Update apis/chat_api.py

apis/chat_api.py

@@ -3,6 +3,7 @@ import markdown2
 import os
 import sys
 import uvicorn
+import requests
 
 from pathlib import Path
 from typing import Union, Optional
@@ -28,6 +29,29 @@ from networks.openai_streamer import OpenaiStreamer
 from sentence_transformers import SentenceTransformer
 import tiktoken
 
+# class EmbeddingsAPIInference:
+#     def __init__(self, model_name):
+#         self.model_name=model_name
+#     def encode(self, x, headers=None, api_key=None):
+#         if api_key:
+#             if headers:
+#                 headers.update({"Authorization": f"Bearer {api_key}"})
+#             else:
+#                 headers = {"Authorization": f"Bearer {api_key}"}
+                
+#         API_URL = "https://api-inference.huggingface.co/models/"+self.model_name
+        
+#         payload = {
+#             "inputs": {
+#                 "source_sentence": "That is a happy person",
+#                 "sentences": ["That is a happy dog", "That is a very happy person", "Today is a sunny day"],
+#             }
+#         }
+        
+#         requests.post(API_URL, headers=headers, json=payload).json()
+        
+        
+
 class ChatAPIApp:
     def __init__(self):
         self.app = FastAPI(
@@ -39,7 +63,8 @@ class ChatAPIApp:
         self.setup_routes()
         self.embeddings = {
             "mxbai-embed-large":SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1"),
-            "nomic-embed-text": SentenceTransformer("nomic-ai/nomic-embed-text-v1.5", trust_remote_code=True)
+            "nomic-embed-text": SentenceTransformer("nomic-ai/nomic-embed-text-v1.5", trust_remote_code=True),
+            "multilingual-e5-large-instruct":SentenceTransformer("intfloat/multilingual-e5-large-instruct"),
         }
 
     def get_available_models(self):