Extra logging and more tests

communication_simulator_test.py

@@ -366,7 +366,10 @@ def parse_arguments():
     parser.add_argument("--list-tests", action="store_true", help="List available tests and exit")
     parser.add_argument("--individual", "-i", help="Run a single test individually")
     parser.add_argument(
-        "--skip-docker", action="store_true", help="Skip Docker setup (assumes containers are already running)"
+        "--skip-docker", action="store_true", default=True, help="Skip Docker setup (assumes containers are already running) - DEFAULT"
+    )
+    parser.add_argument(
+        "--rebuild-docker", action="store_true", help="Force rebuild Docker environment (overrides --skip-docker)"
     )
 
     return parser.parse_args()
@@ -442,10 +445,13 @@ def main():
     simulator = CommunicationSimulator(verbose=args.verbose, keep_logs=args.keep_logs, selected_tests=args.tests)
 
     # Determine execution mode and run
+    # Override skip_docker if rebuild_docker is specified
+    skip_docker = args.skip_docker and not args.rebuild_docker
+    
     if args.individual:
-        exit_code = run_individual_test(simulator, args.individual, args.skip_docker)
+        exit_code = run_individual_test(simulator, args.individual, skip_docker)
     else:
-        exit_code = run_test_suite(simulator, args.skip_docker)
+        exit_code = run_test_suite(simulator, skip_docker)
 
     sys.exit(exit_code)
 

docker-compose.yml

@@ -7,7 +7,7 @@ services:
       - "6379:6379"
     volumes:
       - redis_data:/data
-    command: redis-server --save 60 1 --loglevel warning --maxmemory 512mb --maxmemory-policy allkeys-lru
+    command: redis-server --save 60 1 --loglevel warning --maxmemory 64mb --maxmemory-policy allkeys-lru
     healthcheck:
       test: ["CMD", "redis-cli", "ping"]
       interval: 30s
@@ -39,6 +39,8 @@ services:
     volumes:
       - ${HOME:-/tmp}:/workspace:ro
       - mcp_logs:/tmp  # Shared volume for logs
+      - /etc/localtime:/etc/localtime:ro
+      - /etc/timezone:/etc/timezone:ro
     stdin_open: true
     tty: true
     entrypoint: ["python"]
@@ -55,6 +57,8 @@ services:
       - PYTHONUNBUFFERED=1
     volumes:
       - mcp_logs:/tmp  # Shared volume for logs
+      - /etc/localtime:/etc/localtime:ro
+      - /etc/timezone:/etc/timezone:ro
     entrypoint: ["python"]
     command: ["log_monitor.py"]
 

server.py

@@ -51,6 +51,19 @@ from tools.models import ToolOutput
 # Can be controlled via LOG_LEVEL environment variable (DEBUG, INFO, WARNING, ERROR)
 log_level = os.getenv("LOG_LEVEL", "INFO").upper()
 
+# Create timezone-aware formatter
+import time
+class LocalTimeFormatter(logging.Formatter):
+    def formatTime(self, record, datefmt=None):
+        """Override to use local timezone instead of UTC"""
+        ct = self.converter(record.created)
+        if datefmt:
+            s = time.strftime(datefmt, ct)
+        else:
+            t = time.strftime("%Y-%m-%d %H:%M:%S", ct)
+            s = "%s,%03d" % (t, record.msecs)
+        return s
+
 # Configure both console and file logging
 log_format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
 logging.basicConfig(
@@ -60,18 +73,22 @@ logging.basicConfig(
     stream=sys.stderr,  # Use stderr to avoid interfering with MCP stdin/stdout protocol
 )
 
+# Apply local time formatter to root logger
+for handler in logging.getLogger().handlers:
+    handler.setFormatter(LocalTimeFormatter(log_format))
+
 # Add file handler for Docker log monitoring
 try:
     file_handler = logging.FileHandler("/tmp/mcp_server.log")
     file_handler.setLevel(getattr(logging, log_level, logging.INFO))
-    file_handler.setFormatter(logging.Formatter(log_format))
+    file_handler.setFormatter(LocalTimeFormatter(log_format))
     logging.getLogger().addHandler(file_handler)
 
     # Create a special logger for MCP activity tracking
     mcp_logger = logging.getLogger("mcp_activity")
     mcp_file_handler = logging.FileHandler("/tmp/mcp_activity.log")
     mcp_file_handler.setLevel(logging.INFO)
-    mcp_file_handler.setFormatter(logging.Formatter("%(asctime)s - %(message)s"))
+    mcp_file_handler.setFormatter(LocalTimeFormatter("%(asctime)s - %(message)s"))
     mcp_logger.addHandler(mcp_file_handler)
     mcp_logger.setLevel(logging.INFO)
 
@@ -196,6 +213,8 @@ async def handle_call_tool(name: str, arguments: dict[str, Any]) -> list[TextCon
     if "continuation_id" in arguments and arguments["continuation_id"]:
         continuation_id = arguments["continuation_id"]
         logger.debug(f"Resuming conversation thread: {continuation_id}")
+        logger.debug(f"[CONVERSATION_DEBUG] Tool '{name}' resuming thread {continuation_id} with {len(arguments)} arguments")
+        logger.debug(f"[CONVERSATION_DEBUG] Original arguments keys: {list(arguments.keys())}")
 
         # Log to activity file for monitoring
         try:
@@ -205,6 +224,9 @@ async def handle_call_tool(name: str, arguments: dict[str, Any]) -> list[TextCon
             pass
 
         arguments = await reconstruct_thread_context(arguments)
+        logger.debug(f"[CONVERSATION_DEBUG] After thread reconstruction, arguments keys: {list(arguments.keys())}")
+        if '_remaining_tokens' in arguments:
+            logger.debug(f"[CONVERSATION_DEBUG] Remaining token budget: {arguments['_remaining_tokens']:,}")
 
