392 lines
15 KiB
Python
392 lines
15 KiB
Python
#!/usr/bin/env python3
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"""
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MCP Server for Document Translation API
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Model Context Protocol server for AI assistant integration
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"""
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import sys
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import json
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import asyncio
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import base64
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import requests
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from pathlib import Path
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from typing import Any, Optional
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# MCP Protocol Constants
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JSONRPC_VERSION = "2.0"
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class MCPServer:
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"""MCP Server for Document Translation"""
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def __init__(self):
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self.api_base = "http://localhost:8000"
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self.capabilities = {
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"tools": {}
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}
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def get_tools(self) -> list:
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"""Return list of available tools"""
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return [
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{
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"name": "translate_document",
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"description": "Translate a document (Excel, Word, PowerPoint) to another language while preserving formatting",
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"inputSchema": {
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"type": "object",
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"properties": {
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"file_path": {
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"type": "string",
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"description": "Path to the document file (.xlsx, .docx, .pptx)"
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},
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"target_language": {
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"type": "string",
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"description": "Target language code (e.g., 'en', 'fr', 'es', 'fa', 'de')"
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},
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"provider": {
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"type": "string",
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"enum": ["google", "ollama", "deepl", "libre"],
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"description": "Translation provider (default: google)"
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},
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"ollama_model": {
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"type": "string",
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"description": "Ollama model to use (e.g., 'llama3.2', 'gemma3:12b')"
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},
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"translate_images": {
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"type": "boolean",
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"description": "Extract and translate text from images using vision model"
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},
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"system_prompt": {
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"type": "string",
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"description": "Custom system prompt with context, glossary, or instructions for LLM translation"
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},
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"output_path": {
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"type": "string",
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"description": "Path where to save the translated document (optional)"
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}
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},
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"required": ["file_path", "target_language"]
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}
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},
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{
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"name": "list_ollama_models",
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"description": "List available Ollama models for translation",
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"inputSchema": {
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"type": "object",
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"properties": {
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"base_url": {
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"type": "string",
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"description": "Ollama server URL (default: http://localhost:11434)"
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}
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}
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}
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},
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{
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"name": "get_supported_languages",
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"description": "Get list of supported language codes for translation",
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"inputSchema": {
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"type": "object",
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"properties": {}
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}
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},
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{
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"name": "configure_translation",
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"description": "Configure translation settings",
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"inputSchema": {
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"type": "object",
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"properties": {
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"provider": {
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"type": "string",
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"enum": ["google", "ollama", "deepl", "libre"],
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"description": "Default translation provider"
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},
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"ollama_url": {
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"type": "string",
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"description": "Ollama server URL"
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},
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"ollama_model": {
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"type": "string",
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"description": "Default Ollama model"
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}
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}
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}
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},
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{
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"name": "check_api_health",
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"description": "Check if the translation API is running and healthy",
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"inputSchema": {
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"type": "object",
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"properties": {}
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}
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}
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]
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async def handle_tool_call(self, name: str, arguments: dict) -> dict:
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"""Handle tool calls"""
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try:
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if name == "translate_document":
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return await self.translate_document(arguments)
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elif name == "list_ollama_models":
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return await self.list_ollama_models(arguments)
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elif name == "get_supported_languages":
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return await self.get_supported_languages()
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elif name == "configure_translation":
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return await self.configure_translation(arguments)
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elif name == "check_api_health":
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return await self.check_api_health()
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else:
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return {"error": f"Unknown tool: {name}"}
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except Exception as e:
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return {"error": str(e)}
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async def translate_document(self, args: dict) -> dict:
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"""Translate a document file"""
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file_path = Path(args["file_path"])
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if not file_path.exists():
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return {"error": f"File not found: {file_path}"}
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# Prepare form data
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with open(file_path, 'rb') as f:
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files = {'file': (file_path.name, f)}
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data = {
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'target_language': args['target_language'],
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'provider': args.get('provider', 'google'),
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'translate_images': str(args.get('translate_images', False)).lower(),
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}
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if args.get('ollama_model'):
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data['ollama_model'] = args['ollama_model']
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if args.get('system_prompt'):
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data['system_prompt'] = args['system_prompt']
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try:
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response = requests.post(
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f"{self.api_base}/translate",
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files=files,
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data=data,
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timeout=300 # 5 minutes timeout
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)
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if response.status_code == 200:
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# Save translated file
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output_path = args.get('output_path')
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if not output_path:
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output_path = file_path.parent / f"translated_{file_path.name}"
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output_path = Path(output_path)
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with open(output_path, 'wb') as out:
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out.write(response.content)
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return {
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"success": True,
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"message": f"Document translated successfully",
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"output_path": str(output_path),
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"source_file": str(file_path),
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"target_language": args['target_language'],
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"provider": args.get('provider', 'google')
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}
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else:
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error_detail = response.json() if response.headers.get('content-type') == 'application/json' else response.text
