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_Last updated: 2026-04-24 — rebuttal plan + full contributor handoff_
---
## Rebuttal goal and stakeholder requests (summary)
**Publication:** IEEE TIST journal rebuttal for MATS (multi-agent Text2SQL with small language models and execution feedback).
**Requests captured across the project (themes, not verbatim):**
1. **Rebuttal package:** Correct Overleaf/IEEE-style rebuttal workflow; read reviewers in `overleaf-journal-TIST/review.txt`; plan answers, extra experiments, and missing checkpoints; keep rebuttal assets under `MATS-rebuttal/`.
2. **Recent baselines:** Compare to FINER-SQL, Arctic-Text2SQL-R1, ExCoT SQL, Alpha-SQL (some use execution feedback). **Baseline accuracies are entered manually** in the paper — no mandatory eval harness for those models in this repo.
3. **Accuracy:** Use BIRD `database_description/*.csv` (`column_description`, `value_description`) and **CHESS-style DDL** schema text in prompts for **SFT and ORPO** data prep.
4. **BM25 wording:** Reviewer asked about fallback vs “representative example from V_ci”. **Behavior stays** (first indexed doc as fixed representative); **paper + code comment** clarify — no score filter change required.
5. **Training code:** **Keep `alignment-handbook`** (custom **ORPO** in `scripts/run_orpo.py`); do **not** replace with TRL-only SFT as the sole stack.
6. **Repos:** All edits in **`mats-sql-tist/`** fork only — **not** `/home/datht/mats`. **Do not** use `sql_writer/` for MATS (FINER-SQL area).
7. **Compute:** Local dev + **`ssh gf-henry`** for GPU; **edit locally, rsync** to remote (`scripts/sync_code.sh`). Build BM25 indexes locally; sync `mats/data` to remote as needed.
8. **Tracked tasks:** Run `build_all_bm25_indexes.py` (done); enriched SFT generation (`scripts/build_sft_data.py` / `prepare_sft_datasets.py`); validator–fixer synthetic data (`scripts/generate_val_fix_sft_data.py`); **1.5B** Qwen recipe for gf-henry; maintain **`PROGRESS.md`**.
9. **Ops on gf-henry:** Moved **`mats/data`** (~106 GB) and **`mats/alignment-handbook/output`** (~26 GB) to **`/hdd/datht/mats/...`** with **symlinks**; fixed **Java 11**, **faiss-cpu**, **scipy** (GLIBC), duplicate **`accelerate` dist-info**, **fp16** for Turing GPUs.
---
## Handoff for another contributor (read this first)
| Item | Where / what |
|------|----------------|
| Paper + review | `mats-sql-tist/overleaf-journal-TIST/` (`review.txt`, main `.tex`) |
| Point-by-point rebuttal draft | `mats-sql-tist/MATS-rebuttal/response_to_reviewers.md` (numbers still placeholders until eval) |
| Checkpoint plan | `mats-sql-tist/MATS-rebuttal/checkpoint_tracking.md` |
| Command cheatsheet | `mats-sql-tist/MATS-rebuttal/scripts/training_commands.sh` |
| Remote runbook | `mats-sql-tist/WORKFLOW_GF_HENRY.md` |
| Staged remote script | `mats-sql-tist/scripts/run_training_gf_henry.sh` |
| **Code edits** | **Only** `mats-sql-tist/` — sync with `scripts/sync_code.sh` to **`gf-henry`** |
| **Data (local)** | Symlink `mats-sql-tist/data` → `/home/datht/mats/data` |
| **Data (gf-henry)** | `/home/datht/mats/data` → **`/hdd/datht/mats/data`** (symlink); keep chain intact |
| **Models (gf-henry)** | `~/huggingface` → **`/hdd/datht/huggingface/`** |
| **Conda** | `conda activate mats` (see **Conda Environment** below) |
| **BM25 server** | `db_content_retrieval/lsh_api.py` — **JDK 11+**, heap e.g. `-Xmx6g` |
| **Training precision** | **fp16** on gf-henry (RTX 2080 Ti / TITAN RTX — no native bf16) |
**First actions on pickup:** Read **Resume here** → confirm disk/symlinks on gf-henry → start BM25 API → retry validator–fixer SFT → eval and fill rebuttal numbers.
**Source code:** Upstream is `https://github.com/thanhdath/mats-sql` — this workspace uses the **TIST fork folder** `mats-sql-tist/` (not `/home/datht/mats`).
**SSH:** Configure a `Host gf-henry` entry in `~/.ssh/config` on your laptop (hostname, user, key) so `ssh gf-henry` matches what the sync scripts expect — or edit `scripts/sync_code.sh` to your target.
