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https://github.com/NousResearch/hermes-agent.git
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fix(agent): detect truncated streaming tool calls before execution
When a streaming response is cut mid-tool-call (connection drop, timeout), the accumulated function.arguments is invalid JSON. The mock response builder defaulted finish_reason to 'stop', so the agent loop treated it as a valid completed turn and tried to execute tools with broken args. Fix: validate tool call arguments with json.loads() during mock response reconstruction. If any are invalid JSON, override finish_reason to 'length'. In the main loop's length handler, if tool calls are present, refuse to execute and return partial=True with a clear error instead of silently failing or wasting retries. Also fixes _thinking_exhausted to not short-circuit when tool calls are present — truncated tool calls are not thinking exhaustion. Original cherry-picked from PR #6776 by AIandI0x1. Closes #6638.
This commit is contained in:
AIandI0x1
Teknium
parent
3b554bf839
commit
2d0d05a337
2 changed files with 125 additions and 5 deletions
54
run_agent.py
54
run_agent.py
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@ -4584,20 +4584,31 @@ class AIAgent:
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# Build mock response matching non-streaming shape
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full_content = "".join(content_parts) or None
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mock_tool_calls = None
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has_truncated_tool_args = False
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if tool_calls_acc:
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mock_tool_calls = []
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for idx in sorted(tool_calls_acc):
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tc = tool_calls_acc[idx]
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arguments = tc["function"]["arguments"]
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if arguments and arguments.strip():
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try:
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json.loads(arguments)
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except json.JSONDecodeError:
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has_truncated_tool_args = True
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mock_tool_calls.append(SimpleNamespace(
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id=tc["id"],
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type=tc["type"],
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extra_content=tc.get("extra_content"),
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function=SimpleNamespace(
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name=tc["function"]["name"],
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arguments=tc["function"]["arguments"],
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arguments=arguments,
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),
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))
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effective_finish_reason = finish_reason or "stop"
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if has_truncated_tool_args:
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effective_finish_reason = "length"
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full_reasoning = "".join(reasoning_parts) or None
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mock_message = SimpleNamespace(
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role=role,
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@ -4608,7 +4619,7 @@ class AIAgent:
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mock_choice = SimpleNamespace(
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index=0,
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message=mock_message,
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finish_reason=finish_reason or "stop",
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finish_reason=effective_finish_reason,
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)
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return SimpleNamespace(
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id="stream-" + str(uuid.uuid4()),
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@ -7319,6 +7330,7 @@ class AIAgent:
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interrupted = False
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codex_ack_continuations = 0
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length_continue_retries = 0
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truncated_tool_call_retries = 0
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truncated_response_prefix = ""
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compression_attempts = 0
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_turn_exit_reason = "unknown" # Diagnostic: why the loop ended
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@ -7787,9 +7799,11 @@ class AIAgent:
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# retries are pointless. Detect this early and give a
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# targeted error instead of wasting 3 API calls.
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_trunc_content = None
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_trunc_has_tool_calls = False
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if self.api_mode == "chat_completions":
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_trunc_msg = response.choices[0].message if (hasattr(response, "choices") and response.choices) else None
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_trunc_content = getattr(_trunc_msg, "content", None) if _trunc_msg else None
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_trunc_has_tool_calls = bool(getattr(_trunc_msg, "tool_calls", None)) if _trunc_msg else False
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elif self.api_mode == "anthropic_messages":
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# Anthropic response.content is a list of blocks
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_text_parts = []
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@ -7799,9 +7813,11 @@ class AIAgent:
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_trunc_content = "\n".join(_text_parts) if _text_parts else None
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_thinking_exhausted = (
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_trunc_content is not None
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and not self._has_content_after_think_block(_trunc_content)
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) or _trunc_content is None
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not _trunc_has_tool_calls and (
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(_trunc_content is not None and not self._has_content_after_think_block(_trunc_content))
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or _trunc_content is None
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)
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)
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if _thinking_exhausted:
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_exhaust_error = (
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@ -7877,6 +7893,34 @@ class AIAgent:
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"error": "Response remained truncated after 3 continuation attempts",
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}
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if self.api_mode == "chat_completions":
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assistant_message = response.choices[0].message
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if assistant_message.tool_calls:
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if truncated_tool_call_retries < 1:
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truncated_tool_call_retries += 1
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self._vprint(
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f"{self.log_prefix}⚠️ Truncated tool call detected — retrying API call...",
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force=True,
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)
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# Don't append the broken response to messages;
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# just re-run the same API call from the current
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# message state, giving the model another chance.
