. A function name marks the
+                                                # start of a new call → allocate a fresh slot;
+                                                # an arg-only continuation attaches to the last.
+                                                if func.get("name") or _tc_last_idx[0] < 0:
+                                                    # Next free slot ABOVE any existing key (not
+                                                    # len()), so a provider mixing integer indices
+                                                    # with index=None can never collide.
+                                                    idx = max(_tc_acc, default=-1) + 1
+                                                else:
+                                                    idx = _tc_last_idx[0]
+                                            else:
+                                                idx = raw_idx
+                                            _tc_last_idx[0] = idx
                                             if idx not in _tc_acc:
                                                 _tc_acc[idx] = {"id": "", "name": "", "arguments": ""}
                                             if tc.get("id"):
                                                 _tc_acc[idx]["id"] = tc["id"]
-                                            func = tc.get("function") or {}
+                                            # Gemini 3 returns an opaque thought_signature in
+                                            # extra_content on the function-call delta. It MUST be
+                                            # echoed back on the assistant tool_call next round or the
+                                            # follow-up request 400s ("Function call is missing a
+                                            # thought_signature"). Preserve it verbatim; other
+                                            # providers never send it, so this is a no-op for them.
+                                            if tc.get("extra_content"):
+                                                _tc_acc[idx]["extra_content"] = tc["extra_content"]
                                             if func.get("name"):
                                                 _tc_acc[idx]["name"] = func["name"]
                                             if "arguments" in func:

tests/test_agent_loop.py

@@ -301,3 +301,39 @@ class TestAppendToolResultsNativeContent:
         assert messages[0]["content"] == "thinking..."
         assert messages[1]["role"] == "user"
         assert "tool output" in messages[1]["content"]
+
+
+class TestAppendToolResultsThoughtSignature:
+    """Gemini 3 returns an opaque thought_signature (in extra_content) with each
+    function call and rejects the follow-up turn with HTTP 400 unless it is
+    echoed back on the assistant tool_call. _append_tool_results must replay it
+    when present, and omit the field entirely otherwise (other providers never
+    send it)."""
+
+    def test_extra_content_is_replayed_when_present(self):
+        native = [{
+            "id": "call_g",
+            "name": "app_api",
+            "arguments": '{"action": "get_memory"}',
+            "extra_content": {"google": {"thought_signature": "EuIDCt8DAQ=="}},
+        }]
+        messages = []
+        _append_tool_results(
+            messages, "", native, [{}], ["mem"],
+            used_native=True, round_num=1,
+        )
+        tc = messages[0]["tool_calls"][0]
+        assert tc["extra_content"] == {"google": {"thought_signature": "EuIDCt8DAQ=="}}
+        # function payload is still well-formed alongside it
+        assert tc["function"]["name"] == "app_api"
+        assert tc["id"] == "call_g"
+
+    def test_no_extra_content_key_when_absent(self):
+        native = [{"id": "call_o", "name": "app_api", "arguments": "{}"}]
+        messages = []
+        _append_tool_results(
+            messages, "", native, [{}], ["r"],
+            used_native=True, round_num=1,
+        )
+        # No empty/None extra_content leaks onto non-Gemini tool calls.
+        assert "extra_content" not in messages[0]["tool_calls"][0]

