Support Ollama (#261)

### What problem does this PR solve?

Issue link:#221

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

rag/llm/embedding_model.py

@@ -16,13 +16,12 @@
 from zhipuai import ZhipuAI
 import os
 from abc import ABC
-
+from ollama import Client
 import dashscope
 from openai import OpenAI
 from FlagEmbedding import FlagModel
 import torch
 import numpy as np
-from huggingface_hub import snapshot_download
 
 from api.utils.file_utils import get_project_base_directory
 from rag.utils import num_tokens_from_string
@@ -150,3 +149,24 @@ class ZhipuEmbed(Base):
         res = self.client.embeddings.create(input=text,
                                             model=self.model_name)
         return np.array(res.data[0].embedding), res.usage.total_tokens
+
+
+class OllamaEmbed(Base):
+    def __init__(self, key, model_name, **kwargs):
+        self.client = Client(host=kwargs["base_url"])
+        self.model_name = model_name
+
+    def encode(self, texts: list, batch_size=32):
+        arr = []
+        tks_num = 0
+        for txt in texts:
+            res = self.client.embeddings(prompt=txt,
+                                            model=self.model_name)
+            arr.append(res["embedding"])
+            tks_num += 128
+        return np.array(arr), tks_num
+
+    def encode_queries(self, text):
+        res = self.client.embeddings(prompt=text,
+                                            model=self.model_name)
+        return np.array(res["embedding"]), 128