mirror of
https://github.com/NousResearch/hermes-agent.git
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43de1ca8c2
NormalizedResponse and ToolCall now have backward-compat properties
so the agent loop can read them directly without the shim:
ToolCall: .type, .function (returns self), .call_id, .response_item_id
NormalizedResponse: .reasoning_content, .reasoning_details,
.codex_reasoning_items
This eliminates the 35-line shim and its 4 call sites in run_agent.py.
Also changes flush_memories guard from hasattr(response, 'choices')
to self.api_mode in ('chat_completions', 'bedrock_converse') so it
works with raw boto3 dicts too.
WS1 items 3+4 of Cycle 2 (#14418).
114 lines
4.6 KiB
Python
114 lines
4.6 KiB
Python
"""Regression test for anthropic_messages truncation continuation.
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When an Anthropic response hits ``stop_reason: max_tokens`` (mapped to
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``finish_reason == 'length'`` in run_agent), the agent must retry with
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a continuation prompt — the same behavior it has always had for
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chat_completions and bedrock_converse. Before this PR, the
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``if self.api_mode in ('chat_completions', 'bedrock_converse'):`` guard
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silently dropped Anthropic-wire truncations on the floor, returning a
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half-finished response with no retry.
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We don't exercise the full agent loop here (it's 3000 lines of inference,
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streaming, plugin hooks, etc.) — instead we verify the normalization
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adapter produces exactly the shape the continuation block now consumes.
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"""
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from __future__ import annotations
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from types import SimpleNamespace
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import pytest
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def _make_anthropic_text_block(text: str) -> SimpleNamespace:
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return SimpleNamespace(type="text", text=text)
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def _make_anthropic_tool_use_block(name: str = "my_tool") -> SimpleNamespace:
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return SimpleNamespace(
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type="tool_use",
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id="toolu_01",
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name=name,
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input={"foo": "bar"},
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)
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def _make_anthropic_response(blocks, stop_reason: str = "max_tokens"):
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return SimpleNamespace(
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id="msg_01",
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type="message",
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role="assistant",
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model="claude-sonnet-4-6",
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content=blocks,
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stop_reason=stop_reason,
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stop_sequence=None,
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usage=SimpleNamespace(input_tokens=100, output_tokens=200),
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)
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class TestTruncatedAnthropicResponseNormalization:
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"""AnthropicTransport.normalize_response() gives us the shape _build_assistant_message expects."""
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def test_text_only_truncation_produces_text_content_no_tool_calls(self):
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"""Pure-text Anthropic truncation → continuation path should fire."""
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from agent.transports import get_transport
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response = _make_anthropic_response(
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[_make_anthropic_text_block("partial response that was cut off")]
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)
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nr = get_transport("anthropic_messages").normalize_response(response)
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# The continuation block checks these two attributes:
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# assistant_message.content → appended to truncated_response_prefix
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# assistant_message.tool_calls → guards the text-retry branch
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assert nr.content is not None
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assert "partial response" in nr.content
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assert not nr.tool_calls, (
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"Pure-text truncation must have no tool_calls so the text-continuation "
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"branch (not the tool-retry branch) fires"
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)
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assert nr.finish_reason == "length", "max_tokens stop_reason must map to OpenAI-style 'length'"
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def test_truncated_tool_call_produces_tool_calls(self):
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"""Tool-use truncation → tool-call retry path should fire."""
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from agent.transports import get_transport
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response = _make_anthropic_response(
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[
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_make_anthropic_text_block("thinking..."),
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_make_anthropic_tool_use_block(),
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]
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)
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nr = get_transport("anthropic_messages").normalize_response(response)
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assert bool(nr.tool_calls), (
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"Truncation mid-tool_use must expose tool_calls so the "
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"tool-call retry branch fires instead of text continuation"
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)
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assert nr.finish_reason == "length"
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def test_empty_content_does_not_crash(self):
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"""Empty response.content — defensive: treat as a truncation with no text."""
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from agent.transports import get_transport
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response = _make_anthropic_response([])
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nr = get_transport("anthropic_messages").normalize_response(response)
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# Depending on the adapter, content may be "" or None — both are
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# acceptable; what matters is no exception.
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assert nr is not None
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assert not nr.tool_calls
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class TestContinuationLogicBranching:
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"""Symbolic check that the api_mode gate now includes anthropic_messages."""
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@pytest.mark.parametrize("api_mode", ["chat_completions", "bedrock_converse", "anthropic_messages"])
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def test_all_three_api_modes_hit_continuation_branch(self, api_mode):
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# The guard in run_agent.py is:
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# if self.api_mode in ("chat_completions", "bedrock_converse", "anthropic_messages"):
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assert api_mode in ("chat_completions", "bedrock_converse", "anthropic_messages")
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def test_codex_responses_still_excluded(self):
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# codex_responses has its own truncation path (not continuation-based)
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# and should NOT be routed through the shared block.
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assert "codex_responses" not in ("chat_completions", "bedrock_converse", "anthropic_messages")
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