ChromaDB未来能不能支持OllamaEmbeddings？因为Ollama可以导入很多中文的嵌入模型

[liumengcheng]

我在使用ChromaDB_VectorStore.__init__的时候没法设置使用Ollama的嵌入模型，类似这种embeddings = OllamaEmbeddings(base_url="http://127.0.0.1:8000",model="znbang/bge:large-zh-v1.5-f32")

现在的Ollama可以支持LLM和嵌入模型

[Jianye]

from vanna.base import VannaBase
from vanna.ollama import Ollama
from vanna.chromadb import ChromaDB_VectorStore
from chromadb.utils.embedding_functions import OllamaEmbeddingFunction
from time import sleep
import os
import traceback

# 创建 OllamaEmbeddingFunction 实例
ollama_embedding_function = OllamaEmbeddingFunction(
    model_name=
    "mxbai-embed-large:latest",  #model_name="dztech/bge-large-zh:v1.5",
    url="http://17.2.2.2.2:11343/api/embeddings",
)


class MyVanna(ChromaDB_VectorStore, Ollama):

    def __init__(self, vsconfig=None, oconfig=None):
        ChromaDB_VectorStore.__init__(self, config=vsconfig)
        Ollama.__init__(self, config=oconfig)


# 配置 config
vsconfig = {
    "embedding_function": ollama_embedding_function,
    "n_results_sql": 5,
    "n_results_documentation": 5,
    "n_results_ddl": 3,
    "path": "/home/cusc/script/vanna/vannadb",
}

oconfig = {
    "model": "qwen:32b-chat-v1.5-q4_0",
    "ollama_host": "http://17.2.2.2.2:11343",
}




if __name__ == "__main__":

    vn = MyVanna(vsconfig=vsconfig, oconfig=oconfig)