diff --git a/samples/travel-planner-local-mcp/.env.example b/samples/travel-planner-local-mcp/.env.example deleted file mode 100644 index 1514d9e7..00000000 --- a/samples/travel-planner-local-mcp/.env.example +++ /dev/null @@ -1,4 +0,0 @@ -UIPATH_URL=https://alpha.uipath.com/ada/byoa -UIPATH_ACCESS_TOKEN=xxx -UIPATH_TENANT_ID=6961a069-3392-40ca-bf5d-276f4e54c8ff -UIPATH_ORGANIZATION_ID=b7006b1c-11c3-4a80-802e-fee0ebf9c360 diff --git a/samples/travel-planner-local-mcp/README.md b/samples/travel-planner-local-mcp/README.md deleted file mode 100644 index cccc4764..00000000 --- a/samples/travel-planner-local-mcp/README.md +++ /dev/null @@ -1,64 +0,0 @@ -# Travel planner agent with stdio mcp - -Use LangGrahp with UiPath LLMs to automatically create a travel plan. -Shows the usage of stdio mcp. - -## Debug - -1. Clone the repository: -```bash -git clone -cd samples\travel-planner-local-mcp -``` - -2. Install dependencies: -```bash -pip install uv -uv venv -p 3.11 .venv -.venv\Scripts\activate -uv sync -``` - -3. Init uipath -``` -uipath init -uipath auth -``` - -4. Create a `.env` file in the project root with the following configuration: -```env -UIPATH_URL=https://alpha.uipath.com/ada/byoa -UIPATH_ACCESS_TOKEN=xxx -UIPATH_TENANT_ID=6961a069-3392-40ca-bf5d-276f4e54c8ff -UIPATH_ORGANIZATION_ID=b7006b1c-11c3-4a80-802e-fee0ebf9c360 -``` - -```bash -uipath run [--resume] -``` - -### Run - -To classify a ticket, run the script using UiPath CLI: - -```bash -uipath run agent '{"message": "Help me plan a ski vacation on a hard track." }' -``` - -### Input JSON Format - -The input ticket should be in the following format: -```json -{ - "message": "Plan a trip to...", -} -``` - -### Output Format - -The script outputs JSON with a markdown summary: -```json -{ - "summary": "# Final Report\n\n## Ski Vacation Options\n\n### 1. Aspen Snowmass\n- **Location:** Colorado, USA\n- **Elevation:** 12,510 ft\n- **Trails:** 362\n- **Best For:** Intermediate to advanced skiers\n- **Season:** November to April\n- **Highlights:** Aspen Snowmass features four mountains with varied terrain, luxury amenities, and a vibrant après-ski scene.\n- **Weather Forecast:** Currently unavailable, but typically sunny and around 75°F based on seasonal averages.\n\n### 2. Vail\n- **Location:** Colorado, USA\n- **Elevation:** 11,570 ft\n- **Trails:** 195\n- **Best For:** Intermediate to advanced skiers\n- **Season:** November to April\n- **Highlights:** Vail is known for its Back Bowls, European-style village, and extensive groomed terrain.\n- **Current Weather:** 25°F, Light Snow with 70% humidity and 8 mph winds. Current snow depth is 30 inches.\n\nBoth Aspen Snowmass and Vail offer excellent facilities and challenging tracks for advanced skiers. You can enjoy a mix of thrilling ski experiences and luxurious amenities. Vail currently has favorable skiing conditions with fresh snow, making it an attractive option for your ski vacation." -} -``` diff --git a/samples/travel-planner-local-mcp/agent.mermaid b/samples/travel-planner-local-mcp/agent.mermaid deleted file mode 100644 index b3fe1dfa..00000000 --- a/samples/travel-planner-local-mcp/agent.mermaid +++ /dev/null @@ -1,22 +0,0 @@ ---- -config: - flowchart: - curve: linear ---- -graph TD; - __start__([

__start__

]):::first - init(init) - agent(agent) - tools(tools) - output_summary(output_summary) - __end__([

