Sub-skill of opper — start there for discovery and setup guidance. Source: https://github.com/opper-ai/opper-skills/blob/main/opper-sdks/SKILL.md

Opper SDKs

The Python and TypeScript SDKs for Opper live in a single monorepo: github.com/opper-ai/opper-sdks. Both publish as opperai (PyPI / npm). Agents are part of the SDK — there is no separate opperai-agents package.

The upstream READMEs (python/README.md, typescript/README.md) and the numbered example files are the source of truth. This skill points at them; it does not duplicate them.

Pick your primitive

The unified opperai package exposes a few different shapes. Pick by what you're building:

One-shot structured task (input → typed output): the recommended path is a compat chat endpoint with response_format, called through the provider SDK you already know — point the OpenAI SDK's base_url at https://api.opper.ai/v3/compat and pass your Pydantic / Zod model via chat.completions.parse(...). Seeds below; full shape in the opper-api skill.
Streaming: stream: true on the same compat call — standard OpenAI SSE semantics.
Multi-turn chat or message-thread style: the compat chat endpoints are message-native — carry the messages array forward.
Tool-using agent, multi-step reasoning, multi-agent, MCP: the Agent SDK (Agent, tool, Conversation, Hooks, mcp) is recommended for any "model decides what to do next" flow. Use agent.run(...) for a single shot or agent.stream(...) for live progress.
Knowledge bases / RAG: opper.knowledge.* — create, query, add, etc.
opper.call(...) / opper.stream(...) are legacy. They ride Opper's /call surface, which is being sunset — don't start new work on them, and don't use them in examples. The opperai SDK itself is being reworked to no longer use /call; a future release drops it. Existing code migrates to compat + response_format; the field-by-field mapping (name → X-Opper-Name header, output_schema → response_format, result.data → parsed message content) is in the opper-api skill's references/migration.md.