| # Canonical Planner Pipeline |
|
|
| ONE configuration. No variants. |
|
|
| ## Schema sequence format (used in BOTH train and dev prompts) |
|
|
| ``` |
| table T , columns = [ |
| T.col | [primary key ;] type: {text|integer|real} ; [meaning: <column_description from BIRD CSV> ;] [value description: <value_description from BIRD CSV> ;] [has None ;] [values: <BM25-retrieved-top-k for question>] |
| ... |
| ] |
| foreign keys: |
| T1.c1 = T2.c2 |
| ... |
| ``` |
|
|
| All five fields used (when applicable): |
| 1. **type / primary key** — from SQLite PRAGMA |
| 2. **meaning** — `column_description` from `bird/<split>/<db>/database_description/*.csv` |
| 3. **value description** — `value_description` from same CSV |
| 4. **has None** — count of NULL values > 0 in column |
| 5. **values** — top-2 BM25 hits for the question against `db_contents_index/<db>/<table>-**-<column>/`. Falls back to first indexed doc if BM25 returns no query-relevant hits. |
|
|
| ## Files |
|
|
| | Asset | Path | |
| |---|---| |
| | Training data | `data/sft_planner_canonical/` | |
| | Dev prompts | `data/bird_dev_planner_prompts.json` | |
| | Training recipe | `alignment-handbook/recipes/llama-1b-bird/planner-fft-canonical.yaml` | |
| | Trained checkpoint | `alignment-handbook/output/planner-canonical/` | |
| | Builder for dev prompts | `scripts/build_canonical_prompts.py` | |
| | BM25 server | `db_content_retrieval/lsh_api.py` (start with `--lazy_load --db_content_index bird-dev`) | |
|
|
| ## How to rebuild dev prompts from scratch |
|
|
| ```bash |
| # 1) Start BM25 server (lazy_load avoids OOM) |
| JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64 JAVA_TOOL_OPTIONS=-Xmx12g \ |
| python db_content_retrieval/lsh_api.py --port 8005 --db_content_index bird-dev --lazy_load & |
| |
| # 2) Build canonical dev prompts |
| python scripts/build_canonical_prompts.py \ |
| --source bird-dev \ |
| --data data/sft_bird_with_evidence_dev_text2sql.json \ |
| --bird_dir data/bird/dev/dev_databases \ |
| --out data/bird_dev_planner_prompts.json |
| ``` |
|
|
| ## How to retrain |
|
|
| ```bash |
| cd alignment-handbook |
| PYTHONPATH=src/ accelerate launch \ |
| --config_file recipes/accelerate_configs/single_gpu0_local.yaml \ |
| scripts/run_sft.py \ |
| recipes/llama-1b-bird/planner-fft-canonical.yaml |
| ``` |
|
|
| ## Eval |
|
|
| ```bash |
| python scripts/run_eval_vllm.py \ |
| --model alignment-handbook/output/planner-canonical \ |
| --tokenizer_template qwen \ |
| --prompts_json data/bird_dev_planner_prompts.json \ |
| --output_dir eval_results/planner-canonical-bird-dev \ |
| --skip_pass_k --max_model_len 8192 --max_tokens 1024 --dtype bfloat16 |
| ``` |
|
|