Files
danswer/backend/shared_configs/model_server_models.py
Chris Weaver dc542fd7fa Enable default quantization (#4815)
* Adjust migration

* update default in form

* Add cloud indices for bfloat16

* Update backend/shared_configs/configs.py

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

* Update vespa schema gen script

* Move embedding configs

* Remove unused imports

* remove import from shared configs

* Remove unused model

---------

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
2025-06-05 14:02:08 -07:00

88 lines
2.3 KiB
Python

from pydantic import BaseModel
from shared_configs.enums import EmbeddingProvider
from shared_configs.enums import EmbedTextType
from shared_configs.enums import RerankerProvider
Embedding = list[float]
class ConnectorClassificationRequest(BaseModel):
available_connectors: list[str]
query: str
class ConnectorClassificationResponse(BaseModel):
connectors: list[str]
class EmbedRequest(BaseModel):
texts: list[str]
# Can be none for cloud embedding model requests, error handling logic exists for other cases
model_name: str | None = None
deployment_name: str | None = None
max_context_length: int
normalize_embeddings: bool
api_key: str | None = None
provider_type: EmbeddingProvider | None = None
text_type: EmbedTextType
manual_query_prefix: str | None = None
manual_passage_prefix: str | None = None
api_url: str | None = None
api_version: str | None = None
# allows for the truncation of the vector to a lower dimension
# to reduce memory usage. Currently only supported for OpenAI models.
# will be ignored for other providers.
reduced_dimension: int | None = None
# This disables the "model_" protected namespace for pydantic
model_config = {"protected_namespaces": ()}
class EmbedResponse(BaseModel):
embeddings: list[Embedding]
class RerankRequest(BaseModel):
query: str
documents: list[str]
model_name: str
provider_type: RerankerProvider | None = None
api_key: str | None = None
api_url: str | None = None
# This disables the "model_" protected namespace for pydantic
model_config = {"protected_namespaces": ()}
class RerankResponse(BaseModel):
scores: list[float]
class IntentRequest(BaseModel):
query: str
# Sequence classification threshold
semantic_percent_threshold: float
# Token classification threshold
keyword_percent_threshold: float
class IntentResponse(BaseModel):
is_keyword: bool
keywords: list[str]
class InformationContentClassificationRequests(BaseModel):
queries: list[str]
class ContentClassificationPrediction(BaseModel):
predicted_label: int
content_boost_factor: float
class InformationContentClassificationResponses(BaseModel):
information_content_classifications: list[ContentClassificationPrediction]