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152 | class OllamaEmbedding(BaseEmbedding):
"""Class for Ollama embeddings."""
base_url: str = Field(description="Base url the model is hosted by Ollama")
model_name: str = Field(description="The Ollama model to use.")
embed_batch_size: int = Field(
default=DEFAULT_EMBED_BATCH_SIZE,
description="The batch size for embedding calls.",
gt=0,
le=2048,
)
ollama_additional_kwargs: Dict[str, Any] = Field(
default_factory=dict, description="Additional kwargs for the Ollama API."
)
query_instruction: Optional[str] = Field(
default=None, description="Instruction to prepend to query text."
)
text_instruction: Optional[str] = Field(
default=None, description="Instruction to prepend to text."
)
keep_alive: Optional[Union[float, str]] = Field(
default="5m",
description="controls how long the model will stay loaded into memory following the request(default: 5m)",
)
_client: Client = PrivateAttr()
_async_client: AsyncClient = PrivateAttr()
def __init__(
self,
model_name: str,
base_url: str = "http://localhost:11434",
embed_batch_size: int = DEFAULT_EMBED_BATCH_SIZE,
ollama_additional_kwargs: Optional[Dict[str, Any]] = None,
query_instruction: Optional[str] = None,
text_instruction: Optional[str] = None,
callback_manager: Optional[CallbackManager] = None,
client_kwargs: Optional[Dict[str, Any]] = None,
keep_alive: Optional[Union[float, str]] = None,
**kwargs: Any,
) -> None:
super().__init__(
model_name=model_name,
base_url=base_url,
embed_batch_size=embed_batch_size,
ollama_additional_kwargs=ollama_additional_kwargs or {},
query_instruction=query_instruction,
text_instruction=text_instruction,
callback_manager=callback_manager,
keep_alive=keep_alive,
**kwargs,
)
client_kwargs = client_kwargs or {}
self._client = Client(host=self.base_url, **client_kwargs)
self._async_client = AsyncClient(host=self.base_url, **client_kwargs)
@classmethod
def class_name(cls) -> str:
return "OllamaEmbedding"
def _get_query_embedding(self, query: str) -> List[float]:
"""Get query embedding."""
formatted_query = self._format_query(query)
return self.get_general_text_embedding(formatted_query)
async def _aget_query_embedding(self, query: str) -> List[float]:
"""The asynchronous version of _get_query_embedding."""
formatted_query = self._format_query(query)
return await self.aget_general_text_embedding(formatted_query)
def _get_text_embedding(self, text: str) -> List[float]:
"""Get text embedding."""
formatted_text = self._format_text(text)
return self.get_general_text_embedding(formatted_text)
async def _aget_text_embedding(self, text: str) -> List[float]:
"""Asynchronously get text embedding."""
formatted_text = self._format_text(text)
return await self.aget_general_text_embedding(formatted_text)
def _get_text_embeddings(self, texts: List[str]) -> List[List[float]]:
"""Get text embeddings."""
formatted_texts = [self._format_text(text) for text in texts]
return self.get_general_text_embeddings(formatted_texts)
async def _aget_text_embeddings(self, texts: List[str]) -> List[List[float]]:
"""Asynchronously get text embeddings."""
formatted_texts = [self._format_text(text) for text in texts]
return await self.aget_general_text_embeddings(formatted_texts)
def get_general_text_embeddings(self, texts: List[str]) -> List[List[float]]:
"""Get Ollama embeddings."""
result = self._client.embed(
model=self.model_name,
input=texts,
options=self.ollama_additional_kwargs,
keep_alive=self.keep_alive,
)
return result.embeddings
async def aget_general_text_embeddings(self, texts: List[str]) -> List[List[float]]:
"""Asynchronously get Ollama embeddings."""
result = await self._async_client.embed(
model=self.model_name,
input=texts,
options=self.ollama_additional_kwargs,
keep_alive=self.keep_alive,
)
return result.embeddings
def get_general_text_embedding(self, texts: str) -> List[float]:
"""Get Ollama embedding."""
result = self._client.embed(
model=self.model_name,
input=texts,
options=self.ollama_additional_kwargs,
keep_alive=self.keep_alive,
)
return result.embeddings[0]
async def aget_general_text_embedding(self, prompt: str) -> List[float]:
"""Asynchronously get Ollama embedding."""
result = await self._async_client.embed(
model=self.model_name,
input=prompt,
options=self.ollama_additional_kwargs,
keep_alive=self.keep_alive,
)
return result.embeddings[0]
def _format_query(self, query: str) -> str:
"""Format query with instruction if provided."""
if self.query_instruction:
return f"{self.query_instruction.strip()} {query.strip()}".strip()
return query.strip()
def _format_text(self, text: str) -> str:
"""Format text with instruction if provided."""
if self.text_instruction:
return f"{self.text_instruction.strip()} {text.strip()}".strip()
return text.strip()
|