More tests

server.py

@@ -349,6 +349,7 @@ async def reconstruct_thread_context(arguments: dict[str, Any]) -> dict[str, Any
 
     # Calculate remaining token budget for current request files/content
     from config import MAX_CONTENT_TOKENS
+
     remaining_tokens = MAX_CONTENT_TOKENS - conversation_tokens
     enhanced_arguments["_remaining_tokens"] = max(0, remaining_tokens)  # Ensure non-negative
 

test_simulation_files/test_module.py

@@ -2,11 +2,13 @@
 Sample Python module for testing MCP conversation continuity
 """
 
+
 def fibonacci(n):
     """Calculate fibonacci number recursively"""
     if n <= 1:
         return n
-    return fibonacci(n-1) + fibonacci(n-2)
+    return fibonacci(n - 1) + fibonacci(n - 2)
+
 
 def factorial(n):
     """Calculate factorial iteratively"""
@@ -15,6 +17,7 @@ def factorial(n):
         result *= i
     return result
 
+
 class Calculator:
     """Simple calculator class"""
 

tools/base.py

@@ -217,7 +217,9 @@ class BaseTool(ABC):
             # 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.
             if not embedded_files:
-                logger.debug(f"📁 {self.name} tool: No files found in conversation history for thread {continuation_id}")
+                logger.debug(
+                    f"📁 {self.name} tool: No files found in conversation history for thread {continuation_id}"
+                )
                 return requested_files
 
             # Return only files that haven't been embedded yet
@@ -226,7 +228,9 @@ class BaseTool(ABC):
             # Log filtering results for debugging
             if len(new_files) < len(requested_files):
                 skipped = [f for f in requested_files if f in embedded_files]
-                logger.debug(f"📁 {self.name} tool: Filtering {len(skipped)} files already in conversation history: {', '.join(skipped)}")
+                logger.debug(
+                    f"📁 {self.name} tool: Filtering {len(skipped)} files already in conversation history: {', '.join(skipped)}"
+                )
 
             return new_files
 
@@ -238,9 +242,14 @@ class BaseTool(ABC):
             return requested_files
 
     def _prepare_file_content_for_prompt(
-        self, request_files: list[str], continuation_id: Optional[str], context_description: str = "New files",
+        self,
-        max_tokens: Optional[int] = None, reserve_tokens: int = 1_000, remaining_budget: Optional[int] = None,
+        request_files: list[str],
-        arguments: Optional[dict] = None
+        continuation_id: Optional[str],
+        context_description: str = "New files",
+        max_tokens: Optional[int] = None,
+        reserve_tokens: int = 1_000,
+        remaining_budget: Optional[int] = None,
+        arguments: Optional[dict] = None,
     ) -> str:
         """
         Centralized file processing for tool prompts.
@@ -268,7 +277,7 @@ class BaseTool(ABC):
         # Extract remaining budget from arguments if available
         if remaining_budget is None:
             # Use provided arguments or fall back to stored arguments from execute()
-            args_to_use = arguments or getattr(self, '_current_arguments', {})
+            args_to_use = arguments or getattr(self, "_current_arguments", {})
             remaining_budget = args_to_use.get("_remaining_tokens")
 
         # Use remaining budget if provided, otherwise fall back to max_tokens or default
@@ -278,6 +287,7 @@ class BaseTool(ABC):
             effective_max_tokens = max_tokens - reserve_tokens
         else:
             from config import MAX_CONTENT_TOKENS
+
             effective_max_tokens = MAX_CONTENT_TOKENS - reserve_tokens
 
         # Ensure we have a reasonable minimum budget
@@ -291,7 +301,9 @@ class BaseTool(ABC):
         if files_to_embed:
             logger.debug(f"📁 {self.name} tool embedding {len(files_to_embed)} new files: {', '.join(files_to_embed)}")
             try:
-                file_content = read_files(files_to_embed, max_tokens=effective_max_tokens + reserve_tokens, reserve_tokens=reserve_tokens)
+                file_content = read_files(
+                    files_to_embed, max_tokens=effective_max_tokens + reserve_tokens, reserve_tokens=reserve_tokens
+                )
                 self._validate_token_limit(file_content, context_description)
                 content_parts.append(file_content)
 

tools/chat.py

@@ -9,7 +9,6 @@ from pydantic import Field
 
 from config import TEMPERATURE_BALANCED
 from prompts import CHAT_PROMPT
-from utils import read_files
 
 from .base import BaseTool, ToolRequest
 from .models import ToolOutput
@@ -119,9 +118,7 @@ class ChatTool(BaseTool):
         # Add context files if provided (using centralized file handling with filtering)
         if request.files:
             file_content = self._prepare_file_content_for_prompt(
-                request.files, 
+                request.files, request.continuation_id, "Context files"
-                request.continuation_id, 
-                "Context files"
             )
             if file_content:
                 user_content = f"{user_content}\n\n=== CONTEXT FILES ===\n{file_content}\n=== END CONTEXT ===="

tools/precommit.py

@@ -10,7 +10,7 @@ from pydantic import Field
 
 from config import MAX_CONTEXT_TOKENS
 from prompts.tool_prompts import PRECOMMIT_PROMPT
-from utils.file_utils import read_files, translate_file_paths, translate_path_for_environment
+from utils.file_utils import translate_file_paths, translate_path_for_environment
 from utils.git_utils import find_git_repositories, get_git_status, run_git_command
 from utils.token_utils import estimate_tokens
 
@@ -304,7 +304,7 @@ class Precommit(BaseTool):
                 request.continuation_id,
                 "Context files",
                 max_tokens=remaining_tokens + 1000,  # Add back the reserve that was calculated
-                reserve_tokens=1000  # Small reserve for formatting
+                reserve_tokens=1000,  # Small reserve for formatting
             )
 
             if file_content:

utils/conversation_memory.py

@@ -479,6 +479,7 @@ def build_conversation_history(context: ThreadContext, read_files_func=None) ->
     # Calculate total tokens for the complete conversation history
     complete_history = "\n".join(history_parts)
     from utils.token_utils import estimate_tokens
+
     total_conversation_tokens = estimate_tokens(complete_history)
 
     return complete_history, total_conversation_tokens