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GIGAParviz commited on Sep 28, 2025

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web_app.py +390 -0

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+# from flask import Flask, render_template_string, request, jsonify
+# import os
+# from groq import Groq
+# import re
+# from pypdf import PdfReader
+# from langchain_huggingface import HuggingFaceEmbeddings
+# from langchain_community.vectorstores import Chroma
+# from langchain_core.documents import Document
+# from langchain_text_splitters import RecursiveCharacterTextSplitter
+# app = Flask(__name__)
+# app.static_folder = 'static'
+# client = Groq(
+#     api_key="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",
+# )
+# embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
+# vector_store = Chroma(embedding_function=embeddings, collection_name="doc_collection")
+# text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
+# chat_history = []
+# HTML_TEMPLATE = """
+# <!DOCTYPE html>
+# <html lang="en">
+# <head>
+#     <meta charset="UTF-8">
+#     <meta name="viewport" content="width=device-width, initial-scale=1.0">
+#     <title>Chat</title>
+#     <style>
+#         :root {
+#             --bg-gradient-start: #f0f4ff;
+#             --bg-gradient-end: #d9e2ff;
+#             --sidebar-bg: #ffffff;
+#             --sidebar-border: #e0e0e0;
+#             --text-color: #333;
+#             --header-color: #483d8b;
+#             --sidebar-h3: #6a5acd;
+#             --chat-bg: #ffffff;
+#             --user-msg-bg: #6a5acd;
+#             --user-msg-text: white;
+#             --ai-msg-bg: #f0f4ff;
+#             --ai-msg-text: #333;
+#             --input-bg: #ffffff;
+#             --button-bg: #6a5acd;
+#             --button-text: white;
+#             --button-hover: #483d8b;
+#             --thinking-color: #888;
+#             --shadow-color: rgba(0,0,0,0.1);
+#         }
+#         body.dark-mode {
+#             --bg-gradient-start: #1e1e2f;
+#             --bg-gradient-end: #2a2a3f;
+#             --sidebar-bg: #2c2c3e;
+#             --sidebar-border: #3a3a4e;
+#             --text-color: #ddd;
+#             --header-color: #a8a8ff;
+#             --sidebar-h3: #a8a8ff;
+#             --chat-bg: #2c2c3e;
+#             --user-msg-bg: #4a4a7f;
+#             --user-msg-text: #fff;
+#             --ai-msg-bg: #3a3a4e;
+#             --ai-msg-text: #ddd;
+#             --input-bg: #2c2c3e;
+#             --button-bg: #4a4a7f;
+#             --button-text: #fff;
+#             --button-hover: #6a6a9f;
+#             --thinking-color: #aaa;
+#             --shadow-color: rgba(0,0,0,0.3);
+#         }
+#         body {
+#             margin: 0; font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+#             background: linear-gradient(135deg, var(--bg-gradient-start), var(--bg-gradient-end));
+#             color: var(--text-color); display: flex; height: 100vh;
+#         }
+#         .sidebar {
+#             width: 250px; background: var(--sidebar-bg); border-right: 1px solid var(--sidebar-border);
+#             padding: 20px; box-shadow: 0 2px 10px var(--shadow-color);
+#             transition: width 0.3s ease;
+#         }
+#         .sidebar:hover { width: 260px; }
+#         .sidebar h3 { color: var(--sidebar-h3); margin-bottom: 10px; }
+#         .sidebar ul { list-style: none; padding: 0; }
+#         .sidebar li { padding: 10px; border-radius: 8px; cursor: pointer; transition: background 0.2s; }
+#         .sidebar li:hover { background: rgba(255,255,255,0.1); }
+#         .main { flex: 1; display: flex; flex-direction: column; padding: 20px; }
+#         .header { display: flex; justify-content: space-between; align-items: center; margin-bottom: 20px; }
+#         .header h1 { color: var(--header-color); font-size: 24px; }
+#         .logo { width: 100px; height: auto; display: block; margin: 0 auto 20px auto; } /* اندازه بزرگ‌تر و مرکزی */
+#         .chat-area { flex: 1; overflow-y: auto; background: var(--chat-bg); border-radius: 12px; padding: 20px; box-shadow: 0 4px 20px var(--shadow-color); }
+#         .message { margin-bottom: 15px; padding: 12px 18px; border-radius: 20px; max-width: 70%; }
+#         .user-message { background: var(--user-msg-bg); color: var(--user-msg-text); align-self: flex-end; }
+#         .ai-message { background: var(--ai-msg-bg); color: var(--ai-msg-text); align-self: flex-start; }
