6.9 KiB
6.9 KiB
Phase 2: Multi-Tool Agent Implementation
Objective: Implement agent with multiple validated tools
Python Implementation
from anthropic import Anthropic
from typing import Dict, Any, List
client = Anthropic()
# Define tools
TOOLS = [
{
"name": "search_flights",
"description": "Search for available flights",
"strict": True,
"input_schema": {
"type": "object",
"properties": {
"origin": {"type": "string", "description": "Departure city"},
"destination": {"type": "string", "description": "Arrival city"},
"departure_date": {"type": "string", "format": "date"},
"travelers": {"type": "integer", "enum": [1, 2, 3, 4, 5, 6]}
},
"required": ["origin", "destination", "departure_date", "travelers"],
"additionalProperties": False
}
},
{
"name": "book_flight",
"description": "Book a selected flight",
"strict": True,
"input_schema": {
"type": "object",
"properties": {
"flight_id": {"type": "string", "description": "Flight identifier"},
"passengers": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": {"type": "string"},
"passport": {"type": "string"}
},
"required": ["name", "passport"],
"additionalProperties": False
}
}
},
"required": ["flight_id", "passengers"],
"additionalProperties": False
}
},
{
"name": "search_hotels",
"description": "Search for hotels in a city",
"strict": True,
"input_schema": {
"type": "object",
"properties": {
"city": {"type": "string", "description": "City name"},
"check_in": {"type": "string", "format": "date"},
"check_out": {"type": "string", "format": "date"},
"guests": {"type": "integer", "enum": [1, 2, 3, 4]}
},
"required": ["city", "check_in", "check_out", "guests"],
"additionalProperties": False
}
}
]
# Tool execution functions
def search_flights(origin: str, destination: str, departure_date: str, travelers: int) -> Dict:
"""Execute flight search - calls actual API."""
# Implementation here
return {"flights": [...]}
def book_flight(flight_id: str, passengers: List[Dict]) -> Dict:
"""Book the flight - calls actual API."""
# Implementation here
return {"confirmation": "ABC123", "status": "confirmed"}
def search_hotels(city: str, check_in: str, check_out: str, guests: int) -> Dict:
"""Search hotels - calls actual API."""
# Implementation here
return {"hotels": [...]}
# Tool registry
TOOL_FUNCTIONS = {
"search_flights": search_flights,
"book_flight": book_flight,
"search_hotels": search_hotels,
}
# Agent loop
def run_agent(user_request: str, max_turns: int = 10):
"""Run agent with tool validation."""
messages = [{"role": "user", "content": user_request}]
for turn in range(max_turns):
response = client.beta.messages.create(
model="claude-sonnet-4-5",
max_tokens=2048,
betas=["structured-outputs-2025-11-13"],
messages=messages,
tools=TOOLS,
)
# Process response
if response.stop_reason == "end_turn":
# Agent finished
return extract_final_answer(response)
if response.stop_reason == "tool_use":
# Execute tools
tool_results = []
for block in response.content:
if block.type == "tool_use":
# Tool input is GUARANTEED to match schema
tool_name = block.name
tool_input = block.input # Already validated!
# Execute tool
tool_function = TOOL_FUNCTIONS[tool_name]
result = tool_function(**tool_input) # Type-safe!
tool_results.append({
"type": "tool_result",
"tool_use_id": block.id,
"content": str(result)
})
# Add assistant response and tool results to conversation
messages.append({"role": "assistant", "content": response.content})
messages.append({"role": "user", "content": tool_results})
else:
raise Exception(f"Unexpected stop reason: {response.stop_reason}")
raise Exception("Max turns reached")
# Usage
result = run_agent("Book a flight from SF to Paris for 2 people, departing May 15")
print(result)
TypeScript Implementation
import Anthropic from '@anthropic-ai/sdk';
const client = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });
const TOOLS: Anthropic.Tool[] = [
{
name: "search_flights",
description: "Search for available flights",
strict: true,
input_schema: {
type: "object",
properties: {
origin: { type: "string", description: "Departure city" },
destination: { type: "string", description: "Arrival city" },
departure_date: { type: "string", format: "date" },
travelers: { type: "integer", enum: [1, 2, 3, 4, 5, 6] }
},
required: ["origin", "destination", "departure_date", "travelers"],
additionalProperties: false
}
},
// ... other tools
];
async function runAgent(userRequest: string, maxTurns: number = 10) {
const messages: Anthropic.MessageParam[] = [
{ role: "user", content: userRequest }
];
for (let turn = 0; turn < maxTurns; turn++) {
const response = await client.beta.messages.create({
model: "claude-sonnet-4-5",
max_tokens: 2048,
betas: ["structured-outputs-2025-11-13"],
messages,
tools: TOOLS,
});
if (response.stop_reason === "end_turn") {
return extractFinalAnswer(response);
}
if (response.stop_reason === "tool_use") {
const toolResults: Anthropic.ToolResultBlockParam[] = [];
for (const block of response.content) {
if (block.type === "tool_use") {
// Input guaranteed to match schema!
const result = await executeTool(block.name, block.input);
toolResults.push({
type: "tool_result",
tool_use_id: block.id,
content: JSON.stringify(result)
});
}
}
messages.push({ role: "assistant", content: response.content });
messages.push({ role: "user", content: toolResults });
}
}
throw new Error("Max turns reached");
}
Output
Working multi-tool agent with validated tool schemas.