creating prompt bench

.gitignore

@@ -169,3 +169,7 @@ test.*
 # Frontend build output
 frontend/dist/
 frontend/node_modules/
+
+# data dir for training, validation, and testing
+data/
+config.toml

overlays/default.nix

@@ -24,6 +24,7 @@
         fastapi
         fastapi-cli
         httpx
+        huggingface-hub
         mypy
         orjson
         polars
@@ -41,6 +42,7 @@
         sqlalchemy
         tenacity
         textual
+        tiktoken
         tinytuya
         typer
         websockets

pyproject.toml

@@ -12,6 +12,7 @@ dependencies = [
     "alembic",
     "apprise",
     "apscheduler",
+    "huggingface-hub",
     "httpx",
     "python-multipart",
     "polars",
@@ -26,6 +27,11 @@ dependencies = [
 [project.scripts]
 database = "python.database_cli:app"
 van-inventory = "python.van_inventory.main:serve"
+prompt-bench = "python.prompt_bench.main:cli"
+prompt-bench-download = "python.prompt_bench.downloader:cli"
+finetune = "python.prompt_bench.finetune:cli"
+finetune-container = "python.prompt_bench.finetune_container:cli"
+build-finetune-dataset = "python.prompt_bench.build_finetune_dataset:cli"
 
 [dependency-groups]
 dev = [
@@ -81,6 +87,11 @@ lint.ignore = [
 "python/eval_warnings/**" = [
     "S607", # (perm) gh and git are expected on PATH in the runner environment
 ]
+"python/prompt_bench/**" = [
+    "FBT002",  # (perm) typer requires boolean defaults for --flag/--no-flag options
+    "PLR0913", # (perm) typer CLIs naturally have many parameters
+    "S607",    # (perm) docker and nvidia-smi are expected on PATH
+]
 "python/alembic/**" = [
     "INP001", # (perm) this creates LSP issues for alembic
 ]

python/prompt_bench/Dockerfile.finetune

@@ -0,0 +1,25 @@
+# Unsloth fine-tuning container for Qwen 3.5 4B on RTX 3090.
+#
+# Build:
+#   docker build -f python/prompt_bench/Dockerfile.finetune -t bill-finetune .
+#
+# Run:
+#   docker run --rm --device=nvidia.com/gpu=all --ipc=host \
+#     -v $(pwd)/output:/workspace/output \
+#     -v $(pwd)/output/finetune_dataset.jsonl:/workspace/dataset.jsonl:ro \
+#     -v /zfs/models/hf:/models \
+#     bill-finetune \
+#     --dataset /workspace/dataset.jsonl \
+#     --output-dir /workspace/output/qwen-bill-summarizer
+
+FROM ghcr.io/unslothai/unsloth:latest
+
+RUN pip install --no-cache-dir typer
+
+WORKDIR /workspace
+COPY python/prompt_bench/finetune.py python/prompt_bench/finetune.py
+COPY python/prompt_bench/summarization_prompts.py python/prompt_bench/summarization_prompts.py
+COPY python/prompt_bench/__init__.py python/prompt_bench/__init__.py
+COPY python/__init__.py python/__init__.py
+
+ENTRYPOINT ["python", "-m", "python.prompt_bench.finetune"]

python/prompt_bench/__init__.py

@@ -0,0 +1 @@
+"""Prompt benchmarking system for evaluating LLMs via vLLM."""

