raysurfer 0.2.2

Python SDK for RaySurfer - code block caching and retrieval for AI agents with Claude Agent SDK integration

RaySurfer Python SDK

Drop-in replacement for Claude Agent SDK with automatic code caching. Same API, 20-30x faster.

Install

pip install raysurfer

Quick Start

Swap ClaudeSDKClient for RaysurferClient - everything else stays the same:

# from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions
from raysurfer import RaysurferClient, RaysurferAgentOptions

options = RaysurferAgentOptions(
    raysurfer_api_key="your-api-key",
    allowed_tools=["Read", "Write", "Bash"],
    model="claude-sonnet-4-20250514",
)

# async with ClaudeSDKClient(options) as client:
async with RaysurferClient(options) as client:
    await client.query("Generate quarterly sales report")
    async for msg in client.receive_response():
        print(msg)

That's it. Your agent now automatically:

• Pre-fetches relevant cached code before each task
• Injects proven code snippets into the system prompt
• Stores successful outputs for future reuse

How It Works

1. On query(): Retrieves cached code blocks matching your task
2. Downloads to sandbox: Files ready for the agent to execute
3. Injects into prompt: Agent sees proven code snippets
4. After success: New code is cached for next time

Measured Results:

• Without RaySurfer: 34.2s, 11 iterations, 2 tool calls
• With RaySurfer: 1.4s, 1 iteration, 0 tool calls
• Speedup: 24x faster

RaysurferAgentOptions

All ClaudeAgentOptions fields are supported, plus:

RaysurferAgentOptions(
    # Raysurfer-specific
    raysurfer_api_key="your-api-key",
    prefetch_count=5,           # Code files to pre-fetch
    min_verdict_score=0.3,      # Quality threshold

    # Standard Claude Agent SDK options
    allowed_tools=["Read", "Write", "Bash"],
    model="claude-sonnet-4-20250514",
    system_prompt="You are helpful.",
    permission_mode="acceptEdits",
    # ... all other ClaudeAgentOptions
)

Low-Level API

For direct code block storage and retrieval:

from raysurfer import RaySurfer

rs = RaySurfer(api_key="your-api-key")

# Store a code block
rs.store_code_block(
    name="fetch_weather",
    source="def fetch_weather(city): ...",
    entrypoint="fetch_weather",
    language="python",
)

# Retrieve by task
results = rs.retrieve("get weather data")
for match in results.code_blocks:
    print(f"{match.code_block.name}: {match.score}")

Verdict System

RaySurfer learns which code actually works through thumbs up/down verdicts:

• A technical error can be thumbs up (correct validation)
• A successful run can be thumbs down (useless output)

The system learns usefulness, not just whether code runs.

Examples

See examples/ for complete demos.