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feat: add voyage ai as a new model provider (#8747)
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@ -40,3 +40,4 @@
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- fireworks
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- mixedbread
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- nomic
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- voyage
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3 37 8 -2 4 -39 80 -83 170 -43 89 -84 162 -92 162 -7 0 -50 -76 -96 -170z
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-71 -60 -71 -93 0 -142 57 -142 164 0 44 5 60 25 85 47 55 136 65 184 20 30
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-28 35 -20 11 19 -19 31 -22 32 -82 32 -35 -1 -76 -7 -93 -14z"/><path d="M1955 230 l0 -170 91 0 c76 0 93 3 98 16 4 9 5 18 4 20 -2 1 -31 -1
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-66 -5 -34 -4 -64 -5 -67 -3 -3 3 -5 36 -5 73 l0 68 55 -6 c49 -5 55 -4 55 13
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0 17 -6 19 -55 16 l-55 -4 0 61 0 61 64 0 c48 0 65 4 70 15 4 13 -10 15 -92
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15 l-97 0 0 -170z"/></g></svg>
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After Width: | Height: | Size: 2.2 KiB |
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@ -0,0 +1,8 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<svg width="64px" height="64px" viewBox="0 0 64 64" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<title>voyage</title>
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<g id="voyage" stroke="none" stroke-width="1" fill="none" fill-rule="evenodd">
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<rect id="矩形" fill="#333333" x="0" y="0" width="64" height="64" rx="12"></rect>
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<path d="M12.1128004,51.4376727 C13.8950799,45.8316747 30.5922254,11.1847688 31.7178757,11.0009656 C32.6559176,10.8171624 45.5070913,36.9172188 51.9795803,52.2647871 C52.1671887,52.6323936 51.0415384,53 49.4468672,53 C47.2893709,53 46.5389374,52.540492 46.5389374,51.4376727 C46.5389374,49.967247 33.2187427,17.8935861 32.8435259,18.3530942 C32.0930924,19.3640118 19.3357228,48.5887229 18.8667019,50.5186566 C18.3038768,52.6323936 17.7410516,53 14.926926,53 C12.2066045,53 11.7375836,52.7242952 12.1128004,51.4376727 Z" id="路径" fill="#FFFFFF" transform="translate(32, 32) scale(1, -1) translate(-32, -32)"></path>
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</g>
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</svg>
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After Width: | Height: | Size: 1.0 KiB |
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model: rerank-1
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model_type: rerank
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model_properties:
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context_size: 8000
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model: rerank-lite-1
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model_type: rerank
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model_properties:
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context_size: 4000
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123
api/core/model_runtime/model_providers/voyage/rerank/rerank.py
Normal file
123
api/core/model_runtime/model_providers/voyage/rerank/rerank.py
Normal file
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from typing import Optional
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import httpx
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from core.model_runtime.entities.common_entities import I18nObject
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from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType
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from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult
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from core.model_runtime.errors.invoke import (
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InvokeAuthorizationError,
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InvokeBadRequestError,
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InvokeConnectionError,
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InvokeError,
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InvokeRateLimitError,
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InvokeServerUnavailableError,
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)
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from core.model_runtime.errors.validate import CredentialsValidateFailedError
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from core.model_runtime.model_providers.__base.rerank_model import RerankModel
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class VoyageRerankModel(RerankModel):
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"""
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Model class for Voyage rerank model.