**Secrets:** Validator–fixer training data was generated **without** paid LLM APIs (heuristic SQL mutations). If you add API-based data generation later, store keys outside git.
**Overleaf / IEEE form:** Use the journal’s official rebuttal / response-to-reviewers template from IEEE TIST author instructions or Overleaf; keep the canonical review text at `overleaf-journal-TIST/review.txt`.
---
## Resume here (next session)
**Policy:** Edit code only under `mats-sql-tist/` on this machine, then `bash scripts/sync_code.sh` (or your usual `rsync`) to `gf-henry`. Avoid editing project files directly on the remote unless unavoidable.
**On gf-henry — do next (in order):**
1. **Confirm env:** `conda activate mats` — `accelerate` should be **0.34.2** only (stale `accelerate-0.23.0.dist-info` was removed; if training still complains, reinstall `accelerate`).
2. **BM25 API:** `JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64`, `JAVA_TOOL_OPTIONS=-Xmx6g`, then start `lsh_api.py` as in `WORKFLOW_GF_HENRY.md` / `scripts/run_training_gf_henry.sh`.
3. **Retry 1.5B validator–fixer SFT:** recipe `alignment-handbook/recipes/qwen-1.5b-bird/validator-fixer-fft-rebuttal.yaml` + accelerate config `recipes/accelerate_configs/single_gpu.yaml` (**fp16**, Turing GPUs — no bf16).
4. After that succeeds: broader SFT/ORPO per `MATS-rebuttal/checkpoint_tracking.md` and `MATS-rebuttal/scripts/training_commands.sh`.
5. **Paper / rebuttal:** fill baseline numbers (ExCoT, Arctic, Alpha-SQL, FINER-SQL) yourself; polish `overleaf-journal-TIST/` and `MATS-rebuttal/response_to_reviewers.md`.
**Large paths on gf-henry:** `mats/data` and `mats/alignment-handbook/output` live under `/hdd/datht/mats/…` with symlinks from `$HOME` — do not delete the symlinks.
---
## Repository Setup
| Task | Status | Notes |
|---|---|---|
| Clone `github.com/thanhdath/mats-sql` → `mats-sql-tist/` | ✅ Done | User cloned; all TIST edits live here only |
| Move `overleaf-journal-TIST/` into `mats-sql-tist/` | ✅ Done | Path: `mats-sql-tist/overleaf-journal-TIST/` |
| Rename conda env `handbook` → `mats` | ✅ Done | `conda rename -n handbook mats` |
| Fix broken `more-itertools` in `mats` env | ✅ Done | `pip install more-itertools` |
| Verify all key libs in `mats` env | ✅ Done | torch 2.2.2, transformers 4.45.0, trl 0.8.6, accelerate 0.34.2, peft 0.6.1, alignment-handbook ✓ |
---
## Code Changes in `mats-sql-tist/` (TIST fork)
### A. BIRD CSV Descriptions (value_description / column_description)
**Problem:** MATS was ignoring the rich `database_description/*.csv` files that BIRD provides per-database.
These contain `column_description` and `value_description` for every column — missing them hurts accuracy.
| File | Status | What changed |
|---|---|---|
| `utils/bird_csv_utils.py` | ✅ **New file** | CHESS-style CSV loader. `load_db_descriptions(db_dir)` reads all CSVs under `database_description/`; handles UTF-8/CP1252 encodings. Also provides `load_all_db_descriptions(split_dir)` for bulk loading. |
| `utils/db_utils.py` — `get_db_schema()` | ✅ Done | Added `db_descriptions=None` parameter. When provided, populates `column_descriptions` and `value_descriptions` lists on each schema item from BIRD CSVs. |
| `utils/db_utils.py` — `get_db_schema_sequence()` | ✅ Done | Rewritten to **CHESS DDL-style format**: `CREATE TABLE … ( col TYPE, -- Example Values: … \| Column Description: … \| Value Description: … )`. Falls back gracefully if fields are absent. |
| `prepare_sft_datasets.py` | ✅ Done | Imports `load_db_descriptions`; auto-detects BIRD sources and loads CSV descriptions; passes them to `get_db_schema()` per `db_id`. |
| `evaluate_end2end.py` | ✅ Done | Imports `get_db_schema_sequence`; regenerates `schema_sequence` at load-time for any sample where it is missing — backward-compatible with old JSON inputs. |
