Update app.py

app.py

@@ -2,9 +2,21 @@ import gradio as gr
 import gradio_client
 from gradio_client import Client 
 
-def chat_api_interface(messages, model, frequency_penalty=0, logit_bias=None, max_tokens=None, n=1, presence_penalty=0, response_format="text", seed=None, stop=None, stream=False, temperature=1, top_p=1, tools=None, tool_choice="none", user=None):
-    # Your API interaction logic goes here
-    return "API response here"
+title = """# Welcome To Tonic's Easy YI-6B-200K"""
+description = """This is a [connector that looks like open ai](https://huggingface.co/spaces/Tonic1/TonicsYI-6B-200k) on the inputs , then ignores all that and connects to my [YI-6B-200K endpoint](https://huggingface.co/01-ai/Yi-6B-200K). This helps using [Yi for AGI here](https://huggingface.co/spaces/Tonic/AGYIntelligence)"""
+client = Client("https://tonic1-tonicsyi-6b-200k.hf.space/--replicas/cvjqf/")
+def chat_api_interface(messages, model, frequency_penalty=0, logit_bias=None, max_tokens=None, n=1, presence_penalty=0, response_format="text", seed=None, stop=None, stream=False, temperature=0.9, top_p=1, tools=None, tool_choice="none", user=None):
+    result = client.predict(
+        your_message = messages,
+        system_prompt = "I am YiTonic, an AI language model created by Tonic-AI. I am a cautious assistant. I carefully follow instructions. I am helpful and harmless and I follow ethical guidelines and promote positive behavior.",
+        max_new_tokens = 16000,
+        temperature,
+        top_p,
+        top_k,
+        disable_for_faster_inference,
+        api_name="/predict"
+    )
+    return result
 
 with gr.Blocks() as demo:
     with gr.Row():