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"""
Test Model on Multi-Bank Benchmark.
Author: Ranjit Behera
"""
import json
import subprocess
import sys
import re
from collections import defaultdict
MODEL_PATH = "models/base/phi3-finance-base"
ADAPTER_PATH = "models/adapters/finee-adapter-v1" # Updated for V1.0
BENCHMARK_FILE = "data/benchmark/multi_bank_comprehensive.jsonl" # Updated to generated file
def generate(prompt: str, adapter_path: str = ADAPTER_PATH) -> str:
cmd = [
sys.executable, "-m", "mlx_lm.generate",
"--model", MODEL_PATH,
"--adapter-path", adapter_path,
"--prompt", prompt,
"--max-tokens", "200"
]
try:
result = subprocess.run(cmd, capture_output=True, text=True, timeout=120)
return result.stdout
except Exception as e:
return f"Error: {e}"
def parse_json_from_output(output: str) -> dict:
try:
match = re.search(r'\{[^{}]+\}', output, re.DOTALL)
if match:
return json.loads(match.group())
except:
pass
return {}
def normalize(val: str) -> str:
if not val:
return ''
val = str(val).lower().strip()
val = val.replace(',', '').replace('.00', '').rstrip('0').rstrip('.')
return val
def run_test(limit: int = None, adapter_path: str = ADAPTER_PATH):
print("=" * 70)
print("🧪 MULTI-BANK BENCHMARK TEST - v1.0")
print("=" * 70)
# Handle JSONL format (lines of JSON)
benchmark = []
try:
with open(BENCHMARK_FILE) as f:
if BENCHMARK_FILE.endswith('.jsonl'):
for line in f:
if line.strip():
benchmark.append(json.loads(line))
else:
benchmark = json.load(f)
except FileNotFoundError:
print(f"Benchmark file not found: {BENCHMARK_FILE}")
return
if limit:
benchmark = benchmark[:limit]
print(f"Testing {len(benchmark)} samples across multiple banks...")
field_stats = defaultdict(lambda: {'correct': 0, 'total': 0})
bank_stats = defaultdict(lambda: {'correct': 0, 'total': 0, 'fields_correct': 0, 'fields_total': 0})
for i, sample in enumerate(benchmark):
# Handle difference between generation format and test format if any
# The generator produces: "prompt", "completion", "bank", "txn_type"
# The old benchmark expected: "text", "expected_entities"
if 'prompt' in sample and 'completion' in sample:
# Parse completion JSON string to dict
try:
expected = json.loads(sample['completion'])
except:
expected = sample['completion']
# Extract text from prompt (it's embedded in the prompt string)
# The prompt format is: ...\n\n{email_text}\n\n...
# A simple way is to use the raw text if available, but here we only have prompt.
# We can pass the prompt DIRECTLY to the model if we trained on it!
# BUT wait, generate() appends its own prompt template?
# No, mlx_lm.generate takes a prompt.
# If we pass sample['prompt'], it's the FULL prompt including "Output JSON:".
prompt = sample['prompt']
# For reporting/debugging, we want the bank name
bank = sample.get('bank', 'unknown')
else:
# Fallback to old format
text = sample['text']
expected = sample['expected_entities']
bank = expected.get('bank', 'unknown')
prompt = f"""Extract financial entities from this {bank.upper()} Bank email:
{text[:500]}
Extract: amount, type, date, account, reference, merchant
Output JSON:"""
output = generate(prompt, adapter_path)
predicted = parse_json_from_output(output)
sample_correct = 0
sample_total = 0
# Define fields to check
fields_to_check = ['amount', 'type', 'date', 'account', 'reference']
if 'merchant' in expected: fields_to_check.append('merchant')
for field in fields_to_check:
exp_val = normalize(expected.get(field, ''))
pred_val = normalize(predicted.get(field, ''))
if exp_val:
field_stats[field]['total'] += 1
bank_stats[bank]['fields_total'] += 1
sample_total += 1
if exp_val == pred_val:
field_stats[field]['correct'] += 1
bank_stats[bank]['fields_correct'] += 1
sample_correct += 1
# Track bank-level (all fields match)
bank_stats[bank]['total'] += 1
if sample_total > 0 and sample_correct == sample_total:
bank_stats[bank]['correct'] += 1
if (i + 1) % 10 == 0:
print(f" Processed {i + 1}/{len(benchmark)}...")
print()
print("=" * 70)
print("📈 RESULTS BY FIELD")
print("=" * 70)
total_correct = 0
total_fields = 0
for field in sorted(field_stats.keys()):
stats = field_stats[field]
acc = stats['correct'] / stats['total'] * 100 if stats['total'] > 0 else 0
status = "✅" if acc >= 90 else "⚠️" if acc >= 70 else "❌"
print(f" {field:12} {stats['correct']:3}/{stats['total']:3} = {acc:5.1f}% {status}")
total_correct += stats['correct']
total_fields += stats['total']
overall = total_correct / total_fields * 100 if total_fields > 0 else 0
print(f"\n {'OVERALL':12} {total_correct:3}/{total_fields:3} = {overall:5.1f}%")
print()
print("=" * 70)
print("📈 RESULTS BY BANK (Field-Level Accuracy)")
print("=" * 70)
for bank in sorted(bank_stats.keys()):
stats = bank_stats[bank]
field_acc = stats['fields_correct'] / stats['fields_total'] * 100 if stats['fields_total'] > 0 else 0
# full_acc = stats['correct'] / stats['total'] * 100 if stats['total'] > 0 else 0
status = "✅" if field_acc >= 90 else "⚠️" if field_acc >= 70 else "❌"
print(f" {bank.upper():10} Fields: {stats['fields_correct']:3}/{stats['fields_total']:3} = {field_acc:5.1f}% | Full Match: {stats['correct']}/{stats['total']} {status}")
print("=" * 70)
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--limit', type=int, default=40, help='Number of samples')
parser.add_argument('--adapter', type=str, default=ADAPTER_PATH, help='Adapter path')
args = parser.parse_args()
run_test(limit=args.limit, adapter_path=args.adapter)
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