     # Route to AI-powered tools that require Gemini API calls
     if name in TOOLS:
@@ -300,9 +322,11 @@ async def reconstruct_thread_context(arguments: dict[str, Any]) -> dict[str, Any
     continuation_id = arguments["continuation_id"]
 
     # Get thread context from Redis
+    logger.debug(f"[CONVERSATION_DEBUG] Looking up thread {continuation_id} in Redis")
     context = get_thread(continuation_id)
     if not context:
         logger.warning(f"Thread not found: {continuation_id}")
+        logger.debug(f"[CONVERSATION_DEBUG] Thread {continuation_id} not found in Redis or expired")
 
         # Log to activity file for monitoring
         try:
@@ -324,15 +348,26 @@ async def reconstruct_thread_context(arguments: dict[str, Any]) -> dict[str, Any
     if user_prompt:
         # Capture files referenced in this turn
         user_files = arguments.get("files", [])
+        logger.debug(f"[CONVERSATION_DEBUG] Adding user turn to thread {continuation_id}")
+        logger.debug(f"[CONVERSATION_DEBUG] User prompt length: {len(user_prompt)} chars")
+        logger.debug(f"[CONVERSATION_DEBUG] User files: {user_files}")
         success = add_turn(continuation_id, "user", user_prompt, files=user_files)
         if not success:
             logger.warning(f"Failed to add user turn to thread {continuation_id}")
+            logger.debug(f"[CONVERSATION_DEBUG] Failed to add user turn - thread may be at turn limit or expired")
+        else:
+            logger.debug(f"[CONVERSATION_DEBUG] Successfully added user turn to thread {continuation_id}")
 
     # Build conversation history and track token usage
+    logger.debug(f"[CONVERSATION_DEBUG] Building conversation history for thread {continuation_id}")
+    logger.debug(f"[CONVERSATION_DEBUG] Thread has {len(context.turns)} turns, tool: {context.tool_name}")
     conversation_history, conversation_tokens = build_conversation_history(context)
+    logger.debug(f"[CONVERSATION_DEBUG] Conversation history built: {conversation_tokens:,} tokens")
+    logger.debug(f"[CONVERSATION_DEBUG] Conversation history length: {len(conversation_history)} chars")
 
     # Add dynamic follow-up instructions based on turn count
     follow_up_instructions = get_follow_up_instructions(len(context.turns))
+    logger.debug(f"[CONVERSATION_DEBUG] Follow-up instructions added for turn {len(context.turns)}")
 
     # Merge original context with new prompt and follow-up instructions
     original_prompt = arguments.get("prompt", "")
@@ -352,14 +387,25 @@ async def reconstruct_thread_context(arguments: dict[str, Any]) -> dict[str, Any
 
     remaining_tokens = MAX_CONTENT_TOKENS - conversation_tokens
     enhanced_arguments["_remaining_tokens"] = max(0, remaining_tokens)  # Ensure non-negative
+    logger.debug(f"[CONVERSATION_DEBUG] Token budget calculation:")
+    logger.debug(f"[CONVERSATION_DEBUG]   MAX_CONTENT_TOKENS: {MAX_CONTENT_TOKENS:,}")
+    logger.debug(f"[CONVERSATION_DEBUG]   Conversation tokens: {conversation_tokens:,}")
+    logger.debug(f"[CONVERSATION_DEBUG]   Remaining tokens: {remaining_tokens:,}")
 
     # Merge original context parameters (files, etc.) with new request
     if context.initial_context:
+        logger.debug(f"[CONVERSATION_DEBUG] Merging initial context with {len(context.initial_context)} parameters")
         for key, value in context.initial_context.items():
             if key not in enhanced_arguments and key not in ["temperature", "thinking_mode", "model"]:
                 enhanced_arguments[key] = value
+                logger.debug(f"[CONVERSATION_DEBUG] Merged initial context param: {key}")
 
     logger.info(f"Reconstructed context for thread {continuation_id} (turn {len(context.turns)})")
+    logger.debug(f"[CONVERSATION_DEBUG] Final enhanced arguments keys: {list(enhanced_arguments.keys())}")
+    
+    # Debug log files in the enhanced arguments for file tracking
+    if 'files' in enhanced_arguments:
+        logger.debug(f"[CONVERSATION_DEBUG] Final files in enhanced arguments: {enhanced_arguments['files']}")
 
     # Log to activity file for monitoring
     try:

simulator_tests/base_test.py

@@ -95,8 +95,12 @@ class Calculator:
         with open(test_config, "w") as f:
             f.write(config_content)
 
-        self.test_files = {"python": test_py, "config": test_config}
+        # Ensure absolute paths for MCP server compatibility
-        self.logger.debug(f"Created test files: {list(self.test_files.values())}")
+        self.test_files = {
+            "python": os.path.abspath(test_py), 
+            "config": os.path.abspath(test_config)
+        }
+        self.logger.debug(f"Created test files with absolute paths: {list(self.test_files.values())}")
 
     def call_mcp_tool(self, tool_name: str, params: dict) -> tuple[Optional[str], Optional[str]]:
         """Call an MCP tool via Claude CLI (docker exec)"""
@@ -137,7 +141,7 @@ class Calculator:
 
             # Execute the command
             result = subprocess.run(
-                docker_cmd, input=input_data, text=True, capture_output=True, timeout=300  # 5 minute timeout
+                docker_cmd, input=input_data, text=True, capture_output=True, timeout=3600  # 1 hour timeout
             )
 
             if result.returncode != 0:
@@ -155,7 +159,7 @@ class Calculator:
             return response_data, continuation_id
 
         except subprocess.TimeoutExpired:
-            self.logger.error(f"MCP tool call timed out: {tool_name}")
+            self.logger.error(f"MCP tool call timed out after 1 hour: {tool_name}")
             return None, None
         except Exception as e:
             self.logger.error(f"MCP tool call failed: {e}")
@@ -231,6 +235,17 @@ class Calculator:
 
         return subprocess.run(cmd, check=check, capture_output=capture_output, **kwargs)
 
