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

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abhishekbhakat
2025-03-26 19:06:21 +00:00
parent ab8d5fe074
commit bae517a322
2 changed files with 48 additions and 50 deletions
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50
src/providers/anthropic_provider/tools.py
View File

@@ -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:

48
src/tools/conversion.py
View File

@@ -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).