Any line that doesn't start with a valid prefix now returns 0.0
instead of just counting as a penalty. This prevents any prose,
explanations, bullet points, or other invalid content.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Zero reward for outputs containing:
- <|im_start|>, <|im_end|> tokens
- <think>, </think> tags (Qwen3 thinking mode)
- Role markers like \nassistant\n, \nuser\n
- <|endoftext|> token
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Major changes:
- train.py: Generic SFT training script using YAML config
- rl.py: Generic GRPO training script using YAML config
- configs/: YAML configs per training run (sft_v4.yaml, grpo_v4.yaml)
- dataset/: Data preparation scripts moved here
- tui.py: Interactive model testing interface
Training results:
- SFT v4: 98.8% avg score (all Excellent)
- GRPO v4: 0% (failed - model drifted to verbose explanations)
Removed per-model scripts (train_0.6B.py, train_1.7B.py, etc)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add explicit HF_TOKEN login before training
- Use SCORING.md criteria as RL reward function
- Conservative training: LR 1e-6, LoRA rank 4
- Reward scores: good=0.94, bad=0.38
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
New scoring criteria (0-100 points):
- Format (30): Must have lex: and vec: prefixes
- Diversity (30): Multiple types, no echoing query, diverse expansions
- Hyde (20): Optional, concise, no newlines, no word repetition
- Quality (20): Lex=keywords, vec=natural language
See SCORING.md for full documentation.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Use max_completion_length instead of max_new_tokens
- Use processing_class instead of tokenizer
- Use args instead of config for GRPOTrainer
- Add __name__ attribute to reward function class
- Accept **kwargs in reward function for extra TRL args
- Add new LoRA adapter after merging SFT weights
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add normalizeDocid() to strip quotes and # prefix
- Add isDocid() to detect docid patterns including quoted forms
- Update findDocumentByDocid, findDocument, getDocument to use new helpers
- All formats now work: #abc123, abc123, "#abc123", "abc123", '#abc123', 'abc123'
- Add 18 unit tests for normalizeDocid and isDocid
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
The `qmd get` command was documented to support docid lookups
(e.g., `qmd get "#abc123"` or `qmd get abc123`), but the
implementation in getDocument() never actually handled docids.
The findDocumentByDocid() function existed in store.ts and worked
correctly, but getDocument() in qmd.ts reimplemented document
lookup without calling it.
This adds docid detection at the start of getDocument() to resolve
docids to virtual paths before other path handling.
Co-authored-by: Joshua Mitchell <jlelonmitchell@gmail.com >
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
The code uses Qwen3-1.7B (~2.2GB) for query expansion, but the README
documented Qwen3-0.6B (~640MB) in three places:
- Model requirements table
- Architecture diagram
- Code configuration sample
This caused confusion when users saw a 2GB+ download instead of 640MB.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Previously, the "Run 'qmd embed' to update embeddings" message was
printed after each collection was indexed, repeating the same global
count multiple times. Now it's shown once at the end of the update.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add detailed comments explaining why two-step query is necessary
- Add regression test for sqlite-vec JOIN hang bug
- Link to PR in comments for future reference
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
sqlite-vec virtual tables don't work correctly with JOINs in the same
query - they cause the query to hang indefinitely.
Changes:
- searchVec: Rewrite to use two-step approach
1. Query vectors_vec table alone (no JOINs)
2. Look up document info separately using result hash_seqs
- vsearch: Change from Promise.all to sequential for loop
(node-llama-cpp embedding context doesn't handle concurrent calls)
This fixes vsearch and hybrid query commands that were hanging at
"Searching N vector queries..."
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Empty files have nothing useful to index or embed. Previously they would
be indexed with an empty body, causing confusing "1 need embedding" status
messages that could never be resolved.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Issue #11: Collection filter (-c) SQL error
- Fixed searchVec to properly parameterize collection filter
- Changed collectionId check from !== undefined to truthy
- Added test for searchVec with collection filter
Issue #10: Non-ASCII filename support
- Updated handelize() to use Unicode property escapes (\p{L}\p{N})
- Now supports Cyrillic, Japanese, and other Unicode filenames
- Updated tests to verify Unicode filename handling
Also:
- Fixed expandQuery to filter out lex entries when includeLexical=false
- Updated expandQuery tests to match actual behavior
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Fix SQL syntax error when collectionId is empty string (searchFTS, searchVec)
- Add 1-second timeout to llama.dispose() to prevent indefinite hang
- Add process.exit(0) after cleanup for clean CLI exit
- Include hash/docid in search results mapping
- Update query expansion to use structured Queryable types
- Switch to Qwen3-1.7B model for better query expansion
- Improve bun discovery in qmd wrapper script
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Instead of calling countTokens() multiple times during binary search
for chunk boundaries, tokenize the document once upfront and slice
token arrays. This reduces tokenizer calls from O(chunks × iterations)
to O(1) per document.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The previous implementation spawned a subprocess for every file during
indexing (e.g., 4500 subprocess spawns for a large collection). This
caused resource exhaustion and random hangs. Using Node's native
realpathSync is orders of magnitude faster.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The installPhase was trying to copy qmd.ts from root, but it's at
src/qmd.ts. Updated to copy the src directory and point the wrapper
to the correct path.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Fix ReferenceError in vectorIndex(): firstResult was used but never
defined. Added code to embed first chunk to get embedding dimensions.
