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import sys |
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if sys.version_info < (3, 9): |
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pass |
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else: |
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pass |
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import pipmaster as pm |
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if not pm.is_installed("lmdeploy"): |
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pm.install("lmdeploy") |
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from openai import ( |
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APIConnectionError, |
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RateLimitError, |
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APITimeoutError, |
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) |
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from tenacity import ( |
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retry, |
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stop_after_attempt, |
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wait_exponential, |
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retry_if_exception_type, |
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) |
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import numpy as np |
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import aiohttp |
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import base64 |
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import struct |
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@retry( |
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stop=stop_after_attempt(3), |
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wait=wait_exponential(multiplier=1, min=4, max=60), |
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retry=retry_if_exception_type( |
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(RateLimitError, APIConnectionError, APITimeoutError) |
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), |
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) |
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async def siliconcloud_embedding( |
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texts: list[str], |
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model: str = "netease-youdao/bce-embedding-base_v1", |
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base_url: str = "https://api.siliconflow.cn/v1/embeddings", |
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max_token_size: int = 512, |
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api_key: str = None, |
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) -> np.ndarray: |
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if api_key and not api_key.startswith("Bearer "): |
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api_key = "Bearer " + api_key |
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headers = {"Authorization": api_key, "Content-Type": "application/json"} |
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truncate_texts = [text[0:max_token_size] for text in texts] |
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payload = {"model": model, "input": truncate_texts, "encoding_format": "base64"} |
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base64_strings = [] |
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async with aiohttp.ClientSession() as session: |
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async with session.post(base_url, headers=headers, json=payload) as response: |
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content = await response.json() |
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if "code" in content: |
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raise ValueError(content) |
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base64_strings = [item["embedding"] for item in content["data"]] |
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embeddings = [] |
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for string in base64_strings: |
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decode_bytes = base64.b64decode(string) |
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n = len(decode_bytes) // 4 |
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float_array = struct.unpack("<" + "f" * n, decode_bytes) |
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embeddings.append(float_array) |
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return np.array(embeddings) |
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