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Adding support for DashScopeEmbeddings to handle Aliyun embedding models #16

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2 changes: 1 addition & 1 deletion backend/config/init_config.yaml.copy
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@ LLM_MODELS:
EMBEDDING_MODELS:
# OpenAI Embedding model
- name: "text-embedding-ada-002" # Model name
deployment_type: "cloud" # Deployment type: cloud or local
deployment_type: "cloud" # Deployment type: cloud or cloud-aliyun or local
category: "embedding" # Model category
api_base: "https://api.openai.com/v1" # API base URL
api_key: "your-openai-api-key" # Replace with your actual API key
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8 changes: 8 additions & 0 deletions backend/llm_model/embeddings.py
Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
from typing import List, Union, Optional, Dict
from langchain_openai import OpenAIEmbeddings
from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings
from langchain_community.embeddings import DashScopeEmbeddings
from tenacity import retry, stop_after_attempt, wait_random_exponential

from models import LLMModel
Expand Down Expand Up @@ -93,6 +94,13 @@ def load_embedding(self, model_config: dict):
openai_api_key=model_config['api_key'],
openai_api_base=model_config['api_base']
)
elif model_config["deployment_type"] == "cloud-aliyun":
# Cloud model (Aliyun)
# Ref: https://help.aliyun.com/zh/model-studio/use-bailian-in-langchain
embedding = DashScopeEmbeddings(
model=model_config["name"],
dashscope_api_key=model_config["api_key"],
)
else:
import torch
# Determine device
Expand Down