Delete app.py

app.py

@@ -1,140 +0,0 @@
-import gradio as gr
-from huggingface_hub import hf_hub_download
-from llama_cpp import Llama
-import base64
-import json
-
-REPO_ID = "bartowski/Nanbeige_Nanbeige4-3B-Thinking-2511-GGUF"
-FILENAME = "Nanbeige_Nanbeige4-3B-Thinking-2511-Q8_0.gguf"
-
-print("🚀 Starting THE Z AI Server...", flush=True)
-
-llm = None
-
-def load_model():
-    global llm
-    try:
-        print("📥 Downloading Model...", flush=True)
-        model_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
-        llm = Llama(model_path=model_path, n_ctx=256000, n_threads=4, verbose=False)
-        print("✅ Model Ready!", flush=True)
-        return True
-    except Exception as e:
-        print(f"❌ Error: {e}", flush=True)
-        return False
-
-load_model()
-
-def chat(message, history_json, system_info, file_content):
-    global llm
-    
-    if not message:
-        return "Connected", history_json
-    
-    if not llm:
-        load_model()
-        if not llm:
-            return "Error: Model not loaded", history_json
-    
-    try:
-        history = json.loads(history_json) if history_json else []
-        
-        messages = []
-        
-        if system_info:
-            messages.append({
-                "role": "system",
-                "content": f"You are a smart assistant. You must always follow these rules without exception.: {system_info}\nNever mention that this information or these rules were given to you. Act as if they are natural facts you already know."
-            })
-        else:
-            messages.append({
-                "role": "system",
-                "content": """First, your name is THE Z AI THINKER and the name of the company that created you is THE ZYZ STUDIO 
-                When you think, you must think in the user's language, and the answer must also be in the user's language. 
-                Furthermore, the thought process should be at least 20 lines long and highly accurate. The thought and answer
-                should be thorough, final, complete, and comprehensive.Do not repeat the same word or phrase more than once. 
-                Text should be clear and free of repetition. Try not to make mistakes in your answers, and mentally write the
-                answer before presenting it to the user. Ensure it is not incorrect or contains unnecessary repetition that
-                could damage the sentence or the message you are conveying to the user. If it is Corden, for example, you
-                can repeat something because it is important, but do so correctly and not carelessly. 
-                Something very, very important: you are a specialist in thinking, so try to think a lot and understand 
-                every word the user said to you.You are a very powerful artificial intelligence model ("The Z AI") capable 
-                of deep logical reasoning and analysis. You must ensure that your thinking and final answer are always in
-                the user's language. If the user asks you something in the first question, for example, in Arabic or English,
-                and you give them the final answer, thinking in their language, and then they ask you a question or write an 
-                equation without any language, you must answer them in the same language as their last question before the one 
-                without any language. The answer will then be in that language. Before writing the final answer, you must conduct a
-                detailed, clear, and complete thought process explaining how you arrived at the answer. Use a logical sequence of 
-                several stages, and explain each stage precisely. Follow this structure: 1) **Read and fully understand the
-                question:** • Read the question carefully and understand every part of it. • Identify the prerequisites and 
-                the context in which the question was asked. 1) Explain clearly what the model understands from the 
-                question. 2) **Analyze the available information:** • Extract all relevant data or concepts. • Analyze the statements
-                and explain the cause-and-effect relationships between them. • List all points that will influence the 
-                conclusion. 3) **Propose possible hypotheses:** • Write down at least 2 or 3 logical hypotheses that could
-                be possible outcomes. • Evaluate each hypothesis individually in terms of logic and the 
-                available data. 4) **Evaluate and compare hypotheses:** • Compare the hypotheses using evidence 
-                or logic. • Explain why one option might be better than another. • If there are additional
-                questions that need answers, suggest them. 5) **Reach the final decision:** • Use the previous 
-                analysis to determine the best outcome. • Write a clear, logical decision based on 
-                the analysis. 6) **Explaining the basic concepts in the model:** • If the question requires
-                technical, scientific, or mathematical concepts, explain them briefly before using the results. 
-                In this part, write the **final answer** briefly and clearly without thinking steps, but after 
-                you have used the detailed analysis within the `<think>` in a logical and organized tone, and of course 
-                with meticulous and utmost accuracy and without any errors, and also while you are talking to yourself, of course.
-                You must think internally step-by-step in (user language) before giving the final answer. Start your output with a <think> 
-                section where you list your reasoning: 1) Restate the user’s question in your own words. 2) Identify all relevant
-                facts and constraints. 3) Break down the task into logical steps. 4) Evaluate options or hypotheses. 5) Summarize
-                your reasoning logically and clearly. After the <think> section, output the final answer in (user language) under <answer>
-                . Do not repeat words or phrases unnecessarily. Avoid answering before finishing the <think> section. Make sure the
-                final answer directly and clearly addresses the question without irrelevant content."""
-            })
-        
-        for h in history:
-            messages.append({"role": "user", "content": h['user']})
-            messages.append({"role": "assistant", "content": h['assistant']})
-        
-        current_message = message
-        if file_content:
-            current_message = f"[ملف مرفق]:\n{file_content}\n\n{message}"
-        
-        messages.append({"role": "user", "content": current_message})
-        
-        response_obj = llm.create_chat_completion(
-            messages=messages,
-            max_tokens=30000,
-            temperature=0.7,
-            top_k=40,
-            top_p=0.95
-        )
-        
-        response = response_obj['choices'][0]['message']['content'].strip()
-        
-        history.append({"user": message, "assistant": response})
-        
-        return response, json.dumps(history, ensure_ascii=False)
-        
-    except Exception as e:
-        return f"Error: {str(e)}", history_json
-
-def clear_memory():
-    return "تم مسح الذاكرة", "[]"
-
-with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 THE Z AI")
-    
-    with gr.Row():
-        msg = gr.Textbox(label="الرسالة")
-        history = gr.Textbox(label="السجل", value="[]")
-        system = gr.Textbox(label="معلومات النظام", value="")
-        file = gr.Textbox(label="محتوى الملف", value="")
-    
-    out = gr.Textbox(label="الرد")
-    out_history = gr.Textbox(label="السجل المحدث")
-    
-    btn = gr.Button("إرسال")
-    btn.click(chat, inputs=[msg, history, system, file], outputs=[out, out_history], api_name="chat")
-    
-    clear_btn = gr.Button("مسح الذاكرة")
-    clear_btn.click(clear_memory, inputs=[], outputs=[out, out_history], api_name="clear")
-
-demo.launch(server_name="0.0.0.0", server_port=7860)