feat(US1): text triple extraction — POST /api/v1/text/extract

- app/models/text_models.py: TripleItem, SourceOffset, TextExtract{Request,Response}
- app/services/text_service.py: TXT/PDF/DOCX parsing + LLM call + JSON parse
- app/routers/text.py: POST /text/extract handler with Depends injection
- tests/test_text_service.py: 6 unit tests (formats, errors)
- tests/test_text_router.py: 4 router tests (200, 400, 502×2)
- 10/10 tests passing
This commit is contained in:
wh
2026-04-10 15:27:27 +08:00
parent e1eb5e47b1
commit dd8da386f4
18 changed files with 321 additions and 1 deletions

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app/models/text_models.py Normal file
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from pydantic import BaseModel
class SourceOffset(BaseModel):
start: int
end: int
class TripleItem(BaseModel):
subject: str
predicate: str
object: str
source_snippet: str
source_offset: SourceOffset
class TextExtractRequest(BaseModel):
file_path: str
file_name: str
model: str | None = None
prompt_template: str | None = None
class TextExtractResponse(BaseModel):
items: list[TripleItem]

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from fastapi import APIRouter
from fastapi import APIRouter, Depends
from app.clients.llm.base import LLMClient
from app.clients.storage.base import StorageClient
from app.core.dependencies import get_llm_client, get_storage_client
from app.models.text_models import TextExtractRequest, TextExtractResponse
from app.services import text_service
router = APIRouter(tags=["Text"])
@router.post("/text/extract", response_model=TextExtractResponse)
async def extract_text(
req: TextExtractRequest,
llm: LLMClient = Depends(get_llm_client),
storage: StorageClient = Depends(get_storage_client),
) -> TextExtractResponse:
return await text_service.extract_triples(req, llm, storage)

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import io
import pdfplumber
import docx
from app.clients.llm.base import LLMClient
from app.clients.storage.base import StorageClient
from app.core.config import get_config
from app.core.exceptions import UnsupportedFileTypeError
from app.core.json_utils import extract_json
from app.core.logging import get_logger
from app.models.text_models import (
SourceOffset,
TextExtractRequest,
TextExtractResponse,
TripleItem,
)
logger = get_logger(__name__)
_SUPPORTED_EXTENSIONS = {".txt", ".pdf", ".docx"}
_DEFAULT_PROMPT = (
"请从以下文本中提取知识三元组,以 JSON 数组格式返回,每条包含字段:"
"subject主语、predicate谓语、object宾语"
"source_snippet原文证据片段、source_offset{{start, end}} 字符偏移)。\n\n"
"文本内容:\n{text}"
)
def _file_extension(file_name: str) -> str:
idx = file_name.rfind(".")
return file_name[idx:].lower() if idx != -1 else ""
def _parse_txt(data: bytes) -> str:
return data.decode("utf-8", errors="replace")
def _parse_pdf(data: bytes) -> str:
with pdfplumber.open(io.BytesIO(data)) as pdf:
pages = [page.extract_text() or "" for page in pdf.pages]
return "\n".join(pages)
def _parse_docx(data: bytes) -> str:
doc = docx.Document(io.BytesIO(data))
return "\n".join(p.text for p in doc.paragraphs)
async def extract_triples(
req: TextExtractRequest,
llm: LLMClient,
storage: StorageClient,
) -> TextExtractResponse:
ext = _file_extension(req.file_name)
if ext not in _SUPPORTED_EXTENSIONS:
raise UnsupportedFileTypeError(f"不支持的文件格式: {ext}")
cfg = get_config()
bucket = cfg["storage"]["buckets"]["source_data"]
model = req.model or cfg["models"]["default_text"]
data = await storage.download_bytes(bucket, req.file_path)
if ext == ".txt":
text = _parse_txt(data)
elif ext == ".pdf":
text = _parse_pdf(data)
else:
text = _parse_docx(data)
prompt_template = req.prompt_template or _DEFAULT_PROMPT
prompt = prompt_template.format(text=text) if "{text}" in prompt_template else prompt_template + "\n\n" + text
messages = [{"role": "user", "content": prompt}]
raw = await llm.chat(model, messages)
logger.info("text_extract", extra={"file": req.file_name, "model": model})
items_raw = extract_json(raw)
items = [
TripleItem(
subject=item["subject"],
predicate=item["predicate"],
object=item["object"],
source_snippet=item["source_snippet"],
source_offset=SourceOffset(
start=item["source_offset"]["start"],
end=item["source_offset"]["end"],
),
)
for item in items_raw
]
return TextExtractResponse(items=items)