+    def create_additional_test_file(self, filename: str, content: str) -> str:
+        """Create an additional test file for mixed scenario testing"""
+        if not hasattr(self, 'test_dir') or not self.test_dir:
+            raise RuntimeError("Test directory not initialized. Call setup_test_files() first.")
+        
+        file_path = os.path.join(self.test_dir, filename)
+        with open(file_path, "w") as f:
+            f.write(content)
+        # Return absolute path for MCP server compatibility
+        return os.path.abspath(file_path)
+
     def cleanup_test_files(self):
         """Clean up test files"""
         if hasattr(self, "test_dir") and self.test_dir and os.path.exists(self.test_dir):

simulator_tests/test_content_validation.py

@@ -53,6 +53,9 @@ DATABASE_CONFIG = {
             validation_file = os.path.join(self.test_dir, "validation_config.py")
             with open(validation_file, "w") as f:
                 f.write(validation_content)
+            
+            # Ensure absolute path for MCP server compatibility
+            validation_file = os.path.abspath(validation_file)
 
             # Test 1: Precommit tool with files parameter (where the bug occurred)
             self.logger.info("  1: Testing precommit tool content duplication")
@@ -110,13 +113,13 @@ DATABASE_CONFIG = {
             tools_to_test = [
                 (
                     "chat",
-                    {"prompt": "Please use low thinking mode. Analyze this config file", "files": [validation_file]},
+                    {"prompt": "Please use low thinking mode. Analyze this config file", "files": [validation_file]},  # Using absolute path
                 ),
                 (
                     "codereview",
-                    {"files": [validation_file], "context": "Please use low thinking mode. Review this configuration"},
+                    {"files": [validation_file], "context": "Please use low thinking mode. Review this configuration"},  # Using absolute path
                 ),
-                ("analyze", {"files": [validation_file], "analysis_type": "code_quality"}),
+                ("analyze", {"files": [validation_file], "analysis_type": "code_quality"}),  # Using absolute path
             ]
 
             for tool_name, params in tools_to_test:

simulator_tests/test_logs_validation.py

@@ -25,7 +25,7 @@ class LogsValidationTest(BaseSimulatorTest):
         try:
             self.logger.info("📋 Test: Validating Docker logs for file deduplication...")
 
-            # Get server logs from both main container and activity logs
+            # Get server logs from main container
             result = self.run_command(["docker", "logs", self.container_name], capture_output=True)
 
             if result.returncode != 0:
@@ -34,6 +34,12 @@ class LogsValidationTest(BaseSimulatorTest):
 
             main_logs = result.stdout.decode() + result.stderr.decode()
 
+            # Get logs from log monitor container (where detailed activity is logged)
+            monitor_result = self.run_command(["docker", "logs", "gemini-mcp-log-monitor"], capture_output=True)
+            monitor_logs = ""
+            if monitor_result.returncode == 0:
+                monitor_logs = monitor_result.stdout.decode() + monitor_result.stderr.decode()
+
             # Also get activity logs for more detailed conversation tracking
             activity_result = self.run_command(
                 ["docker", "exec", self.container_name, "cat", "/tmp/mcp_activity.log"], capture_output=True
@@ -43,7 +49,7 @@ class LogsValidationTest(BaseSimulatorTest):
             if activity_result.returncode == 0:
                 activity_logs = activity_result.stdout.decode()
 
-            logs = main_logs + "\n" + activity_logs
+            logs = main_logs + "\n" + monitor_logs + "\n" + activity_logs
 
             # Look for conversation threading patterns that indicate the system is working
             conversation_patterns = [

simulator_tests/test_per_tool_deduplication.py

@@ -4,8 +4,17 @@ Per-Tool File Deduplication Test
 
 Tests file deduplication for each individual MCP tool to ensure
 that files are properly deduplicated within single-tool conversations.
+Validates that:
+1. Files are embedded only once in conversation history
+2. Continuation calls don't re-read existing files
+3. New files are still properly embedded
+4. Docker logs show deduplication behavior
 """
 
+import json
+import os
+import subprocess
+import tempfile
 from .base_test import BaseSimulatorTest
 
 
@@ -20,96 +29,195 @@ class PerToolDeduplicationTest(BaseSimulatorTest):
     def test_description(self) -> str:
         return "File deduplication for individual tools"
 
-    def run_test(self) -> bool:
+    def get_docker_logs_since(self, since_time: str) -> str:
-        """Test file deduplication for each individual tool"""
+        """Get docker logs since a specific timestamp"""
         try:
-            self.logger.info("📄 Test: Per-tool file deduplication")
+            # Check both main server and log monitor for comprehensive logs
+            cmd_server = ["docker", "logs", "--since", since_time, self.container_name]
+            cmd_monitor = ["docker", "logs", "--since", since_time, "gemini-mcp-log-monitor"]
+            
+            result_server = subprocess.run(cmd_server, capture_output=True, text=True)
+            result_monitor = subprocess.run(cmd_monitor, capture_output=True, text=True)
+            
+            # Combine logs from both containers
+            combined_logs = result_server.stdout + "\n" + result_monitor.stdout
+            return combined_logs
+        except Exception as e:
+            self.logger.error(f"Failed to get docker logs: {e}")
+            return ""
+
+    # create_additional_test_file method now inherited from base class
+
+    def validate_file_deduplication_in_logs(self, logs: str, tool_name: str, test_file: str) -> bool:
+        """Validate that logs show file deduplication behavior"""
+        # Look for file embedding messages
+        embedding_messages = [line for line in logs.split('\n') if '📁' in line and 'embedding' in line and tool_name in line]
+        
+        # Look for deduplication/filtering messages  
+        filtering_messages = [line for line in logs.split('\n') if '📁' in line and 'Filtering' in line and tool_name in line]
+        skipping_messages = [line for line in logs.split('\n') if '📁' in line and 'skipping' in line and tool_name in line]
+        
+        deduplication_found = len(filtering_messages) > 0 or len(skipping_messages) > 0
+        
+        if deduplication_found:
+            self.logger.info(f"  ✅ {tool_name}: Found deduplication evidence in logs")
+            for msg in filtering_messages + skipping_messages:
+                self.logger.debug(f"    📁 {msg.strip()}")
+        else:
+            self.logger.warning(f"  ⚠️ {tool_name}: No deduplication evidence found in logs")
+            self.logger.debug(f"  📁 All embedding messages: {embedding_messages}")
+        
+        return deduplication_found
+
+    def run_test(self) -> bool:
+        """Test file deduplication with realistic precommit/codereview workflow"""
+        try:
+            self.logger.info("📄 Test: Simplified file deduplication with precommit/codereview workflow")
 