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return {"error": f"Translation failed: {error_detail}"}
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except requests.exceptions.ConnectionError:
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return {"error": "Cannot connect to translation API. Make sure the server is running on http://localhost:8000"}
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except requests.exceptions.Timeout:
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return {"error": "Translation request timed out"}
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async def list_ollama_models(self, args: dict) -> dict:
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"""List available Ollama models"""
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base_url = args.get('base_url', 'http://localhost:11434')
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try:
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response = requests.get(
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f"{self.api_base}/ollama/models",
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params={'base_url': base_url},
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timeout=10
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)
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if response.status_code == 200:
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data = response.json()
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return {
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"models": data.get('models', []),
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"count": data.get('count', 0),
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"ollama_url": base_url
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}
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else:
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return {"error": "Failed to list models", "models": []}
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except requests.exceptions.ConnectionError:
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return {"error": "Cannot connect to API server", "models": []}
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async def get_supported_languages(self) -> dict:
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"""Get supported language codes"""
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return {
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"languages": [
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{"code": "en", "name": "English"},
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{"code": "fa", "name": "Persian/Farsi"},
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{"code": "fr", "name": "French"},
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{"code": "es", "name": "Spanish"},
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{"code": "de", "name": "German"},
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{"code": "it", "name": "Italian"},
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{"code": "pt", "name": "Portuguese"},
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{"code": "ru", "name": "Russian"},
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{"code": "zh", "name": "Chinese"},
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{"code": "ja", "name": "Japanese"},
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{"code": "ko", "name": "Korean"},
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{"code": "ar", "name": "Arabic"},
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{"code": "nl", "name": "Dutch"},
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{"code": "pl", "name": "Polish"},
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{"code": "tr", "name": "Turkish"},
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{"code": "vi", "name": "Vietnamese"},
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{"code": "th", "name": "Thai"},
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{"code": "hi", "name": "Hindi"},
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{"code": "he", "name": "Hebrew"},
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{"code": "sv", "name": "Swedish"}
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]
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}
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async def configure_translation(self, args: dict) -> dict:
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"""Configure translation settings"""
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config = {}
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if args.get('ollama_url') and args.get('ollama_model'):
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try:
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response = requests.post(
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f"{self.api_base}/ollama/configure",
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data={
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'base_url': args['ollama_url'],
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'model': args['ollama_model']
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},
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timeout=10
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)
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if response.status_code == 200:
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config['ollama'] = response.json()
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except Exception as e:
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config['ollama_error'] = str(e)
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config['provider'] = args.get('provider', 'google')
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return {
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"success": True,
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"configuration": config
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}
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async def check_api_health(self) -> dict:
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"""Check API health status"""
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try:
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response = requests.get(f"{self.api_base}/health", timeout=5)
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if response.status_code == 200:
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return {
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"status": "healthy",
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"api_url": self.api_base,
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"details": response.json()
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}
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else:
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return {"status": "unhealthy", "error": "API returned non-200 status"}
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except requests.exceptions.ConnectionError:
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return {
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"status": "unavailable",
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"error": "Cannot connect to API. Start the server with: python main.py"
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}
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def create_response(self, id: Any, result: Any) -> dict:
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"""Create JSON-RPC response"""
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return {
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"jsonrpc": JSONRPC_VERSION,
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"id": id,
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"result": result
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}
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def create_error(self, id: Any, code: int, message: str) -> dict:
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"""Create JSON-RPC error response"""
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return {
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"jsonrpc": JSONRPC_VERSION,
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"id": id,
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"error": {
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"code": code,
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"message": message
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}
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}
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async def handle_message(self, message: dict) -> Optional[dict]:
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"""Handle incoming JSON-RPC message"""
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msg_id = message.get("id")
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method = message.get("method")
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params = message.get("params", {})
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if method == "initialize":
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return self.create_response(msg_id, {
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"protocolVersion": "2024-11-05",
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"capabilities": self.capabilities,
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"serverInfo": {
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"name": "document-translator",
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"version": "1.0.0"
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}
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})
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elif method == "notifications/initialized":
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return None # No response needed for notifications
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elif method == "tools/list":
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return self.create_response(msg_id, {
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"tools": self.get_tools()
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})
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elif method == "tools/call":
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tool_name = params.get("name")
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tool_args = params.get("arguments", {})
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result = await self.handle_tool_call(tool_name, tool_args)
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return self.create_response(msg_id, {
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"content": [
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{
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"type": "text",
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"text": json.dumps(result, indent=2, ensure_ascii=False)
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}
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]
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})
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elif method == "ping":
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return self.create_response(msg_id, {})
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else:
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return self.create_error(msg_id, -32601, f"Method not found: {method}")
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async def run(self):
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"""Run the MCP server using stdio"""
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while True:
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try:
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line = sys.stdin.readline()
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if not line:
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break
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message = json.loads(line)
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response = await self.handle_message(message)
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if response:
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sys.stdout.write(json.dumps(response) + "\n")
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sys.stdout.flush()
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except json.JSONDecodeError as e:
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error = self.create_error(None, -32700, f"Parse error: {e}")
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sys.stdout.write(json.dumps(error) + "\n")
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sys.stdout.flush()
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except Exception as e:
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error = self.create_error(None, -32603, f"Internal error: {e}")
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sys.stdout.write(json.dumps(error) + "\n")
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sys.stdout.flush()
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def main():
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"""Main entry point"""
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server = MCPServer()
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asyncio.run(server.run())
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if __name__ == "__main__":
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main()
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