tests/test_llm_core_ollama.py

@@ -41,3 +41,75 @@ def test_llm_call_posts_native_ollama_payload(monkeypatch):
     assert seen["headers"]["Authorization"] == "Bearer ollama-key"
     assert seen["json"]["stream"] is False
     assert seen["json"]["options"] == {"temperature": 0.2, "num_predict": 7}
+
+
+# ---------------------------------------------------------------------------
+# Tool-call argument serialization for native Ollama
+#
+# Odysseus carries assistant tool calls in the OpenAI shape, where
+# `function.arguments` is a JSON *string*. Native Ollama /api/chat expects a
+# JSON *object* and rejects the string form with HTTP 400 ("Value looks like
+# object, but can't find closing '}' symbol"), aborting every follow-up
+# (tool-result) round. _build_ollama_payload must parse it back to an object.
+# ---------------------------------------------------------------------------
+
+def _assistant_tool_call_msgs():
+    """A canonical OpenAI-style assistant tool call + tool result, as produced by
+    agent_loop._append_tool_results (arguments are a JSON string)."""
+    return [
+        {"role": "user", "content": "what do you know about me?"},
+        {
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [
+                {
+                    "id": "call_0",
+                    "type": "function",
+                    "function": {"name": "app_api", "arguments": '{"action": "get_memory"}'},
+                }
+            ],
+        },
+        {"role": "tool", "tool_call_id": "call_0", "content": "Memory: user is James."},
+    ]
+
+
+def test_ollama_payload_parses_string_arguments_to_object():
+    payload = llm_core._build_ollama_payload(
+        "gpt-oss:120b", _assistant_tool_call_msgs(), temperature=0.0, max_tokens=0,
+    )
+    asst = payload["messages"][1]
+    args = asst["tool_calls"][0]["function"]["arguments"]
+    # The whole point: arguments must be a dict, not the JSON string.
+    assert args == {"action": "get_memory"}
+    assert not isinstance(args, str)
+    assert asst["tool_calls"][0]["function"]["name"] == "app_api"
+    assert asst["tool_calls"][0]["id"] == "call_0"
+
+
+def test_ollama_payload_drops_gemini_thought_signature():
+    """A cross-provider fallback can hand Ollama a tool call that still carries
+    Gemini's opaque extra_content; it is meaningless to Ollama and must not leak."""
+    msgs = _assistant_tool_call_msgs()
+    msgs[1]["tool_calls"][0]["extra_content"] = {"google": {"thought_signature": "AAAA"}}
+    payload = llm_core._build_ollama_payload(
+        "gpt-oss:120b", msgs, temperature=0.0, max_tokens=0,
+    )
+    tc = payload["messages"][1]["tool_calls"][0]
+    assert "extra_content" not in tc
+    assert tc["function"]["arguments"] == {"action": "get_memory"}
+
+
+def test_ollama_payload_leaves_plain_messages_untouched():
+    msgs = [{"role": "user", "content": "hello"}]
+    payload = llm_core._build_ollama_payload("m", msgs, temperature=0.0, max_tokens=0)
+    assert payload["messages"][0] == {"role": "user", "content": "hello"}
+
+
+def test_ollama_payload_tolerates_malformed_arguments():
+    msgs = [{
+        "role": "assistant",
+        "tool_calls": [{"function": {"name": "x", "arguments": "{not json"}}],
+    }]
+    payload = llm_core._build_ollama_payload("m", msgs, temperature=0.0, max_tokens=0)
+    # Falls back to an empty object rather than raising.
+    assert payload["messages"][0]["tool_calls"][0]["function"]["arguments"] == {}

