Python SDK for Venice AI (github.com)

Venice AI released a full-featured Python SDK (pip install venice-sdk) that exposes the entire Venice API surface — chat completions (with real-time SSE streaming), image generation and editing (DALL·E models, upscaling, styles, data-URL support), text-to-speech (multiple voices, MP3/WAV/AAC), embeddings and semantic search, character/persona management, function/tool calling, model discovery/traits, web search, Web3 API key generation and comprehensive admin/billing and API-key management. The client is easy to instantiate from an env var or explicit key, offers rich runtime controls (temperature ranges, seeding, penalties, streaming options, pagination) and includes a CLI for auth/status. It also advertises drop-in OpenAI SDK compatibility, full type hints, and concrete examples for embeddings similarity, semantic search, batch audio processing and model-compatibility mapping. For AI/ML engineers and product teams this matters because the SDK bundles production-grade features — rate-limit handling, retries, descriptive error types, SSE streaming, function calling, usage tracking and 350+ tests (90%+ pass) — that accelerate integration, reproducibility and monitoring of LLM and multimodal pipelines. The code is AGPLv3-licensed (docs/examples under CC-BY-SA), so teams should weigh copyleft implications when embedding the SDK in networked services. Overall, it’s a pragmatic, enterprise-capable client for building conversational, multimodal and embedding-driven applications with Venice models.