Update app.py

app.py

@@ -1,73 +1,66 @@
 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
-
-"""
-
-"""
-
-title = "Awesome ML App"
-desc = "This is an awesome ML App.  I'm really excited to show you"
-long_desc = "Let me tell you ALL about this awesome ML App"
-iface = gr.Interface(theme=gr.themes.Glass(), 
-                examples=[example1, ref_example, example2], title=title, 
-                description=desc, article=long_desc)
-
-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 pandas as pd
+import plotly.express as px
+import io
+
+# Global cache for dataframe
+df_cache = {}
+
+# Convert DataFrame to markdown
+def df_to_markdown(df):
+    return df.to_markdown(index=False)
+
+# File upload handler
+def handle_file(file):
+    ext = file.name.split('.')[-1]
+    if ext == "csv":
+        df = pd.read_csv(file.name)
+    elif ext in ["xlsx", "xls"]:
+        df = pd.read_excel(file.name)
+    else:
+        return "Unsupported file format", None
+
+    # Save dataframe globally
+    df_cache["df"] = df
+    markdown_table = df_to_markdown(df)
+    return markdown_table, f"File loaded: {file.name}"
+
+# Chatbot response (simple echo for now)
+def chat_response(message, history):
+    return history + [[message, "Terima kasih! Fitur analisis lanjut sedang dikembangkan."]]
+
+# Plot page: visualize table
+def show_plot():
+    df = df_cache.get("df")
+    if df is None:
+        return "Please upload a file on Page 1 first."
+
+    fig = px.bar(df, x=df.columns[0], y=df.columns[1], title="Visualisasi Kolom 1 vs Kolom 2")
+    return fig
+
+# Interface: Page 1 - Upload + Table + Chat
+with gr.Blocks() as page1:
+    gr.Markdown("# Selamat Datang di Tertata 🎉")
+
+    file_input = gr.File(label="Upload CSV atau Excel", file_types=[".csv", ".xlsx", ".xls"])
+    markdown_output = gr.Markdown()
+    file_status = gr.Textbox(label="Status", interactive=False)
+
+    file_input.change(fn=handle_file, inputs=file_input, outputs=[markdown_output, file_status])
+
+    gr.Markdown("## Tanya Jawab 📩")
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(placeholder="Tanyakan sesuatu tentang tabel...")
+    msg.submit(chat_response, inputs=[msg, chatbot], outputs=chatbot)
+
+# Interface: Page 2 - Visualization
+with gr.Blocks() as page2:
+    gr.Markdown("# 📊 Visualisasi Data")
+    gr.Markdown("Menampilkan grafik dari dua kolom pertama.")
+    plot_output = gr.Plot()
+    btn = gr.Button("Tampilkan Visualisasi")
+    btn.click(show_plot, outputs=plot_output)
+
+# Launch with tabs
+app = gr.TabbedInterface([page1, page2], ["Data & Tanya", "Visualisasi"])
+app.launch()