python/prompt_bench/batch_bill_summarizer.py

@@ -0,0 +1,233 @@
+"""Submit an OpenAI Batch API bill-summarization job over compressed text.
+
+Reads the first N bills from a CSV with a `text_content` column, compresses
+each via `bill_token_compression.compress_bill_text`, builds a JSONL file of
+summarization requests, and submits it as an asynchronous Batch API job
+against `/v1/chat/completions`. Also writes a CSV of per-bill pre/post-
+compression token counts.
+"""
+
+from __future__ import annotations
+
+import csv
+import json
+import logging
+import re
+import sys
+from os import getenv
+from pathlib import Path
+from typing import Annotated
+
+import httpx
+import typer
+from tiktoken import Encoding, get_encoding
+
+from python.prompt_bench.bill_token_compression import compress_bill_text
+from python.prompt_bench.summarization_prompts import SUMMARIZATION_SYSTEM_PROMPT, SUMMARIZATION_USER_TEMPLATE
+
+logger = logging.getLogger(__name__)
+
+OPENAI_API_BASE = "https://api.openai.com/v1"
+
+
+def load_bills(csv_path: Path, count: int = 0) -> list[tuple[str, str]]:
+    """Return (bill_id, text_content) tuples with non-empty text.
+
+    If `count` is 0 or negative, all rows are returned.
+    """
+    csv.field_size_limit(sys.maxsize)
+    bills: list[tuple[str, str]] = []
+    with csv_path.open(newline="", encoding="utf-8") as handle:
+        reader = csv.DictReader(handle)
+        for row in reader:
+            text_content = (row.get("text_content") or "").strip()
+            if not text_content:
+                continue
+            bill_id = row.get("bill_id") or row.get("id") or f"row-{len(bills)}"
+            version_code = row.get("version_code") or ""
+            unique_id = f"{bill_id}-{version_code}" if version_code else bill_id
+            bills.append((unique_id, text_content))
+            if count > 0 and len(bills) >= count:
+                break
+    return bills
+
+
+def safe_filename(value: str) -> str:
+    """Make a string safe for use as a filename or batch custom_id."""
+    return re.sub(r"[^A-Za-z0-9._-]+", "_", value).strip("_") or "unnamed"
+
+
+def build_request(custom_id: str, model: str, bill_text: str) -> dict:
+    """Build one OpenAI batch request line."""
+    return {
+        "custom_id": custom_id,
+        "method": "POST",
+        "url": "/v1/chat/completions",
+        "body": {
+            "model": model,
+            "messages": [
+                {"role": "system", "content": SUMMARIZATION_SYSTEM_PROMPT},
+                {"role": "user", "content": SUMMARIZATION_USER_TEMPLATE.format(text_content=bill_text)},
+            ],
+        },
+    }
+
+
+def write_jsonl(path: Path, lines: list[dict]) -> None:
+    """Write a list of dicts as JSONL."""
+    with path.open("w", encoding="utf-8") as handle:
+        for line in lines:
+            handle.write(json.dumps(line, ensure_ascii=False))
+            handle.write("\n")
+
+
+def upload_file(client: httpx.Client, path: Path) -> str:
+    """Upload a JSONL file to the OpenAI Files API and return its file id."""
+    with path.open("rb") as handle:
+        response = client.post(
+            f"{OPENAI_API_BASE}/files",
+            files={"file": (path.name, handle, "application/jsonl")},
+            data={"purpose": "batch"},
+        )
+    response.raise_for_status()
+    return response.json()["id"]
+
+
+def prepare_requests(
+    bills: list[tuple[str, str]],
+    *,
+    model: str,
+    encoder: Encoding,
+) -> tuple[list[dict], list[dict]]:
+    """Build (request_lines, token_rows) from bills.
+
+    Each bill is compressed before being turned into a request line.
+    Each `token_rows` entry has chars + token counts for one bill so the caller
+    can write a per-bill CSV.
+    """
+    request_lines: list[dict] = []
+    token_rows: list[dict] = []
+    for bill_id, text_content in bills:
+        raw_token_count = len(encoder.encode(text_content))
+        compressed_text = compress_bill_text(text_content)
+        compressed_token_count = len(encoder.encode(compressed_text))
+        token_rows.append(
+            {
+                "bill_id": bill_id,
+                "raw_chars": len(text_content),
+                "compressed_chars": len(compressed_text),
+                "raw_tokens": raw_token_count,
+                "compressed_tokens": compressed_token_count,
+                "token_ratio": (compressed_token_count / raw_token_count) if raw_token_count else None,