+#         .thinking { color: var(--thinking-color); font-style: italic; opacity: 0.7; }
+#         .input-area { display: flex; align-items: center; margin-top: 20px; background: var(--input-bg); border-radius: 50px; padding: 10px; box-shadow: 0 2px 10px var(--shadow-color); }
+#         input[type="text"] { flex: 1; border: none; padding: 12px; font-size: 16px; outline: none; background: transparent; color: var(--text-color); }
+#         input[type="file"] { margin-left: 10px; color: var(--text-color); }
+#         button { background: var(--button-bg); color: var(--button-text); border: none; padding: 10px 20px; border-radius: 50px; cursor: pointer; transition: background 0.2s; }
+#         button:hover { background: var(--button-hover); }
+#         .dark-mode-toggle { cursor: pointer; font-size: 20px; }
+#     </style>
+# </head>
+# <body class="dark-mode">
+#     <div class="sidebar">
+#         <img src="/static/logo.png" alt="Logo" class="logo">
+#         <h3>Chats</h3>
+#         <ul>
+#             <li>+ New Chat</li>
+#             <li>Today</li>
+#             <li>Yesterday</li>
+#         </ul>
+#     </div>
+#     <div class="main">
+#         <div class="header">
+#             <h1>Hi User</h1>
+#             <div class="dark-mode-toggle" onclick="toggleDarkMode()">☀️</div>
+#         </div>
+#         <div class="chat-area" id="chat-area">
+#             <div class="message ai-message">How can I help you today?</div>
+#         </div>
+#         <div class="input-area">
+#             <input type="text" id="user-input" placeholder="Type your message...">
+#             <input type="file" id="file-upload">
+#             <button onclick="sendMessage()">Send</button>
+#         </div>
+#     </div>
+#     <script>
+#         function sendMessage() {
+#             const input = document.getElementById('user-input').value;
+#             const fileInput = document.getElementById('file-upload');
+#             const chatArea = document.getElementById('chat-area');
+#             if (input || fileInput.files.length > 0) {
+#                 // Display user message
+#                 const userMsg = document.createElement('div');
+#                 userMsg.className = 'message user-message';
+#                 userMsg.textContent = input || 'Uploaded file: ' + (fileInput.files[0]?.name || '');
+#                 chatArea.appendChild(userMsg);
+#                 // Prepare form data for upload
+#                 const formData = new FormData();
+#                 formData.append('message', input);
+#                 if (fileInput.files.length > 0) {
+#                     formData.append('file', fileInput.files[0]);
+#                 }
+#                 // Send to backend API
+#                 fetch('/chat', {
+#                     method: 'POST',
+#                     body: formData
+#                 })
+#                 .then(response => response.json())
+#                 .then(data => {
+#                     if (data.thinking) {
+#                         const thinkMsg = document.createElement('div');
+#                         thinkMsg.className = 'message ai-message thinking';
+#                         thinkMsg.textContent = data.thinking;
+#                         chatArea.appendChild(thinkMsg);
+#                     }
+#                     const aiMsg = document.createElement('div');
+#                     aiMsg.className = 'message ai-message';
+#                     aiMsg.textContent = data.response;
+#                     chatArea.appendChild(aiMsg);
+#                     chatArea.scrollTop = chatArea.scrollHeight;
+#                 });
+#                 document.getElementById('user-input').value = '';
+#                 fileInput.value = '';
+#             }
+#         }
+#         // Add Enter key listener
+#         document.getElementById('user-input').addEventListener('keydown', function(event) {
+#             if (event.key === 'Enter') {
+#                 event.preventDefault();
+#                 sendMessage();
+#             }
+#         });
+#         // Dark mode toggle function
+#         function toggleDarkMode() {
+#             document.body.classList.toggle('dark-mode');
+#             const toggle = document.querySelector('.dark-mode-toggle');
+#             toggle.textContent = document.body.classList.contains('dark-mode') ? '☀️' : '🌙';
+#         }
+#     </script>
