fix: resolve consensus tool model_context parameter missing issue
Fixed runtime bug where _prepare_file_content_for_prompt was called without required model_context parameter, causing RuntimeError when processing requests with relevant_files. - Create ModelContext instance with model_name in _consult_model method - Pass model_context parameter to _prepare_file_content_for_prompt call - Add comprehensive regression test to prevent future occurrences - Maintain consensus tool's blinded design with independent model contexts
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@@ -331,6 +331,79 @@ class TestConsensusTool:
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result = tool.customize_workflow_response(response_data, request)
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assert result["consensus_workflow_status"] == "ready_for_synthesis"
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async def test_consensus_with_relevant_files_model_context_fix(self):
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"""Test that consensus tool properly handles relevant_files without RuntimeError.
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This is a regression test for the bug where _prepare_file_content_for_prompt
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was called without model_context parameter, causing RuntimeError:
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'Model context not provided for file preparation'
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Bug details:
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- Occurred when consensus tool processed requests with relevant_files
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- _consult_model method called _prepare_file_content_for_prompt without model_context
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- Method expected model_context parameter but got None (default value)
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- Runtime validation in base_tool.py threw RuntimeError
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"""
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from unittest.mock import AsyncMock, Mock, patch
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from utils.model_context import ModelContext
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tool = ConsensusTool()
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# Create a mock request with relevant_files (the trigger condition)
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mock_request = Mock()
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mock_request.relevant_files = ["/test/file1.py", "/test/file2.js"]
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mock_request.continuation_id = None
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# Mock model configuration
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model_config = {"model": "flash", "stance": "neutral"}
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# Mock the provider and model name resolution
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with (
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patch.object(tool, "get_model_provider") as mock_get_provider,
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patch.object(tool, "_prepare_file_content_for_prompt") as mock_prepare_files,
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patch.object(tool, "_get_stance_enhanced_prompt") as mock_get_prompt,
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patch.object(tool, "get_name", return_value="consensus"),
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):
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# Setup mocks
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mock_provider = Mock()
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mock_provider.generate_content = AsyncMock(return_value={"response": "test response"})
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mock_get_provider.return_value = mock_provider
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mock_prepare_files.return_value = ("file content", [])
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mock_get_prompt.return_value = "system prompt"
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# Set up the tool's attributes that would be set during normal execution
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tool.original_proposal = "Test proposal"
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try:
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# This should not raise RuntimeError after the fix
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# The method should create ModelContext and pass it to _prepare_file_content_for_prompt
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await tool._consult_model(model_config, mock_request)
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# Verify that _prepare_file_content_for_prompt was called with model_context
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mock_prepare_files.assert_called_once()
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call_args = mock_prepare_files.call_args
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# Check that model_context was passed as keyword argument
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assert "model_context" in call_args.kwargs, "model_context should be passed as keyword argument"
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# Verify the model_context is a proper ModelContext instance
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model_context = call_args.kwargs["model_context"]
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assert isinstance(model_context, ModelContext), "model_context should be ModelContext instance"
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# Verify model_context properties are correct
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assert model_context.model_name == "flash"
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# Note: provider is accessed lazily, conversation_history and tool_name
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# are not part of ModelContext constructor in current implementation
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except RuntimeError as e:
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if "Model context not provided" in str(e):
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pytest.fail("The model_context fix is not working. RuntimeError still occurs: " + str(e))
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else:
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# Re-raise if it's a different RuntimeError
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raise
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if __name__ == "__main__":
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import unittest
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@@ -29,7 +29,6 @@ from mcp.types import TextContent
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from config import TEMPERATURE_ANALYTICAL
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from systemprompts import CONSENSUS_PROMPT
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from tools.shared.base_models import WorkflowRequest
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from utils.model_context import ModelContext
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from .workflow.base import WorkflowTool
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@@ -534,10 +533,18 @@ of the evidence, even when it strongly points in one direction.""",
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# Steps 2+ contain summaries/notes that must NEVER be sent to other models
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prompt = self.original_proposal if self.original_proposal else self.initial_prompt
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if request.relevant_files:
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# Create a model context for token allocation
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from utils.model_context import ModelContext
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model_context = ModelContext(
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model_name=model_name,
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)
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file_content, _ = self._prepare_file_content_for_prompt(
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request.relevant_files,
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None, # Use None instead of request.continuation_id for blinded consensus
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"Context files",
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model_context=model_context,
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)
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if file_content:
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prompt = f"{prompt}\n\n=== CONTEXT FILES ===\n{file_content}\n=== END CONTEXT ==="
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