altair823
2c058ab175
Spec PR #59 의 §3.8 multi-turn behaviour 구현. RAG facade 가 prior turns 받아 prompt 에 prepend, retrieval query expansion 적용, Answer 에 conversation_id / turn_index 채움. 신규 (kebab-core): - Answer 에 conversation_id (Option<String>) / turn_index (Option<u32>) field 추가. serde skip_serializing_if 로 single-shot 의 wire output 변경 0 (기존 외부 wrapper 영향 없음). - Turn struct (question + answer + citations + created_at). - RefusalReason::LlmStreamAborted variant. 신규 (kebab-rag): - AskOpts 에 history (Vec<Turn>) / conversation_id / turn_index 3 field. - AskOpts::single_shot(mode) helper. - RagPipeline::ask_with_history(query, history, conversation_id, turn_index, opts) — combined opts 로 ask 호출. - expand_query_with_history: history.last() 의 answer 첫 200 자 concat 해 SearchQuery.text 확장 (spec §3.8 의 \"cheap concat\"; LLM-based standalone-question rewriting 은 P+). - serialize_history + remaining_history_budget_chars: spec 의 priority enforcement — system+question 필수, retrieved chunks 가 차지한 뒤 남은 char budget 안에서 newest 우선, oldest drop. - ask 본문: history 가 비어있지 않으면 [이전 대화] 블록을 user prompt 위에 prepend. Answer 생성 site 3 곳 (정상 / NoChunks / ScoreGate refuse) 모두 conversation_id / turn_index 채움. 신규 (kebab-store-sqlite): - refusal_reason_label 가 LlmStreamAborted → 'llm_stream_aborted'. 기존 caller 변경 (single-shot 동작 동일): - kebab-cli main.rs Cmd::Ask: AskOpts 에 history=Vec::new(), conversation_id=None, turn_index=None 명시 (CLI multi-turn 은 p9-fb-18 의 --session/--repl 가 채움). - kebab-tui src/ask.rs spawn site 동일 (multi-turn UI 는 p9-fb-16). - kebab-eval runner.rs golden eval 동일 (single-shot per query). - kebab-app tests/ask_smoke.rs / kebab-tui tests/ask.rs / kebab-rag tests/pipeline.rs / kebab-eval metrics.rs Answer literal 갱신. Test: - 9 신규 lib unit (expand_query 4 / serialize_history 3 / remaining_budget 2). - 기존 12 PASS 회귀 0. Plan 갱신: - p9-fb-15 status planned → in_progress. 머지 후 한 줄 commit 으로 completed flip. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
47 lines
1.9 KiB
Rust
47 lines
1.9 KiB
Rust
//! `kb-app::ask` smoke tests.
|
|
//!
|
|
//! The pipeline's behavior is exhaustively covered by `kb-rag` tests
|
|
//! (which inject `MockLanguageModel` + `MockRetriever`). The kb-app
|
|
//! facade is a thin component wirer: it picks the retriever per
|
|
//! `opts.mode` and constructs an `OllamaLanguageModel`. Exercising
|
|
//! that wiring requires a real Ollama on `127.0.0.1:11434`, so this
|
|
//! test is `#[ignore]` by default — run with `cargo test -p kb-app
|
|
//! --test ask_smoke -- --ignored` against a live Ollama.
|
|
|
|
mod common;
|
|
|
|
use common::TestEnv;
|
|
|
|
/// Lexical-mode ask end-to-end. Requires a real Ollama on
|
|
/// `config.models.llm.endpoint` (default `127.0.0.1:11434`) running the
|
|
/// configured model. The pipeline body is otherwise covered by kb-rag's
|
|
/// integration tests; this just verifies the facade composes the
|
|
/// components correctly.
|
|
#[test]
|
|
#[ignore = "requires real Ollama on 127.0.0.1:11434"]
|
|
fn ask_lexical_smoke() {
|
|
let env = TestEnv::lexical_only();
|
|
kebab_app::ingest_with_config(env.config.clone(), env.scope(), true).unwrap();
|
|
|
|
let opts = kebab_app::AskOpts {
|
|
k: 5,
|
|
explain: false,
|
|
mode: kebab_core::SearchMode::Lexical,
|
|
temperature: Some(0.0),
|
|
seed: Some(0),
|
|
stream_sink: None,
|
|
history: Vec::new(),
|
|
conversation_id: None,
|
|
turn_index: None,
|
|
};
|
|
// The fixture workspace contains "ownership" content; the model's
|
|
// citation behavior depends on its training, so we don't assert on
|
|
// grounded — only that the call returns a structurally-valid Answer.
|
|
let answer = kebab_app::ask_with_config(env.config.clone(), "ownership", opts)
|
|
.expect("ask returns Ok with a real Ollama backend");
|
|
// retrieval summary always populated, regardless of grounded path.
|
|
assert_eq!(answer.retrieval.mode, kebab_core::SearchMode::Lexical);
|
|
assert!(answer.retrieval.k >= 5);
|
|
assert!(answer.retrieval.trace_id.0.starts_with("ret_"));
|
|
}
|