Update app.py

app.py

@@ -1,64 +1,74 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import pandas as pd
+import io
 
-"""
-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")
+# Define admin credentials
+ADMIN_EMAIL = "admin@gmail.com"
+ADMIN_PASSWORD = "123456"
 
+# Variable to store uploaded grades file in memory
+grades_df = None
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+# Admin upload function
+def admin_upload(email, password, file):
+    global grades_df
+    if email == ADMIN_EMAIL and password == ADMIN_PASSWORD:
+        if file is not None:
+            # Read the uploaded file in-memory
+            grades_df = pd.read_excel(io.BytesIO(file.read()))
+            return "File uploaded and processed successfully."
+        else:
+            return "Please upload a valid Excel file."
+    else:
+        return "Invalid credentials."
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+# Intern grade analysis function
+def intern_view(email):
+    if grades_df is not None:
+        # Filter the grades for the provided email
+        intern_grades = grades_df[grades_df['Email'] == email]
+        if not intern_grades.empty:
+            # Generate a summary analysis
+            total_grade = intern_grades['Grade'].sum()
+            average_grade = intern_grades['Grade'].mean()
+            num_records = intern_grades.shape[0]
+            return (
+                f"Total Grade: {total_grade}\n"
+                f"Average Grade: {average_grade}\n"
+                f"Number of Records: {num_records}\n"
+            )
+        else:
+            return "No records found for this email."
+    else:
+        return "No grades file uploaded. Please contact the admin."
 
-    messages.append({"role": "user", "content": message})
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    with gr.Tab("Admin Login"):
+        with gr.Row():
+            admin_email = gr.Textbox(label="Admin Email")
+            admin_password = gr.Textbox(label="Admin Password", type="password")
+            admin_file = gr.File(label="Upload Grades Excel File")
+            admin_submit = gr.Button("Submit")
+            admin_output = gr.Textbox(label="Admin Output")
 
-    response = ""
+        admin_submit.click(
+            admin_upload,
+            inputs=[admin_email, admin_password, admin_file],
+            outputs=admin_output,
+        )
+    
+    with gr.Tab("Intern Login"):
+        with gr.Row():
+            intern_email = gr.Textbox(label="Intern Email")
+            intern_submit = gr.Button("View Grades")
+            intern_output = gr.Textbox(label="Intern Output")
 
-    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
+        intern_submit.click(
+            intern_view,
+            inputs=[intern_email],
+            outputs=intern_output,
+        )
 
-        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()
+# Launch the app
+demo.launch()