+# </body>
+# </html>
+# """
+# @app.route('/')
+# def index():
+#     return render_template_string(HTML_TEMPLATE)
+# def process_file(file_obj):
+#     if not file_obj:
+#         return None
+#     file_path = file_obj.filename
+#     file_extension = os.path.splitext(file_path)[1].lower()
+#     try:
+#         if file_extension == ".pdf":
+#             reader = PdfReader(file_obj)
+#             file_text = "\n".join(page.extract_text() or "" for page in reader.pages)
+#         elif file_extension == ".txt":
+#             file_text = file_obj.read().decode('utf-8')
+#         else:
+#             raise ValueError(f"Unsupported file format: {file_extension}")
+#         file_docs = [Document(page_content=file_text, metadata={"source": "uploaded_file"})]
+#         file_splits = text_splitter.split_documents(file_docs)
+#         vector_store.add_documents(file_splits)
+#         return file_text
+#     except Exception as e:
+#         raise RuntimeError(f"Error processing file: {str(e)}")
+# @app.route('/chat', methods=['POST'])
+# def chat():
+#     user_message = request.form.get('message', '')
+#     uploaded_file = request.files.get('file')
+#     system_prompt = "You are an AI assistant developed by Holding Khalij Fars, tasked with responding to user queries accurately and helpfully."
+#     messages = [{"role": "system", "content": system_prompt}]
+#     model = "qwen/qwen3-32b"
+#     relevant_content = ""
+#     if uploaded_file:
+#         try:
+#             file_text = process_file(uploaded_file)
+#             if file_text:
+#                 search_query = user_message
+#                 retrieved_docs = vector_store.similarity_search(search_query, k=3)
+#                 relevant_content = "\n".join(doc.page_content for doc in retrieved_docs)
+#             if relevant_content:
+#                 user_message += f"\nRelevant document content: {relevant_content}"
+#             messages.append({"role": "user", "content": user_message})
+#         except Exception as e:
+#             messages.append({"role": "user", "content": f"Error processing file: {str(e)}. {user_message}"})
+#     else:
+#         messages.append({"role": "user", "content": user_message})
+#     try:
+#         chat_completion = client.chat.completions.create(
+#             messages=messages,
+#             model=model,
+#         )
+#         ai_response = chat_completion.choices[0].message.content
+#         think_parts = re.findall(r'<think>(.*?)</think>', ai_response, re.DOTALL)
+#         thinking = '\n'.join(think_parts).strip() if think_parts else ''
+#         final_response = re.sub(r'<think>.*?</think>', '', ai_response, flags=re.DOTALL).strip()
+#     except Exception as e:
+#         thinking = ''
+#         final_response = ''
+#     return jsonify({'thinking': thinking, 'response': final_response})
+# if __name__ == '__main__':
+#     app.run(debug=True)
+import gradio as gr
+import os
+import base64
+from groq import Groq
+import re
+from pypdf import PdfReader
+from langchain_huggingface import HuggingFaceEmbeddings
+from langchain_community.vectorstores import Chroma
+from langchain_core.documents import Document
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+client = Groq(
+    api_key="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",
+)
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
+vector_store = Chroma(embedding_function=embeddings, collection_name="doc_collection")
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
+chat_history = []
+def process_file(file_obj):
+    if not file_obj:
+        return None
+    file_path = file_obj.name
+    file_extension = os.path.splitext(file_path)[1].lower()
+    if file_extension == ".pdf":
+        reader = PdfReader(file_obj)
+        file_text = "\n".join(page.extract_text() or "" for page in reader.pages)
+    elif file_extension == ".txt":
+        file_text = file_obj.read().decode('utf-8')
+    else:
+        raise ValueError(f"Unsupported file format: {file_extension}")
+    file_docs = [Document(page_content=file_text, metadata={"source": "uploaded_file"})]
+    file_splits = text_splitter.split_documents(file_docs)
+    vector_store.add_documents(file_splits)
+    return file_text
+def chat(user_message, uploaded_file):
+    system_prompt = "You are an AI assistant developed by Holding Khalij Fars, tasked with responding to user queries accurately and helpfully."
