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235 | class SiliconFlowEmbedding(BaseEmbedding):
"""SiliconFlow class for embeddings."""
model: str = Field(
default="BAAI/bge-m3",
description="""\
The name of the embedding model to use.
512 tokens for all models input except `bge-m3` which is 8192.
""",
)
api_key: Optional[str] = Field(
default=None,
description="The SiliconFlow API key.",
)
base_url: str = Field(
default=DEFAULT_SILICONFLOW_API_URL,
description="The base URL for the SiliconFlow API.",
)
encoding_format: str = Field(
default="float",
description="The format to return the embeddings in. Can be either float or base64.",
) # TODO: Consider whether to fix the encoding format as float.
max_retries: int = Field(
default=3,
description="The maximum number of API retries.",
ge=0,
)
_headers: Any = PrivateAttr()
def __init__(
self,
model: str = "BAAI/bge-m3",
api_key: Optional[str] = None,
base_url: str = DEFAULT_SILICONFLOW_API_URL,
encoding_format: Optional[str] = "float",
max_retries: int = 3,
callback_manager: Optional[CallbackManager] = None,
**kwargs: Any,
) -> None:
super().__init__(
model=model,
api_key=api_key,
base_url=base_url,
encoding_format=encoding_format,
max_retries=max_retries,
callback_manager=callback_manager,
**kwargs,
)
assert (
self.encoding_format in VALID_ENCODING
), f"""\
Encoding_format parameter {self.encoding_format} not supported.
Please choose one of {VALID_ENCODING}".
"""
self._headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
}
@classmethod
def class_name(cls) -> str:
return "SiliconFlowEmbedding"
def _data_formatting(self, response: list) -> List[List[float]]:
results = sorted(response["data"], key=lambda e: e["index"])
if self.encoding_format == "base64":
return [base64_to_float_list(data["embedding"]) for data in results]
else:
return [data["embedding"] for data in results]
def _get_query_embedding(self, query: str) -> List[float]:
"""Get query embedding."""
return self._get_text_embeddings([query])[0]
async def _aget_query_embedding(self, query: str) -> List[float]:
"""The asynchronous version of _get_query_embedding."""
result = await self._aget_text_embeddings([query])
return result[0]
def _get_text_embedding(self, text: str) -> List[float]:
"""Get text embedding."""
return self._get_text_embeddings([text])[0]
async def _aget_text_embedding(self, text: str) -> List[float]:
"""Asynchronously get text embedding."""
result = await self._aget_text_embeddings([text])
return result[0]
@embedding_retry_decorator
def _get_text_embeddings(self, texts: List[str]) -> List[List[float]]:
with requests.Session() as session:
input_json = {
"model": self.model,
"input": texts,
"encoding_format": self.encoding_format,
}
response = session.post(
self.base_url, json=input_json, headers=self._headers
).json()
if "data" not in response:
raise RuntimeError(response)
return self._data_formatting(response)
@embedding_retry_decorator
async def _aget_text_embeddings(
self,
texts: List[str],
) -> List[List[float]]:
async with aiohttp.ClientSession() as session:
input_json = {
"input": texts,
"model": self.model,
"encoding_format": self.encoding_format,
}
async with session.post(
self.base_url, json=input_json, headers=self._headers
) as response:
response_json = await response.json()
response.raise_for_status()
return self._data_formatting(response_json)
|
