קבלת פלט מובנה מסוכנים

Here's a classic chocolate chip cookie recipe!

**Chocolate Chip Cookies**
Prep time: 15 minutes | Cook time: 10 minutes

Ingredients:
- 2 1/4 cups all-purpose flour
- 1 cup butter, softened
...

{
  "name": "Chocolate Chip Cookies",
  "prep_time_minutes": 15,
  "cook_time_minutes": 10,
  "ingredients": [
    { "item": "all-purpose flour", "amount": 2.25, "unit": "cups" },
    { "item": "butter, softened", "amount": 1, "unit": "cup" }
    // ...
  ],
  "steps": ["Preheat oven to 375°F", "Cream butter and sugar" /* ... */]
}

import { query } from "@anthropic-ai/claude-agent-sdk";

// Define the shape of data you want back
const schema = {
  type: "object",
  properties: {
    company_name: { type: "string" },
    founded_year: { type: "number" },
    headquarters: { type: "string" }
  },
  required: ["company_name"]
};

try {
  for await (const message of query({
    prompt: "Research Anthropic and provide key company information",
    options: {
      outputFormat: {
        type: "json_schema",
        schema: schema
      }
    }
  })) {
    // The result message contains structured_output with validated data
    if (message.type === "result" && message.subtype === "success" && message.structured_output) {
      console.log(message.structured_output);
      // { company_name: "Anthropic", founded_year: 2021, headquarters: "San Francisco, CA" }
    }
  }
} catch (error) {
  // A single-shot query() throws after yielding an error result, such as
  // error_max_structured_output_retries; see the Error handling section.
  console.error(`Session ended with an error: ${error}`);
}

import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage

# Define the shape of data you want back
schema = {
    "type": "object",
    "properties": {
        "company_name": {"type": "string"},
        "founded_year": {"type": "number"},
        "headquarters": {"type": "string"},
    },
    "required": ["company_name"],
}


async def main():
    try:
        async for message in query(
            prompt="Research Anthropic and provide key company information",
            options=ClaudeAgentOptions(
                output_format={"type": "json_schema", "schema": schema}
            ),
        ):
            
# The result message contains structured_output with validated data
            if isinstance(message, ResultMessage) and message.structured_output:
                print(message.structured_output)
                
# {'company_name': 'Anthropic', 'founded_year': 2021, 'headquarters': 'San Francisco, CA'}
    except Exception as error:
        
# A single-shot query() raises after yielding an error result, such as
        
# error_max_structured_output_retries; see the Error handling section.
        print(f"Session ended with an error: {error}")


asyncio.run(main())

import { z } from "zod";
import { query } from "@anthropic-ai/claude-agent-sdk";

// Define schema with Zod
const FeaturePlan = z.object({
  feature_name: z.string(),
  summary: z.string(),
  steps: z.array(
    z.object({
      step_number: z.number(),
      description: z.string(),
      estimated_complexity: z.enum(["low", "medium", "high"])
    })
  ),
  risks: z.array(z.string())
});

type FeaturePlan = z.infer<typeof FeaturePlan>;

// Convert to JSON Schema using the draft-07 target the SDK expects
const schema = z.toJSONSchema(FeaturePlan, { target: "draft-7" });

// Use in query
try {
  for await (const message of query({
    prompt:
      "Plan how to add dark mode support to a React app. Break it into implementation steps.",
    options: {
      outputFormat: {
        type: "json_schema",
        schema: schema
      }
    }
  })) {
    if (message.type === "result" && message.subtype === "success" && message.structured_output) {
      // Validate and get fully typed result
      const parsed = FeaturePlan.safeParse(message.structured_output);
      if (parsed.success) {
        const plan: FeaturePlan = parsed.data;
        console.log(`Feature: ${plan.feature_name}`);
        console.log(`Summary: ${plan.summary}`);
        plan.steps.forEach((step) => {
          console.log(`${step.step_number}. [${step.estimated_complexity}] ${step.description}`);
        });
      }
    }
  }
} catch (error) {
  // A single-shot query() throws after yielding an error result, such as
  // error_max_structured_output_retries; see the Error handling section.
  console.error(`Session ended with an error: ${error}`);
}

import asyncio
from pydantic import BaseModel
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage


class Step(BaseModel):
    step_number: int
    description: str
    estimated_complexity: str  
# 'low', 'medium', 'high'


class FeaturePlan(BaseModel):
    feature_name: str
    summary: str
    steps: list[Step]
    risks: list[str]


async def main():
    try:
        async for message in query(
            prompt="Plan how to add dark mode support to a React app. Break it into implementation steps.",
            options=ClaudeAgentOptions(
                output_format={
                    "type": "json_schema",
                    "schema": FeaturePlan.model_json_schema(),
                }
            ),
        ):
            if isinstance(message, ResultMessage) and message.structured_output:
                