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"""
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def _invoke(
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self,
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model: str,
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credentials: dict,
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query: str,
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docs: list[str],
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score_threshold: Optional[float] = None,
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top_n: Optional[int] = None,
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user: Optional[str] = None,
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) -> RerankResult:
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"""
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Invoke rerank model
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:param model: model name
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:param credentials: model credentials
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:param query: search query
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:param docs: docs for reranking
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:param score_threshold: score threshold
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:param top_n: top n documents to return
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:param user: unique user id
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:return: rerank result
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"""
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if len(docs) == 0:
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return RerankResult(model=model, docs=[])
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base_url = credentials.get("base_url", "https://api.voyageai.com/v1")
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base_url = base_url.removesuffix("/")
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try:
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response = httpx.post(
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base_url + "/rerank",
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json={"model": model, "query": query, "documents": docs, "top_k": top_n, "return_documents": True},
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headers={"Authorization": f"Bearer {credentials.get('api_key')}", "Content-Type": "application/json"},
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)
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response.raise_for_status()
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results = response.json()
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rerank_documents = []
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for result in results["data"]:
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rerank_document = RerankDocument(
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index=result["index"],
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text=result["document"],
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score=result["relevance_score"],
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)
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if score_threshold is None or result["relevance_score"] >= score_threshold:
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rerank_documents.append(rerank_document)
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return RerankResult(model=model, docs=rerank_documents)
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except httpx.HTTPStatusError as e:
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raise InvokeServerUnavailableError(str(e))
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def validate_credentials(self, model: str, credentials: dict) -> None:
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"""
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Validate model credentials
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:param model: model name
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:param credentials: model credentials
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:return:
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"""
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try:
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self._invoke(
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model=model,
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credentials=credentials,
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query="What is the capital of the United States?",
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docs=[
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"Carson City is the capital city of the American state of Nevada. At the 2010 United States "
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"Census, Carson City had a population of 55,274.",
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"The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that "
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"are a political division controlled by the United States. Its capital is Saipan.",
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],
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score_threshold=0.8,
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)
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except Exception as ex:
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raise CredentialsValidateFailedError(str(ex))
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@property
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def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
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"""
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Map model invoke error to unified error
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"""
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return {
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InvokeConnectionError: [httpx.ConnectError],
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InvokeServerUnavailableError: [httpx.RemoteProtocolError],
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InvokeRateLimitError: [],
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InvokeAuthorizationError: [httpx.HTTPStatusError],
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InvokeBadRequestError: [httpx.RequestError],
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}
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def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity:
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"""
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generate custom model entities from credentials
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"""
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entity = AIModelEntity(
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model=model,
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label=I18nObject(en_US=model),
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model_type=ModelType.RERANK,
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fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
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model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", "8000"))},
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)
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return entity
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import time
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from json import JSONDecodeError, dumps