__end__

]):::last - __start__ --> init; - init --> agent; - output_summary --> __end__; - tools --> agent; - agent -.-> tools; - agent -.-> output_summary; - agent -.-> agent; - classDef default fill:#f2f0ff,line-height:1.2 - classDef first fill-opacity:0 - classDef last fill:#bfb6fc diff --git a/samples/travel-planner-local-mcp/langgraph.json b/samples/travel-planner-local-mcp/langgraph.json deleted file mode 100644 index 14e809a4..00000000 --- a/samples/travel-planner-local-mcp/langgraph.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - "dependencies": [ - "." - ], - "graphs": { - "agent": "./main.py:make_graph" - }, - "env": ".env" -} \ No newline at end of file diff --git a/samples/travel-planner-local-mcp/main.py b/samples/travel-planner-local-mcp/main.py deleted file mode 100644 index 6fedf5de..00000000 --- a/samples/travel-planner-local-mcp/main.py +++ /dev/null @@ -1,101 +0,0 @@ -import os -import sys -from contextlib import asynccontextmanager - -from langchain_core.messages import HumanMessage, SystemMessage -from langchain_mcp_adapters.client import MultiServerMCPClient -from langgraph.graph import END, START, MessagesState, StateGraph -from langgraph.prebuilt import ToolNode -from pydantic import BaseModel -from uipath_langchain.chat.models import ( - UiPathNormalizedChatModel, -) - - -class GraphInput(BaseModel): - message: str - - -class GraphOutput(BaseModel): - summary: str - - -def get_file_path(filename): - """Get absolute path to file in current directory.""" - return os.path.abspath(os.path.join(os.getcwd(), filename)) - - -mcp_config = { - "travel_mcp": { - "command": sys.executable, - "args": [get_file_path("./mcps/travel_mcp.py")], - "transport": "stdio", - } -} - - -@asynccontextmanager -async def make_graph(): - async with MultiServerMCPClient(mcp_config) as client: - tools = client.get_tools() - tool_node = ToolNode(tools) - - def init(state: GraphInput): - return { - "messages": [ - SystemMessage( - content="You are a helpful travel planner assistant!. When you are done please write your report in markdown as a single message and begin with `# Final Report`" - ), - HumanMessage(content=state.message), - ] - } - - def should_continue(state: MessagesState): - messages = state["messages"] - last_message = messages[-1] - - # Check if the last message contains a final report indicator - if hasattr(last_message, "content") and isinstance( - last_message.content, str - ): - if "# final report" in last_message.content.lower(): - return "output_summary" - - if last_message.tool_calls: - return "tools" - - return "agent" - - def output_summary(state: MessagesState): - messages = state["messages"] - last_message = messages[-1] - return {"summary": last_message.content} - - async def call_model(state: MessagesState): - messages = state["messages"] - - agent = UiPathNormalizedChatModel().bind_tools(tools) - response = agent.invoke(messages) - - return {"messages": [response]} - - workflow = StateGraph(MessagesState, input=GraphInput, output=GraphOutput) - # workflow = StateGraph(MessagesState) - - # Define the two nodes we will cycle between - workflow.add_node("init", init) - workflow.add_node("agent", call_model) - workflow.add_node("tools", tool_node) - workflow.add_node("output_summary", output_summary) - - workflow.add_edge(START, "init") - workflow.add_edge("init", "agent") - workflow.add_conditional_edges( - "agent", should_continue, ["tools", "output_summary", "agent"] - ) - workflow.add_edge("tools", "agent") - workflow.add_edge("output_summary", END) - - graph = workflow.compile() - - yield graph diff --git a/samples/travel-planner-local-mcp/mcps/estate_mcp.py b/samples/travel-planner-local-mcp/mcps/estate_mcp.py deleted file mode 100644 index 9e5b6ceb..00000000 --- a/samples/travel-planner-local-mcp/mcps/estate_mcp.py +++ /dev/null @@ -1,388 +0,0 @@ -import sqlite3 -from datetime import datetime -from typing import Dict, List, Optional - -from mcp.server.fastmcp import FastMCP - -# Initialize FastMCP instance -mcp = FastMCP("Real Estate Database 🏠") - -# Database setup -DB_PATH = "real_estate.db" - - -def