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README.md

@@ -1,12 +1,6 @@
 ---
 title: SannyChatMini
-emoji: 👁
-colorFrom: green
-colorTo: indigo
+app_file: main.py
 sdk: gradio
 sdk_version: 5.27.0
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

main.py

@@ -0,0 +1,231 @@
+import os
+import json
+import gradio as gr
+from datetime import datetime
+from threading import Lock
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+import torch
+# ========== Auto-create folders ==========
+os.makedirs("chat_history", exist_ok=True)
+os.makedirs("system", exist_ok=True)
+
+# ========== Load System Context ==========
+context_path = "system/context.txt"
+if not os.path.exists(context_path):
+    raise FileNotFoundError(f"Missing system context file at {context_path}!")
+
+with open(context_path, "r", encoding="utf-8") as f:
+    loaded_context = f.read()
+
+# ========== Simple Chatbot Logic ==========
+lock = Lock()
+
+# Provide the folder path, not the file path
+model_folder = "model/Mistral-7B-Instruct-v0.3"
+
+# Load the model and tokenizer
+model = AutoModelForCausalLM.from_pretrained(model_folder, torch_dtype=torch.bfloat16)
+tokenizer = AutoTokenizer.from_pretrained(model_folder)
+
+# Set pad_token to eos_token if pad_token is not available
+if tokenizer.pad_token is None:
+    tokenizer.pad_token = tokenizer.eos_token
+
+# Initialize the pipeline for text generation
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+
+# ========== Helper Functions ==========
+
+def sanitize_username(username):
+    return ''.join(c for c in username if c.isalnum() or c in ('_', '-')).strip()
+
+def user_folder(username):
+    return os.path.join("chat_history", username)
+
+def load_latest_history(username):
+    folder = user_folder(username)
+    if not os.path.exists(folder):
+        os.makedirs(folder, exist_ok=True)
+        return []
+    files = sorted(os.listdir(folder), reverse=True)
+    if not files:
+        return []
+    latest_file = os.path.join(folder, files[0])
+    with open(latest_file, "r", encoding="utf-8") as f:
+        lines = f.readlines()
+    history = []
+    for line in lines:
+        if ": " in line:
+            user, msg = line.split(": ", 1)
+            history.append((user.strip(), msg.strip()))
+    return history
+
+def save_history(username, history):
+    folder = user_folder(username)
+    os.makedirs(folder, exist_ok=True)
+    filepath = os.path.join(folder, "history.txt")
+    
+    with open(filepath, "a", encoding="utf-8") as f:
+        # Only write the last two new entries (user + Sanny Lin)
+        for user, msg in history[-2:]:
+            f.write(f"{user}: {msg}\n")
+
+def format_chat(history):
+    formatted = ""
+    for user, msg in history:
+        if user == "Sanny Lin":
+            formatted += f"""
+            <div style='text-align: left; margin: 5px;'>
+                <span class='sanny-message' style='background-color: #e74c3c; color: white; padding: 10px 15px; border-radius: 20px; display: inline-block; max-width: 70%; word-wrap: break-word;'>
+                    {msg}
+                </span>
+            </div>
+            """
+        else:
+            formatted += f"""
+            <div style='text-align: right; margin: 5px;'>
+                <span style='background-color: #3498db; color: white; padding: 10px 15px; border-radius: 20px; display: inline-block; max-width: 70%; word-wrap: break-word;'>
+                    {msg}
+                </span>
+            </div>
+            """
+    return formatted
+
+
+def generate_reply(username, user_message, history):
+    with lock:
+        if not user_message.strip():
+            return history
+
+        # Retrieve the last 30 messages, including history from the user
+        history = history[-30:]  # Limit to the last 30 messages
+
+        messages = []
+        
+        # Start with the system context
+        if not history:
+            messages.append({"role": "system", "content": loaded_context})
+        
+        # Add the last 30 messages to the conversation history
+        for user, msg in history:
+            role = "user" if user == username else "assistant"
+            messages.append({"role": role, "content": msg})
+
+        # Add the user message at the end
+        messages.append({"role": "user", "content": user_message})
+
+        # Append the personalized prompt "You are chatting with {{ username }} now:" at the end of the context
+        user_prompt = f"You are chatting with {username} now. Reply to this message:"
