OpenClaw Developer Guide

# 1. Fork and clone
git clone https://github.com/YOUR_USERNAME/openclaw
cd openclaw

# 2. Create virtual environment
python -m venv .venv && source .venv/bin/activate

# 3. Install in dev mode
pip install -e ".[dev]"

# 4. Install pre-commit hooks
pre-commit install

# 5. Run tests to verify setup
pytest tests/ -v --tb=short

import openclaw

agent = openclaw.Agent(
    provider="openai",
    model="gpt-4o-mini",
    tools=["web_search", "read_file"]
)

result = agent.run("Summarize the latest news on AI regulation")
print(result.output)

from openclaw.tools import tool
from typing import Optional

@tool
def fetch_stock_price(ticker: str, currency: str = "USD") -> dict:
    """Fetch the latest stock price for a given ticker symbol.

    Args:
        ticker: Stock ticker symbol, e.g. 'AAPL' or 'TSLA'.
        currency: Currency code for the price. Defaults to 'USD'.

    Returns:
        dict with keys: ticker, price, currency, timestamp.
    """
    # implementation here
    import yfinance as yf
    data = yf.Ticker(ticker).fast_info
    return {
        "ticker": ticker,
        "price": data.last_price,
        "currency": currency,
        "timestamp": data.last_trade_date.isoformat(),
    }

from your_tools import fetch_stock_price

agent = openclaw.Agent(
    provider="openai",
    model="gpt-4o",
    tools=[fetch_stock_price, "web_search"]  # mix custom and built-in
)
print(agent.run("What is today's Apple stock price?").output)

from openclaw.providers import BaseLLM, LLMResponse
from typing import Iterator

class MyPrivateLLM(BaseLLM):
    """Provider for an internal fine-tuned model behind a private API."""

    def complete(self, prompt: str, **kwargs) -> LLMResponse:
        response = self._call_internal_api(prompt, stream=False)
        return LLMResponse(
            content=response["text"],
            tokens_used=response["usage"]["total_tokens"],
            model=self.model_name,
        )

    def stream(self, prompt: str, **kwargs) -> Iterator[str]:
        for chunk in self._call_internal_api(prompt, stream=True):
            yield chunk["delta"]

    def _call_internal_api(self, prompt: str, stream: bool) -> dict:
        import requests
        return requests.post(
            self.config.endpoint,
            json={"prompt": prompt, "stream": stream},
            headers={"X-API-Key": self.config.api_key},
            timeout=60,
        ).json()

from openclaw.events import on_event

@on_event("llm.response")
def track_token_cost(event):
    cost = event.total_tokens * 0.000002  # $0.002 / 1K tokens
    print(f"Task {event.task_id}: ${cost:.4f} ({event.total_tokens} tokens)")