Added multi model config

app.py

@@ -1,26 +1,43 @@
 import os
+import json
 from typing import List, Tuple
+from collections import OrderedDict
 
 import gradio as gr
 from openai import OpenAI
 
 
+config = json.loads(os.environ['CONFIG'])
+
+
+model_names = list(config.keys())
+personas = list(OrderedDict.fromkeys(persona for name in config for persona in config[name]["personas"]))
 
-client = OpenAI(
-    base_url=f"{os.environ['BASE_URL']}/v1",
-    api_key=os.environ["API_KEY"],
-)
+
+clients = {}
+for name in config:
+    client = OpenAI(
+        base_url=f"{os.environ[config[name]['api_url']]}/v1",
+        api_key=os.environ[config[name]['api_key']],
+    )
+    clients[name] = client
 
 
 
 def respond(
     message,
     history: List[Tuple[str, str]],
+    model,
+    persona,
     conversational,
     max_tokens,
 ):
     messages = []
 
+    system_prompt = config[model]["personas"][persona] 
+    if system_prompt is not None:
+        messages.append({"role": "system", "content": system_prompt})
+
     if conversational:
         for val in history[-2:]:
             if val[0]:
@@ -30,7 +47,7 @@ def respond(
 
     messages.append({"role": "user", "content": message})
 
-    completion = client.chat.completions.create(
+    completion = clients[model].chat.completions.create(
         model="neongeckocom/NeonLLM",
         messages=messages,
         max_tokens=max_tokens,
@@ -48,6 +65,8 @@ def respond(
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
+        gr.Radio(choices=model_names, value="stable", label="model"),
+        gr.Radio(choices=personas, value="default", label="persona"),
         gr.Checkbox(value=True, label="conversational"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
     ],