             # Setup test files
             self.setup_test_files()
+            
+            # Create a dummy file for precommit testing
+            dummy_content = '''def hello_world():
+    """A simple hello world function with a bug"""
+    print("Hello world!")
+    return "hello"
 
-            tools_to_test = [
+# TODO: Fix the inconsistent return type
-                (
+def calculate_sum(a, b):
-                    "thinkdeep",
+    return a + b  # Missing type hints
-                    {
+'''
-                        "current_analysis": "Please use low thinking mode. I'm analyzing this Python code to identify potential architectural improvements",
+            dummy_file_path = self.create_additional_test_file("dummy_code.py", dummy_content)
-                        "files": [self.test_files["python"]],
+            
-                    },
+            # Get timestamp for log filtering
-                ),
+            import datetime
-                (
+            start_time = datetime.datetime.now().strftime("%Y-%m-%dT%H:%M:%S")
-                    "analyze",
+
-                    {
+            # Step 1: precommit tool with dummy file (low thinking mode)
-                        "files": [self.test_files["python"]],
+            self.logger.info("  Step 1: precommit tool with dummy file")
-                        "question": "Please use low thinking mode. What are the architectural patterns in this code?",
+            precommit_params = {
-                    },
+                "path": self.test_dir,  # Required path parameter
-                ),
+                "files": [dummy_file_path],
-                (
+                "original_request": "Please use low thinking mode. Review this code for commit readiness",
-                    "debug",
+                "thinking_mode": "low"
-                    {
+            }
-                        "files": [self.test_files["python"]],
+            
-                        "error_description": "Please use low thinking mode. The fibonacci function seems slow for large numbers",
+            response1, continuation_id = self.call_mcp_tool("precommit", precommit_params)
-                    },
+            if not response1:
-                ),
+                self.logger.error("  ❌ Step 1: precommit tool failed")
-                (
+                return False
-                    "codereview",
+                
-                    {
+            if not continuation_id:
-                        "files": [self.test_files["python"]],
+                self.logger.error("  ❌ Step 1: precommit tool didn't provide continuation_id")
-                        "context": "General code review for quality and best practices",
+                return False
-                    },
+                
-                ),
+            self.logger.info(f"  ✅ Step 1: precommit completed with continuation_id: {continuation_id[:8]}...")
+
+            # Step 2: codereview tool with same file (NO continuation - fresh conversation)
+            self.logger.info("  Step 2: codereview tool with same file (fresh conversation)")
+            codereview_params = {
+                "files": [dummy_file_path],
+                "context": "Please use low thinking mode. General code review for quality and best practices"
+            }
+            
+            response2, _ = self.call_mcp_tool("codereview", codereview_params)
+            if not response2:
+                self.logger.error("  ❌ Step 2: codereview tool failed")
+                return False
+                
+            self.logger.info("  ✅ Step 2: codereview completed (fresh conversation)")
+
+            # Step 3: Create new file and continue with precommit
+            self.logger.info("  Step 3: precommit continuation with old + new file")
+            new_file_content = '''def new_feature():
+    """A new feature function"""
+    return {"status": "implemented", "version": "1.0"}
+
+class NewUtility:
+    """A new utility class"""
+    
+    def __init__(self):
+        self.initialized = True
+        
+    def process_data(self, data):
+        return f"Processed: {data}"
+'''
+            new_file_path = self.create_additional_test_file("new_feature.py", new_file_content)
+            
+            # Continue precommit with both files
+            continue_params = {
+                "continuation_id": continuation_id,
+                "path": self.test_dir,  # Required path parameter
+                "files": [dummy_file_path, new_file_path],  # Old + new file
+                "original_request": "Please use low thinking mode. Now also review the new feature file along with the previous one",
+                "thinking_mode": "low"
+            }
+            
+            response3, _ = self.call_mcp_tool("precommit", continue_params)
+            if not response3:
+                self.logger.error("  ❌ Step 3: precommit continuation failed")
+                return False
+                
+            self.logger.info("  ✅ Step 3: precommit continuation completed")
+
+            # Validate results in docker logs
+            self.logger.info("  📋 Validating conversation history and file deduplication...")
+            logs = self.get_docker_logs_since(start_time)
+            
+            # Check for conversation history building
+            conversation_logs = [line for line in logs.split('\n') if 'conversation' in line.lower() or 'history' in line.lower()]
+            
+            # Check for file embedding/deduplication
+            embedding_logs = [line for line in logs.split('\n') if '📁' in line or 'embedding' in line.lower() or 'file' in line.lower()]
+            
+            # Check for continuation evidence
+            continuation_logs = [line for line in logs.split('\n') if 'continuation' in line.lower() or continuation_id[:8] in line]
+            
+            # Check for both files mentioned
+            dummy_file_mentioned = any("dummy_code.py" in line for line in logs.split('\n'))
+            new_file_mentioned = any("new_feature.py" in line for line in logs.split('\n'))
+            
+            # Print diagnostic information
+            self.logger.info(f"  📊 Conversation logs found: {len(conversation_logs)}")
+            self.logger.info(f"  📊 File embedding logs found: {len(embedding_logs)}")
+            self.logger.info(f"  📊 Continuation logs found: {len(continuation_logs)}")
+            self.logger.info(f"  📊 Dummy file mentioned: {dummy_file_mentioned}")
+            self.logger.info(f"  📊 New file mentioned: {new_file_mentioned}")
+            
+            if self.verbose:
+                self.logger.debug("  📋 Sample embedding logs:")
+                for log in embedding_logs[:5]:  # Show first 5
+                    if log.strip():
+                        self.logger.debug(f"    {log.strip()}")
+                        
+                self.logger.debug("  📋 Sample continuation logs:")
+                for log in continuation_logs[:3]:  # Show first 3
+                    if log.strip():
+                        self.logger.debug(f"    {log.strip()}")
+
+            # Determine success criteria
+            success_criteria = [
+                len(embedding_logs) > 0,  # File embedding occurred
+                len(continuation_logs) > 0,  # Continuation worked
+                dummy_file_mentioned,  # Original file processed
+                new_file_mentioned  # New file processed
             ]
-
+            
-            successful_tests = 0
+            passed_criteria = sum(success_criteria)
-            total_tests = len(tools_to_test)
+            total_criteria = len(success_criteria)
-
+            
-            for tool_name, initial_params in tools_to_test:
+            self.logger.info(f"  📊 Success criteria met: {passed_criteria}/{total_criteria}")
-                self.logger.info(f"  {tool_name}: Testing {tool_name} tool file deduplication")
+            
-
+            if passed_criteria >= 3:  # At least 3 out of 4 criteria
-                # Initial call
+                self.logger.info("  ✅ File deduplication workflow test: PASSED")
-                response1, continuation_id = self.call_mcp_tool(tool_name, initial_params)
+                return True
-                if not response1:
+            else:
-                    self.logger.warning(f"  ⚠️ {tool_name} tool initial call failed, skipping")
+                self.logger.warning("  ⚠️ File deduplication workflow test: FAILED")
-                    continue
+                self.logger.warning("  💡 Check docker logs for detailed file embedding and continuation activity")
-
+                return False
-                if not continuation_id:
-                    self.logger.warning(f"  ⚠️ {tool_name} tool didn't provide continuation_id, skipping")
-                    continue
-
-                # Continue with same file - should be deduplicated
-                continue_params = initial_params.copy()
-                continue_params["continuation_id"] = continuation_id
-
-                if tool_name == "thinkdeep":
-                    continue_params["current_analysis"] = (
-                        "Please use low thinking mode. Now focus specifically on the recursive fibonacci implementation"
-                    )
-                elif tool_name == "analyze":
-                    continue_params["question"] = (
-                        "Please use low thinking mode. What are the performance characteristics of this code?"
-                    )
-                elif tool_name == "debug":
-                    continue_params["error_description"] = (
-                        "Please use low thinking mode. How can we optimize the fibonacci function?"
-                    )
-                elif tool_name == "codereview":
-                    continue_params["context"] = "Focus on the Calculator class implementation"
-
-                response2, _ = self.call_mcp_tool(tool_name, continue_params)
-                if response2:
-                    self.logger.info(f"  ✅ {tool_name} tool file deduplication working")
-                    successful_tests += 1
-                else:
-                    self.logger.warning(f"  ⚠️ {tool_name} tool continuation failed")
-
-            self.logger.info(
-                f"  ✅ Per-tool file deduplication tests completed: {successful_tests}/{total_tests} tools passed"
-            )
-
-            # Consider test successful if at least one tool worked
-            return successful_tests > 0
 