**Example output from new DDL schema format:**
```sql
CREATE TABLE frpm
(
cdscode TEXT, -- Example Values: `01100170` | Column Description: CDSCode identifier | Primary Key
free_meal_count REAL, -- Example Values: `191.0`, `1.0` | Column Description: Free meal count for K-12 | Value Description: 0 = Not eligible; 1 = Eligible
);
```
### B. BM25 Fallback Clarification
| File | Status | What changed |
|---|---|---|
| `db_content_retrieval/lsh_api.py` | ✅ Done | Added inline docstring comment on the fallback path (lines ~82–85): when BM25 finds no hits but the column is non-empty, returning `searcher.doc(0)` is a fixed, reproducible, deterministic "representative example from V_ci" — directly addressing Reviewer concern. No behavioral change. |
### C. Training Framework
| Decision | Status | Notes |
|---|---|---|
| Keep `alignment-handbook` (do NOT switch to TRL SFT) | ✅ Confirmed | `alignment-handbook/scripts/run_orpo.py` contains custom ORPO edits critical to MATS; `train_bird.sh` documents the accelerate launch commands |
---
## BM25 Content Index Status
### Data symlink
`mats-sql-tist/data` → `/home/datht/mats/data` (symlink created)
### Index build script
`scripts/build_all_bm25_indexes.py` — builds / symlinks all indexes; run with:
```bash
conda activate mats
cd mats-sql-tist
python scripts/build_all_bm25_indexes.py
```
### Dataset index status
| Dataset | Index path | Status | Notes |
|---|---|---|---|
| BIRD dev | `data/bird/dev/db_contents_index` | ✅ Done | 11 dbs |
| BIRD train | `data/bird/train/db_contents_index` | ✅ Done | 69 dbs |
| sft_data_collections/bird/dev | symlink → bird/dev | ✅ Done | same 11 dbs |
| sft_data_collections/bird/train | symlink → bird/train | ✅ Done | same 69 dbs |
| Spider (dev/test/train) | `data/spider/db_contents_index` | ✅ Done | 169 dbs |
| Spider-Syn | symlink → spider | ✅ Done | same databases |
| spider-realistic | symlink → spider | ✅ Done | same databases |
| Spider-DK | `sft_data_collections/Spider-DK/db_contents_index` | ✅ Done | 3 new dbs |
| Dr.Spider NLQ\_\* (9 sets) | symlink → spider | ✅ Done | same databases |
| Dr.Spider SQL\_\* (5 sets) | symlink → spider | ✅ Done | same databases |
| Dr.Spider DB\_schema\_synonym | `…/DB_schema_synonym/db_contents_index` | ✅ Done | 96/96 dbs |
| Dr.Spider DB\_schema\_abbreviation | `…/DB_schema_abbreviation/db_contents_index` | ✅ Done | 96/96 dbs |
| Dr.Spider DB\_DBcontent\_equivalence | `…/DB_DBcontent_equivalence/db_contents_index` | ✅ Done | 63/63 dbs |
| Domain datasets (Bank/Aminer) | `sft_data_collections/domain_datasets/db_contents_index` | ✅ Done | 2/2 dbs |
_Full index build finished; `build_all_bm25_indexes.py` is not required to run again unless databases change._
### `lsh_api.py` source paths updated
All sources now correctly mapped in `db_content_retrieval/lsh_api.py`:
- BIRD dev/train → `data/bird/{dev,train}/db_contents_index`
- Spider-train → `data/spider/db_contents_index`
- Spider-dev/syn/realistic → synonym of spider-train
- Dr.Spider DB_\* → own index paths
- Dr.Spider NLQ_\*/SQL_\* → own index paths (symlinked to spider)
- Bank/Aminer domain datasets → domain_datasets index
- Startup auto-filters sources whose index dir does not yet exist (no crash on missing dirs)
---
## Completed (local + gf-henry) — since core code landed
| Area | Status | Notes |
|------|--------|------|
| BM25 indexes (all planned sets) | ✅ | Built locally via `scripts/build_all_bm25_indexes.py`; synced to gf-henry with `mats/data` |
| Enriched BIRD SFT JSON/JSONL | ✅ Local + synced | `scripts/build_sft_data.py` → e.g. `mats/data/rebuttal_sft_bird_{train,dev}_text2sql.json(l)` (CHESS-style schema + BM25 evidence) |
