diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 268efc1d..0d154b38 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -3,10 +3,10 @@ from pydantic import BaseModel
 import logging
 import argparse
 from lightrag import LightRAG, QueryParam
-# from lightrag.llm import lollms_model_complete, lollms_embed
-# from lightrag.llm import ollama_model_complete, ollama_embed, openai_embedding
-from lightrag.llm import openai_complete_if_cache, ollama_embedding
-# from lightrag.llm import azure_openai_complete_if_cache, azure_openai_embedding
+from lightrag.llm import lollms_model_complete, lollms_embed
+from lightrag.llm import ollama_model_complete, ollama_embed
+from lightrag.llm import openai_complete_if_cache, openai_embedding
+from lightrag.llm import azure_openai_complete_if_cache, azure_openai_embedding
 
 from lightrag.utils import EmbeddingFunc
 from typing import Optional, List, Union
@@ -24,28 +24,13 @@ from fastapi.middleware.cors import CORSMiddleware
 from starlette.status import HTTP_403_FORBIDDEN
 import pipmaster as pm
 
-from dotenv import load_dotenv
-load_dotenv()
-
-async def llm_model_func(
-    prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
-) -> str:
-    return await openai_complete_if_cache(
-        "deepseek-chat",
-        prompt,
-        system_prompt=system_prompt,
-        history_messages=history_messages,
-        api_key=os.getenv("DEEPSEEK_API_KEY"),
-        base_url=os.getenv("DEEPSEEK_ENDPOINT"),
-        **kwargs,
-    )
 
 def get_default_host(binding_type: str) -> str:
     default_hosts = {
-        "ollama": "http://m4.lan.znipower.com:11434",
+        "ollama": "http://localhost:11434",
         "lollms": "http://localhost:9600",
         "azure_openai": "https://api.openai.com/v1",
-        "openai": os.getenv("DEEPSEEK_ENDPOINT"),
+        "openai": "https://api.openai.com/v1",
     }
     return default_hosts.get(
         binding_type, "http://localhost:11434"
@@ -334,12 +319,44 @@ def create_app(args):
     # Initialize RAG
     rag = LightRAG(
         working_dir=args.working_dir,
-        llm_model_func=llm_model_func,
+        llm_model_func=lollms_model_complete
+        if args.llm_binding == "lollms"
+        else ollama_model_complete
+        if args.llm_binding == "ollama"
+        else azure_openai_complete_if_cache
+        if args.llm_binding == "azure_openai"
+        else openai_complete_if_cache,
+        llm_model_name=args.llm_model,
+        llm_model_max_async=args.max_async,
+        llm_model_max_token_size=args.max_tokens,
+        llm_model_kwargs={
+            "host": args.llm_binding_host,
+            "timeout": args.timeout,
+            "options": {"num_ctx": args.max_tokens},
+        },
         embedding_func=EmbeddingFunc(
-            embedding_dim=1024,
-            max_token_size=8192,
-            func=lambda texts: ollama_embedding(
-                texts, embed_model="bge-m3:latest", host="http://m4.lan.znipower.com:11434"
+            embedding_dim=args.embedding_dim,
+            max_token_size=args.max_embed_tokens,
+            func=lambda texts: lollms_embed(
+                texts,
+                embed_model=args.embedding_model,
+                host=args.embedding_binding_host,
+            )
+            if args.llm_binding == "lollms"
+            else ollama_embed(
+                texts,
+                embed_model=args.embedding_model,
+                host=args.embedding_binding_host,
+            )
+            if args.llm_binding == "ollama"
+            else azure_openai_embedding(
+                texts,
+                model=args.embedding_model,  # no host is used for openai
+            )
+            if args.llm_binding == "azure_openai"
+            else openai_embedding(
+                texts,
+                model=args.embedding_model,  # no host is used for openai
             ),
         ),
     )