retrieval fusion
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@@ -73,7 +73,7 @@ service by ID after the vector search.
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The core four-service architecture is complete and operational. Key capabilities:
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- **Hybrid memory retrieval** — recent episodes + semantic search combined into every prompt
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- **Retrieval fusion** — Reciprocal Rank Fusion (RRF) merges semantic (Qdrant vector search) and keyword (SQLite FTS5) episode retrieval into a single ranked result set. Weights are configurable per strategy via settings; keyword search is off by default (`keywordWeight: 0`) and can be enabled without a service restart
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- **Entity layer + Knowledge graph** — automatic extraction of named entities and relationships from conversations via qwen2.5:3b. Entities and relationships are stored in SQLite with `mention_count` tracking. A graph traversal layer expands Qdrant entity search hits into a 1-hop neighborhood subgraph, injecting structured connected knowledge into every prompt
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- **Projects** — sessions grouped with shared or isolated memory pools
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- **Auto-naming** — sessions named automatically from first exchange via inference
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@@ -202,7 +202,9 @@ Returns `503` if llama-server is unreachable.
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|---|---|---|---|
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| `recentEpisodeLimit` | integer | 1–20 | Recent episodes injected into prompt |
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| `semanticLimit` | integer | 1–20 | Max semantic search results |
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| `scoreThreshold` | float | 0–1 | Minimum similarity score |
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| `scoreThreshold` | float | 0–1 | Minimum similarity score for Qdrant results |
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| `semanticWeight` | float | 0–5 | RRF weight for Qdrant semantic results |
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| `keywordWeight` | float | 0–5 | RRF weight for FTS5 keyword results (`0` = disabled) |
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| `modelsFolderPath` | string | — | Path to folder containing .gguf files |
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| `temperature` | float | 0–2 | Inference randomness |
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| `repeatPenalty` | float | 1–2 | Repeat token penalty |
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@@ -64,11 +64,11 @@ The highest-leverage memory upgrade. Transforms NexusAI from "remembers conversa
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- [x] Relationship traversal queries
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- [x] Graph-aware context assembly in orchestration
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### 2. Retrieval Fusion + Full-Text Search
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### 2. Retrieval Fusion + Full-Text Search ✅
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Multi-strategy retrieval merged into a single ranked result set.
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- [ ] Reciprocal Rank Fusion (RRF) — merge semantic (Qdrant) + keyword (FTS5) results
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- [ ] Configurable weights per retrieval strategy
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- [ ] Score threshold tuning per collection
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- [x] Reciprocal Rank Fusion (RRF) — merge semantic (Qdrant) + keyword (FTS5) results
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- [x] Configurable weights per retrieval strategy (`semanticWeight`, `keywordWeight` via `PATCH /settings`)
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- [x] Score threshold retained per-strategy; FTS scoped to session/project sessions; `keywordWeight: 0` default (disabled until tuned)
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### 3. Memory Consolidation Lifecycle
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Prevents long-term memory degradation and enables compression.
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@@ -72,7 +72,9 @@ via `appSettings.load()` — changes apply immediately without a service restart
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|---|---|---|
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| `recentEpisodeLimit` | 5 | Recent episodes injected into prompt |
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| `semanticLimit` | 5 | Semantic search results injected into prompt |
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| `scoreThreshold` | 0.5 | Minimum similarity score for semantic results |
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| `scoreThreshold` | 0.5 | Minimum similarity score for Qdrant semantic results |
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| `semanticWeight` | 1.0 | RRF weight for Qdrant semantic results |
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| `keywordWeight` | 0 | RRF weight for FTS5 keyword results (`0` = disabled) |
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| `modelsFolderPath` | `/mnt/nexus-models` | Path to folder containing .gguf files |
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| `temperature` | 0.7 | Inference temperature |
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| `repeatPenalty` | 1.1 | Repeat token penalty |
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@@ -101,8 +103,12 @@ difference is how the inference response is delivered to the client.
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4. **Recent episode retrieval** — fetch most recent episodes (`recentEpisodeLimit`).
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5. **Semantic search** — embed user message, query Qdrant for similar past
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episodes. Deduplicated against recent episodes. Non-critical.
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5. **Fused episode retrieval** — runs semantic (Qdrant) and keyword (FTS5)
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search in parallel, then merges results via Reciprocal Rank Fusion (RRF).
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Both paths are filtered against `recentIds` before fusion. FTS is scoped
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to the current session or all project sessions. If `keywordWeight` is `0`,
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the FTS call is skipped entirely. Non-critical — failures fall back to
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whichever strategy succeeded.
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6. **Entity search** — query `entities` Qdrant collection filtered by
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`projectId`. Returns entity IDs alongside Qdrant payload data (the Qdrant
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@@ -114,8 +120,8 @@ difference is how the inference response is delivered to the client.
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If no entities were found or the graph call fails, falls back to flat entity
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list (no edges). Non-critical.
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8. **Prompt assembly** — combine system prompt, graph context, semantic
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episodes, recent episodes, and user message.
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8. **Prompt assembly** — combine system prompt, graph context, fused episodes,
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recent episodes, and user message.
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9. **Inference** — send to inference service. `/chat` awaits full response;
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`/chat/stream` pipes SSE chunks to the client.
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153
docs/services/retrieval-fusion.md
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153
docs/services/retrieval-fusion.md
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@@ -0,0 +1,153 @@
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# Retrieval Fusion
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**Implementation:** `packages/orchestration-service/src/chat/index.js`
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**FTS scoping:** `packages/memory-service/src/episodic/index.js`, `src/index.js`
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**Settings:** `semanticWeight`, `keywordWeight` via `PATCH /settings`
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## Purpose
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Rather than relying solely on Qdrant vector similarity (which finds semantically
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related content but misses exact keyword matches) or FTS5 keyword search alone
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(which finds exact matches but not paraphrases), Reciprocal Rank Fusion (RRF)
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merges the ranked results from both strategies into a single better-ranked list.