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tests/test_text_router.py Normal file
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import pytest
from unittest.mock import AsyncMock
SAMPLE_TRIPLES_JSON = '''[
{
"subject": "变压器",
"predicate": "额定电压",
"object": "110kV",
"source_snippet": "该变压器额定电压为110kV",
"source_offset": {"start": 0, "end": 12}
}
]'''
def test_text_extract_returns_200(client, mock_llm, mock_storage):
mock_storage.download_bytes = AsyncMock(return_value=b"some text content")
mock_llm.chat = AsyncMock(return_value=SAMPLE_TRIPLES_JSON)
resp = client.post(
"/api/v1/text/extract",
json={"file_path": "text/test.txt", "file_name": "test.txt"},
)
assert resp.status_code == 200
data = resp.json()
assert "items" in data
assert data["items"][0]["subject"] == "变压器"
assert data["items"][0]["source_offset"]["start"] == 0
def test_text_extract_unsupported_format_returns_400(client, mock_storage):
mock_storage.download_bytes = AsyncMock(return_value=b"data")
resp = client.post(
"/api/v1/text/extract",
json={"file_path": "text/test.xlsx", "file_name": "data.xlsx"},
)
assert resp.status_code == 400
assert resp.json()["code"] == "UNSUPPORTED_FILE_TYPE"
def test_text_extract_storage_error_returns_502(client, mock_llm, mock_storage):
from app.core.exceptions import StorageError
mock_storage.download_bytes = AsyncMock(side_effect=StorageError("RustFS unreachable"))
resp = client.post(
"/api/v1/text/extract",
json={"file_path": "text/test.txt", "file_name": "test.txt"},
)
assert resp.status_code == 502
assert resp.json()["code"] == "STORAGE_ERROR"
def test_text_extract_llm_parse_error_returns_502(client, mock_llm, mock_storage):
mock_storage.download_bytes = AsyncMock(return_value=b"content")
mock_llm.chat = AsyncMock(return_value="not json {{{{")
resp = client.post(
"/api/v1/text/extract",
json={"file_path": "text/test.txt", "file_name": "test.txt"},
)
assert resp.status_code == 502
assert resp.json()["code"] == "LLM_PARSE_ERROR"

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tests/test_text_service.py Normal file
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import pytest
from unittest.mock import AsyncMock, MagicMock
from app.core.exceptions import LLMParseError, StorageError, UnsupportedFileTypeError
from app.models.text_models import TextExtractRequest
SAMPLE_TRIPLES_JSON = '''[
{
"subject": "变压器",
"predicate": "额定电压",
"object": "110kV",
"source_snippet": "该变压器额定电压为110kV",
"source_offset": {"start": 0, "end": 12}
}
]'''
@pytest.fixture
def req_txt():
return TextExtractRequest(file_path="text/test.txt", file_name="test.txt")
@pytest.fixture
def req_pdf():
return TextExtractRequest(file_path="text/test.pdf", file_name="report.pdf")
@pytest.fixture
def req_docx():
return TextExtractRequest(file_path="text/test.docx", file_name="doc.docx")
@pytest.fixture
def llm(mock_llm):
mock_llm.chat = AsyncMock(return_value=SAMPLE_TRIPLES_JSON)
return mock_llm
@pytest.mark.asyncio
async def test_txt_extraction_returns_triples(llm, mock_storage):
mock_storage.download_bytes = AsyncMock(return_value=b"test content")
from app.services.text_service import extract_triples
req = TextExtractRequest(file_path="text/test.txt", file_name="test.txt")
result = await extract_triples(req, llm, mock_storage)
assert len(result.items) == 1
assert result.items[0].subject == "变压器"
assert result.items[0].predicate == "额定电压"
assert result.items[0].object == "110kV"
assert result.items[0].source_offset.start == 0
assert result.items[0].source_offset.end == 12
@pytest.mark.asyncio
async def test_pdf_extraction(llm, mock_storage, tmp_path):
import pdfplumber, io
# We mock download_bytes to return a minimal PDF-like response
# and mock pdfplumber.open to return pages with text
mock_storage.download_bytes = AsyncMock(return_value=b"%PDF fake")
with pytest.MonkeyPatch().context() as mp:
mock_page = MagicMock()
mock_page.extract_text.return_value = "PDF content here"
mock_pdf = MagicMock()
mock_pdf.__enter__ = lambda s: s
mock_pdf.__exit__ = MagicMock(return_value=False)
mock_pdf.pages = [mock_page]
mp.setattr("pdfplumber.open", lambda f: mock_pdf)
from app.services import text_service
import importlib
importlib.reload(text_service)
req = TextExtractRequest(file_path="text/test.pdf", file_name="doc.pdf")
result = await text_service.extract_triples(req, llm, mock_storage)
assert len(result.items) == 1
@pytest.mark.asyncio
async def test_docx_extraction(llm, mock_storage):
mock_storage.download_bytes = AsyncMock(return_value=b"PK fake docx bytes")
with pytest.MonkeyPatch().context() as mp:
mock_para = MagicMock()
mock_para.text = "Word paragraph content"
mock_doc = MagicMock()
mock_doc.paragraphs = [mock_para]
mp.setattr("docx.Document", lambda f: mock_doc)
from app.services import text_service
import importlib
importlib.reload(text_service)
req = TextExtractRequest(file_path="text/test.docx", file_name="doc.docx")
result = await text_service.extract_triples(req, llm, mock_storage)
assert len(result.items) == 1
@pytest.mark.asyncio
async def test_unsupported_format_raises_error(llm, mock_storage):
mock_storage.download_bytes = AsyncMock(return_value=b"data")
from app.services.text_service import extract_triples
req = TextExtractRequest(file_path="text/test.xlsx", file_name="data.xlsx")
with pytest.raises(UnsupportedFileTypeError):
await extract_triples(req, llm, mock_storage)
@pytest.mark.asyncio
async def test_storage_error_propagates(llm, mock_storage):
mock_storage.download_bytes = AsyncMock(side_effect=StorageError("not found"))
from app.services.text_service import extract_triples
req = TextExtractRequest(file_path="text/test.txt", file_name="test.txt")
with pytest.raises(StorageError):
await extract_triples(req, llm, mock_storage)
@pytest.mark.asyncio
async def test_llm_parse_error_propagates(mock_llm, mock_storage):
mock_storage.download_bytes = AsyncMock(return_value=b"content")
mock_llm.chat = AsyncMock(return_value="not json {{")
from app.services.text_service import extract_triples
req = TextExtractRequest(file_path="text/test.txt", file_name="test.txt")
with pytest.raises(LLMParseError):
await extract_triples(req, mock_llm, mock_storage)