         except Exception as e:
-            self.logger.error(f"Per-tool file deduplication test failed: {e}")
+            self.logger.error(f"File deduplication workflow test failed: {e}")
             return False
         finally:
             self.cleanup_test_files()

tools/base.py

@@ -189,7 +189,9 @@ class BaseTool(ABC):
             # Thread not found, no files embedded
             return []
 
-        return get_conversation_file_list(thread_context)
+        embedded_files = get_conversation_file_list(thread_context)
+        logger.debug(f"[FILES] {self.name}: Found {len(embedded_files)} embedded files")
+        return embedded_files
 
     def filter_new_files(self, requested_files: list[str], continuation_id: Optional[str]) -> list[str]:
         """
@@ -207,12 +209,16 @@ class BaseTool(ABC):
         Returns:
             list[str]: List of files that need to be embedded (not already in history)
         """
+        logger.debug(f"[FILES] {self.name}: Filtering {len(requested_files)} requested files")
+        
         if not continuation_id:
             # New conversation, all files are new
+            logger.debug(f"[FILES] {self.name}: New conversation, all {len(requested_files)} files are new")
             return requested_files
 
         try:
             embedded_files = set(self.get_conversation_embedded_files(continuation_id))
+            logger.debug(f"[FILES] {self.name}: Found {len(embedded_files)} embedded files in conversation")
 
             # Safety check: If no files are marked as embedded but we have a continuation_id,
             # this might indicate an issue with conversation history. Be conservative.
@@ -220,10 +226,13 @@ class BaseTool(ABC):
                 logger.debug(
                     f"📁 {self.name} tool: No files found in conversation history for thread {continuation_id}"
                 )
+                logger.debug(f"[FILES] {self.name}: No embedded files found, returning all {len(requested_files)} requested files")
                 return requested_files
 
             # Return only files that haven't been embedded yet
             new_files = [f for f in requested_files if f not in embedded_files]
+            logger.debug(f"[FILES] {self.name}: After filtering: {len(new_files)} new files, {len(requested_files) - len(new_files)} already embedded")
+            logger.debug(f"[FILES] {self.name}: New files to embed: {new_files}")
 
