Migration from Docker to Standalone Python Server (#73)
* Migration from docker to standalone server Migration handling Fixed tests Use simpler in-memory storage Support for concurrent logging to disk Simplified direct connections to localhost * Migration from docker / redis to standalone script Updated tests Updated run script Fixed requirements Use dotenv Ask if user would like to install MCP in Claude Desktop once Updated docs * More cleanup and references to docker removed * Cleanup * Comments * Fixed tests * Fix GitHub Actions workflow for standalone Python architecture - Install requirements-dev.txt for pytest and testing dependencies - Remove Docker setup from simulation tests (now standalone) - Simplify linting job to use requirements-dev.txt - Update simulation tests to run directly without Docker Fixes unit test failures in CI due to missing pytest dependency. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> * Remove simulation tests from GitHub Actions - Removed simulation-tests job that makes real API calls - Keep only unit tests (mocked, no API costs) and linting - Simulation tests should be run manually with real API keys - Reduces CI costs and complexity GitHub Actions now only runs: - Unit tests (569 tests, all mocked) - Code quality checks (ruff, black) 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> * Fixed tests * Fixed tests --------- Co-authored-by: Claude <noreply@anthropic.com>
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Beehive Innovations
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GitHub
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@@ -37,7 +37,7 @@ from utils.conversation_memory import (
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get_conversation_file_list,
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get_thread,
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)
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from utils.file_utils import read_file_content, read_files, translate_path_for_environment
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from utils.file_utils import read_file_content, read_files
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from .models import SPECIAL_STATUS_MODELS, ContinuationOffer, ToolOutput
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@@ -1229,15 +1229,13 @@ When recommending searches, be specific about what information you need and why
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updated_files = []
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for file_path in files:
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# Translate path for current environment (Docker/direct)
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translated_path = translate_path_for_environment(file_path)
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# Check if the filename is exactly "prompt.txt"
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# This ensures we don't match files like "myprompt.txt" or "prompt.txt.bak"
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if os.path.basename(translated_path) == "prompt.txt":
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if os.path.basename(file_path) == "prompt.txt":
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try:
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# Read prompt.txt content and extract just the text
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content, _ = read_file_content(translated_path)
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content, _ = read_file_content(file_path)
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# Extract the content between the file markers
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if "--- BEGIN FILE:" in content and "--- END FILE:" in content:
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lines = content.split("\n")
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@@ -1568,6 +1566,17 @@ When recommending searches, be specific about what information you need and why
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parsed_status = status_model.model_validate(potential_json)
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logger.debug(f"{self.name} tool detected special status: {status_key}")
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# Enhance mandatory_instructions for files_required_to_continue
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if status_key == "files_required_to_continue" and hasattr(
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parsed_status, "mandatory_instructions"
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):
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original_instructions = parsed_status.mandatory_instructions
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enhanced_instructions = self._enhance_mandatory_instructions(original_instructions)
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# Create a new model instance with enhanced instructions
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enhanced_data = parsed_status.model_dump()
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enhanced_data["mandatory_instructions"] = enhanced_instructions
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parsed_status = status_model.model_validate(enhanced_data)
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# Extract model information for metadata
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metadata = {
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"original_request": (
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@@ -1936,7 +1945,7 @@ When recommending searches, be specific about what information you need and why
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elif "gpt" in model_name.lower() or "o3" in model_name.lower():
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# Register OpenAI provider if not already registered
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from providers.base import ProviderType
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from providers.openai import OpenAIModelProvider
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from providers.openai_provider import OpenAIModelProvider
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ModelProviderRegistry.register_provider(ProviderType.OPENAI, OpenAIModelProvider)
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provider = ModelProviderRegistry.get_provider(ProviderType.OPENAI)
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@@ -1948,3 +1957,28 @@ When recommending searches, be specific about what information you need and why
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)
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return provider
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def _enhance_mandatory_instructions(self, original_instructions: str) -> str:
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"""
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Enhance mandatory instructions for files_required_to_continue responses.
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This adds generic guidance to help Claude understand the importance
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of providing the requested files and context.
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Args:
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original_instructions: The original instructions from the model
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Returns:
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str: Enhanced instructions with additional guidance
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"""
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generic_guidance = (
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"\n\nIMPORTANT GUIDANCE:\n"
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"• The requested files are CRITICAL for providing accurate analysis\n"
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"• Please include ALL files mentioned in the files_needed list\n"
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"• Use FULL absolute paths to real files/folders - DO NOT SHORTEN paths - and confirm that these exist\n"
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"• If you cannot locate specific files or the files are extremely large, think hard, study the code and provide similar/related files that might contain the needed information\n"
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"• After providing the files, use the same tool again with the continuation_id to continue the analysis\n"
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"• The tool cannot proceed to perform its function accurately without this additional context"
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)
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return f"{original_instructions}{generic_guidance}"
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