Add application file

app.py

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+import gradio as gr
+
+from langchain.prompts import PromptTemplate
+from langchain_openai import ChatOpenAI
+from langchain.schema import HumanMessage
+
+# Set your OpenAI API key (replace 'your-api-key' with the actual key)
+#os.environ["OPENAI_API_KEY"] = "your-api-key"
+
+# Initialize the OpenAI model
+llm = ChatOpenAI(model="gpt-4", temperature=0.5)
+
+# Define a reusable prompt template using LangChain
+template = """
+Turn these questions and answers into a four-paragraph essay about my approach to leadership.
+Please write the essay in the first person, using a conversational and engaging style, 
+as if you're chatting with a friend. Use simple, relatable language and avoid formalities. 
+Add personal touches and insights to make it feel genuine and approachable.
+
+Questions and Answers:
+1. Three words that describe the culture: {q1}
+2. How personal values align with work: {q2}
+3. What drives me to come to work each day: {q3}
+4. Areas I'm working on to be a better leader: {q4}
+5. How I stay connected with daily operations: {q5}
+6. What I want for the people I lead: {q6}
+7. How I show dignity and respect: {q7}
+8. How people perceive me: {q8}
+9. How others describe my management style: {q9}
+10. Three things you need to excel with me: {q10}
+11. What people should always feel free to do: {q11}
+"""
+
+# Create a LangChain prompt template object
+prompt = PromptTemplate(
+    input_variables=["q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "q9", "q10", "q11"],
+    template=template,
+)
+
+# Function to generate the essay using the template and answers
+def stream_leadership_essay(*answers):
+    # Format the prompt with the answers
+    filled_prompt = prompt.format(
+        q1=answers[0], q2=answers[1], q3=answers[2], q4=answers[3], q5=answers[4], 
+        q6=answers[5], q7=answers[6], q8=answers[7], q9=answers[8], q10=answers[9], q11=answers[10]
+    )
+
+    # Send the prompt as a HumanMessage and stream the response
+    response_stream = llm.stream([HumanMessage(content=filled_prompt)])
+    
+    # Yield the content chunk-by-chunk
+    essay = ""
+    for chunk in response_stream:
+        essay += chunk.content
+        yield essay, filled_prompt  # Yield partial essay to the Gradio output in real-time
+
+# Define the Gradio interface (form layout)
+with gr.Blocks() as demo:
+    gr.Markdown("## Leadership Insights Form")
+
+    inputs = [
+        gr.Textbox(label="Three words that describe the culture we are building include..."),
+        gr.Textbox(label="My personal values align with our work in the following ways..."),
+        gr.Textbox(label="Here’s what drives me to get up and come to work each day..."),
+        gr.Textbox(label="I’m working on the following areas to be a better leader for my team."),
+        gr.Textbox(label="I stay connected with the daily realities of our operations by..."),
+        gr.Textbox(label="Here’s what I want for the people I lead and work with. I want them to..."),
+        gr.Textbox(label="I take these actions to show dignity and respect to those I work with."),
+        gr.Textbox(label="At times, people can perceive me as..."),
+        gr.Textbox(label="Others have described my management style as..."),
+        gr.Textbox(label="To excel with me, you need to do three things..."),
+        gr.Textbox(label="When working with me, always feel free to...")
+    ]
+
+    submit_button = gr.Button("Submit")
+
+    # Output area for the response summary
+
+    output = gr.Textbox(label="Generated Leadership Essay", lines=10)
+
+    prompt_template = gr.Textbox(label="This is the prompt that was sent to ChatGPT", lines=10)
+
+    # Link the submit button with the function
+    submit_button.click(
+        stream_leadership_essay,
+        inputs=inputs, 
+        outputs=[output, prompt_template]
+    )
+
+# Launch the Gradio app
+demo.launch()
+
+