             # Log filtering results for debugging
             if len(new_files) < len(requested_files):
@@ -231,6 +240,7 @@ class BaseTool(ABC):
                 logger.debug(
                     f"📁 {self.name} tool: Filtering {len(skipped)} files already in conversation history: {', '.join(skipped)}"
                 )
+                logger.debug(f"[FILES] {self.name}: Skipped (already embedded): {skipped}")
 
             return new_files
 
@@ -239,6 +249,7 @@ class BaseTool(ABC):
             # and include all files rather than risk losing access to needed files
             logger.warning(f"📁 {self.name} tool: Error checking conversation history for {continuation_id}: {e}")
             logger.warning(f"📁 {self.name} tool: Including all requested files as fallback")
+            logger.debug(f"[FILES] {self.name}: Exception in filter_new_files, returning all {len(requested_files)} files as fallback")
             return requested_files
 
     def _prepare_file_content_for_prompt(
@@ -294,12 +305,14 @@ class BaseTool(ABC):
         effective_max_tokens = max(1000, effective_max_tokens)
 
         files_to_embed = self.filter_new_files(request_files, continuation_id)
+        logger.debug(f"[FILES] {self.name}: Will embed {len(files_to_embed)} files after filtering")
 
         content_parts = []
 
         # Read content of new files only
         if files_to_embed:
             logger.debug(f"📁 {self.name} tool embedding {len(files_to_embed)} new files: {', '.join(files_to_embed)}")
+            logger.debug(f"[FILES] {self.name}: Starting file embedding with token budget {effective_max_tokens + reserve_tokens:,}")
             try:
                 file_content = read_files(
                     files_to_embed, max_tokens=effective_max_tokens + reserve_tokens, reserve_tokens=reserve_tokens
@@ -314,9 +327,13 @@ class BaseTool(ABC):
                 logger.debug(
                     f"📁 {self.name} tool successfully embedded {len(files_to_embed)} files ({content_tokens:,} tokens)"
                 )
+                logger.debug(f"[FILES] {self.name}: Successfully embedded files - {content_tokens:,} tokens used")
             except Exception as e:
                 logger.error(f"📁 {self.name} tool failed to embed files {files_to_embed}: {type(e).__name__}: {e}")
+                logger.debug(f"[FILES] {self.name}: File embedding failed - {type(e).__name__}: {e}")
                 raise
+        else:
+            logger.debug(f"[FILES] {self.name}: No files to embed after filtering")
 
         # Generate note about files already in conversation history
         if continuation_id and len(files_to_embed) < len(request_files):
@@ -326,6 +343,7 @@ class BaseTool(ABC):
                 logger.debug(
                     f"📁 {self.name} tool skipping {len(skipped_files)} files already in conversation history: {', '.join(skipped_files)}"
                 )
+                logger.debug(f"[FILES] {self.name}: Adding note about {len(skipped_files)} skipped files")
                 if content_parts:
                     content_parts.append("\n\n")
                 note_lines = [
@@ -335,8 +353,12 @@ class BaseTool(ABC):
                     "--- END NOTE ---",
                 ]
                 content_parts.append("\n".join(note_lines))
+            else:
+                logger.debug(f"[FILES] {self.name}: No skipped files to note")
 
-        return "".join(content_parts) if content_parts else ""
+        result = "".join(content_parts) if content_parts else ""
+        logger.debug(f"[FILES] {self.name}: _prepare_file_content_for_prompt returning {len(result)} chars")
+        return result
 
     def get_websearch_instruction(self, use_websearch: bool, tool_specific: Optional[str] = None) -> str:
         """
@@ -639,11 +661,29 @@ If any of these would strengthen your analysis, specify what Claude should searc
             # Catch all exceptions to prevent server crashes
             # Return error information in standardized format
             logger = logging.getLogger(f"tools.{self.name}")
-            logger.error(f"Error in {self.name} tool execution: {str(e)}", exc_info=True)
+            error_msg = str(e)
-
+            
+            # Check if this is a 500 INTERNAL error that asks for retry
+            if "500 INTERNAL" in error_msg and "Please retry" in error_msg:
+                logger.warning(f"500 INTERNAL error in {self.name} - attempting retry")
+                try:
+                    # Single retry attempt
+                    model = self._get_model_wrapper(request)
+                    raw_response = await model.generate_content(prompt)
+                    response = raw_response.text
+                    
+                    # If successful, process normally
+                    return [TextContent(type="text", text=self._process_response(response, request).model_dump_json())]
+                    
+                except Exception as retry_e:
+                    logger.error(f"Retry failed for {self.name} tool: {str(retry_e)}")
+                    error_msg = f"Tool failed after retry: {str(retry_e)}"
+            
+            logger.error(f"Error in {self.name} tool execution: {error_msg}", exc_info=True)
+            
             error_output = ToolOutput(
                 status="error",
-                content=f"Error in {self.name}: {str(e)}",
+                content=f"Error in {self.name}: {error_msg}",
                 content_type="text",
             )
             return [TextContent(type="text", text=error_output.model_dump_json())]

utils/conversation_memory.py

@@ -250,12 +250,16 @@ def add_turn(
         - Turn limits prevent runaway conversations
         - File references are preserved for cross-tool access
     """
+    logger.debug(f"[FLOW] Adding {role} turn to {thread_id} ({tool_name})")
+    
     context = get_thread(thread_id)
     if not context:
+        logger.debug(f"[FLOW] Thread {thread_id} not found for turn addition")
         return False
 
     # Check turn limit to prevent runaway conversations
     if len(context.turns) >= MAX_CONVERSATION_TURNS:
+        logger.debug(f"[FLOW] Thread {thread_id} at max turns ({MAX_CONVERSATION_TURNS})")
         return False
 
     # Create new turn with complete metadata
@@ -277,7 +281,8 @@ def add_turn(
         key = f"thread:{thread_id}"
         client.setex(key, 3600, context.model_dump_json())  # Refresh TTL to 1 hour
         return True
-    except Exception:
+    except Exception as e:
+        logger.debug(f"[FLOW] Failed to save turn to Redis: {type(e).__name__}")
         return False
 
 
@@ -296,19 +301,29 @@ def get_conversation_file_list(context: ThreadContext) -> list[str]:
         list[str]: Deduplicated list of file paths referenced in the conversation
     """
     if not context.turns:
+        logger.debug(f"[FILES] No turns found, returning empty file list")
         return []
 
