refactor: move convert_to_anthropic_tools function to tools.py for better organization

src/providers/anthropic_provider/tools.py

@@ -4,8 +4,6 @@ from typing import Any
 
 from anthropic.types import Message
 
-from src.tools.conversion import convert_to_anthropic_tools
-
 logger = logging.getLogger(__name__)
 
 
@@ -63,6 +61,54 @@ def format_tool_results(tool_call_id: str, result: Any) -> dict[str, Any]:
     return {"type": "tool_result", "tool_use_id": tool_call_id, "content": content_str}
 
 
+def convert_to_anthropic_tools(mcp_tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    """
+    Convert MCP tools to Anthropic tool definitions.
+
+    Args:
+        mcp_tools: List of MCP tools (each with server_name, name, description, inputSchema).
+
+    Returns:
+        List of Anthropic tool definitions.
+    """
+    logger.debug(f"Converting {len(mcp_tools)} MCP tools to Anthropic format")
+    anthropic_tools = []
+
+    for tool in mcp_tools:
+        server_name = tool.get("server_name")
+        tool_name = tool.get("name")
+        description = tool.get("description")
+        input_schema = tool.get("inputSchema")
+
+        if not server_name or not tool_name or not description or not input_schema:
+            logger.warning(f"Skipping invalid MCP tool definition during Anthropic conversion: {tool}")
+            continue
+
+        # Prefix tool name with server name for routing
+        prefixed_tool_name = f"{server_name}__{tool_name}"
+
+        # Initialize the Anthropic tool structure
+        # Anthropic's format is quite close to JSON Schema
+        anthropic_tool = {"name": prefixed_tool_name, "description": description, "input_schema": input_schema}
+
+        # Basic validation/cleaning of schema if needed
+        if not isinstance(input_schema, dict) or input_schema.get("type") != "object":
+            logger.warning(f"Input schema for tool '{prefixed_tool_name}' is not a valid JSON object schema. Anthropic might reject this.")
+            # Ensure basic structure if missing
+            if not isinstance(input_schema, dict):
+                input_schema = {}
+            if "type" not in input_schema:
+                input_schema["type"] = "object"
+            if "properties" not in input_schema:
+                input_schema["properties"] = {}
+            anthropic_tool["input_schema"] = input_schema
+
+        anthropic_tools.append(anthropic_tool)
+        logger.debug(f"Converted MCP tool to Anthropic: {prefixed_tool_name}")
+
+    return anthropic_tools
+
+
 def convert_tools(tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
     logger.debug(f"Converting {len(tools)} tools to Anthropic format.")
     try:

src/tools/conversion.py

@@ -64,54 +64,6 @@ def convert_to_openai_tools(mcp_tools: list[dict[str, Any]]) -> list[dict[str, A
     return openai_tools
 
 
-def convert_to_anthropic_tools(mcp_tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
-    """
-    Convert MCP tools to Anthropic tool definitions.
-
-    Args:
-        mcp_tools: List of MCP tools (each with server_name, name, description, inputSchema).
-
-    Returns:
-        List of Anthropic tool definitions.
-    """
-    logger.debug(f"Converting {len(mcp_tools)} MCP tools to Anthropic format")
-    anthropic_tools = []
-
-    for tool in mcp_tools:
-        server_name = tool.get("server_name")
-        tool_name = tool.get("name")
-        description = tool.get("description")
-        input_schema = tool.get("inputSchema")
-
-        if not server_name or not tool_name or not description or not input_schema:
-            logger.warning(f"Skipping invalid MCP tool definition during Anthropic conversion: {tool}")
-            continue
-
-        # Prefix tool name with server name for routing
-        prefixed_tool_name = f"{server_name}__{tool_name}"
-
-        # Initialize the Anthropic tool structure
-        # Anthropic's format is quite close to JSON Schema
-        anthropic_tool = {"name": prefixed_tool_name, "description": description, "input_schema": input_schema}
-
-        # Basic validation/cleaning of schema if needed
-        if not isinstance(input_schema, dict) or input_schema.get("type") != "object":
-            logger.warning(f"Input schema for tool '{prefixed_tool_name}' is not a valid JSON object schema. Anthropic might reject this.")
-            # Ensure basic structure if missing
-            if not isinstance(input_schema, dict):
-                input_schema = {}
-            if "type" not in input_schema:
-                input_schema["type"] = "object"
-            if "properties" not in input_schema:
-                input_schema["properties"] = {}
-            anthropic_tool["input_schema"] = input_schema
-
-        anthropic_tools.append(anthropic_tool)
-        logger.debug(f"Converted MCP tool to Anthropic: {prefixed_tool_name}")
-
-    return anthropic_tools
-
-
 def convert_to_google_tools(mcp_tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
     """
     Convert MCP tools to Google Gemini format (dictionary structure).