+            },
+        )
+        safe_id = safe_filename(bill_id)
+        request_lines.append(build_request(safe_id, model, compressed_text))
+    return request_lines, token_rows
+
+
+def write_token_csv(path: Path, token_rows: list[dict]) -> tuple[int, int]:
+    """Write per-bill token counts to CSV. Returns (raw_total, compressed_total)."""
+    with path.open("w", newline="", encoding="utf-8") as handle:
+        writer = csv.DictWriter(
+            handle,
+            fieldnames=["bill_id", "raw_chars", "compressed_chars", "raw_tokens", "compressed_tokens", "token_ratio"],
+        )
+        writer.writeheader()
+        writer.writerows(token_rows)
+    raw_total = sum(row["raw_tokens"] for row in token_rows)
+    compressed_total = sum(row["compressed_tokens"] for row in token_rows)
+    return raw_total, compressed_total
+
+
+def create_batch(client: httpx.Client, input_file_id: str, description: str) -> dict:
+    """Create a batch job and return its full response payload."""
+    response = client.post(
+        f"{OPENAI_API_BASE}/batches",
+        json={
+            "input_file_id": input_file_id,
+            "endpoint": "/v1/chat/completions",
+            "completion_window": "24h",
+            "metadata": {"description": description},
+        },
+    )
+    response.raise_for_status()
+    return response.json()
+
+
+def main(
+    csv_path: Annotated[Path, typer.Option("--csv", help="Bills CSV path")] = Path("bills.csv"),
+    output_dir: Annotated[Path, typer.Option("--output-dir", help="Where to write JSONL + metadata")] = Path(
+        "output/openai_batch",
+    ),
+    model: Annotated[str, typer.Option(help="OpenAI model id")] = "gpt-5-mini",
+    count: Annotated[int, typer.Option(help="Max bills to process, 0 = all")] = 0,
+    log_level: Annotated[str, typer.Option(help="Log level")] = "INFO",
+) -> None:
+    """Submit an OpenAI Batch job of compressed bill summaries."""
+    logging.basicConfig(level=log_level, format="%(asctime)s %(levelname)s %(name)s: %(message)s")
+
+    api_key = getenv("CLOSEDAI_TOKEN") or getenv("OPENAI_API_KEY")
+    if not api_key:
+        message = "Neither CLOSEDAI_TOKEN nor OPENAI_API_KEY is set"
+        raise typer.BadParameter(message)
+    if not csv_path.is_file():
+        message = f"CSV not found: {csv_path}"
+        raise typer.BadParameter(message)
+
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    logger.info("Loading %d bills from %s", count, csv_path)
+    bills = load_bills(csv_path, count)
+    if len(bills) < count:
+        logger.warning("Only %d bills available (requested %d)", len(bills), count)
+
+    encoder = get_encoding("o200k_base")
+    request_lines, token_rows = prepare_requests(bills, model=model, encoder=encoder)
+
+    token_csv_path = output_dir / "token_counts.csv"
+    raw_tokens_total, compressed_tokens_total = write_token_csv(token_csv_path, token_rows)
+    logger.info(
+        "Token counts: raw=%d compressed=%d ratio=%.3f -> %s",
+        raw_tokens_total,
+        compressed_tokens_total,
+        (compressed_tokens_total / raw_tokens_total) if raw_tokens_total else 0.0,
+        token_csv_path,
+    )
+
+    jsonl_path = output_dir / "requests.jsonl"
+    write_jsonl(jsonl_path, request_lines)
+    logger.info("Wrote %s (%d bills)", jsonl_path, len(request_lines))
+
+    headers = {"Authorization": f"Bearer {api_key}"}
+    with httpx.Client(headers=headers, timeout=httpx.Timeout(300.0)) as client:
+        logger.info("Uploading JSONL")
+        file_id = upload_file(client, jsonl_path)
+        logger.info("Uploaded: %s", file_id)
+
+        logger.info("Creating batch")
+        batch = create_batch(client, file_id, f"compressed bill summaries x{len(request_lines)} ({model})")
+        logger.info("Batch created: %s", batch["id"])
+
+    metadata = {
+        "model": model,
+        "count": len(bills),
+        "jsonl": str(jsonl_path),
+        "input_file_id": file_id,
+        "batch_id": batch["id"],
+        "raw_tokens_total": raw_tokens_total,
+        "compressed_tokens_total": compressed_tokens_total,
+        "batch": batch,
+    }
+    metadata_path = output_dir / "batch.json"
+    metadata_path.write_text(json.dumps(metadata, indent=2))
+    logger.info("Wrote metadata to %s", metadata_path)
+
+
+def cli() -> None:
+    """Typer entry point."""
+    typer.run(main)
+
+
+if __name__ == "__main__":
+    cli()