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from typing import Optional
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import requests
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from core.embedding.embedding_constant import EmbeddingInputType
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from core.model_runtime.entities.common_entities import I18nObject
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from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType
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from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
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from core.model_runtime.errors.invoke import (
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InvokeAuthorizationError,
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InvokeBadRequestError,
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InvokeConnectionError,
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InvokeError,
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InvokeRateLimitError,
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InvokeServerUnavailableError,
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)
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from core.model_runtime.errors.validate import CredentialsValidateFailedError
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from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
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class VoyageTextEmbeddingModel(TextEmbeddingModel):
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"""
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Model class for Voyage text embedding model.
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"""
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api_base: str = "https://api.voyageai.com/v1"
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def _invoke(
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self,
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model: str,
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credentials: dict,
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texts: list[str],
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user: Optional[str] = None,
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input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT,
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) -> TextEmbeddingResult:
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"""
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Invoke text embedding model
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:param model: model name
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:param credentials: model credentials
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:param texts: texts to embed
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:param user: unique user id
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:param input_type: input type
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:return: embeddings result
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"""
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api_key = credentials["api_key"]
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if not api_key:
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raise CredentialsValidateFailedError("api_key is required")
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base_url = credentials.get("base_url", self.api_base)
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base_url = base_url.removesuffix("/")
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url = base_url + "/embeddings"
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headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"}
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voyage_input_type = "null"
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if input_type is not None:
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voyage_input_type = input_type.value
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data = {"model": model, "input": texts, "input_type": voyage_input_type}
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try:
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response = requests.post(url, headers=headers, data=dumps(data))
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except Exception as e:
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raise InvokeConnectionError(str(e))
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if response.status_code != 200:
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try:
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resp = response.json()
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msg = resp["detail"]
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if response.status_code == 401:
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raise InvokeAuthorizationError(msg)
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elif response.status_code == 429:
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raise InvokeRateLimitError(msg)
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elif response.status_code == 500:
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raise InvokeServerUnavailableError(msg)
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else:
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raise InvokeBadRequestError(msg)
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except JSONDecodeError as e:
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raise InvokeServerUnavailableError(
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f"Failed to convert response to json: {e} with text: {response.text}"
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)
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try:
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resp = response.json()
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embeddings = resp["data"]
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usage = resp["usage"]
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except Exception as e:
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raise InvokeServerUnavailableError(f"Failed to convert response to json: {e} with text: {response.text}")
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usage = self._calc_response_usage(model=model, credentials=credentials, tokens=usage["total_tokens"])
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result = TextEmbeddingResult(
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model=model, embeddings=[[float(data) for data in x["embedding"]] for x in embeddings], usage=usage
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)
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return result
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def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
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"""
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Get number of tokens for given prompt messages
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:param model: model name
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:param credentials: model credentials
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:param texts: texts to embed
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:return:
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"""
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return sum(self._get_num_tokens_by_gpt2(text) for text in texts)
