101 lines
2.9 KiB
Python
101 lines
2.9 KiB
Python
"""
|
|
Ollama Embedding客户端
|
|
调用Ollama的OpenAI兼容API获取文本向量表示
|
|
"""
|
|
import time
|
|
from typing import List
|
|
|
|
import numpy as np
|
|
import requests
|
|
|
|
|
|
class OllamaEmbedder:
|
|
"""
|
|
基于Ollama部署的Embedding模型客户端
|
|
默认使用 quentinz/bge-large-zh-v1.5 (中文向量模型)
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
base_url: str = "http://192.168.1.250:11434",
|
|
model: str = "quentinz/bge-large-zh-v1.5",
|
|
timeout: int = 180,
|
|
):
|
|
"""
|
|
参数：
|
|
base_url: Ollama服务地址
|
|
model: Embedding模型名称
|
|
timeout: 请求超时时间（秒）
|
|
"""
|
|
self.base_url = base_url.rstrip("/")
|
|
self.model = model
|
|
self.timeout = timeout
|
|
self.endpoint = f"{self.base_url}/v1/embeddings"
|
|
|
|
print(f"[OllamaEmbedder] Initialized url={self.endpoint} model={model}")
|
|
|
|
def encode(self, texts: List[str]) -> np.ndarray:
|
|
"""
|
|
将文本列表编码为向量
|
|
|
|
参数：
|
|
texts: 待编码的文本列表
|
|
|
|
返回：
|
|
shape为(len(texts), embedding_dim)的numpy数组
|
|
"""
|
|
if not texts:
|
|
return np.array([])
|
|
|
|
t0 = time.time()
|
|
print(f"[OllamaEmbedder] Encoding {len(texts)} texts...")
|
|
|
|
payload = {
|
|
"model": self.model,
|
|
"input": texts,
|
|
}
|
|
|
|
try:
|
|
resp = requests.post(
|
|
self.endpoint,
|
|
json=payload,
|
|
timeout=self.timeout
|
|
)
|
|
dt = time.time() - t0
|
|
|
|
if resp.status_code != 200:
|
|
print(f"[OllamaEmbedder] Error status={resp.status_code} body={resp.text[:200]}")
|
|
resp.raise_for_status()
|
|
|
|
data = resp.json()
|
|
|
|
# 解析OpenAI格式的响应: {"data": [{"embedding": [...]}, ...]}
|
|
if "data" not in data:
|
|
raise RuntimeError(f"Unexpected response format: {data}")
|
|
|
|
embeddings = []
|
|
for item in data["data"]:
|
|
if "embedding" not in item:
|
|
raise RuntimeError(f"Missing 'embedding' in response item: {item}")
|
|
embeddings.append(item["embedding"])
|
|
|
|
result = np.array(embeddings, dtype=np.float32)
|
|
print(f"[OllamaEmbedder] Success shape={result.shape} elapsed={dt:.2f}s")
|
|
|
|
return result
|
|
|
|
except Exception as e:
|
|
dt = time.time() - t0
|
|
print(f"[OllamaEmbedder] Failed after {dt:.2f}s: {e}")
|
|
raise
|
|
|
|
def encode_single(self, text: str) -> np.ndarray:
|
|
"""
|
|
编码单个文本（便捷方法）
|
|
|
|
返回：
|
|
shape为(embedding_dim,)的1D数组
|
|
"""
|
|
result = self.encode([text])
|
|
return result[0] if len(result) > 0 else np.array([])
|