Upload app.py

app.py

@@ -1,64 +1,128 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()
+import gradio as gr
+import os
+import PyPDF2
+import google.generativeai as genai
+
+# ตั้งค่า API Key
+API_KEY = "AIzaSyDED9cUVryPKz7_zXkdVBL3Agrnb3hC1qk"  # 🔒 ใส่ API Key จริงของคุณ
+os.environ["GOOGLE_API_KEY"] = API_KEY
+genai.configure(api_key=API_KEY)
+
+# สร้าง model
+try:
+    model = genai.GenerativeModel('gemini-1.5-flash')
+    print("✅ เชื่อมต่อ Gemini API สำเร็จ")
+except Exception as e:
+    print(f"❌ เกิดข้อผิดพลาดในการเชื่อมต่อ API: {e}")
+    model = None
+
+# ฟังก์ชันอ่าน PDF
+def extract_text_from_pdf(pdf_file):
+    try:
+        if pdf_file is None:
+            return ""
+        pdf_reader = PyPDF2.PdfReader(pdf_file)
+        text = ""
+        for page in pdf_reader.pages:
+            text += page.extract_text() + "\n"
+        return text
+    except Exception as e:
+        return f"เกิดข้อผิดพลาดในการอ่านไฟล์ PDF: {str(e)}"
+
+def extract_text_from_multiple_pdfs(pdf_files):
+    if not pdf_files:
+        return ""
+    combined_text = ""
+    for i, pdf_file in enumerate(pdf_files):
+        filename = getattr(pdf_file, 'name', f'ไฟล์ที่ {i+1}')
+        filename = filename.split('/')[-1]
+        text = extract_text_from_pdf(pdf_file)
+        combined_text += f"\n\n=== ไฟล์: {filename} ===\n{text}\n"
+    return combined_text
+
+def generate_response(prompt, system_prompt=""):
+    try:
+        if model is None:
+            return "❌ ไม่สามารถเชื่อมต่อกับ Gemini API ได้"
+        full_prompt = f"{system_prompt}\n\n{prompt}" if system_prompt else prompt
+        response = model.generate_content(full_prompt)
+        return getattr(response, 'text', "ไม่สามารถสร้างคำตอบได้")
+    except Exception as e:
+        return f"เกิดข้อผิดพลาด: {str(e)}"
+
+def chat_with_pdf(pdf_files, question, chat_history):
+    system_prompt = """
+    คุณเป็นผู้ช่วยอัจฉริยะของกรมประชาสัมพันธ์ประเทศไทย...
+    """
+    if not pdf_files or all(pdf is None for pdf in pdf_files):
+        response = "❌ กรุณาอัปโหลดไฟล์ PDF อย่างน้อย 1 ไฟล์ก่อนถามคำถาม"
+    elif not question.strip():
+        response = "❌ กรุณาใส่คำถาม"
+    else:
+        combined_text = extract_text_from_multiple_pdfs(pdf_files)
+        prompt = f"""
+        เอกสารทั้งหมด:
+        {combined_text}
+        
+        คำถาม: {question}
+        """
+        response = generate_response(prompt, system_prompt)
+    chat_history.append([question, response])
+    return "", chat_history
+
+def general_prd_chat(question, chat_history):
+    system_prompt = "คุณเป็นผู้ช่วยอัจฉริยะของกรมประชาสัมพันธ์..."
+    if not question.strip():
+        response = "❌ กรุณาใส่คำถาม"
+    else:
+        response = generate_response(question, system_prompt)
+    chat_history.append([question, response])
+    return "", chat_history
+
+def news_activities_chat(question, chat_history):
+    system_prompt = "คุณเป็นผู้ช่วยอัจฉริยะของกรมประชาสัมพันธ์..."
+    if not question.strip():
+        response = "❌ กรุณาใส่คำถาม"
+    else:
+        response = generate_response(question, system_prompt)
+    chat_history.append([question, response])
+    return "", chat_history
+
+def clear_chat():
+    return []
+
+def create_interface():
+    with gr.Blocks(title="Chatbot กรมประชาสัมพันธ์") as app:
+        with gr.Tab("📄 PDF"):
+            pdf_files = gr.File(label="📎 PDF", file_types=[".pdf"], file_count="multiple")
+            pdf_question = gr.Textbox(label="คำถาม", lines=2)
+            pdf_submit = gr.Button("🔍 ถาม")
+            pdf_clear = gr.Button("🗑️ ล้าง")
+            pdf_chatbot = gr.Chatbot(height=500)
+
+            pdf_submit.click(chat_with_pdf, [pdf_files, pdf_question, pdf_chatbot], [pdf_question, pdf_chatbot])
+            pdf_clear.click(clear_chat, outputs=pdf_chatbot)
+
+        with gr.Tab("🏛️ ข้อมูลทั่วไป"):
+            general_question = gr.Textbox(label="คำถาม", lines=3)
+            general_submit = gr.Button("🔍 ถาม")
+            general_clear = gr.Button("🗑️ ล้าง")
+            general_chatbot = gr.Chatbot(height=500)
+
+            general_submit.click(general_prd_chat, [general_question, general_chatbot], [general_question, general_chatbot])
+            general_clear.click(clear_chat, outputs=general_chatbot)
+
+        with gr.Tab("📰 ข่าวกิจกรรม"):
+            news_question = gr.Textbox(label="คำถาม", lines=3)
+            news_submit = gr.Button("🔍 ถาม")
+            news_clear = gr.Button("🗑️ ล้าง")
+            news_chatbot = gr.Chatbot(height=500)
+
+            news_submit.click(news_activities_chat, [news_question, news_chatbot], [news_question, news_chatbot])
+            news_clear.click(clear_chat, outputs=news_chatbot)
+
+    return app
+
+if __name__ == "__main__":
+    app = create_interface()
+    app.launch(server_name="0.0.0.0", server_port=7860, share=True, debug=True)