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Python SDK for Semantys AI - Semantic LLM Cache

Project description

Semantys Python SDK

Drop-in replacement for the OpenAI Python client with automatic semantic caching.

Installation

pip install semantys

For automatic OpenAI fallback when Semantys is unreachable:

pip install semantys[openai]

Quick Start

from semantys import SemantysCache

cache = SemantysCache(api_key="sc-myorg-xxxxxxxx")

# OpenAI-compatible interface
response = cache.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "What is machine learning?"}],
)
print(response.choices[0].message.content)
print(f"Cache: {response.meta.hit} | Similarity: {response.meta.similarity}")

Zero-Code Integration (Proxy Mode)

Point your existing OpenAI client at Semantys:

import openai

client = openai.OpenAI(
    base_url="https://api.semantys.ai/v1",
    api_key="sc-myorg-xxxxxxxx",
)

# Existing code works unchanged - caching is transparent
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "What is ML?"}],
)

Self-Hosted

cache = SemantysCache(
    api_key="sc-myorg-xxxxxxxx",
    base_url="http://localhost:8000",
)

Features

  • OpenAI-compatible: Drop-in replacement, same interface
  • Automatic retry: Exponential backoff on 429/5xx errors
  • Fallback: If Semantys is unreachable, falls back to direct OpenAI (with [openai] extra)
  • Cache metadata: Every response includes meta.hit, meta.similarity, meta.latency_ms
  • Context manager: Use with with for automatic cleanup

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