- Fix 87 TypeScript errors across codebase:
- formatter.ts: Define MultiGetFile type locally (was missing from store.ts)
- collections.ts: Add non-null assertion for array access
- mcp.ts: Fix StatusResult type to match store.ts CollectionInfo,
add list parameter to ResourceTemplate, fix undefined checks
- qmd.ts: Fix boolean/string type coercions, undefined array access
- llm.test.ts: Update expandQuery tests for Queryable[] return type,
fix array access assertions
- store.test.ts: Add non-null assertions for array access in tests
- eval-harness.ts: Fix array access assertion
Let node-llama-cpp handle context size and sequences automatically.
The mutex still serializes generation calls for safety.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Reduce context sequences from 4 to 1 to minimize VRAM usage
when multiple models (embed, generate, rerank) are loaded
- Add mutex to serialize generation calls to prevent "No sequences left"
error when concurrent requests occur with single sequence
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- dispose() now just calls llama.dispose() which cascades to models/contexts
per node-llama-cpp lifecycle docs
- Remove disposeDefaultLlamaCpp calls from tests - they don't help with
the Metal cleanup crash
- Use singleton getDefaultLlamaCpp() in llm tests for consistency
The Metal backend crash at process exit is a known llama.cpp issue:
https://github.com/ggml-org/llama.cpp/pull/17869
All tests pass - the abort happens after test completion.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The Metal backend crash happens regardless of whether we dispose or not.
It's a known llama.cpp issue during process exit static destructor cleanup:
https://github.com/ggml-org/llama.cpp/pull/17869
All 297 tests pass - the abort happens after tests complete.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The Metal crash was caused by not disposing resources in the right order
at the right time. The fix:
1. Restore proper dispose() that disposes contexts → models → llama in order
2. Move disposeDefaultLlamaCpp() to global afterAll (after all tests complete)
3. Keep disposed flag to prevent double-dispose
The issue was that disposing per-suite broke tests that share llama,
and not disposing at all left orphaned Metal resources at process exit.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add 6 "fusion" queries designed to test cases where neither BM25 nor
vector search alone succeeds, but combining them with RRF does:
- "how much runway before running out of money" → fundraising
- "datacenter replication sync strategy" → distributed-systems
- "splitting data for training and testing" → machine-learning
- "JSON response codes error messages" → api-design
- "video calls camera async messaging" → remote-work
- "CI/CD pipeline testing coverage" → product-launch
The fusion test verifies:
1. Hybrid achieves ≥50% Hit@3 on these multi-signal queries
2. Hybrid outperforms or matches the best individual method
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add disposed flag to prevent double-dispose
- Don't explicitly dispose llama resources in dispose() - just clear refs
- Let process exit handle Metal cleanup naturally
- Remove disposeDefaultLlamaCpp call from eval tests
Note: llama.cpp Metal backend still crashes at process exit due to
ggml-metal cleanup issues. This is a known upstream issue:
https://github.com/ggml-org/llama.cpp/pull/17869
All tests pass (12/12), the abort happens after test completion.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Pass model and embeddedAt parameters to insertEmbedding
- Convert embedding to Float32Array for sqlite-vec compatibility
- Make hybrid search thresholds conditional on vector availability
(falls back to BM25-only thresholds when no embeddings exist)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Three test suites with different thresholds:
- BM25: easy≥80%, medium≥15%, hard≥15%, overall≥40%
- Vector: easy≥60%, medium≥40%, hard≥30%, overall≥50%
- Hybrid (RRF): easy≥80%, medium≥50%, hard≥35%, overall≥60%
Hybrid should outperform individual methods on semantic queries.
Vector/hybrid tests have 60-120s timeouts for embedding generation.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add enableProductionMode() that qmd.ts calls at startup
- getDefaultDbPath() throws in test mode unless INDEX_PATH is set
- Update store.test.ts to expect throws for default path tests
- Add eval.test.ts with 18 BM25 quality tests (easy/medium/hard)
- Tests now cannot accidentally write to ~/.cache/qmd/
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Skip expensive LLM query expansion when initial BM25 search has
strong signals (top result score > 0.7). This saves LLM calls and
latency for queries that already match well.
- Run initial BM25 search first
- Check if top result has strong score
- Skip expansion if signal is strong
- Reuse initial search results for retrieval
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Instead of reranking just 1 keyword-matched chunk per doc, now:
- Select top 3 chunks per document (by keyword score)
- Rerank all selected chunks
- Aggregate scores using top-2 average (rewards consistency)
- Use best-scoring chunk for snippet display
This improves ranking for long documents where the keyword-matched
chunk isn't always the most relevant to the query.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Added safety net deduplication after reranking to prevent the same
file appearing multiple times in results. Uses Set to keep only
first (highest-scored) occurrence of each file.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
