Create app.py

app.py

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+import gradio as gr
+import matplotlib.pyplot as plt
+from huggingface_hub import InferenceClient
+
+# Initialize Hugging Face Inference Client
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
+# Set default values for model parameters and system message
+DEFAULT_MAX_TOKENS = 512
+DEFAULT_TEMPERATURE = 0.7
+DEFAULT_TOP_P = 0.95
+DEFAULT_SYSTEM_MESSAGE = "You are an expert in environmental psychology. Provide expert recommendations."
+
+def generate_recommendations(comfort, social_interaction, stressors, privacy, max_tokens=DEFAULT_MAX_TOKENS, temperature=DEFAULT_TEMPERATURE, top_p=DEFAULT_TOP_P, system_message=DEFAULT_SYSTEM_MESSAGE):
+    # Construct the input message for the model with context
+    message = (f"{system_message}\n"
+               f"On a scale of 1-5, with 5 being the highest and 1 being the least ideal, the user rated the following:\n"
+               f"Comfort and Well-being: {comfort}\n"
+               f"Social Interaction: {social_interaction}\n"
+               f"Environmental Stressors: {stressors}\n"
+               f"Privacy and Personal Space: {privacy}\n"
+               f"Provide recommendations for improving the environment based on these ratings.")
+
+    # Generate recommendations using the Hugging Face model
+    response = client.chat_completion(
+        [{"role": "user", "content": message}],
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p
+    )
+
+    recommendations = response.choices[0].message['content']
+    return recommendations
+
+def analyze_environmental_concerns(comfort, social_interaction, stressors, privacy):
+    # Generate a bar graph for the input scores
+    fig, ax = plt.subplots()
+    categories = ["Comfort and Well-being", "Social Interaction", "Environmental Stressors", "Privacy and Personal Space"]
+    values = [comfort, social_interaction, stressors, privacy]
+    ax.bar(categories, values, color=['blue', 'orange', 'green', 'red'])
+    ax.set_ylabel('Score')
+    ax.set_title('Environmental Psychology Concerns')
+    
+    # Generate recommendations using the model
+    recommendations = generate_recommendations(comfort, social_interaction, stressors, privacy)
+    
+    return fig, recommendations
+
+# Create the Gradio interface without exposing internal parameters to the user
+inputs = [
+    gr.Slider(minimum=1, maximum=5, step=1, label="Comfort and Well-being"),
+    gr.Slider(minimum=1, maximum=5, step=1, label="Social Interaction"),
+    gr.Slider(minimum=1, maximum=5, step=1, label="Environmental Stressors"),
+    gr.Slider(minimum=1, maximum=5, step=1, label="Privacy and Personal Space"),
+]
+
+outputs = [
+    gr.Plot(label="Concerns Graph"),
+    gr.Textbox(label="Recommendations", lines=5)
+]
+
+gr.Interface(
+    fn=analyze_environmental_concerns,
+    inputs=inputs,
+    outputs=outputs,
+    title="Mazingira: Environmental Psychology Concerns Analyzer",
+    description="Input your environmental psychology concerns to receive personalized recommendations and a visual graph."
+).launch()