mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-04-25 00:51:20 +00:00
feat: call_llm/async_call_llm + config slots + migrate all consumers
Add centralized call_llm() and async_call_llm() functions that own the full LLM request lifecycle: 1. Resolve provider + model from task config or explicit args 2. Get or create a cached client for that provider 3. Format request args (max_tokens handling, provider extra_body) 4. Make the API call with max_tokens/max_completion_tokens retry 5. Return the response Config: expanded auxiliary section with provider:model slots for all tasks (compression, vision, web_extract, session_search, skills_hub, mcp, flush_memories). Config version bumped to 7. Migrated all auxiliary consumers: - context_compressor.py: uses call_llm(task='compression') - vision_tools.py: uses async_call_llm(task='vision') - web_tools.py: uses async_call_llm(task='web_extract') - session_search_tool.py: uses async_call_llm(task='session_search') - browser_tool.py: uses call_llm(task='vision'/'web_extract') - mcp_tool.py: uses call_llm(task='mcp') - skills_guard.py: uses call_llm(provider='openrouter') - run_agent.py flush_memories: uses call_llm(task='flush_memories') Tests updated for context_compressor and MCP tool. Some test mocks still need updating (15 remaining failures from mock pattern changes, 2 pre-existing).
This commit is contained in:
teknium1
parent
013cc4d2fc
commit
0aa31cd3cb
13 changed files with 552 additions and 375 deletions
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@ -1828,8 +1828,8 @@ class TestSamplingCallbackText:
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)
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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params = _make_sampling_params()
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result = asyncio.run(self.handler(None, params))
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@ -1847,13 +1847,13 @@ class TestSamplingCallbackText:
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fake_client.chat.completions.create.return_value = _make_llm_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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):
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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) as mock_call:
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params = _make_sampling_params(system_prompt="Be helpful")
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asyncio.run(self.handler(None, params))
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call_args = fake_client.chat.completions.create.call_args
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call_args = mock_call.call_args
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messages = call_args.kwargs["messages"]
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assert messages[0] == {"role": "system", "content": "Be helpful"}
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@ -1865,8 +1865,8 @@ class TestSamplingCallbackText:
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)
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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params = _make_sampling_params()
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result = asyncio.run(self.handler(None, params))
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@ -1889,8 +1889,8 @@ class TestSamplingCallbackToolUse:
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fake_client.chat.completions.create.return_value = _make_llm_tool_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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params = _make_sampling_params()
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result = asyncio.run(self.handler(None, params))
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@ -1916,8 +1916,8 @@ class TestSamplingCallbackToolUse:
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)
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(self.handler(None, _make_sampling_params()))
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@ -1939,8 +1939,8 @@ class TestToolLoopGovernance:
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fake_client.chat.completions.create.return_value = _make_llm_tool_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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params = _make_sampling_params()
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# Round 1, 2: allowed
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@ -1959,8 +1959,8 @@ class TestToolLoopGovernance:
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fake_client = MagicMock()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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# Tool response (round 1 of 1 allowed)
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fake_client.chat.completions.create.return_value = _make_llm_tool_response()
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@ -1984,8 +1984,8 @@ class TestToolLoopGovernance:
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fake_client.chat.completions.create.return_value = _make_llm_tool_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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assert isinstance(result, ErrorData)
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@ -2003,8 +2003,8 @@ class TestSamplingErrors:
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fake_client.chat.completions.create.return_value = _make_llm_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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# First call succeeds
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r1 = asyncio.run(handler(None, _make_sampling_params()))
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@ -2017,20 +2017,16 @@ class TestSamplingErrors:
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def test_timeout_error(self):
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handler = SamplingHandler("to", {"timeout": 0.05})
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fake_client = MagicMock()
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def slow_call(**kwargs):
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import threading
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# Use an event to ensure the thread truly blocks long enough
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evt = threading.Event()
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evt.wait(5) # blocks for up to 5 seconds (cancelled by timeout)
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return _make_llm_response()
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fake_client.chat.completions.create.side_effect = slow_call
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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side_effect=slow_call,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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assert isinstance(result, ErrorData)
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@ -2041,12 +2037,11 @@ class TestSamplingErrors:
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handler = SamplingHandler("np", {})
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(None, None),
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"agent.auxiliary_client.call_llm",
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side_effect=RuntimeError("No LLM provider configured"),
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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assert isinstance(result, ErrorData)
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assert "No LLM provider" in result.message
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assert handler.metrics["errors"] == 1
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def test_empty_choices_returns_error(self):
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@ -2060,8 +2055,8 @@ class TestSamplingErrors:
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)
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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@ -2080,8 +2075,8 @@ class TestSamplingErrors:
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)
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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@ -2099,8 +2094,8 @@ class TestSamplingErrors:
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)
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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@ -2120,8 +2115,8 @@ class TestModelWhitelist:
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fake_client.chat.completions.create.return_value = _make_llm_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "test-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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assert isinstance(result, CreateMessageResult)
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@ -2131,8 +2126,8 @@ class TestModelWhitelist:
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fake_client = MagicMock()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "gpt-3.5-turbo"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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assert isinstance(result, ErrorData)
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@ -2145,8 +2140,8 @@ class TestModelWhitelist:
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fake_client.chat.completions.create.return_value = _make_llm_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "any-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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assert isinstance(result, CreateMessageResult)
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@ -2166,8 +2161,8 @@ class TestMalformedToolCallArgs:
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)
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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@ -2194,8 +2189,8 @@ class TestMalformedToolCallArgs:
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fake_client.chat.completions.create.return_value = response
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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result = asyncio.run(handler(None, _make_sampling_params()))
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@ -2214,8 +2209,8 @@ class TestMetricsTracking:
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fake_client.chat.completions.create.return_value = _make_llm_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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asyncio.run(handler(None, _make_sampling_params()))
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@ -2229,8 +2224,8 @@ class TestMetricsTracking:
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fake_client.chat.completions.create.return_value = _make_llm_tool_response()
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(fake_client, "default-model"),
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"agent.auxiliary_client.call_llm",
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return_value=fake_client.chat.completions.create.return_value,
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):
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asyncio.run(handler(None, _make_sampling_params()))
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@ -2241,8 +2236,8 @@ class TestMetricsTracking:
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handler = SamplingHandler("met3", {})
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with patch(
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"agent.auxiliary_client.get_text_auxiliary_client",
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return_value=(None, None),
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"agent.auxiliary_client.call_llm",
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side_effect=RuntimeError("No LLM provider configured"),
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):
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asyncio.run(handler(None, _make_sampling_params()))
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