initialize_database(): - """Create database and tables if they don't exist""" - conn = sqlite3.connect(DB_PATH) - cursor = conn.cursor() - - # Create properties table - cursor.execute(""" - CREATE TABLE IF NOT EXISTS properties ( - id INTEGER PRIMARY KEY AUTOINCREMENT, - address TEXT NOT NULL, - city TEXT NOT NULL, - state TEXT NOT NULL, - zip_code TEXT NOT NULL, - price REAL NOT NULL, - bedrooms INTEGER NOT NULL, - bathrooms REAL NOT NULL, - sq_feet INTEGER NOT NULL, - property_type TEXT NOT NULL, - year_built INTEGER, - description TEXT, - listed_date TEXT - ) - """) - - conn.commit() - conn.close() - - -def populate_sample_data(): - """Add sample real estate data if the database is empty""" - conn = sqlite3.connect(DB_PATH) - cursor = conn.cursor() - - # Check if data already exists - cursor.execute("SELECT COUNT(*) FROM properties") - count = cursor.fetchone()[0] - - if count == 0: - # Sample properties - properties = [ - { - "address": "123 Main St", - "city": "San Francisco", - "state": "CA", - "zip_code": "94105", - "price": 1250000, - "bedrooms": 3, - "bathrooms": 2.5, - "sq_feet": 1800, - "property_type": "Condo", - "year_built": 2010, - "description": "Modern condo with bay views", - "listed_date": "2025-03-01", - }, - { - "address": "456 Oak Ave", - "city": "New York", - "state": "NY", - "zip_code": "10001", - "price": 2100000, - "bedrooms": 2, - "bathrooms": 2, - "sq_feet": 1100, - "property_type": "Apartment", - "year_built": 1998, - "description": "Luxury apartment in heart of Manhattan", - "listed_date": "2025-02-15", - }, - { - "address": "789 Pine Rd", - "city": "Austin", - "state": "TX", - "zip_code": "78701", - "price": 550000, - "bedrooms": 4, - "bathrooms": 3, - "sq_feet": 2500, - "property_type": "Single Family", - "year_built": 2015, - "description": "Spacious home with backyard", - "listed_date": "2025-03-10", - }, - { - "address": "321 Maple Dr", - "city": "Seattle", - "state": "WA", - "zip_code": "98101", - "price": 875000, - "bedrooms": 3, - "bathrooms": 2, - "sq_feet": 1650, - "property_type": "Townhouse", - "year_built": 2018, - "description": "Modern townhouse near downtown", - "listed_date": "2025-01-20", - }, - { - "address": "555 Cedar Ln", - "city": "Chicago", - "state": "IL", - "zip_code": "60601", - "price": 720000, - "bedrooms": 2, - "bathrooms": 1.5, - "sq_feet": 1200, - "property_type": "Condo", - "year_built": 2005, - "description": "Renovated condo with lake views", - "listed_date": "2025-02-28", - }, - ] - - # Insert sample data - for prop in properties: - cursor.execute( - """ - INSERT INTO properties - (address, city, state, zip_code, price, bedrooms, bathrooms, - sq_feet, property_type, year_built, description, listed_date) - VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) - """, - ( - prop["address"], - prop["city"], - prop["state"], - prop["zip_code"], - prop["price"], - prop["bedrooms"], - prop["bathrooms"], - prop["sq_feet"], - prop["property_type"], - prop["year_built"], - prop["description"], - prop["listed_date"], - ), - ) - - conn.commit() - print("Sample data added to the database.") - - conn.close() - - -# Initialize the database -initialize_database() -populate_sample_data() - -# MCP Tools for interacting with the database - - -@mcp.tool() -def get_all_properties() -> List[Dict]: - """Get all properties from the database""" - conn = sqlite3.connect(DB_PATH) - conn.row_factory = sqlite3.Row - cursor = conn.cursor() - - cursor.execute("SELECT * FROM properties") - rows = cursor.fetchall() - - properties = [dict(row) for row in rows] - conn.close() - - return properties - - -@mcp.tool() -def get_property(property_id: int) -> Optional[Dict]: - """Get a specific property by ID""" - conn = sqlite3.connect(DB_PATH) - conn.row_factory = sqlite3.Row - cursor = conn.cursor() - - cursor.execute("SELECT * FROM properties WHERE id = ?", (property_id,)) - row = cursor.fetchone() - - if row: - property_data = dict(row) - else: - property_data = None - - conn.close() - return property_data - - -@mcp.tool() -def search_properties( - city: Optional[str] = None, - min_price: Optional[float] = None, - max_price: Optional[float] = None, - min_bedrooms: Optional[int] = None, - property_type: Optional[str] = None, -) -> List[Dict]: - """ - Search for properties with various filters - """ - conn = sqlite3.connect(DB_PATH) - conn.row_factory = sqlite3.Row - cursor = conn.cursor() - - query = "SELECT * FROM properties WHERE 1=1" - params = [] - - if city: - query += " AND city = ?" - params.append(city) - - if min_price is not None: - query += " AND price >= ?" - params.append(min_price) - - if max_price is not None: - query += " AND price <= ?" - params.append(max_price) - - if min_bedrooms is not None: - query += " AND bedrooms >= ?" - params.append(min_bedrooms) - - if property_type: - query += " AND property_type = ?" - params.append(property_type) - - cursor.execute(query, params) - rows = cursor.fetchall() - - properties = [dict(row) for row in rows] - conn.close() - - return properties - - -@mcp.tool() -def add_property( - address: str, - city: str, - state: str, - zip_code: str, - price: float, - bedrooms: int, - bathrooms: float, - sq_feet: int, - property_type: str, - year_built: Optional[int] = None, - description: Optional[str] = None, -) -> Dict: - """Add a new property to the database""" - conn = sqlite3.connect(DB_PATH) - cursor = conn.cursor() - - listed_date = datetime.now().strftime("%Y-%m-%d") - - cursor.execute( - """ - INSERT INTO properties - (address, city, state, zip_code, price, bedrooms, bathrooms, - sq_feet, property_type, year_built, description, listed_date) - VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) - """, - ( - address, - city, - state, - zip_code, - price, - bedrooms, - bathrooms, - sq_feet, - property_type, - year_built, - description, - listed_date, - ), - ) - - property_id = cursor.lastrowid - conn.commit() - conn.close() - - return {"id": property_id, "message": "Property added successfully"} - - -@mcp.tool() -def update_property( - property_id: int, price: Optional[float] = None, description: Optional[str] = None -) -> Dict: - """Update price and/or description of an existing property""" - conn = sqlite3.connect(DB_PATH) - cursor = conn.cursor() - - # Check if property exists - cursor.execute("SELECT id FROM properties WHERE id = ?", (property_id,)) - if not cursor.fetchone(): - conn.close() - return {"error": f"Property with ID {property_id} not found"} - - updates = [] - params = [] - - if price is not None: - updates.append("price = ?") - params.append(price) - - if description is not None: - updates.append("description = ?") - params.append(description) - - if not updates: - conn.close() - return {"error": "No updates provided"} - - query = f"UPDATE properties SET {', '.join(updates)} WHERE id = ?" - params.append(property_id) - - cursor.execute(query, params) - conn.commit() - conn.close() - - return {"message": f"Property {property_id} updated successfully"} - - -@mcp.tool() -def delete_property(property_id: int) -> Dict: - """Delete a property from the database""" - conn = sqlite3.connect(DB_PATH) - cursor = conn.cursor() - - # Check if property exists - cursor.execute("SELECT id FROM properties WHERE id = ?", (property_id,)) - if not cursor.fetchone(): - conn.close() - return {"error": f"Property with ID {property_id} not found"} - - cursor.execute("DELETE FROM properties WHERE id = ?", (property_id,)) - conn.commit() - conn.close() - - return {"message": f"Property {property_id} deleted successfully"} - - -@mcp.tool() -def get_statistics() -> Dict: - """Get statistics about the real estate database""" - conn = sqlite3.connect(DB_PATH) - cursor = conn.cursor() - - stats = {} - - cursor.execute("SELECT COUNT(*) FROM properties") - stats["total_properties"] = cursor.fetchone()[0] - - cursor.execute("SELECT AVG(price) FROM properties") - stats["average_price"] = round(cursor.fetchone()[0], 2) - - cursor.execute("SELECT MIN(price) FROM properties") - stats["min_price"] = cursor.fetchone()[0] - - cursor.execute("SELECT MAX(price) FROM properties") - stats["max_price"] = cursor.fetchone()[0] - - cursor.execute( - "SELECT property_type, COUNT(*) FROM properties GROUP BY property_type" - ) - stats["property_types"] = {row[0]: row[1] for row in cursor.fetchall()} - - cursor.execute("SELECT city, COUNT(*) FROM properties GROUP BY city") - stats["cities"] = {row[0]: row[1] for row in cursor.fetchall()} - - conn.close() - return stats - - -if __name__ == "__main__": - # Start the MCP service - mcp.run() diff --git a/samples/travel-planner-local-mcp/mcps/travel_mcp.py b/samples/travel-planner-local-mcp/mcps/travel_mcp.py deleted file mode 100644 index 9990f6b7..00000000 --- a/samples/travel-planner-local-mcp/mcps/travel_mcp.py +++ /dev/null @@ -1,356 +0,0 @@ -# demo.py -import json -from datetime import datetime - -from mcp.server.fastmcp import FastMCP - -mcp = FastMCP("travel-planner-local-mcp") - - -@mcp.tool() -def get_weather(location: str): - """Get the current weather for a specific location. - - Args: - location: City name or common abbreviation - - Returns: - Detailed weather information for the requested location - """ - weather_data = { - "san francisco": { - "temp": "60°F", - "condition": "Foggy", - "humidity": "75%", - "wind": "15 mph", - }, - "sf": { - "temp": "60°F", - "condition": "Foggy", - "humidity": "75%", - "wind": "15 mph", - }, - "new york": { - "temp": "72°F", - "condition": "Partly Cloudy", - "humidity": "68%", - "wind": "8 mph", - }, - "nyc": { - "temp": "72°F", - "condition": "Partly Cloudy", - "humidity": "68%", - "wind": "8 mph", - }, - "miami": { - "temp": "88°F", - "condition": "Sunny", - "humidity": "80%", - "wind": "10 mph", - }, - "chicago": { - "temp": "65°F", - "condition": "Windy", - "humidity": "60%", - "wind": "25 mph", - }, - "las vegas": { - "temp": "95°F", - "condition": "Clear", - "humidity": "20%", - "wind": "5 mph", - }, - "seattle": { - "temp": "55°F", - "condition": "Rainy", - "humidity": "85%", - "wind": "12 mph", - }, - # Adding ski resort destinations - "aspen": { - "temp": "28°F", - "condition": "Snowy", - "humidity": "65%", - "wind": "12 mph", - "snow_depth": "24 inches", - }, - "vail": { - "temp": "25°F", - "condition": "Light Snow", - "humidity": "70%", - "wind": "8 mph", - "snow_depth": "30 inches", - }, - "park city": { - "temp": "30°F", - "condition": "Snowy", - "humidity": "60%", - "wind": "15 mph", - "snow_depth": "22 inches", - }, - "lake tahoe": { - "temp": "32°F", - "condition": "Heavy Snow", - "humidity": "75%", - "wind": "10 mph", - "snow_depth": "28 inches", - }, - "whistler": { - "temp": "22°F", - "condition": "Powder Snow", - "humidity": "80%", - "wind": "6 mph", - "snow_depth": "35 inches", - }, - "zermatt": { - "temp": "20°F", - "condition": "Fresh Powder", - "humidity": "65%", - "wind": "9 mph", - "snow_depth": "40 inches", - }, - } - - location = location.lower() - if location in weather_data: - data = weather_data[location] - if "snow_depth" in data: - return f"Current weather in {location.title()}: {data['temp']}, {data['condition']} with {data['humidity']} humidity and {data['wind']} winds. Current snow depth: {data['snow_depth']}." - else: - return f"Current weather in {location.title()}: {data['temp']}, {data['condition']} with {data['humidity']} humidity and {data['wind']} winds." - else: - return f"Weather data for {location} not available. Forecasting sunny and 75°F based on seasonal averages." - - -@mcp.tool() -def get_coolest_cities(): - """Get a list of cool cities to visit with descriptions of what makes them interesting. - - Returns: - JSON formatted data about top travel destinations - """ - cool_cities = [ - { - "name": "New York City", - "highlights": "Vibrant culture, Broadway shows, Central Park, world-class dining", - "best_season": "Fall", - }, - { - "name": "San Francisco", - "highlights": "Golden Gate Bridge, tech hub, diverse food scene, unique neighborhoods", - "best_season": "Summer", - }, - { - "name": "Tokyo", - "highlights": "Blend of traditional and ultramodern, amazing food, efficient transit", - "best_season": "Spring", - }, - { - "name": "Paris", - "highlights": "Art, architecture, romance, cuisine, fashion", - "best_season": "Spring/Fall", - }, - { - "name": "Barcelona", - "highlights": "Stunning architecture, beaches, tapas, vibrant nightlife", - "best_season": "Spring/Fall", - }, - ] - return json.dumps(cool_cities, indent=2) - - -@mcp.tool() -def get_attractions(city: str): - """Get top tourist attractions for a specific city. - - Args: - city: Name of the city or ski resort area - - Returns: - List of top attractions with brief descriptions - """ - attractions_by_city = { - "san francisco": [ - "Golden Gate Bridge - Iconic suspension bridge with fantastic views", - "Alcatraz Island - Historic federal prison with audio tours", - "Fisherman's Wharf - Popular waterfront with restaurants and sea lions", - "Chinatown - Oldest and largest Chinatown outside of Asia", - "Golden Gate Park - Large urban park with museums and gardens", - ], - "new york": [ - "Empire State Building - Iconic 102-story skyscraper with observation decks", - "Statue of Liberty - Famous copper statue on Liberty Island", - "Central Park - Massive urban park with various attractions", - "Times Square - Vibrant intersection known for bright advertisements", - "Metropolitan Museum of Art - One of the world's largest art museums", - ], - "london": [ - "Tower of London - Historic castle and former prison on the Thames", - "British Museum - World-class collection of art and antiquities", - "Buckingham Palace - Home of the British monarchy", - "London Eye - Giant observation wheel with panoramic views", - "Westminster Abbey - Gothic church and site of royal coronations", - ], - # Adding ski resort attractions - "aspen": [ - "Aspen Mountain (Ajax) - Challenging terrain with breathtaking views of Aspen", - "Snowmass - Family-friendly mountain with diverse terrain for all skill levels", - "Aspen Art Museum - Contemporary art in a striking building designed by Shigeru Ban", - "Wheeler Opera House - Historic venue offering performances and cultural events", - "Maroon Bells - Iconic twin peaks offering spectacular photography opportunities", - ], - "vail": [ - "Back Bowls - Seven legendary powder bowls spanning over 3,000 acres", - "Vail Village - Charming European-inspired pedestrian village with shops and dining", - "Blue Sky Basin - Remote skiing experience with natural terrain features", - "Betty Ford Alpine Gardens - Highest botanical garden in North America", - "Colorado Ski & Snowboard Museum - Historical exhibits on ski culture and Winter Olympics", - ], - "park city": [ - "Park City Mountain Resort - Largest ski resort in the United States", - "Main Street - Historic district with Victorian buildings, galleries and restaurants", - "Utah Olympic Park - 2002 Winter Olympics venue with museum and activities", - "Deer Valley Resort - Luxury ski-only resort