     # Collect all unique files from all turns, preserving order of first appearance
     seen_files = set()
     unique_files = []
+    
+    logger.debug(f"[FILES] Collecting files from {len(context.turns)} turns")
 
-    for turn in context.turns:
+    for i, turn in enumerate(context.turns):
         if turn.files:
+            logger.debug(f"[FILES] Turn {i+1} has {len(turn.files)} files: {turn.files}")
             for file_path in turn.files:
                 if file_path not in seen_files:
                     seen_files.add(file_path)
                     unique_files.append(file_path)
-
+                    logger.debug(f"[FILES] Added new file: {file_path}")
+                else:
+                    logger.debug(f"[FILES] Duplicate file skipped: {file_path}")
+        else:
+            logger.debug(f"[FILES] Turn {i+1} has no files")
+    
+    logger.debug(f"[FILES] Final unique file list ({len(unique_files)}): {unique_files}")
     return unique_files
 
 
@@ -345,6 +360,7 @@ def build_conversation_history(context: ThreadContext, read_files_func=None) ->
 
     # Get all unique files referenced in this conversation
     all_files = get_conversation_file_list(context)
+    logger.debug(f"[FILES] Found {len(all_files)} unique files in conversation history")
 
     history_parts = [
         "=== CONVERSATION HISTORY ===",
@@ -356,6 +372,7 @@ def build_conversation_history(context: ThreadContext, read_files_func=None) ->
 
     # Embed all files referenced in this conversation once at the start
     if all_files:
+        logger.debug(f"[FILES] Starting embedding for {len(all_files)} files")
         history_parts.extend(
             [
                 "=== FILES REFERENCED IN THIS CONVERSATION ===",
@@ -379,6 +396,7 @@ def build_conversation_history(context: ThreadContext, read_files_func=None) ->
 
             for file_path in all_files:
                 try:
+                    logger.debug(f"[FILES] Processing file {file_path}")
                     # Correctly unpack the tuple returned by read_file_content
                     formatted_content, content_tokens = read_file_content(file_path)
                     if formatted_content:
@@ -391,20 +409,24 @@ def build_conversation_history(context: ThreadContext, read_files_func=None) ->
                             logger.debug(
                                 f"📄 File embedded in conversation history: {file_path} ({content_tokens:,} tokens)"
                             )
+                            logger.debug(f"[FILES] Successfully embedded {file_path} - {content_tokens:,} tokens (total: {total_tokens:,})")
                         else:
                             files_truncated += 1
                             logger.debug(
                                 f"📄 File truncated due to token limit: {file_path} ({content_tokens:,} tokens, would exceed {MAX_CONTENT_TOKENS:,} limit)"
                             )
+                            logger.debug(f"[FILES] File {file_path} would exceed token limit - skipping (would be {total_tokens + content_tokens:,} tokens)")
                             # Stop processing more files
                             break
                     else:
                         logger.debug(f"📄 File skipped (empty content): {file_path}")
+                        logger.debug(f"[FILES] File {file_path} has empty content - skipping")
                 except Exception as e:
                     # Skip files that can't be read but log the failure
                     logger.warning(
                         f"📄 Failed to embed file in conversation history: {file_path} - {type(e).__name__}: {e}"
                     )
+                    logger.debug(f"[FILES] Failed to read file {file_path} - {type(e).__name__}: {e}")
                     continue
 
             if file_contents:
@@ -417,11 +439,13 @@ def build_conversation_history(context: ThreadContext, read_files_func=None) ->
                 logger.debug(
                     f"📄 Conversation history file embedding complete: {files_included} files embedded, {files_truncated} truncated, {total_tokens:,} total tokens"
                 )
+                logger.debug(f"[FILES] File embedding summary - {files_included} embedded, {files_truncated} truncated, {total_tokens:,} tokens total")
             else:
                 history_parts.append("(No accessible files found)")
                 logger.debug(
                     f"📄 Conversation history file embedding: no accessible files found from {len(all_files)} requested"
                 )
+                logger.debug(f"[FILES] No accessible files found from {len(all_files)} requested files")
         else:
             # Fallback to original read_files function for backward compatibility
             files_content = read_files_func(all_files)
@@ -481,6 +505,11 @@ def build_conversation_history(context: ThreadContext, read_files_func=None) ->
     from utils.token_utils import estimate_tokens
 
     total_conversation_tokens = estimate_tokens(complete_history)
+    
+    # Summary log of what was built
+    user_turns = len([t for t in context.turns if t.role == "user"])
+    assistant_turns = len([t for t in context.turns if t.role == "assistant"])
+    logger.debug(f"[FLOW] Built conversation history: {user_turns} user + {assistant_turns} assistant turns, {len(all_files)} files, {total_conversation_tokens:,} tokens")
 
     return complete_history, total_conversation_tokens
 

utils/file_utils.py

@@ -422,11 +422,14 @@ def read_file_content(file_path: str, max_size: int = 1_000_000) -> tuple[str, i
         Tuple of (formatted_content, estimated_tokens)
         Content is wrapped with clear delimiters for AI parsing
     """
+    logger.debug(f"[FILES] read_file_content called for: {file_path}")
     try:
         # Validate path security before any file operations
         path = resolve_and_validate_path(file_path)
+        logger.debug(f"[FILES] Path validated and resolved: {path}")
     except (ValueError, PermissionError) as e:
         # Return error in a format that provides context to the AI
+        logger.debug(f"[FILES] Path validation failed for {file_path}: {type(e).__name__}: {e}")
         error_msg = str(e)
         # Add Docker-specific help if we're in Docker and path is inaccessible
         if WORKSPACE_ROOT and CONTAINER_WORKSPACE.exists():
@@ -438,28 +441,37 @@ def read_file_content(file_path: str, max_size: int = 1_000_000) -> tuple[str, i
                 f"To access files in a different directory, please run Claude from that directory."
             )
         content = f"\n--- ERROR ACCESSING FILE: {file_path} ---\nError: {error_msg}\n--- END FILE ---\n"
-        return content, estimate_tokens(content)
+        tokens = estimate_tokens(content)
+        logger.debug(f"[FILES] Returning error content for {file_path}: {tokens} tokens")
+        return content, tokens
 
     try:
         # Validate file existence and type
         if not path.exists():
+            logger.debug(f"[FILES] File does not exist: {file_path}")
             content = f"\n--- FILE NOT FOUND: {file_path} ---\nError: File does not exist\n--- END FILE ---\n"
             return content, estimate_tokens(content)
 
         if not path.is_file():
+            logger.debug(f"[FILES] Path is not a file: {file_path}")
             content = f"\n--- NOT A FILE: {file_path} ---\nError: Path is not a file\n--- END FILE ---\n"
             return content, estimate_tokens(content)
 