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def validate_credentials(self, model: str, credentials: dict) -> None:
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"""
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Validate model credentials
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:param model: model name
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:param credentials: model credentials
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:return:
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"""
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try:
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self._invoke(model=model, credentials=credentials, texts=["ping"])
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except Exception as e:
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raise CredentialsValidateFailedError(f"Credentials validation failed: {e}")
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@property
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def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
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return {
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InvokeConnectionError: [InvokeConnectionError],
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InvokeServerUnavailableError: [InvokeServerUnavailableError],
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InvokeRateLimitError: [InvokeRateLimitError],
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InvokeAuthorizationError: [InvokeAuthorizationError],
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InvokeBadRequestError: [KeyError, InvokeBadRequestError],
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}
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def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage:
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"""
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Calculate response usage
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:param model: model name
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:param credentials: model credentials
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:param tokens: input tokens
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:return: usage
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"""
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# get input price info
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input_price_info = self.get_price(
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model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens
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)
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# transform usage
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usage = EmbeddingUsage(
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tokens=tokens,
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total_tokens=tokens,
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unit_price=input_price_info.unit_price,
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price_unit=input_price_info.unit,
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total_price=input_price_info.total_amount,
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currency=input_price_info.currency,
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latency=time.perf_counter() - self.started_at,
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)
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return usage
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|
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def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity:
|
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"""
|
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generate custom model entities from credentials
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"""
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entity = AIModelEntity(
|
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model=model,
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label=I18nObject(en_US=model),
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model_type=ModelType.TEXT_EMBEDDING,
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fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
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model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size"))},
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)
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return entity
|
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@ -0,0 +1,8 @@
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model: voyage-3-lite
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model_type: text-embedding
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model_properties:
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context_size: 32000
|
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pricing:
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input: '0.00002'
|
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unit: '0.001'
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currency: USD
|
|
@ -0,0 +1,8 @@
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model: voyage-3
|
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model_type: text-embedding
|
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model_properties:
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context_size: 32000
|
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pricing:
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input: '0.00006'
|
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unit: '0.001'
|
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currency: USD
|
28
api/core/model_runtime/model_providers/voyage/voyage.py
Normal file
28
api/core/model_runtime/model_providers/voyage/voyage.py
Normal file
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@ -0,0 +1,28 @@
|
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import logging
|
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|
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from core.model_runtime.entities.model_entities import ModelType
|
||||
from core.model_runtime.errors.validate import CredentialsValidateFailedError
|
||||
from core.model_runtime.model_providers.__base.model_provider import ModelProvider
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class VoyageProvider(ModelProvider):
|
||||
def validate_provider_credentials(self, credentials: dict) -> None:
|
||||
"""
|
||||
Validate provider credentials
|
||||
if validate failed, raise exception
|
||||
|
||||
:param credentials: provider credentials, credentials form defined in `provider_credential_schema`.
|
||||
"""
|
||||
try:
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model_instance = self.get_model_instance(ModelType.TEXT_EMBEDDING)
|
||||
|
||||
# Use `voyage-3` model for validate,
|
||||
# no matter what model you pass in, text completion model or chat model
|
||||
model_instance.validate_credentials(model="voyage-3", credentials=credentials)
|
||||
except CredentialsValidateFailedError as ex:
|
||||
raise ex
|
||||
except Exception as ex:
|
||||
logger.exception(f"{self.get_provider_schema().provider} credentials validate failed")
|
||||
raise ex
|
31
api/core/model_runtime/model_providers/voyage/voyage.yaml
Normal file
31
api/core/model_runtime/model_providers/voyage/voyage.yaml
Normal file
|
@ -0,0 +1,31 @@
|
|||
provider: voyage
|
||||
label:
|
||||
en_US: Voyage
|
||||
description:
|
||||
en_US: Embedding and Rerank Model Supported
|
||||
icon_small:
|
||||
en_US: icon_s_en.svg
|
||||
icon_large:
|
||||
en_US: icon_l_en.svg
