agentic-rag-research v0.1.0 — bounded research, visible decisions

agentic-rag-research v0.1.0 — bounded research, visible decisions

These notes describe M1–M6 on the exact release commit. The tag is created only after the
SHIP.md gate and exact-SHA CI pass.

What this release is

agentic-rag-research is a bounded research loop that plans sub-questions, retrieves
evidence, critiques coverage, and either produces a cited report or stops with an explicit
reason. Its default path is deterministic, local, and credential-free.

This is portfolio series project #2. It consumes the evidence contract from
production-rag through an optional HTTP
boundary instead of copying that service's hybrid retrieval stack.

Included

• Library, FastAPI, and CLI surfaces over the same research loop.
• done, refused, and budget_exhausted terminal outcomes.
• Step budgets, no-repeat progress, named evidence gaps, resolvable citations, and a full
  plan/tool/critique/synthesis/stop trace.
• A default fake retriever over 20 packaged passages: no key, network, signup, or billed
  provider call.
• An opt-in production-rag HTTP retriever with mock-transport and contract tests. A live
  end-to-end service result is not claimed by this release draft.
• A 17-case deterministic evaluation set spanning five behavior slices. The JSON scorecard
  reports expectation pass rate, mean steps, citation presence, and terminal-status counts.
• A dark accessible UI at / with the report, resolved citations, status, retrieval steps,
  request id, expandable trace timeline, and typed HTML failures.
• A deterministic search_notes tool the critic may request to inspect notes already
  gathered. It cannot retrieve, generate, write, or contact a provider.

Evidence boundary

The fake evaluation measures control-flow conformance against a committed fixture. It does
not measure retrieval quality, answer quality, faithfulness, latency, production readiness,
or agent uplift over a one-pass answer baseline. The current runner has no such baseline.

Free verification

python -m pip install -e ".[dev]"
python -m pytest -q
python -m agentic_rag.evals.run --pretty
python -m agentic_rag.research \
  --question "Why use reciprocal rank fusion?" --retriever fake
python -m uvicorn agentic_rag.main:app --port 8010

Open http://127.0.0.1:8010/ for the UI. Expected evaluation evidence: 17 cases evaluated
with provider fake, billed cost $0, and every declared expectation passing.

Known limits

• No hosted demo, hosted-model quality result, authentication, rate limiting, streaming, or
  multi-tenancy.
• No arbitrary web, shell, filesystem, write, or sub-agent tools.
• HTTP retrieval requires a separately running, compatible production-rag service.
• Multi-agent coordination belongs to series project #3, not this release.