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fix(tools): deduplicate tool names at API boundary for Vertex/Azure/Bedrock
Providers like Google Vertex, Azure, and Amazon Bedrock reject API requests with duplicate tool names (HTTP 400: 'Tool names must be unique'). The upstream injection paths in run_agent.py already dedup after PR #17335, but two API-boundary functions pass tools through without checking: - agent/auxiliary_client.py: _build_call_kwargs() (all non-Anthropic providers in chat_completions mode) - agent/anthropic_adapter.py: convert_tools_to_anthropic() (Anthropic Messages API path) Add defensive dedup guards at both sites. Duplicates are dropped with a warning log, converting a hard 400 failure into a recoverable condition. This is intentionally conservative — the root-cause dedup in run_agent.py is the primary defense; these guards add resilience against future injection-path regressions. Includes 8 new tests covering unique passthrough, duplicate removal, empty/None edge cases. Closes #18478
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parent
699b3679bc
commit
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4 changed files with 153 additions and 2 deletions
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@ -1241,10 +1241,24 @@ def convert_tools_to_anthropic(tools: List[Dict]) -> List[Dict]:
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if not tools:
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return []
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result = []
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seen_names: set = set()
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for t in tools:
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fn = t.get("function", {})
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name = fn.get("name", "")
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# Defensive dedup: Anthropic rejects requests with duplicate tool
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# names. Upstream injection paths already dedup, but this guard
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# converts a hard API failure into a warning. See: #18478
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if name and name in seen_names:
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logger.warning(
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"convert_tools_to_anthropic: duplicate tool name '%s' "
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"— dropping second occurrence",
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name,
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)
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continue
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if name:
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seen_names.add(name)
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result.append({
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"name": fn.get("name", ""),
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"name": name,
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"description": fn.get("description", ""),
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"input_schema": _normalize_tool_input_schema(
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fn.get("parameters", {"type": "object", "properties": {}})
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@ -3237,7 +3237,26 @@ def _build_call_kwargs(
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kwargs["max_tokens"] = max_tokens
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if tools:
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kwargs["tools"] = tools
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# Defensive dedup: providers like Google Vertex, Azure, and Bedrock
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# reject requests with duplicate tool names (HTTP 400). The upstream
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# injection paths (run_agent.py) already dedup, but this guard
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# converts a hard API failure into a warning if an upstream regression
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# reintroduces duplicates. See: #18478
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_seen: set = set()
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_deduped: list = []
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for _t in tools:
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_tname = (_t.get("function") or {}).get("name", "")
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if _tname and _tname in _seen:
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logger.warning(
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"_build_call_kwargs: duplicate tool name '%s' removed "
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"(provider=%s model=%s)",
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_tname, provider, model,
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)
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continue
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if _tname:
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_seen.add(_tname)
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_deduped.append(_t)
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kwargs["tools"] = _deduped
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# Provider-specific extra_body
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merged_extra = dict(extra_body or {})
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@ -1836,3 +1836,55 @@ class TestResolveMessagesMaxTokens:
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result = _resolve_anthropic_messages_max_tokens(0.5, "claude-opus-4-6")
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assert result > 0
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assert result != 0
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# ---------------------------------------------------------------------------
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# convert_tools_to_anthropic — tool dedup at API boundary
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# ---------------------------------------------------------------------------
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class TestConvertToolsToAnthropicDedup:
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"""convert_tools_to_anthropic must deduplicate tool names.
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Anthropic rejects requests with duplicate tool names. This guard converts
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a hard failure into a warning log. See:
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https://github.com/NousResearch/hermes-agent/issues/18478
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"""
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def _make_openai_tool(self, name: str) -> dict:
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return {
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"type": "function",
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"function": {
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"name": name,
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"description": f"Tool {name}",
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"parameters": {"type": "object", "properties": {}},
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},
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}
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def test_unique_tools_pass_through(self):
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tools = [self._make_openai_tool("alpha"), self._make_openai_tool("beta")]
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result = convert_tools_to_anthropic(tools)
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assert len(result) == 2
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names = [t["name"] for t in result]
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assert names == ["alpha", "beta"]
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def test_duplicate_tool_names_are_deduplicated(self):
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"""RED test — must fail until dedup guard is added."""
