read.markets/app/services/llm_csv_parser.py
Giorgio Gilestro f8a0ed3923 csv-parser: add _fingerprint helper
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-27 12:08:34 +02:00

42 lines
1.6 KiB
Python

"""LLM-fallback CSV parser.
When the deterministic Trading 212 parser (``csv_import.parse_t212_csv``)
raises ``CSVImportError`` on an unrecognised format, this service kicks
in:
1. Detect the CSV dialect (delimiter, preamble offset).
2. Compute a fingerprint of the normalised header row.
3. Look up ``CsvFormatTemplate`` by fingerprint. On hit, replay the
cached column-mapping deterministically. On miss, ask the LLM for a
mapping, validate it, persist a new template, and apply it.
The LLM sees only headers + the first 3-5 sample rows. It returns a
column-mapping JSON, never transcribed numbers. The system never
auto-promotes a learned format to a hand-written parser — the operator
does that by inspecting collected ``sample_row`` values.
"""
from __future__ import annotations
import hashlib
from app.services.csv_import import CSVImportError
class LLMParseError(CSVImportError):
"""Raised when the LLM call fails or returns an unusable mapping.
Inherits from ``CSVImportError`` so route-level error handling can
treat both deterministic and LLM-path failures uniformly when
desired."""
def _fingerprint(headers: list[str]) -> str:
"""Stable hash of the header row.
Lowercases each header, strips surrounding whitespace, joins with
``|`` (a character extremely unlikely to appear inside a real
header), and returns the sha256 hex digest. Whitespace/case drift
in the same broker's export does not change the fingerprint;
adding or removing a column does."""
normalised = "|".join(h.strip().lower() for h in headers)
return hashlib.sha256(normalised.encode("utf-8")).hexdigest()