TypeScript解释器

use zapcode_core::{ZapcodeRun, Value, ResourceLimits, VmState};

// Simple expression
let runner = ZapcodeRun::new(
    "1 + 2 * 3".to_string(), vec![], vec![],
    ResourceLimits::default(),
)?;
assert_eq!(runner.run_simple()?, Value::Int(7));

// With inputs and external functions (snapshot/resume)
let runner = ZapcodeRun::new(
    r#"const weather = await getWeather(city);
       `${city}: ${weather.condition}, ${weather.temp}°C`"#.to_string(),
    vec!["city".to_string()],
    vec!["getWeather".to_string()],
    ResourceLimits::default(),
)?;

let state = runner.start(vec![
    ("city".to_string(), Value::String("London".into())),
])?;

if let VmState::Suspended { snapshot, .. } = state {
    let weather = Value::Object(indexmap::indexmap! {
        "condition".into() => Value::String("Cloudy".into()),
        "temp".into() => Value::Int(12),
    });
    let final_state = snapshot.resume(weather)?;
    // VmState::Complete("London: Cloudy, 12°C")
}

<script type="module">
import init, { Zapcode } from './zapcode-wasm/zapcode_wasm.js';

await init();

const b = new Zapcode(`
    const items = [10, 20, 30];
    items.map(x => x * 2).reduce((a, b) => a + b, 0)
`);
const result = b.run();
console.log(result.output);  // 120
</script>

import Anthropic from "@anthropic-ai/sdk";
import { Zapcode, ZapcodeSnapshotHandle } from "@unchartedfr/zapcode";

const tools = {
  getWeather: async (city: string) => {
    const res = await fetch(`https://api.weather.com/${city}`);
    return res.json();
  },
};

const client = new Anthropic();
const response = await client.messages.create({
  model: "claude-sonnet-4-20250514",
  max_tokens: 1024,
  system: `Write TypeScript to answer the user's question.
Available functions (use await): getWeather(city: string) → { condition, temp }
Last expression = output. No markdown fences.`,
  messages: [{ role: "user", content: "What's the weather in Tokyo?" }],
});

const code = response.content[0].type === "text" ? response.content[0].text : "";

// Execute + resolve tool calls via snapshot/resume
const sandbox = new Zapcode(code, { externalFunctions: ["getWeather"] });
let state = sandbox.start();
while (!state.completed) {
  const result = await tools[state.functionName](...state.args);
  state = ZapcodeSnapshotHandle.load(state.snapshot).resume(result);
}
console.log(state.output);

import anthropic
from zapcode import Zapcode

client = anthropic.Anthropic()
response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    system="""Write TypeScript to answer the user's question.
Available functions (use await): getWeather(city: string) → { condition, temp }
Last expression = output. No markdown fences.""",
    messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
)
code = response.content[0].text

sandbox = Zapcode(code, external_functions=["getWeather"])
state = sandbox.start()
while state.get("suspended"):
    result = get_weather(*state["args"])
    state = state["snapshot"].resume(result)
print(state["output"])

const { system, tools, openaiTools, anthropicTools, handleToolCall } = zapcode({
  tools: { getWeather: { ... } },
});

// Vercel AI SDK
await generateText({ model: anthropic("claude-sonnet-4-20250514"), system, tools, messages });

// OpenAI SDK
await openai.chat.completions.create({
  messages: [{ role: "system", content: system }, ...userMessages],
  tools: openaiTools,
});

// Anthropic SDK
await anthropic.messages.create({ system, tools: anthropicTools, messages });

// Any SDK — just extract the code from the tool call and pass it to handleToolCall
const result = await handleToolCall(codeFromToolCall);

b = zapcode(tools={...})
b.anthropic_tools  # → Anthropic SDK format
b.openai_tools     # → OpenAI SDK format
b.handle_tool_call(code)  # → Universal handler

import { zapcode, createAdapter } from "@unchartedfr/zapcode-ai";

const myAdapter = createAdapter("my-sdk", (ctx) => {
  return {
    systemMessage: ctx.system,
    actions: [{
      id: ctx.toolName,
      schema: ctx.toolSchema,
      run: async (input: { code: string }) => {
        return ctx.handleToolCall(input.code);
      },
    }],
  };
});

const { custom } = zapcode({
  tools: { ... },
  adapters: [myAdapter],
});

const myConfig = custom["my-sdk"];

from zapcode_ai import zapcode, Adapter, AdapterContext

class LangChainAdapter(Adapter):
    name = "langchain"

    def adapt(self, ctx: AdapterContext):
        from langchain_core.tools import StructuredTool
        return StructuredTool.from_function(
            func=lambda code: ctx.handle_tool_call(code),
            name=ctx.tool_name,
            description=ctx.tool_description,
        )

b = zapcode(tools={...}, adapters=[LangChainAdapter()])
langchain_tool = b.custom["langchain"]

cargo test -p zapcode-core --test security   # run the security tests