Files
LangBot/src/langbot/pkg/provider/modelmgr/requesters/seekdbembed.py
Junyan Qin (Chin) fc6e414be4 feat: add GitHub Actions workflow for linting with Ruff (#1929)
* feat: add GitHub Actions workflow for linting with Ruff

* refactor: rename lint job and add formatting step to Ruff workflow

* chore: run ruff format

* chore: rename Ruff lint job to 'Lint' and add frontend linting workflow
2026-01-23 13:43:12 +08:00

61 lines
1.8 KiB
Python

from __future__ import annotations
import typing
from .. import requester
REQUESTER_NAME: str = 'seekdb-embedding'
class SeekDBEmbedding(requester.ProviderAPIRequester):
"""SeekDB built-in embedding requester.
Uses pyseekdb's local embedding function (all-MiniLM-L6-v2).
The base_url config is reserved for future remote embedding support.
"""
default_config: dict[str, typing.Any] = {
'base_url': '',
}
_embedding_function = None
async def initialize(self):
try:
import pyseekdb
except ImportError:
raise ImportError('pyseekdb is not installed. Install it with: pip install pyseekdb')
self._embedding_function = pyseekdb.get_default_embedding_function()
async def invoke_llm(
self,
query,
model: requester.RuntimeLLMModel,
messages: typing.List,
funcs: typing.List = None,
extra_args: dict[str, typing.Any] = {},
remove_think: bool = False,
):
raise NotImplementedError('SeekDB embedding does not support LLM inference')
async def invoke_embedding(
self,
model: requester.RuntimeEmbeddingModel,
input_text: typing.List[str],
extra_args: dict[str, typing.Any] = {},
) -> typing.List[typing.List[float]]:
"""Generate embeddings using SeekDB's built-in embedding function."""
try:
if self._embedding_function is None:
await self.initialize()
if self._embedding_function is None:
raise RuntimeError('SeekDB embedding function initialization failed')
return self._embedding_function(input_text)
except Exception as e:
from .. import errors
raise errors.RequesterError(f'SeekDB embedding failed: {str(e)}')