Create app.py

app.py

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+import gradio as gr
+import openai
+import os
+
+# Set your OpenAI API key
+openai.api_key = os.getenv('OPENAI_API_KEY')
+
+def print_like_dislike(x: gr.LikeData):
+    print(x.index, x.value, x.liked)
+
+def add_text(history, text):
+    history.append((text, "**That's cool!**"))
+    return history
+
+def add_file(history, file):
+    # Assuming you want to display the name of the uploaded file
+    file_info = (f"Uploaded file: {file.name}", "")
+    history.append(file_info)
+    return history
+
+def initialize_chat():
+    # This function initializes the chat with a "Hello" message.
+    return [(None, "Hello, my name is <strong>Andrea</strong>, I'm a <em>Friendly Chatbot</em> and will help you with your learning journey. <br>Select a question from below to start!")]
+
+chat_history = initialize_chat()
+
+def generate_response(selected_question):
+    global chat_history
+    prompt = selected_question  # Ensure selected_question is a string
+    
+    try:
+        response = openai.Completion.create(
+            engine="text-davinci-003",
+            prompt=prompt,
+            max_tokens=150,
+            n=1,
+            stop=None,
+            temperature=0.7,
+        ).choices[0].text.strip()
+        
+        topics_str = "Topic analysis not available"
+        
+        # Adjusted to return a list of tuples as expected by the Chatbot component
+        new_response = (None, response + "\n\nTopics: " + topics_str)
+        chat_history.append(new_response)
+    except Exception as e:
+        new_response = (None, f"Error generating response: {e}")
+        chat_history.append(new_response)
+    
+    return chat_history
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+    """
+    # Child safe chatbot project!
+    In the realm of digital communication, the development of an advanced chatbot that incorporates topic modeling represents a significant leap towards enhancing user interaction and maintaining focus during conversations. This innovative chatbot design is specifically engineered to streamline discussions by guiding users to select from a curated list of suggested questions. This approach is crafted to mitigate the risk of diverging into off-topic dialogues, which are common pitfalls in conventional chatbot systems.
+    """
+    )
+    
+    chatbot = gr.Chatbot(
+        initialize_chat(),
+        elem_id="chatbot",
+        bubble_full_width=False,
+        label="Safe Chatbot v1",
+        avatar_images=(None, os.path.join(os.getcwd(), "avatar.png"))
+    )
+    
+    with gr.Row():
+        txt = gr.Textbox(scale=4, show_label=False, placeholder="Select Question", container=False, interactive=False)  # Adjust based on need
+        btn = gr.Button("Submit")
+
+    btn.click(fn=generate_response, inputs=[txt], outputs=chatbot)
+
+    examples = [
+        ["What are the basic requirements to become an airforce pilot?"],
+        ["How long does it take to train as an airforce pilot?"],
+        ["Can you describe a day in the life of an airforce pilot?"]
+    ]
+    gr.Examples(examples, inputs=[txt], outputs=[chatbot], label="Select Question")
+
+    chatbot.like(print_like_dislike, None, None)
+
+if __name__ == "__main__":
+    demo.launch()