Release 0.3.0: Tape-First UX Refresh

[PsiACE]

This release refines Republic around a tape-first, practical developer workflow. The API surface is smaller and more intentional, docs/examples were fully rewritten, and reliability improved in streaming and fallback behavior.

Highlights

• Tape-first flow with explicit anchors (handoff) and queryable execution history.
• Unified LLM facade for chat, tools, streaming, text decisions, and embeddings.
• Structured return pattern (value + error) across core interfaces.
• Improved event streaming, including more robust tool-call delta merging.
• Better error classification and fallback handling across provider exception shapes.
• New docs and runnable examples with a simpler, usage-first style.
• Contract-style test suite focused on user-facing behavior.

Example

import os

from republic import LLM

llm = LLM(model="openrouter:openrouter/free", api_key=os.environ["LLM_API_KEY"])

out = llm.chat("Describe Republic in one sentence.", max_tokens=48)
print(out.value if out.error is None else out.error.message)

tape = llm.tape("release-notes")
tape.handoff("draft_v1", state={"owner": "assistant"})

reply = tape.chat("Summarize the latest changes in three bullets.", max_tokens=96)
print(reply.value if reply.error is None else reply.error.message)

Upgrade Notes

• Main usage is now centered on LLM + structured outputs.
• Docs were reorganized to a Quickstart + focused Guides layout.
• Streaming/tool behavior is aligned around explicit inspectable results.
• Error/retry/fallback logic was updated for mixed provider environments.
• Core dependency surface now includes pydantic.

Thanks

Derived from lightning-ai/litai, inspired by pydantic/pydantic-ai, and adapted into Republic’s tape-first execution style.

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This discussion was created from the release Release 0.3.0: Tape-First UX Refresh.