|
||||
background: "#EFFDFD"
|
||||
help:
|
||||
title:
|
||||
en_US: Get your API key from Voyage AI
|
||||
zh_Hans: 从 Voyage 获取 API Key
|
||||
url:
|
||||
en_US: https://dash.voyageai.com/
|
||||
supported_model_types:
|
||||
- text-embedding
|
||||
- rerank
|
||||
configurate_methods:
|
||||
- predefined-model
|
||||
provider_credential_schema:
|
||||
credential_form_schemas:
|
||||
- variable: api_key
|
||||
label:
|
||||
en_US: API Key
|
||||
type: secret-input
|
||||
required: true
|
||||
placeholder:
|
||||
zh_Hans: 在此输入您的 API Key
|
||||
en_US: Enter your API Key
|
|
@ -123,6 +123,7 @@ FIRECRAWL_API_KEY = "fc-"
|
|||
TEI_EMBEDDING_SERVER_URL = "http://a.abc.com:11451"
|
||||
TEI_RERANK_SERVER_URL = "http://a.abc.com:11451"
|
||||
MIXEDBREAD_API_KEY = "mk-aaaaaaaaaaaaaaaaaaaa"
|
||||
VOYAGE_API_KEY = "va-aaaaaaaaaaaaaaaaaaaa"
|
||||
|
||||
[tool.poetry]
|
||||
name = "dify-api"
|
||||
|
|
|
@ -0,0 +1,25 @@
|
|||
import os
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from core.model_runtime.errors.validate import CredentialsValidateFailedError
|
||||
from core.model_runtime.model_providers.voyage.voyage import VoyageProvider
|
||||
|
||||
|
||||
def test_validate_provider_credentials():
|
||||
provider = VoyageProvider()
|
||||
|
||||
with pytest.raises(CredentialsValidateFailedError):
|
||||
provider.validate_provider_credentials(credentials={"api_key": "hahahaha"})
|
||||
with patch("requests.post") as mock_post:
|
||||
mock_response = Mock()
|
||||
mock_response.json.return_value = {
|
||||
"object": "list",
|
||||
"data": [{"object": "embedding", "embedding": [0.23333 for _ in range(1024)], "index": 0}],
|
||||
"model": "voyage-3",
|
||||
"usage": {"total_tokens": 1},
|
||||
}
|
||||
mock_response.status_code = 200
|
||||
mock_post.return_value = mock_response
|
||||
provider.validate_provider_credentials(credentials={"api_key": os.environ.get("VOYAGE_API_KEY")})
|
|
@ -0,0 +1,92 @@
|
|||
import os
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from core.model_runtime.entities.rerank_entities import RerankResult
|
||||
from core.model_runtime.errors.validate import CredentialsValidateFailedError
|
||||
from core.model_runtime.model_providers.voyage.rerank.rerank import VoyageRerankModel
|
||||
|
||||
|
||||
def test_validate_credentials():
|
||||
model = VoyageRerankModel()
|
||||
|
||||
with pytest.raises(CredentialsValidateFailedError):
|
||||
model.validate_credentials(
|
||||
model="rerank-lite-1",
|
||||
credentials={"api_key": "invalid_key"},
|
||||
)
|
||||
with patch("httpx.post") as mock_post:
|
||||
mock_response = Mock()
|
||||
mock_response.json.return_value = {
|
||||
"object": "list",
|
||||
"data": [
|
||||
{
|
||||
"relevance_score": 0.546875,
|
||||
"index": 0,
|
||||
"document": "Carson City is the capital city of the American state of Nevada. At the 2010 United "
|
||||
"States Census, Carson City had a population of 55,274.",
|
||||
},
|
||||
{
|
||||
"relevance_score": 0.4765625,
|
||||
"index": 1,
|
||||
"document": "The Commonwealth of the Northern Mariana Islands is a group of islands in the "
|
||||
"Pacific Ocean that are a political division controlled by the United States. Its "
|
||||
"capital is Saipan.",
|
||||
},
|
||||
],
|
||||
"model": "rerank-lite-1",
|
||||
"usage": {"total_tokens": 96},
|
||||
}
|
||||
mock_response.status_code = 200
|
||||
mock_post.return_value = mock_response
|
||||
model.validate_credentials(
|
||||
model="rerank-lite-1",
|
||||
credentials={
|
||||
"api_key": os.environ.get("VOYAGE_API_KEY"),
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
def test_invoke_model():
|
||||
model = VoyageRerankModel()
|
||||
with patch("httpx.post") as mock_post:
|
||||
mock_response = Mock()
|
||||
mock_response.json.return_value = {
|
||||
"object": "list",
|
||||
"data": [
|
||||
{
|
||||
"relevance_score": 0.84375,
|
||||
"index": 0,
|
||||
"document": "Kasumi is a girl name of Japanese origin meaning mist.",
|
||||
},
|
||||
{
|
||||
"relevance_score": 0.4765625,
|
||||
"index": 1,
|
||||
"document": "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music and she "
|
||||
"leads a team named PopiParty.",
|
||||
},
|
||||
],
|
||||
"model": "rerank-lite-1",
|
||||
"usage": {"total_tokens": 59},
|
||||
}
|
||||
mock_response.status_code = 200
|
||||
mock_post.return_value = mock_response
|
||||
result = model.invoke(
|
||||
model="rerank-lite-1",
|
||||
credentials={
|
||||
"api_key": os.environ.get("VOYAGE_API_KEY"),
|
||||
},
|
||||
query="Who is Kasumi?",
|
||||
docs=[
|
||||
"Kasumi is a girl name of Japanese origin meaning mist.",
|
||||
"Her music is a kawaii bass, a mix of future bass, pop, and kawaii music and she leads a team named "
|
||||
"PopiParty.",
|
||||
],
|
||||
score_threshold=0.5,
|
||||
)
|
||||
|
||||
assert isinstance(result, RerankResult)
|
||||
assert len(result.docs) == 1
|
||||
assert result.docs[0].index == 0
|
||||
assert result.docs[0].score >= 0.5
|
|
@ -0,0 +1,70 @@
|
|||
import os
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
|
||||
from core.model_runtime.errors.validate import CredentialsValidateFailedError
|
||||
from core.model_runtime.model_providers.voyage.text_embedding.text_embedding import VoyageTextEmbeddingModel
|
||||
|
||||
|
||||
def test_validate_credentials():
|
||||
model = VoyageTextEmbeddingModel()
|
||||
|
||||
with pytest.raises(CredentialsValidateFailedError):
|
||||
model.validate_credentials(model="voyage-3", credentials={"api_key": "invalid_key"})
|
||||
with patch("requests.post") as mock_post:
|
||||
mock_response = Mock()
|
||||
mock_response.json.return_value = {
|
||||
"object": "list",
|
||||
"data": [{"object": "embedding", "embedding": [0.23333 for _ in range(1024)], "index": 0}],
|
||||
"model": "voyage-3",
|
||||
"usage": {"total_tokens": 1},
|
||||
}
|
||||
mock_response.status_code = 200
|
||||
mock_post.return_value = mock_response
|
||||
model.validate_credentials(model="voyage-3", credentials={"api_key": os.environ.get("VOYAGE_API_KEY")})
|
||||
|
||||
|
||||
def test_invoke_model():
|
||||
model = VoyageTextEmbeddingModel()
|
||||
|
||||
with patch("requests.post") as mock_post:
|
||||
mock_response = Mock()
|
||||
mock_response.json.return_value = {
|
||||
"object": "list",
|
||||
"data": [
|
||||
{"object": "embedding", "embedding": [0.23333 for _ in range(1024)], "index": 0},
|
||||
{"object": "embedding", "embedding": [0.23333 for _ in range(1024)], "index": 1},
|
||||
],
|
||||
"model": "voyage-3",
|
||||
"usage": {"total_tokens": 2},
|
||||
}
|
||||
mock_response.status_code = 200
|
||||
mock_post.return_value = mock_response
|
||||
result = model.invoke(
|
||||
model="voyage-3",
|
||||
credentials={
|
||||
"api_key": os.environ.get("VOYAGE_API_KEY"),
|
||||
},
|
||||
texts=["hello", "world"],
|
||||
user="abc-123",
|
||||
)
|
||||
|
||||
assert isinstance(result, TextEmbeddingResult)
|
||||
assert len(result.embeddings) == 2
|
||||
assert result.usage.total_tokens == 2
|
||||
|
||||
|
||||
def test_get_num_tokens():
|
||||
model = VoyageTextEmbeddingModel()
|
||||
|
||||
num_tokens = model.get_num_tokens(
|
||||
model="voyage-3",
|
||||
credentials={
|
||||
"api_key": os.environ.get("VOYAGE_API_KEY"),
|
||||
},
|
||||
texts=["ping"],
|
||||
)
|
||||
|
||||
assert num_tokens == 1
|
|
@ -9,4 +9,5 @@ pytest api/tests/integration_tests/model_runtime/anthropic \
|
|||
api/tests/integration_tests/model_runtime/upstage \
|
||||
api/tests/integration_tests/model_runtime/fireworks \
|
||||
api/tests/integration_tests/model_runtime/nomic \
|
||||
api/tests/integration_tests/model_runtime/mixedbread
|
||||
api/tests/integration_tests/model_runtime/mixedbread \
|
||||
api/tests/integration_tests/model_runtime/voyage
|
Loading…
Reference in New Issue
Block a user