+    messages = [{"role": "system", "content": system_prompt}]
+    model = "qwen/qwen3-32b"
+    relevant_content = ""
+    if uploaded_file:
+        try:
+            file_text = process_file(uploaded_file)
+            if file_text:
+                search_query = user_message
+                retrieved_docs = vector_store.similarity_search(search_query, k=3)
+                relevant_content = "\n".join(doc.page_content for doc in retrieved_docs)
+            if relevant_content:
+                user_message += f"\nRelevant document content: {relevant_content}"
+            messages.append({"role": "user", "content": user_message})
+        except Exception as e:
+            messages.append({"role": "user", "content": f"Error processing file: {str(e)}. {user_message}"})
+    else:
+        messages.append({"role": "user", "content": user_message})
+    chat_completion = client.chat.completions.create(
+        messages=messages,
+        model=model,
+    )
+    ai_response = chat_completion.choices[0].message.content
+    think_parts = re.findall(r'<think>(.*?)</think>', ai_response, re.DOTALL)
+    thinking = '\n'.join(think_parts).strip() if think_parts else ''
+    final_response = re.sub(r'<think>.*?</think>', '', ai_response, flags=re.DOTALL).strip()
+    return thinking, final_response
+def update_chat_history(user_input, file, thinking_output, response_output):
+    global chat_history
+    chat_history.append((user_input or f"Uploaded: {file.name if file else 'None'}", response_output))
+    return [(msg, resp) for msg, resp in chat_history]
+def toggle_theme():
+    return gr.update(theme=gr.themes.Default() if gr.themes.get_default() == gr.themes.Soft() else gr.themes.Soft())
+with gr.Blocks(title="Virtual AI Chat", theme=gr.themes.Soft()) as app:
+    with gr.Row():
+        with gr.Column(scale=1, min_width=250):
+            gr.Image("/static/logo.png", label="Logo", elem_classes=["logo"])
+            gr.Markdown("### Chats")
+            gr.State(value=["+ New Chat", "Today", "Yesterday"])
+        with gr.Column(scale=4):
+            with gr.Row():
+                gr.Markdown("Good afternoon, User", elem_classes=["header"])
+                theme_button = gr.Button("🌙", elem_classes=["dark-mode-toggle"])
+            chat_output = gr.Chatbot(elem_classes=["chat-area"])
+            with gr.Row():
+                user_input = gr.Textbox(placeholder="Type your message...", elem_classes=["input-area"])
+                file_input = gr.File(file_types=[".pdf", ".txt"], elem_classes=["input-area"])
+                send_button = gr.Button("Send", elem_classes=["input-area"])
+            thinking_output = gr.Textbox(visible=False)
+    theme_button.click(
+        fn=toggle_theme,
+        inputs=None,
+        outputs=app,
+    )
+    send_button.click(
+        fn=chat,
+        inputs=[user_input, file_input],
+        outputs=[thinking_output, chat_output],
+    ).then(
+        fn=update_chat_history,
+        inputs=[user_input, file_input, thinking_output, chat_output],
+        outputs=[chat_output]
+    )
+    user_input.submit(
+        fn=chat,
+        inputs=[user_input, file_input],
+        outputs=[thinking_output, chat_output],
+    ).then(
+        fn=update_chat_history,
+        inputs=[user_input, file_input, thinking_output, chat_output],
+        outputs=[chat_output]
+    )
+app.launch()