tests/test_llm_core_streaming.py

@@ -0,0 +1,151 @@
+"""Streaming tool-call accumulation tests for the OpenAI-compatible path.
+
+Regression for Gemini's OpenAI-compat layer, which (a) attaches an opaque
+thought_signature in `extra_content` on the function-call delta and (b) omits
+`index` on PARALLEL tool calls — every parallel delta arrives as index=None.
+The accumulator must give each parallel call its own slot (otherwise they
+collide into slot 0, overwriting the first call's name and concatenating —
+corrupting — its arguments) and must preserve extra_content per call.
+"""
+import json
+import asyncio
+
+from src import llm_core
+
+
+class _FakeResp:
+    def __init__(self, lines):
+        self._lines = lines
+        self.status_code = 200
+
+    async def aiter_lines(self):
+        for ln in self._lines:
+            yield ln
+
+    async def aread(self):
+        return b""
+
+
+class _FakeStreamCtx:
+    def __init__(self, lines):
+        self._lines = lines
+
+    async def __aenter__(self):
+        return _FakeResp(self._lines)
+
+    async def __aexit__(self, *a):
+        return False
+
+
+class _FakeClient:
+    def __init__(self, lines):
+        self._lines = lines
+
+    def stream(self, method, url, **kw):
+        return _FakeStreamCtx(self._lines)
+
+
+def _drive(monkeypatch, lines, model="gemini-3.1-pro-preview-customtools"):
+    """Run stream_llm against a canned SSE line list; return parsed events."""
+    monkeypatch.setattr(llm_core, "_get_http_client", lambda: _FakeClient(lines))
+    monkeypatch.setattr(llm_core, "_is_host_dead", lambda u: False)
+    monkeypatch.setattr(llm_core, "note_model_activity", lambda *a, **k: None)
+    monkeypatch.setattr(llm_core, "_clear_host_dead", lambda *a, **k: None)
+
+    async def run():
+        events = []
+        async for chunk in llm_core.stream_llm(
+            "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions",
+            model,
+            [{"role": "user", "content": "hi"}],
+            headers={"Authorization": "Bearer k"},
+            tools=[{"type": "function", "function": {"name": "x", "parameters": {}}}],
+        ):
+            for ln in chunk.split("\n"):
+                ln = ln.strip()
+                if ln.startswith("data: ") and ln[6:] != "[DONE]":
+                    try:
+                        events.append(json.loads(ln[6:]))
+                    except ValueError:
+                        pass
+        return events
+
+    return asyncio.run(run())
+
+
+def _sse(delta):
+    return "data: " + json.dumps({"choices": [{"delta": delta}]})
+
+
+def test_parallel_calls_with_null_index_do_not_collide(monkeypatch):
+    # Two parallel calls, each complete in one delta, both with index=None
+    # (exactly what Gemini's OpenAI-compat layer emits). Only the first carries
+    # a thought_signature.
+    lines = [
+        _sse({"tool_calls": [{
+            "index": None, "id": "call_a", "type": "function",
+            "function": {"name": "get_memory", "arguments": "{}"},
+            "extra_content": {"google": {"thought_signature": "SIG0"}},
+        }]}),
+        _sse({"tool_calls": [{
+            "index": None, "id": "call_b", "type": "function",
+            "function": {"name": "bash", "arguments": '{"command":"echo hi"}'},
+        }]}),
+        "data: [DONE]",
+    ]
+    events = _drive(monkeypatch, lines)
+    calls = next(e["calls"] for e in events if e.get("type") == "tool_calls")
+    assert len(calls) == 2, f"parallel calls collided: {calls}"
+    by_name = {c["name"]: c for c in calls}
+    assert set(by_name) == {"get_memory", "bash"}
+    # arguments are NOT corrupted by concatenation
+    assert by_name["get_memory"]["arguments"] == "{}"
+    assert by_name["bash"]["arguments"] == '{"command":"echo hi"}'
+    # signature preserved on the first call only, exactly as received
+    assert by_name["get_memory"]["extra_content"] == {"google": {"thought_signature": "SIG0"}}
+    assert "extra_content" not in by_name["bash"]
+
+
+def test_single_call_chunked_arguments_still_accumulate(monkeypatch):
+    # Conformant OpenAI style: index present, arguments streamed in pieces.
+    lines = [
+        _sse({"tool_calls": [{"index": 0, "id": "c", "type": "function",
+                              "function": {"name": "search", "arguments": '{"q":"'}}]}),
+        _sse({"tool_calls": [{"index": 0, "function": {"arguments": 'cats"}'}}]}),
+        "data: [DONE]",
+    ]
+    events = _drive(monkeypatch, lines, model="gpt-4o-test")
+    calls = next(e["calls"] for e in events if e.get("type") == "tool_calls")
+    assert len(calls) == 1
+    assert calls[0]["name"] == "search"
+    assert calls[0]["arguments"] == '{"q":"cats"}'
+
+
+def test_null_index_chunked_arguments_attach_to_last_call(monkeypatch):
+    # index=None where the name arrives first, then an arg-only continuation:
+    # the continuation must attach to the just-started call, not open a new one.
+    lines = [
+        _sse({"tool_calls": [{"index": None, "id": "c", "type": "function",
+                              "function": {"name": "search", "arguments": '{"q":'}}]}),
+        _sse({"tool_calls": [{"index": None, "function": {"arguments": '"dogs"}'}}]}),
+        "data: [DONE]",
+    ]
+    events = _drive(monkeypatch, lines)
+    calls = next(e["calls"] for e in events if e.get("type") == "tool_calls")
+    assert len(calls) == 1, f"continuation opened a spurious call: {calls}"
+    assert calls[0]["arguments"] == '{"q":"dogs"}'
+
+
+def test_sparse_integer_indices_then_null_do_not_collide(monkeypatch):
+    # Hardening: a provider that uses sparse integer indices (0 and 2) and then
+    # a null-index call must allocate ABOVE the max key, not at len()==2 (which
+    # would overwrite slot 2). Three distinct calls must survive.
+    lines = [
+        _sse({"tool_calls": [{"index": 0, "id": "a", "function": {"name": "f0", "arguments": "{}"}}]}),
+        _sse({"tool_calls": [{"index": 2, "id": "b", "function": {"name": "f2", "arguments": "{}"}}]}),
+        _sse({"tool_calls": [{"index": None, "id": "c", "function": {"name": "fn", "arguments": "{}"}}]}),
+        "data: [DONE]",
+    ]
+    events = _drive(monkeypatch, lines)
+    calls = next(e["calls"] for e in events if e.get("type") == "tool_calls")
+    assert sorted(c["name"] for c in calls) == ["f0", "f2", "fn"], f"collision: {calls}"