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tools = [
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self._make_openai_tool("lcm_grep"),
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self._make_openai_tool("lcm_describe"),
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self._make_openai_tool("lcm_grep"), # duplicate
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self._make_openai_tool("lcm_expand"),
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self._make_openai_tool("lcm_describe"), # duplicate
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]
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result = convert_tools_to_anthropic(tools)
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names = [t["name"] for t in result]
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assert len(names) == len(set(names)), (
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f"Duplicate tool names found: {names}"
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)
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assert len(result) == 3 # lcm_grep, lcm_describe, lcm_expand
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def test_empty_tools_returns_empty(self):
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assert convert_tools_to_anthropic([]) == []
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def test_none_tools_returns_empty(self):
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assert convert_tools_to_anthropic(None) == []
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@ -16,6 +16,7 @@ from agent.auxiliary_client import (
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auxiliary_max_tokens_param,
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call_llm,
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async_call_llm,
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_build_call_kwargs,
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_read_codex_access_token,
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_get_provider_chain,
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_is_payment_error,
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@ -1752,3 +1753,68 @@ class TestVisionAutoSkipsKimiCoding:
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"kimi-coding",
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"kimi-coding-cn",
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})
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# ---------------------------------------------------------------------------
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# _build_call_kwargs — tool dedup at API boundary
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# ---------------------------------------------------------------------------
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class TestBuildCallKwargsToolDedup:
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"""_build_call_kwargs must deduplicate tool names before passing to API.
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Providers like Google Vertex, Azure, and Bedrock reject requests with
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duplicate tool names (HTTP 400). This guard converts a hard failure into
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a warning log so agent turns succeed even if an upstream injection path
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regresses. See: https://github.com/NousResearch/hermes-agent/issues/18478
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"""
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def _make_tool(self, name: str) -> dict:
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return {
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"type": "function",
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"function": {
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"name": name,
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"description": f"Tool {name}",
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"parameters": {"type": "object", "properties": {}},
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},
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}
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def test_unique_tools_pass_through_unchanged(self):
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tools = [self._make_tool("alpha"), self._make_tool("beta")]
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kwargs = _build_call_kwargs(
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provider="openai", model="gpt-4o", messages=[], tools=tools,
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)
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assert len(kwargs["tools"]) == 2
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names = [t["function"]["name"] for t in kwargs["tools"]]
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assert names == ["alpha", "beta"]
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def test_duplicate_tool_names_are_deduplicated(self):
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"""RED test — must fail until dedup guard is added."""
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tools = [
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self._make_tool("lcm_grep"),
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self._make_tool("lcm_describe"),
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self._make_tool("lcm_grep"), # duplicate
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self._make_tool("lcm_expand"),
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self._make_tool("lcm_describe"), # duplicate
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]
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kwargs = _build_call_kwargs(
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provider="google", model="gemini-2.5-pro", messages=[], tools=tools,
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)
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result_tools = kwargs["tools"]
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names = [t["function"]["name"] for t in result_tools]
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# Must be deduplicated — no repeated names
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assert len(names) == len(set(names)), (
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f"Duplicate tool names found: {names}"
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)
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assert len(result_tools) == 3 # lcm_grep, lcm_describe, lcm_expand
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def test_empty_tools_unchanged(self):
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kwargs = _build_call_kwargs(
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provider="openai", model="gpt-4o", messages=[], tools=[],
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)
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assert kwargs.get("tools") == [] or "tools" not in kwargs
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def test_none_tools_unchanged(self):
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kwargs = _build_call_kwargs(
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provider="openai", model="gpt-4o", messages=[], tools=None,
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)
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assert "tools" not in kwargs
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