Initial commit for Hugging Face Space

.idea/.gitignore

@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml

.idea/Exercises_HuggingFace.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/Obsidian" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.11 (Exercises_HuggingFace)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.11 (Exercises_HuggingFace)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (Exercises_HuggingFace)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/Exercises_HuggingFace.iml" filepath="$PROJECT_DIR$/.idea/Exercises_HuggingFace.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

README.md

@@ -9,4 +9,4 @@ app_file: app.py
 pinned: false
 ---
 
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+Under construction.

app.py

@@ -1,64 +1,112 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import openai
+import os
 
-"""
-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")
+# Load secrets
+CORRECT_PASSWORD = os.getenv("APP_PASSWORD")  # Set this in Hugging Face Spaces secrets
+openai.api_key = os.getenv("OPENAI_API_KEY")     # Also store securely
 
+# -------------------------------
+# Define Functions for App Logic
+# -------------------------------
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+def login(password):
+    """
+    Check the submitted password.
+    If correct, hide the login container and show the main app.
+    Otherwise, return an error message.
+    """
+    if password == CORRECT_PASSWORD:
+        # Hide login page, show main app, and clear error message
+        return gr.update(visible=False), gr.update(visible=True), ""
+    else:
+        # Remain on login page with an error message
+        return gr.update(visible=True), gr.update(visible=False), "❌ Incorrect password. Please try again or contact Ben."
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+def diagnoser_query(user_query):
+    """
+    Process the Diagnoser query.
+    (For now, simply pass the query to the OpenAI API.)
+    """
+    response = openai.ChatCompletion.create(
+        model="gpt-4o-mini",
+        messages=[
+            {
+                "role": "user",
+                "content": (
+                    "What is wrong with this exercise? In other words, what about it should be improved? "
+                    "What stands between it and a perfect exercise that couldn't be better? Don't give solutions yet, "
+                    "only a diagnosis\n "
+                    f"{user_query}"
+                ),
+            }
+        ],
+    )
+    return response["choices"][0]["message"]["content"]
 
-    messages.append({"role": "user", "content": message})
+def distractors_query(user_query):
+    """
+    Process the Distractors brainstorm query.
+    (For now, simply pass the query to the OpenAI API.)
+    """
+    response = openai.ChatCompletion.create(
+        model="gpt-4o-mini",
+        messages=[{"role": "user", "content": user_query}]
+    )
+    return response["choices"][0]["message"]["content"]
 
-    response = ""
+# -------------------------------
+# Build the Gradio Interface
+# -------------------------------
 
-    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
+with gr.Blocks() as demo:
+    # --- Login Page ---
+    with gr.Column(visible=True, elem_id="login_page") as login_container:
+        gr.Markdown("## 🔒 Please Login")
+        password_input = gr.Textbox(label="Enter Password", type="password", placeholder="Enter password to access the app")
+        login_button = gr.Button("Login")
+        login_error = gr.Markdown(value="")  # To display error messages
 
-        response += token
-        yield response
+    # --- Main App (initially hidden) ---
+    with gr.Column(visible=False, elem_id="main_app") as app_container:
+        gr.Markdown("## Core Functionalities")
+        # Use gr.Tabs for persistent states between functionalities
+        with gr.Tabs():
+            with gr.TabItem("Diagnoser"):
+                gr.Markdown("### Diagnoser")
+                diagnoser_input = gr.Textbox(label="Enter Diagnoser Query", placeholder="Type your query here...")
+                diagnoser_button = gr.Button("Submit")
+                diagnoser_output = gr.Textbox(label="Response", interactive=False)
+            with gr.TabItem("Distractors brainstorm"):
+                gr.Markdown("### Distractors brainstorm")
+                distractors_input = gr.Textbox(label="Enter Brainstorm Query", placeholder="Type your query here...")
+                distractors_button = gr.Button("Submit")
+                distractors_output = gr.Textbox(label="Response", interactive=False)
 
+    # -------------------------------
+    # Set Up Interactions
+    # -------------------------------
 
-"""
-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)",
-        ),
-    ],
-)
+    # When the login button is clicked, check the password and update container visibility
+    login_button.click(
+        fn=login,
+        inputs=[password_input],
+        outputs=[login_container, app_container, login_error]
+    )
 
+    # Connect the Diagnoser functionality
+    diagnoser_button.click(
+        fn=diagnoser_query,
+        inputs=[diagnoser_input],
+        outputs=[diagnoser_output]
+    )
 
-if __name__ == "__main__":
-    demo.launch()
+    # Connect the Distractors brainstorm functionality
+    distractors_button.click(
+        fn=distractors_query,
+        inputs=[distractors_input],
+        outputs=[distractors_output]
+    )
+
+# Launch the app
+demo.launch()