update

app.py

@@ -12,12 +12,42 @@ def client_fn(model):
     }
     return InferenceClient(model_map.get(model, "mistralai/Mixtral-8x7B-Instruct-v0.1"))
 
-system_instructions = ("[SYSTEM] You are an assistant designed to provide information, answer questions, and offer helpful advice. "
+system_instructions = ("[SYSTEM] You are an assistant ."
+                       "Your task is to Answer the question."
+                       "Keep conversation very short, clear and concise."
                        "Respond naturally and concisely to the user's queries. "
-                       "Answer questions directly and avoid including unnecessary tags or information. "
+                       "The expectation is that you will avoid introductions and start answering the query directly, Only answer the question asked by user, Do not say unnecessary things."
                        "Begin with a greeting if the user initiates the conversation. "
                        "Here is the user's query: ")
 
+def models(text, model="Mixtral 8x7B"): 
+    
+    client = client_fn(model)
+    
+    generate_kwargs = dict(
+        max_new_tokens=100,
+        do_sample=True,
+    )
+    
+    formatted_prompt = system_instructions1 + text + "[ANSWER]"
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    output = ""
+    for response in stream:        
+        output+=response.token.text
+        if output.endswith("<|assistant|>"):
+            output = output[:-13]
+        elif output.endswith("</s>"):
+            output = output[:-4]
+    return output
+
+description="""# Chat GO
+### Inspired from Google Go"""
+
+demo = gr.Interface(description=description,fn=models, inputs=["text", gr.Dropdown([ 'Mixtral 8x7B','Nous Hermes Mixtral 8x7B DPO','StarChat2 15b','Mistral 7B v0.3','Phi 3 mini', ], value="Mistral 7B v0.3", label="Select Model") ], outputs="text", live=True, batch=True, max_batch_size=10000)
+demo.queue(max_size=300000)
+demo.launch()
+
+
 # Function to generate model responses
 def models(text, model="Mixtral 8x7B"):
     client = client_fn(model)