| Validator–fixer SFT data (synthetic) | ✅ Local + synced | `scripts/generate_val_fix_sft_data.py` → `data/multi-agents/fixed/sft-validator-fixer-bird_with_evidence/` (HF `DatasetDict`) |
| gf-henry `mats` env | ✅ | torch 2.2.2+cu121, transformers, trl, peft, pyserini, faiss-cpu, scipy wheel compatible with Ubuntu 20.04 / GLIBC 2.31 |
| BM25 API on gf-henry | ✅ Was working | Java **11** (`JAVA_HOME`), heap `-Xmx6g`; `lsh_api.py` filters `synonym_sources` when `--db_content_index` limits loaded corpora (fixes `KeyError`) |
| Qwen2.5-Coder-1.5B-Instruct | ✅ On gf-henry | Under `/home/datht/huggingface/` → `/hdd/datht/huggingface/` (existing symlink layout) |
| Rebuttal draft doc | ✅ Draft | `MATS-rebuttal/response_to_reviewers.md` — still needs **final numbers** and polish |
| Training wiring | ✅ | `alignment-handbook/recipes/qwen-1.5b-bird/validator-fixer-fft-rebuttal.yaml` (fp16); `recipes/accelerate_configs/single_gpu.yaml` (fp16); `scripts/run_training_gf_henry.sh`; `WORKFLOW_GF_HENRY.md` |
---
## Pending work (your turn / GPU)
### Training & evaluation on gf-henry
| Task | Status | Notes |
|------|--------|------|
| Validator–fixer SFT (1.5B Qwen) | ⏳ **Next** | Unblockers applied: disk space, duplicate `accelerate` dist-info removed, fp16 configs — **re-run training** and confirm loss/checkpoint |
| Full agent SFT + ORPO refresh | ⏳ | After rebuttal data/checkpoints agreed; use `alignment-handbook` + `MATS-rebuttal/checkpoint_tracking.md` |
| ORPO preference data regen | ⏳ | After refreshed SFT artifacts if you change prompts/schema again |
| `evaluate_end2end.py` on BIRD dev (new checkpoints) | ⏳ | After models trained |
| Ablations (no Schema Insight, no Validator, SFT-only, oracle selector, etc.) | ⏳ | Plan in rebuttal docs |
### Paper & rebuttal (no GPU)
| Task | Status | Notes |
|------|--------|------|
| Baseline table: ExCoT, Arctic-Text2SQL-R1, Alpha-SQL, FINER-SQL | ⏳ | **You add accuracy** — no eval runs required in this repo |
| Finalize `response_to_reviewers.md` | ⏳ | Merge measured numbers after eval |
| LaTeX polish + RQ-led experiment narrative | ⏳ | `overleaf-journal-TIST/` |
| Pipeline overview figure | ⏳ | New diagram for camera-ready |
| Official hidden-test submission | ⏳ | After final checkpoints |
### Optional code improvements
| Task | Status | Notes |
|------|--------|------|
| Selector: majority vote / self-consistency on execution | ⏳ | No retraining |
---
## Known issues / gotchas (gf-henry)
1. **Root `/` was full** — mitigated by moving `mats/data` (106G) and `mats/alignment-handbook/output` (26G) to `/hdd/datht/mats/…` with symlinks; **keep** that layout.
2. **Turing GPUs** — no bf16: training YAML + accelerate config use **fp16**.
3. **Java** — BM25/Lucene needs **JDK 11+**, not default Java 8.
4. **Do not use** `sql_writer/` in this repo (reserved for FINER-SQL baseline work).
---
## File Map
```
mats-sql-tist/
├── overleaf-journal-TIST/ ← LaTeX paper + review.txt
│ ├── main_multiagent.tex
│ ├── review.txt
│ └── text/
├── MATS-rebuttal/ ← rebuttal plan + drafts + scripts
│ ├── response_to_reviewers.md
│ ├── checkpoint_tracking.md
│ └── scripts/training_commands.sh
├── utils/
│ ├── bird_csv_utils.py ✅ NEW — BIRD CSV description loader
│ ├── db_utils.py ✅ MODIFIED — CHESS DDL schema format
│ └── load_sft_dataset.py
├── db_content_retrieval/
│ └── lsh_api.py ✅ MODIFIED — fixed source paths + BM25 fallback comment
├── scripts/
│ ├── build_all_bm25_indexes.py ✅ builds / symlinks all dataset BM25 indexes
│ ├── build_sft_data.py ✅ enriched BIRD SFT JSONL (calls prepare_sft_datasets)
│ ├── generate_val_fix_sft_data.py ✅ synthetic validator–fixer SFT from gold SQL
│ ├── sync_code.sh ✅ rsync mats-sql-tist → gf-henry
│ ├── setup_env_gf_henry.sh ✅ conda/pip bootstrap for remote
│ └── run_training_gf_henry.sh ✅ staged BM25 / data / training on gf-henry