with impeccable grooming", - "High West Distillery - Award-winning distillery and restaurant in a historic building", - ], - "lake tahoe": [ - "Heavenly Mountain Resort - Panoramic lake views with skiing across California and Nevada", - "Emerald Bay State Park - Stunning natural bay with Fannette Island and Vikingsholm", - "Squaw Valley (Palisades Tahoe) - Olympic venue with challenging terrain", - "Northstar California - Family-friendly resort with excellent tree skiing", - "Lake Tahoe Gondola - Scenic ride offering spectacular views of the lake and mountains", - ], - "whistler": [ - "Peak 2 Peak Gondola - Record-breaking gondola connecting Whistler and Blackcomb mountains", - "Whistler Village - Vibrant pedestrian village with shops, restaurants and nightlife", - "Whistler Olympic Plaza - 2010 Winter Olympics venue with activities and events", - "Audain Art Museum - Contemporary art museum featuring Indigenous works", - "Vallea Lumina - Enchanting night walk through an illuminated forest", - ], - "zermatt": [ - "Matterhorn Glacier Paradise - Highest cable car station in Europe with glacier viewing", - "Gornergrat Railway - Scenic mountain railway offering spectacular Matterhorn views", - "Zermatt Village - Car-free alpine village with traditional chalets and luxury shops", - "Matterhorn Museum - Underground museum showcasing Zermatt's mountaineering history", - "Schwarzsee - Beautiful mountain lake reflecting the Matterhorn, accessible by gondola", - ], - } - - city = city.lower() - if city in attractions_by_city: - return attractions_by_city[city] - else: - return f"No attraction data available for {city}. Please check another popular destination like San Francisco, New York, London, or ski resorts like Aspen, Vail, Whistler, or Zermatt." - - -@mcp.tool() -def convert_currency(amount: float, from_currency: str, to_currency: str): - """Convert an amount from one currency to another. - - Args: - amount: The amount to convert - from_currency: Source currency code (USD, EUR, GBP, JPY) - to_currency: Target currency code (USD, EUR, GBP, JPY) - - Returns: - Converted amount and current exchange rate - """ - rates = { - "usd": {"eur": 0.93, "gbp": 0.79, "jpy": 149.8, "usd": 1.0}, - "eur": {"usd": 1.08, "gbp": 0.85, "jpy": 161.5, "eur": 1.0}, - "gbp": {"usd": 1.27, "eur": 1.18, "jpy": 190.0, "gbp": 1.0}, - "jpy": {"usd": 0.0067, "eur": 0.0062, "gbp": 0.0053, "jpy": 1.0}, - } - - from_currency = from_currency.lower() - to_currency = to_currency.lower() - - if from_currency in rates and to_currency in rates[from_currency]: - rate = rates[from_currency][to_currency] - converted = amount * rate - return f"{amount} {from_currency.upper()} = {converted:.2f} {to_currency.upper()} (Rate: 1 {from_currency.upper()} = {rate} {to_currency.upper()}, as of {datetime.now().strftime('%Y-%m-%d')})" - else: - return f"Conversion from {from_currency.upper()} to {to_currency.upper()} is not supported." - - -@mcp.tool() -def get_ski_resorts(difficulty: str = "all"): - """Get information about ski resorts based on difficulty level. - - Args: - difficulty: Preferred difficulty level (beginner, intermediate, advanced, or all) - - Returns: - JSON formatted data about top ski resorts - """ - ski_resorts = [ - { - "name": "Aspen Snowmass", - "location": "Colorado, USA", - "elevation": "12,510 ft", - "trails": 362, - "best_for": "intermediate to advanced", - "season": "November to April", - "highlights": "Four mountains with varied terrain, luxury amenities, vibrant après-ski scene", - }, - { - "name": "Whistler Blackcomb", - "location": "British Columbia, Canada", - "elevation": "7,494 ft", - "trails": 200, - "best_for": "all levels", - "season": "November to May", - "highlights": "Largest ski resort in North