# Validate and get fully typed result
                plan = FeaturePlan.model_validate(message.structured_output)
                print(f"Feature: {plan.feature_name}")
                print(f"Summary: {plan.summary}")
                for step in plan.steps:
                    print(
                        f"{step.step_number}. [{step.estimated_complexity}] {step.description}"
                    )
    except Exception as error:
        
# A single-shot query() raises after yielding an error result, such as
        
# error_max_structured_output_retries; see the Error handling section.
        print(f"Session ended with an error: {error}")


asyncio.run(main())

import { query } from "@anthropic-ai/claude-agent-sdk";

// Define structure for TODO extraction
const todoSchema = {
  type: "object",
  properties: {
    todos: {
      type: "array",
      items: {
        type: "object",
        properties: {
          text: { type: "string" },
          file: { type: "string" },
          line: { type: "number" },
          author: { type: "string" },
          date: { type: "string" }
        },
        required: ["text", "file", "line"]
      }
    },
    total_count: { type: "number" }
  },
  required: ["todos", "total_count"]
};

// Agent uses Grep to find TODOs, Bash to get git blame info
try {
  for await (const message of query({
    prompt: "Find all TODO comments in this codebase and identify who added them",
    options: {
      outputFormat: {
        type: "json_schema",
        schema: todoSchema
      }
    }
  })) {
    if (message.type === "result" && message.subtype === "success" && message.structured_output) {
      const data = message.structured_output as { total_count: number; todos: Array<{ file: string; line: number; text: string; author?: string; date?: string }> };
      console.log(`Found ${data.total_count} TODOs`);
      data.todos.forEach((todo) => {
        console.log(`${todo.file}:${todo.line} - ${todo.text}`);
        if (todo.author) {
          console.log(`  Added by ${todo.author} on ${todo.date}`);
        }
      });
    }
  }
} catch (error) {
  // A single-shot query() throws after yielding an error result, such as
  // error_max_structured_output_retries; see the Error handling section.
  console.error(`Session ended with an error: ${error}`);
}

import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage

# Define structure for TODO extraction
todo_schema = {
    "type": "object",
    "properties": {
        "todos": {
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "text": {"type": "string"},
                    "file": {"type": "string"},
                    "line": {"type": "number"},
                    "author": {"type": "string"},
                    "date": {"type": "string"},
                },
                "required": ["text", "file", "line"],
            },
        },
        "total_count": {"type": "number"},
    },
    "required": ["todos", "total_count"],
}


async def main():
    
# Agent uses Grep to find TODOs, Bash to get git blame info
    try:
        async for message in query(
            prompt="Find all TODO comments in this codebase and identify who added them",
            options=ClaudeAgentOptions(
                output_format={"type": "json_schema", "schema": todo_schema}
            ),
        ):
            if isinstance(message, ResultMessage) and message.structured_output:
                data = message.structured_output
                print(f"Found {data['total_count']} TODOs")
                for todo in data["todos"]:
                    print(f"{todo['file']}:{todo['line']} - {todo['text']}")
                    if "author" in todo:
                        print(f"  Added by {todo['author']} on {todo['date']}")
    except Exception as error:
        
# A single-shot query() raises after yielding an error result, such as
        
# error_max_structured_output_retries; see the Error handling section.
        print(f"Session ended with an error: {error}")


asyncio.run(main())

import { query } from "@anthropic-ai/claude-agent-sdk";

const contactSchema = {
  type: "object",
  properties: {
    name: { type: "string" },
    email: { type: "string" }
  },
  required: ["name"]
};

try {
  for await (const msg of query({
    prompt: "Extract contact info from the document",
    options: {
      outputFormat: {
        type: "json_schema",
        schema: contactSchema
      }
    }
  })) {
    if (msg.type === "result") {
      if (msg.subtype === "success" && msg.structured_output) {
        // Use the validated output
        console.log(msg.structured_output);
      } else if (msg.subtype === "error_max_structured_output_retries") {
        console.error("Could not produce valid output");
      } else {
        console.error("Run ended without a structured output");
      }
    }
  }
} catch (error) {
  // A single-shot query() throws after yielding an error result. If the
  // failure was an error result, the error subtype branches above have
  // already run; connection or process failures yield no result message.
  console.log(`Session ended with an error: ${error}`);
}

import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage

contact_schema = {
    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "email": {"type": "string"},
    },
    "required": ["name"],
}


async def main():
    try:
        async for message in query(
            prompt="Extract contact info from the document",
            options=ClaudeAgentOptions(
                output_format={"type": "json_schema", "schema": contact_schema}
            ),
        ):
            if isinstance(message, ResultMessage):
                if message.subtype == "success" and message.structured_output:
                    
# Use the validated output
                    print(message.structured_output)
                elif message.subtype == "error_max_structured_output_retries":
                    print("Could not produce valid output")
                else:
                    print("Run ended without a structured output")
      except Exception as error:
          
# A single-shot query() raises after yielding an error result. If the
          
# failure was an error result, the error subtype branches above have
          
# already run; connection or process failures yield no result message.
          print(f"Session ended with an error: {error}")


asyncio.run(main())