Update app.py

app.py

@@ -79,33 +79,98 @@
 # )
 # iface.launch()
 
+# import gradio as gr
+# from groq import Groq
+# import time
+
+# client = Groq(api_key="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")
+
+# def generate_response(message, chat_history):
+#     chat_completion = client.chat.completions.create(
+#         messages=[{"role": "user", "content": message}],
+#         model="llama3-8b-8192",
+#     )
+#     bot_message = chat_completion.choices[0].message.content
+    
+#     for i in range(0, len(bot_message), 10):
+#         yield chat_history + [(message, bot_message[:i + 10])]
+#         time.sleep(0.1)
+    
+#     yield chat_history + [(message, bot_message)]
+
+
+# with gr.Blocks() as demo:
+#     gr.Markdown("<h1 style='text-align: center;'>💬 Parviz Chatbot</h1><p style='text-align: center; color: #e0e0e0;'>زنده باد</p>")
+    
+#     chatbot = gr.Chatbot(label="جواب")
+#     msg = gr.Textbox(label="ورودی", placeholder="اینجا یه چی بپرس... ", lines=1)
+    
+#     msg.submit(generate_response, [msg, chatbot], chatbot)
+    
+#     clear = gr.ClearButton([msg, chatbot])
+# demo.launch()
+
+
+
+
+
+
+
+
 import gradio as gr
-from groq import Groq
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, GenerationConfig
+import re
 import time
 
-client = Groq(api_key="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")
+
+tokenizer = AutoTokenizer.from_pretrained("universitytehran/PersianMind-v1.0")
+model = AutoModelForSeq2SeqLM.from_pretrained("universitytehran/PersianMind-v1.0")
+
 
 def generate_response(message, chat_history):
-    chat_completion = client.chat.completions.create(
-        messages=[{"role": "user", "content": message}],
-        model="llama3-8b-8192",
+
+    TEMPLATE = "{context}\nYou: {prompt}\nParvizGPT "
+    CONTEXT = "This is a conversation with ParvizGPT. It is an artificial intelligence model designed by Amir Mahdi Parviz " \
+        "NLP expert to help you with various tasks such as answering questions, " \
+        "providing recommendations, and helping with decision making. You can ask it anything you want and " \
+        "it will do its best to give you accurate and relevant information."
+    
+    prompt = TEMPLATE.format(context=CONTEXT, prompt=message)
+
+    generation_config = GenerationConfig(
+        max_new_tokens=128,
+        do_sample=True,
+        top_k=50,
+        top_p=0.95,
+        temperature=0.8,
+        repetition_penalty=1.2
     )
-    bot_message = chat_completion.choices[0].message.content
+
+    tokenized_test_text = tokenizer(prompt, return_tensors='pt').input_ids.to("cpu")
+    model.to("cpu")
     
-    for i in range(0, len(bot_message), 10):
-        yield chat_history + [(message, bot_message[:i + 10])]
+
+    outputs = model.generate(tokenized_test_text, generation_config=generation_config, max_new_tokens=128)
+    result = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
+
+    for i in range(0, len(result), 10):
+        yield chat_history + [(message, result[:i + 10])]
         time.sleep(0.1)
-    
-    yield chat_history + [(message, bot_message)]
+
+    yield chat_history + [(message, result)]
+
 
 
 with gr.Blocks() as demo:
-    gr.Markdown("<h1 style='text-align: center;'>💬 Parviz Chatbot</h1><p style='text-align: center; color: #e0e0e0;'>زنده باد</p>")
+    gr.Markdown("<h1 style='text-align: center;'>💬 Parviz GPT</h1><p style='text-align: center;'>made by A.M.Parviz \</p>")
     
     chatbot = gr.Chatbot(label="جواب")
-    msg = gr.Textbox(label="ورودی", placeholder="اینجا یه چی بپرس... ", lines=1)
+    msg = gr.Textbox(label="ورودی", placeholder="سوال خودتو رو بپرس", lines=1)
     
     msg.submit(generate_response, [msg, chatbot], chatbot)
     
     clear = gr.ClearButton([msg, chatbot])
+
 demo.launch()
+