├── WORKFLOW_GF_HENRY.md ✅ remote runbook
├── prepare_sft_datasets.py ✅ MODIFIED — wires BIRD CSV descriptions
├── evaluate_end2end.py ✅ MODIFIED — rebuilds schema_sequence
├── data -> /home/datht/mats/data ✅ NEW symlink — shared data dir
├── alignment-handbook/ ← keep as-is (custom ORPO)
│ ├── recipes/
│ │ ├── accelerate_configs/single_gpu.yaml ✅ fp16, single GPU (gf-henry)
│ │ └── qwen-1.5b-bird/validator-fixer-fft-rebuttal.yaml ✅ rebuttal SFT recipe
│ └── scripts/
│ ├── train_bird.sh
│ ├── run_orpo.py
│ └── run_sft.py
└── PROGRESS.md ← this file
```
---
## Conda Environment
```
conda activate mats
# Key packages:
# torch 2.2.2+cu121
# transformers 4.45.0
# trl 0.8.6
# accelerate 0.34.2
# peft 0.6.1
```
---
## gf-henry transfer and storage (physical layout)
Large trees were moved off the small `/` volume to **`/hdd/datht/`** (symlinks from `$HOME` — **do not remove**):
| Logical path on gf-henry | Physical location (approx.) |
|--------------------------|-------------------------------|
| `/home/datht/mats/data` | `/hdd/datht/mats/data` (~106 GB: BIRD, Spider, indexes, rebuttal JSON, etc.) |
| `/home/datht/mats/alignment-handbook/output` | `/hdd/datht/mats/alignment-handbook/output` (~26 GB checkpoints) |
| `/home/datht/huggingface` | `/hdd/datht/huggingface/` (base models, e.g. Qwen2.5-Coder-1.5B-Instruct) |
**Also synced / present:** `mats-sql-tist` tree, `sft_data_collections`, Dr.Spider / domain paths under `mats/data`, schema_insight checkpoints as applicable, synthetic validator–fixer HF dataset under `data/multi-agents/fixed/sft-validator-fixer-bird_with_evidence/`.
## gf-henry Environment (mats conda env)
| Package | Version | Status |
|---------|---------|--------|
| torch | 2.2.2+cu121 | ✅ CUDA available (2 GPUs) |
| transformers | 4.45.0 | ✅ |
| accelerate | 0.34.2 | ✅ |
| trl | 0.8.6 | ✅ |
| peft | 0.6.1 | ✅ |
| pyserini | 0.21.0 | ✅ |
| numpy | 1.26.4 | ✅ |
| alignment-handbook | 0.2.0.dev0 | ✅ |
**GPUs:** TITAN RTX (23GB VRAM) + RTX 2080 Ti (10GB VRAM)
**Note:** bitsandbytes removed (not needed for FFT training; had scipy binary incompatibility).
## MATS-rebuttal/ Contents
| File | Status |
|------|--------|
| `response_to_reviewers.md` | ✅ Draft complete (placeholders for numbers) |
| `checkpoint_tracking.md` | ✅ Created |
| `scripts/training_commands.sh` | ✅ Created |
## Disk space management (gf-henry, Apr 23, 2026)
_See also **gf-henry transfer and storage** above._ Moved large directories from `/home` (was 100% full) to `/hdd/datht/` and created symlinks:
| Directory | Size | Action |
|-----------|------|--------|
| `/home/datht/mats/data` → `/hdd/datht/mats/data` | 106GB | Moved + symlinked ✅ |
| `/home/datht/mats/alignment-handbook/output` → `/hdd/datht/mats/alignment-handbook/output` | 26GB | Moved + symlinked ✅ |
**Result:** Home partition freed from 100% → 87% used (117GB free now)
**Fixed:** Removed stale `accelerate-0.23.0.dist-info` from `mats` env (was causing `ImportError` during training)
## Later pipeline (after validator–fixer SFT succeeds)
Use **`MATS-rebuttal/checkpoint_tracking.md`** and **`MATS-rebuttal/scripts/training_commands.sh`** as the source of truth. Typical order: broader **SFT** / **ORPO** per agent → **`evaluate_end2end.py`** on BIRD dev → **ablations** (no Schema Insight, no Validator, SFT-only, oracle selector, etc.) → merge metrics into **`response_to_reviewers.md`** and Overleaf tables.
**Do not repeat by default:** Full **`build_all_bm25_indexes.py`** and enriched **rebuttal SFT JSON(L)** generation were already run locally and synced; only re-run if database files, index paths, or prompt schema change materially.
## Previous conversation transcript
[MATS TIST Rebuttal Plan & Setup](a4a8aeb7-1505-431c-9880-59c969998eb0)
|