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PlantAI-rag-new/vstore/embed.py
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"""embed.py —— ollama 嵌入调用封装(httpx,并发 ≤8,bge-m3 1024 维)。
- embed_batch(texts):同步函数,分批并发调 POST {url}/api/embed
- 空文本返回零向量;维度不符抛 EmbedError
- 单元测试注入假 embed(monkeypatch),本模块不依赖真 ollama
"""
from __future__ import annotations
import logging
from concurrent.futures import ThreadPoolExecutor
import httpx
from .settings import (
DEFAULT_EMBED_MODEL,
DEFAULT_EMBED_URL,
EMBED_CONCURRENCY,
EMBED_DIM,
EMBED_TIMEOUT,
get_paths,
)
logger = logging.getLogger(__name__)
class EmbedError(Exception):
"""嵌入调用失败(服务不可达/维度不符/响应异常)。"""
def _zero_vector() -> list[float]:
return [0.0] * EMBED_DIM
def _request_one(client: httpx.Client, url: str, model: str, text: str) -> list[float]:
"""单条嵌入请求。空文本返回零向量(不打上游)。"""
if not text or not text.strip():
return _zero_vector()
try:
resp = client.post(
f"{url.rstrip('/')}/api/embed",
json={"model": model, "input": text},
timeout=EMBED_TIMEOUT,
)
resp.raise_for_status()
payload = resp.json()
embeddings = payload.get("embeddings")
if not embeddings or not isinstance(embeddings[0], list):
raise EmbedError(f"嵌入响应形态异常:{str(payload)[:200]}")
vector = [float(v) for v in embeddings[0]]
if len(vector) != EMBED_DIM:
raise EmbedError(f"嵌入维度不符:期望 {EMBED_DIM},实际 {len(vector)}")
return vector
except EmbedError:
raise
except (httpx.HTTPError, ValueError) as exc:
raise EmbedError(f"嵌入服务调用失败:{exc}") from exc
def embed_batch(
texts: list[str],
url: str | None = None,
model: str | None = None,
) -> list[list[float]]:
"""批量嵌入:线程池并发 ≤ EMBED_CONCURRENCY,保持输入顺序。
url/model 缺省取 settings(VSTORE_EMBED_URL / VSTORE_EMBED_MODEL)。
"""
if not texts:
return []
paths = get_paths()
base_url = url or paths.embed_url or DEFAULT_EMBED_URL
model_name = model or paths.embed_model or DEFAULT_EMBED_MODEL
results: list[list[float] | None] = [None] * len(texts)
with httpx.Client() as client:
with ThreadPoolExecutor(max_workers=EMBED_CONCURRENCY) as pool:
futures = {
pool.submit(_request_one, client, base_url, model_name, text): idx
for idx, text in enumerate(texts)
}
for future in futures:
idx = futures[future]
try:
results[idx] = future.result()
except EmbedError as exc:
logger.warning("embed: 第 %d 条嵌入失败:%s", idx, exc)
results[idx] = None
except Exception as exc: # 线程池其他异常也降级为零向量
logger.warning("embed: 第 %d 条嵌入异常:%s", idx, exc)
results[idx] = None
return [v if v is not None else _zero_vector() for v in results]