fix: update usage for Jina Embeddings v3 (#8771)

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Aaron Ji 2024-09-26 11:29:35 +08:00 committed by GitHub
parent 0c96f0aa51
commit 4c9ef6e830
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2 changed files with 6 additions and 57 deletions

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@ -67,46 +67,3 @@ model_credential_schema:
required: false
type: text-input
default: '8192'
- variable: task
label:
zh_Hans: 下游任务
en_US: Downstream task
placeholder:
zh_Hans: 选择将使用向量模型的下游任务。模型将返回针对该任务优化的向量。
en_US: Select the downstream task for which the embeddings will be used. The model will return the optimized embeddings for that task.
required: false
type: select
options:
- value: retrieval.query
label:
en_US: retrieval.query
- value: retrieval.passage
label:
en_US: retrieval.passage
- value: separation
label:
en_US: separation
- value: classification
label:
en_US: classification
- value: text-matching
label:
en_US: text-matching
- variable: dimensions
label:
zh_Hans: 输出维度
en_US: Output dimensions
placeholder:
zh_Hans: 输入您的输出维度
en_US: Enter output dimensions
required: false
type: text-input
- variable: late_chunking
label:
zh_Hans: 后期分块
en_US: Late chunking
placeholder:
zh_Hans: 应用后期分块技术来利用模型的长上下文功能来生成上下文块向量化。
en_US: Apply the late chunking technique to leverage the model's long-context capabilities for generating contextual chunk embeddings.
required: false
type: switch

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@ -28,7 +28,7 @@ class JinaTextEmbeddingModel(TextEmbeddingModel):
api_base: str = "https://api.jina.ai/v1"
def _to_payload(self, model: str, texts: list[str], credentials: dict) -> dict:
def _to_payload(self, model: str, texts: list[str], credentials: dict, input_type: EmbeddingInputType) -> dict:
"""
Parse model credentials
@ -45,18 +45,10 @@ class JinaTextEmbeddingModel(TextEmbeddingModel):
data = {"model": model, "input": [transform_jina_input_text(model, text) for text in texts]}
task = credentials.get("task")
dimensions = credentials.get("dimensions")
late_chunking = credentials.get("late_chunking")
if task is not None:
data["task"] = task
if dimensions is not None:
data["dimensions"] = int(dimensions)
if late_chunking is not None:
data["late_chunking"] = late_chunking
# model specific parameters
if model == "jina-embeddings-v3":
# set `task` type according to input type for the best performance
data["task"] = "retrieval.query" if input_type == EmbeddingInputType.QUERY else "retrieval.passage"
return data
@ -88,7 +80,7 @@ class JinaTextEmbeddingModel(TextEmbeddingModel):
url = base_url + "/embeddings"
headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"}
data = self._to_payload(model=model, texts=texts, credentials=credentials)
data = self._to_payload(model=model, texts=texts, credentials=credentials, input_type=input_type)
try:
response = post(url, headers=headers, data=dumps(data))