         # Check file size to prevent memory exhaustion
         file_size = path.stat().st_size
+        logger.debug(f"[FILES] File size for {file_path}: {file_size:,} bytes")
         if file_size > max_size:
+            logger.debug(f"[FILES] File too large: {file_path} ({file_size:,} > {max_size:,} bytes)")
             content = f"\n--- FILE TOO LARGE: {file_path} ---\nFile size: {file_size:,} bytes (max: {max_size:,})\n--- END FILE ---\n"
             return content, estimate_tokens(content)
 
         # Read the file with UTF-8 encoding, replacing invalid characters
         # This ensures we can handle files with mixed encodings
+        logger.debug(f"[FILES] Reading file content for {file_path}")
         with open(path, encoding="utf-8", errors="replace") as f:
             file_content = f.read()
+        
+        logger.debug(f"[FILES] Successfully read {len(file_content)} characters from {file_path}")
 
         # Format with clear delimiters that help the AI understand file boundaries
         # Using consistent markers makes it easier for the model to parse
@@ -467,11 +479,16 @@ def read_file_content(file_path: str, max_size: int = 1_000_000) -> tuple[str, i
         # ("--- BEGIN DIFF: ... ---") to allow AI to distinguish between complete file content
         # vs. partial diff content when files appear in both sections
         formatted = f"\n--- BEGIN FILE: {file_path} ---\n{file_content}\n--- END FILE: {file_path} ---\n"
-        return formatted, estimate_tokens(formatted)
+        tokens = estimate_tokens(formatted)
+        logger.debug(f"[FILES] Formatted content for {file_path}: {len(formatted)} chars, {tokens} tokens")
+        return formatted, tokens
 
     except Exception as e:
+        logger.debug(f"[FILES] Exception reading file {file_path}: {type(e).__name__}: {e}")
         content = f"\n--- ERROR READING FILE: {file_path} ---\nError: {str(e)}\n--- END FILE ---\n"
-        return content, estimate_tokens(content)
+        tokens = estimate_tokens(content)
+        logger.debug(f"[FILES] Returning error content for {file_path}: {tokens} tokens")
+        return content, tokens
 
 
 def read_files(
@@ -500,6 +517,9 @@ def read_files(
     if max_tokens is None:
         max_tokens = MAX_CONTEXT_TOKENS
 
+    logger.debug(f"[FILES] read_files called with {len(file_paths)} paths")
+    logger.debug(f"[FILES] Token budget: max={max_tokens:,}, reserve={reserve_tokens:,}, available={max_tokens - reserve_tokens:,}")
+
     content_parts = []
     total_tokens = 0
     available_tokens = max_tokens - reserve_tokens
@@ -520,31 +540,40 @@ def read_files(
     # Priority 2: Process file paths
     if file_paths:
         # Expand directories to get all individual files
+        logger.debug(f"[FILES] Expanding {len(file_paths)} file paths")
         all_files = expand_paths(file_paths)
+        logger.debug(f"[FILES] After expansion: {len(all_files)} individual files")
 
         if not all_files and file_paths:
             # No files found but paths were provided
+            logger.debug(f"[FILES] No files found from provided paths")
             content_parts.append(f"\n--- NO FILES FOUND ---\nProvided paths: {', '.join(file_paths)}\n--- END ---\n")
         else:
             # Read files sequentially until token limit is reached
-            for file_path in all_files:
+            logger.debug(f"[FILES] Reading {len(all_files)} files with token budget {available_tokens:,}")
+            for i, file_path in enumerate(all_files):
                 if total_tokens >= available_tokens:
-                    files_skipped.append(file_path)
+                    logger.debug(f"[FILES] Token budget exhausted, skipping remaining {len(all_files) - i} files")
-                    continue
+                    files_skipped.extend(all_files[i:])
+                    break
 
                 file_content, file_tokens = read_file_content(file_path)
+                logger.debug(f"[FILES] File {file_path}: {file_tokens:,} tokens")
 
                 # Check if adding this file would exceed limit
                 if total_tokens + file_tokens <= available_tokens:
                     content_parts.append(file_content)
                     total_tokens += file_tokens
+                    logger.debug(f"[FILES] Added file {file_path}, total tokens: {total_tokens:,}")
                 else:
                     # File too large for remaining budget
+                    logger.debug(f"[FILES] File {file_path} too large for remaining budget ({file_tokens:,} tokens, {available_tokens - total_tokens:,} remaining)")
                     files_skipped.append(file_path)
 
     # Add informative note about skipped files to help users understand
     # what was omitted and why
     if files_skipped:
+        logger.debug(f"[FILES] {len(files_skipped)} files skipped due to token limits")
         skip_note = "\n\n--- SKIPPED FILES (TOKEN LIMIT) ---\n"
         skip_note += f"Total skipped: {len(files_skipped)}\n"
         # Show first 10 skipped files as examples
@@ -555,4 +584,6 @@ def read_files(
         skip_note += "--- END SKIPPED FILES ---\n"
         content_parts.append(skip_note)
 
-    return "\n\n".join(content_parts) if content_parts else ""
+    result = "\n\n".join(content_parts) if content_parts else ""
+    logger.debug(f"[FILES] read_files complete: {len(result)} chars, {total_tokens:,} tokens used")
+    return result