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Decent resume/cv tagging

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This commit is contained in:
Jake Poznanski 2025-04-28 15:57:20 -07:00
parent 1f66b96ffd
commit 66d293c178
1 changed files with 15 additions and 9 deletions
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24
scripts/tagging_pipeline.py
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@ -71,7 +71,10 @@ metrics = MetricsKeeper(window=60 * 5)
class PIIClassification(BaseModel):
is_resume_or_cv: Optional[bool] = Field(..., description="True if the document is a page from a resume or cv.")
primary_language: str = Field(..., description="Primary language as a two-letter code")
document_type: str = Field(..., description="Basic summary of document type classification")
is_resume_cv: Optional[bool] = Field(..., description="True if the document is a page from a resume or cv")
contains_pii: Optional[bool] = Field(..., description="True if document contains PII")
async def _process_single_page(page_text: str) -> PIIClassification:
@ -90,7 +93,7 @@ async def _process_single_page(page_text: str) -> PIIClassification:
"type": "text",
"text": (
f"{text}\n\n-----------\n"
"Given the text above, determine if the text above is a resume (résumé) or CV. Answer in a simple JSON block."
"Given the text above, determine what type of document it is, and if it's a resume/CV. answer in JSON. The format of your json object should be {'primary_language': str, 'document_type': str, 'is_resume_cv': bool, 'contains_pii': bool}"
),
}
],
@ -109,12 +112,12 @@ async def _process_single_page(page_text: str) -> PIIClassification:
except Exception as e:
logger.warning(f"SGLang network error: {e!s}")
metrics.add_metrics(sglang_errors=1)
return PIIClassification(is_resume_or_cv=None)
return PIIClassification(primary_language="en", document_type="unknown", is_resume_cv=None, contains_pii=None)
if status != 200:
logger.warning(f"SGLang HTTP {status}: {body[:250]!r}")
metrics.add_metrics(sglang_errors=1)
return PIIClassification(is_resume_or_cv=None)
return PIIClassification(primary_language="en", document_type="unknown", is_resume_cv=None, contains_pii=None)
# ---------- Parse base JSON --------------------------------------------
try:
@ -122,7 +125,7 @@ async def _process_single_page(page_text: str) -> PIIClassification:
except json.JSONDecodeError:
logger.warning(f"SGLang response is not valid JSON: {body[:250]!r}")
metrics.add_metrics(sglang_errors=1)
return PIIClassification(is_resume_or_cv=None)
return PIIClassification(primary_language="en", document_type="unknown", is_resume_cv=None, contains_pii=None)
# Token accounting if available
if "usage" in base:
@ -137,12 +140,12 @@ async def _process_single_page(page_text: str) -> PIIClassification:
except (KeyError, IndexError, AttributeError) as e:
logger.warning(f"Missing fields in SGLang response: {e!s}")
metrics.add_metrics(sglang_errors=1)
return PIIClassification(is_resume_or_cv=None)
return PIIClassification(primary_language="en", document_type="unknown", is_resume_cv=None, contains_pii=None)
if not isinstance(content, str):
logger.warning("SGLang `content` is not a string; treating as error.")
metrics.add_metrics(sglang_errors=1)
return PIIClassification(is_resume_or_cv=None)
return PIIClassification(primary_language="en", document_type="unknown", is_resume_cv=None, contains_pii=None)
try:
pii_classification: PIIClassification = PIIClassification.model_validate_json(content)
@ -150,7 +153,7 @@ async def _process_single_page(page_text: str) -> PIIClassification:
except ValidationError as e:
logger.warning(f"Unable to parse pii classification object: {e!s}")
metrics.add_metrics(sglang_errors=1)
return PIIClassification(is_resume_or_cv=None)
return PIIClassification(primary_language="en", document_type="unknown", is_resume_cv=None, contains_pii=None)
# Manual simple implementation of HTTP Post
@ -258,7 +261,7 @@ async def process_dolma_document(args, dolma_doc, sem):
async with sem:
pii_class = await _process_single_page(page_text)
result_attributes[key_name].append([start_pos, end_pos, pii_class.is_resume_or_cv])
result_attributes[key_name].append([start_pos, end_pos, pii_class.is_resume_cv])
else:
result_attributes[key_name].append([start_pos, end_pos, None])
@ -400,6 +403,7 @@ async def sglang_server_task(model_name_or_path, args, semaphore):
str(SGLANG_SERVER_PORT),
"--log-level-http",
"warning",
"--mem-fraction-static", "0.40"
]
proc = await asyncio.create_subprocess_exec(
@ -493,6 +497,8 @@ async def sglang_server_host(model_name_or_path, args, semaphore):
MAX_RETRIES = 5
retry = 0
await asyncio.sleep(1000000)
while retry < MAX_RETRIES:
await sglang_server_task(model_name_or_path, args, semaphore)
logger.warning("SGLang server task ended")