America, incredible backcountry, Olympic venue", - }, - { - "name": "Vail", - "location": "Colorado, USA", - "elevation": "11,570 ft", - "trails": 195, - "best_for": "intermediate to advanced", - "season": "November to April", - "highlights": "Back Bowls, European-style village, extensive groomed terrain", - }, - { - "name": "Park City Mountain", - "location": "Utah, USA", - "elevation": "10,026 ft", - "trails": 348, - "best_for": "all levels", - "season": "November to April", - "highlights": "Largest ski resort in USA, excellent snow quality, charming historic town", - }, - { - "name": "Heavenly", - "location": "Lake Tahoe, California/Nevada, USA", - "elevation": "10,067 ft", - "trails": 97, - "best_for": "intermediate", - "season": "November to April", - "highlights": "Stunning lake views, crosses state lines, vibrant casino nightlife", - }, - { - "name": "Zermatt", - "location": "Switzerland", - "elevation": "12,740 ft", - "trails": 200, - "best_for": "all levels", - "season": "November to April", - "highlights": "Matterhorn views, glacier skiing, car-free village, international cuisine", - }, - ] - - if difficulty.lower() == "all": - return json.dumps(ski_resorts, indent=2) - else: - filtered_resorts = [ - resort for resort in ski_resorts if difficulty.lower() in resort["best_for"] - ] - if filtered_resorts: - return json.dumps(filtered_resorts, indent=2) - else: - return f"No resorts found for {difficulty} difficulty. Try 'beginner', 'intermediate', 'advanced', or 'all'." - - -if __name__ == "__main__": - mcp.run(transport="stdio") diff --git a/samples/travel-planner-local-mcp/pyproject.toml b/samples/travel-planner-local-mcp/pyproject.toml deleted file mode 100644 index 0e2dabe8..00000000 --- a/samples/travel-planner-local-mcp/pyproject.toml +++ /dev/null @@ -1,20 +0,0 @@ -[project] -name = "travel-planner-agent" -version = "0.0.17" -description = "Travel planner agent" -authors = [{ name = "Ion Mincu", email = "ion.mincu@uipath.com" }] -dependencies = [ - "langgraph>=0.2.70", - "langchain-core>=0.3.34", - "langchain-openai>=0.3.9", - "langgraph-checkpoint-sqlite>=2.0.3", - "python-dotenv>=1.0.1", - "uipath-langchain==0.0.88", - "pydantic>=2.10.6", - "aiohttp>=3.11.12", - "typing-extensions>=4.12.2", - "langchain-mcp-adapters>=0.0.5", - "ipython>=8.32.0", - "mcp>=1.4.1", -] -requires-python = ">=3.10" diff --git a/samples/travel-planner-local-mcp/uipath.json b/samples/travel-planner-local-mcp/uipath.json deleted file mode 100644 index 31f10eb2..00000000 --- a/samples/travel-planner-local-mcp/uipath.json +++ /dev/null @@ -1,37 +0,0 @@ -{ - "entryPoints": [ - { - "filePath": "agent", - "uniqueId": "786d5af1-c232-4e94-b114-9ecdcb0aeb0a", - "type": "agent", - "input": { - "type": "object", - "properties": { - "message": { - "title": "Message", - "type": "string" - } - }, - "required": [ - "message" - ] - }, - "output": { - "type": "object", - "properties": { - "summary": { - "title": "Summary", - "type": "string" - } - }, - "required": [ - "summary" - ] - } - } - ], - "bindings": { - "version": "2.0", - "resources": [] - } -} \ No newline at end of file diff --git a/samples/travel-planner-local-mcp/uv.lock b/samples/travel-planner-local-mcp/uv.lock deleted file mode 100644 index 10525367..00000000 --- a/samples/travel-planner-local-mcp/uv.lock +++ /dev/null @@ -1,2256 +0,0 @@ -version = 1 -revision = 1 -requires-python = ">=3.10" -resolution-markers = [ - "python_full_version >= '3.12.4'", - "python_full_version >= '3.11' and python_full_version < '3.12.4'", - "python_full_version < '3.11'", -] - -[[package]] -name = "aiohappyeyeballs" -version = "2.6.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760 } -wheels = [ - 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