+        messages.append({"role": "system", "content": user_prompt})
+
+        # Extract the content part of each message for encoding
+        text_messages = [message["content"] for message in messages]
+
+        # Tokenize using only the content part
+        prompt = tokenizer.batch_encode_plus(text_messages, return_tensors="pt", padding=True, truncation=False)
+
+        # Generate the assistant's reply without the user message being included at the start
+        generated_output = generator(user_message, 
+                                     max_length=32768,
+                                     max_new_tokens=512,# Set max length for truncation
+                                     num_return_sequences=1,
+                                     do_sample=True,
+                                     temperature=0.5,
+                                     top_p=0.5,
+                                     top_k=0,
+                                     typical_p=1,
+                                     repetition_penalty=1)  # Disable sampling for more creative and deterministic responses
+
+        response = generated_output[0]["generated_text"]
+
+        # Clean the response to remove any prefix from the last user message
+        if response.startswith(user_message):
+            response = response[len(user_message):].strip()
+
+        # Smart truncation to cut off at 4096 characters without cutting in the middle of a word
+        max_length = 4096
+        if len(response) > max_length:
+            # Find the last space before the cutoff point
+            truncated_response = response[:max_length]
+            last_space_idx = truncated_response.rfind(" ")
+
+            if last_space_idx != -1:
+                response = truncated_response[:last_space_idx]
+            else:
+                response = truncated_response
+
+        # Add the user message and assistant's response to history
+        history.append((username, user_message))
+        history.append(("Sanny Lin", response))
+
+        save_history(username, history)
+
+        return format_chat(history)
+
+
+
+
+
+# ========== Gradio Interface ==========
+
+with gr.Blocks(theme=gr.themes.Monochrome(), css="""
+    @font-face {
+        font-family: "DaemonFont";
+        src: url('static/daemon.otf') format('opentype');
+    }
+    body { background-color: #121212 !important; }
+    .gradio-container { background-color: #121212 !important; }
+    textarea { background-color: #1e1e1e !important; color: white; }
+    input { background-color: #1e1e1e !important; color: white; }
+    #chat_display { overflow-y: auto; height: calc(100vh - 200px); }
+    .sanny-message {
+        font-family: "DaemonFont", sans-serif;
+    }
+""") as demo:
+
+    chat_display = gr.HTML(value="", elem_id="chat_display", show_label=False)
+
+    with gr.Row():
+        username_box = gr.Textbox(label="Username", placeholder="Enter username...", interactive=True, scale=2)
+        user_input = gr.Textbox(placeholder="Type your message...", lines=2, show_label=False, scale=8)
+        send_button = gr.Button("Send", scale=1)
+
+    username_state = gr.State("")
+    history_state = gr.State([])
+
+    def user_send(user_message, username, history, username_input):
+        if not username_input.strip():
+            return "<div style='color: red;'>Please enter a valid username first.</div>", history, username
+
+        username_input = sanitize_username(username_input)
+        if not username:
+            username = username_input
+
+        history = history or load_latest_history(username)
+
+        return generate_reply(username, user_message, history), history, username
+
+    send_button.click(
+        fn=user_send,
+        inputs=[user_input, username_state, history_state, username_box],
+        outputs=[chat_display, history_state, username_state]
+    )
+
+    send_button.click(lambda: "", None, user_input)  # Clear input after send
+
+    demo.load(None, None, None, js="""
+    () => {
+        const textbox = document.querySelector('textarea');
+        const sendButton = document.querySelector('button');
+
+        textbox.addEventListener('keydown', function(e) {
+            if (e.key === 'Enter' && !e.shiftKey) {
+                e.preventDefault();
+                sendButton.click();
+            }
+        });
+    }
+    """)
+
+demo.launch(share=False)

requirements.txt

@@ -0,0 +1,4 @@
+gradio==3.28.0
+torch==2.1.0+cpu  # Or use 'torch==2.1.0+cu118' for CUDA-enabled GPU support
+transformers==4.30.0
+safetensors==0.3.0