renamed to OpenCHAT mini because this name is better

app.py

@@ -129,7 +129,7 @@ def respond(message, history):
                 web_results = search(query)
                 gr.Info("Extracting relevant Info")
                 web2 = ' '.join([f"Link: {res['link']}\nText: {res['text']}\n\n" for res in web_results])
-                messages = f"<|im_start|>system\nYou are OpenGPT 4o mini a helpful assistant made by KingNish. You are provided with WEB results from which you can find informations to answer users query in Structured and More better way. You do not say Unnecesarry things Only say thing which is important and relevant. You also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions.<|im_end|>"
+                messages = f"<|im_start|>system\nYou are OpenCHAT mini a helpful assistant made by KingNish. You are provided with WEB results from which you can find informations to answer users query in Structured and More better way. You do not say Unnecesarry things Only say thing which is important and relevant. You also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions.<|im_end|>"
                 for msg in history:
                     messages += f"\n<|im_start|>user\n{str(msg[0])}<|im_end|>"
                     messages += f"\n<|im_start|>assistant\n{str(msg[1])}<|im_end|>"
@@ -163,7 +163,7 @@ def respond(message, history):
                     buffer += new_text
                     yield buffer
             else:
-                messages = f"<|start_header_id|>system\nYou are OpenGPT 4o mini a helpful assistant made by KingNish. You answers users query like human friend. You are also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions.<|end_header_id|>"
+                messages = f"<|start_header_id|>system\nYou are OpenCHAT mini a helpful assistant made by KingNish. You answers users query like human friend. You are also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions.<|end_header_id|>"
                 for msg in history:
                     messages += f"\n<|start_header_id|>user\n{str(msg[0])}<|end_header_id|>"
                     messages += f"\n<|start_header_id|>assistant\n{str(msg[1])}<|end_header_id|>"
@@ -175,7 +175,7 @@ def respond(message, history):
                         output += response.token.text
                         yield output
         except:
-            messages = f"<|start_header_id|>system\nYou are OpenGPT 4o mini a helpful assistant made by KingNish. You answers users query like human friend. You are also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions.<|end_header_id|>"
+            messages = f"<|start_header_id|>system\nYou are OpenCHAT mini a helpful assistant made by KingNish. You answers users query like human friend. You are also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions.<|end_header_id|>"
             for msg in history:
                 messages += f"\n<|start_header_id|>user\n{str(msg[0])}<|end_header_id|>"
                 messages += f"\n<|start_header_id|>assistant\n{str(msg[1])}<|end_header_id|>"