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Episodes that rank highly in **both** lists score highest. An episode that is
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the top semantic match but irrelevant by keyword, or vice versa, scores lower
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than one that satisfies both.
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## How RRF Works
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For each episode `d`, its fused score is:
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```
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RRF(d) = w_semantic / (k + rank_semantic(d))
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+ w_keyword / (k + rank_keyword(d))
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```
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- `rank_i(d)` — 1-based position in that strategy's result list (episode absent from a list contributes 0 for that term)
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- `k = 60` — smoothing constant (standard; not exposed in settings)
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- `w_semantic`, `w_keyword` — user-tunable weights (both default-sourced from `RETRIEVAL` constants)
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Setting a weight to `0` removes that strategy's contribution entirely. Setting
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`keywordWeight` to `0` also short-circuits the FTS network call.
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## Architecture
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Fusion lives in orchestration — the service already coordinates multiple data
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sources, and fusion is a retrieval strategy, not a storage concern.
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```
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getFusedEpisodes()
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├── getSemanticEpisodes() — Qdrant embed+search → fetch full rows by ID
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│ (existing path, unchanged)
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└── getFTSResults() — memory-service /episodes/search → full rows directly
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(skipped entirely if keywordWeight == 0)
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↓
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fuseEpisodeResults() — pure RRF, no I/O
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↓
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fusedEpisodes[] — top semanticLimit episodes by RRF score
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```
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### Data Shape Consistency
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Both sides must enter fusion as `Episode[]` — full SQLite row objects with
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the same shape — and both must be filtered against `recentIds` first:
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- **Semantic path**: `recentIds` filter applied before `getEpisodeById` fetch (existing behaviour)
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- **FTS path**: full rows returned directly; `recentIds` filter applied in `getFusedEpisodes` after receiving them
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FTS requests `semanticLimit * 2` results to provide headroom for the
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`recentIds` filter without under-serving the fusion.
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## FTS Session Scoping
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Without scoping, FTS5 searches across all episodes in the database. For
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context assembly, results must be constrained to the current session or
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project session pool — the same scope used for Qdrant semantic search.
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`searchEpisodes(query, limit, sessionIds)` in memory-service accepts an
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optional `sessionIds` array. When provided, the SQL becomes:
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```sql
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SELECT e.* FROM episodes e
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JOIN episodes_fts fts ON e.id = fts.rowid
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WHERE episodes_fts MATCH ?
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AND e.session_id IN (?, ?, ...)
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ORDER BY rank
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LIMIT ?
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```
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The HTTP endpoint `GET /episodes/search` accepts `sessionIds` as a
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comma-separated query param: `?q=hello&sessionIds=1,2,3`.
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In orchestration, `ftsSessionIds` is set to:
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- `projectSessionIds` (all sessions in the project) — if the session belongs to a project
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- `[session.id]` — otherwise (single session only)
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This mirrors the Qdrant scoping logic exactly.
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## `fuseEpisodeResults` — Implementation Detail
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```js
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function fuseEpisodeResults(semanticEps, keywordEps, { semanticWeight, keywordWeight, limit }) {
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const k = RETRIEVAL.RRF_K; // 60
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const scores = new Map(); // episode.id → { episode, score }
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// Score semantic results (already filtered against recentIds)
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semanticEps.forEach((ep, i) => {
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scores.set(ep.id, { episode: ep, score: semanticWeight / (k + i + 1) });
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});
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// Score + merge keyword results (already filtered against recentIds)
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keywordEps.forEach((ep, i) => {
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const contrib = keywordWeight / (k + i + 1);
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if (scores.has(ep.id)) {
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scores.get(ep.id).score += contrib; // appears in both — sum scores
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} else if (contrib > 0) {
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scores.set(ep.id, { episode: ep, score: contrib }); // FTS-only episode
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}
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// contrib == 0 (keywordWeight: 0) → episode not added (guard prevents score-0 bleed-through)
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});
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return [...scores.values()]
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.sort((a, b) => b.score - a.score)
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.slice(0, limit)
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.map(({ episode }) => episode);
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}
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```
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The `else if (contrib > 0)` guard prevents FTS-only episodes from entering
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the result set with a score of 0 when `keywordWeight` is 0 — verified by
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the test suite.
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## Settings
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| Setting | Default | Range | Description |
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|---|---|---|---|
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| `semanticWeight` | 1.0 | 0–5 | Weight applied to Qdrant semantic results |
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| `keywordWeight` | 0 | 0–5 | Weight applied to FTS5 keyword results. `0` = disabled |
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Both are readable via `GET /settings` and writable via `PATCH /settings`
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without a service restart. Changes take effect on the next chat request.
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**To enable keyword search:**
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```bash
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curl -X PATCH http://localhost:4000/settings \
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-H "Content-Type: application/json" \
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-d '{"keywordWeight": 1.0}'
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```
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**To favour keyword matches over semantic:**
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```bash
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curl -X PATCH http://localhost:4000/settings \
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-H "Content-Type: application/json" \
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-d '{"semanticWeight": 0.5, "keywordWeight": 2.0}'
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```
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## Constants (`packages/shared/src/config/constants.js`)
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| Constant | Value | Description |
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| `RETRIEVAL.RRF_K` | 60 | RRF smoothing constant — not exposed in settings |
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| `RETRIEVAL.SEMANTIC_WEIGHT` | 1.0 | Default semantic weight |
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| `RETRIEVAL.KEYWORD_WEIGHT` | 0 | Default keyword weight (off) |
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