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continue
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self._vprint(
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f"{self.log_prefix}⚠️ Truncated tool call response detected again — refusing to execute incomplete tool arguments.",
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force=True,
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)
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self._cleanup_task_resources(effective_task_id)
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self._persist_session(messages, conversation_history)
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return {
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"final_response": None,
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"messages": messages,
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"api_calls": api_call_count,
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"completed": False,
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"partial": True,
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"error": "Response truncated due to output length limit",
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}
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# If we have prior messages, roll back to last complete state
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if len(messages) > 1:
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self._vprint(f"{self.log_prefix} ⏪ Rolling back to last complete assistant turn")
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@ -1949,6 +1949,68 @@ class TestRunConversation:
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assert result["final_response"] is not None
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assert "Thinking Budget Exhausted" in result["final_response"]
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def test_length_with_tool_calls_returns_partial_without_executing_tools(self, agent):
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self._setup_agent(agent)
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bad_tc = _mock_tool_call(
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name="write_file",
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arguments='{"path":"report.md","content":"partial',
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call_id="c1",
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)
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resp = _mock_response(content="", finish_reason="length", tool_calls=[bad_tc])
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agent.client.chat.completions.create.return_value = resp
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with (
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patch("run_agent.handle_function_call") as mock_handle_function_call,
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patch.object(agent, "_persist_session"),
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patch.object(agent, "_save_trajectory"),
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patch.object(agent, "_cleanup_task_resources"),
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):
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result = agent.run_conversation("write the report")
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assert result["completed"] is False
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assert result["partial"] is True
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assert "truncated due to output length limit" in result["error"]
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mock_handle_function_call.assert_not_called()
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def test_truncated_tool_call_retries_once_before_refusing(self, agent):
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"""When tool call args are truncated, the agent retries the API call
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once. If the retry succeeds (valid JSON args), tool execution proceeds."""
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self._setup_agent(agent)
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agent.valid_tool_names.add("write_file")
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bad_tc = _mock_tool_call(
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name="write_file",
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arguments='{"path":"report.md","content":"partial',
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call_id="c1",
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)
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truncated_resp = _mock_response(
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content="", finish_reason="length", tool_calls=[bad_tc],
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)
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good_tc = _mock_tool_call(
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name="write_file",
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arguments='{"path":"report.md","content":"full content"}',
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call_id="c2",
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)
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good_resp = _mock_response(
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content="", finish_reason="stop", tool_calls=[good_tc],
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)
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with (
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patch("run_agent.handle_function_call", return_value='{"success":true}') as mock_hfc,
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patch.object(agent, "_persist_session"),
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patch.object(agent, "_save_trajectory"),
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patch.object(agent, "_cleanup_task_resources"),
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):
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# First call: truncated → retry. Second: valid → execute tool.
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# Third: final text response.
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final_resp = _mock_response(content="Done!", finish_reason="stop")
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agent.client.chat.completions.create.side_effect = [
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truncated_resp, good_resp, final_resp,
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]
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result = agent.run_conversation("write the report")
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# Tool was executed on the retry (good_resp)
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mock_hfc.assert_called_once()
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assert result["final_response"] == "Done!"
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class TestRetryExhaustion:
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"""Regression: retry_count > max_retries was dead code (off-by-one).
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@ -3082,6 +3144,20 @@ class TestStreamingApiCall:
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assert tc[0].function.name == "search"
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assert tc[1].function.name == "read"
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def test_truncated_tool_call_args_upgrade_finish_reason_to_length(self, agent):
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chunks = [
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_make_chunk(tool_calls=[_make_tc_delta(0, "call_1", "write_file", '{"path":"x.txt","content":"hel')]),
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]
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agent.client.chat.completions.create.return_value = iter(chunks)
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resp = agent._interruptible_streaming_api_call({"messages": []})
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tc = resp.choices[0].message.tool_calls
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assert len(tc) == 1
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assert tc[0].function.name == "write_file"
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assert tc[0].function.arguments == '{"path":"x.txt","content":"hel'
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assert resp.choices[0].finish_reason == "length"
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def test_ollama_reused_index_separate_tool_calls(self, agent):
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"""Ollama sends every tool call at index 0 with different ids.
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