"Update space"

Signed-off-by: Emmanuel Frimpong Asante <frimpongasante50@gmail.com>

app.py

@@ -87,24 +87,11 @@ class PoultryFarmBot:
         diagnosis = f"The fecal sample indicates the poultry animal is in a {status} condition, diagnosed with {name}. The recommended action is {recom}."
         return diagnosis, name, status, recom
 
-    # Diagnose Disease Using Fecal Image or Symptoms
-    def diagnose_disease(self, image=None, symptoms=None):
+    # Diagnose Disease Using Fecal Image
+    def diagnose_disease(self, image):
         if image is not None and image.size > 0:  # Ensure image is valid and has elements
             return self.predict(image)
-        elif symptoms:
-            # Generate diagnosis using GPT-based model based on the provided symptoms
-            context = f"Symptoms: {symptoms}."
-            response = openai.ChatCompletion.create(
-                model="gpt-3.5-turbo",
-                messages=[
-                    {"role": "system", "content": "You are an advanced poultry farm management system."},
-                    {"role": "user", "content": context}
-                ],
-                max_tokens=150
-            )
-            diagnosis = response['choices'][0]['message']['content'].strip()
-            return diagnosis, None, None, None
-        return "Please provide an image of poultry fecal matter or describe the symptoms.", None, None, None
+        return "Please provide an image of poultry fecal matter for disease detection.", None, None, None
 
 # Initialize the bot instance
 bot = PoultryFarmBot()
@@ -131,46 +118,49 @@ def mistral_response(user_input):
     except Exception as e:
         return f"Error generating response: {str(e)}"
 
-# Gradio interface for disease diagnosis and chatbot response
-def generate_combined_response(image, text):
-    diagnosis, name, status, recom = bot.diagnose_disease(image=image, symptoms=text)
-    if name and status and recom:
-        context = f"The fecal sample indicates the poultry animal is in a {status} condition, diagnosed with {name}. The recommended action is {recom}. "
-        if text:
-            context += f"Additionally, the user asked: '{text}'"
-        advice = mistral_response(context)
-        return diagnosis + "\n\nAdditional Advice: " + advice
-    else:
-        return diagnosis
-
-# Gradio interface styling and layout
-with gr.Blocks(theme=gr.themes.Soft(primary_hue="green", neutral_hue="slate")) as diagnosis_interface:
-    gr.Markdown("# 🐔 Poultry Fecal Diagnostic Assistant")
+
+# Main chatbot function: handles both generative AI and disease detection
+def chatbot_response(image, text):
+    # If an image is provided, perform disease detection
+    if image is not None:
+        diagnosis, name, status, recom = bot.diagnose_disease(image)
+        if name and status and recom:
+            return diagnosis
+        else:
+            return diagnosis  # Return only the diagnostic message if no disease found
+
+    # If no image is provided, proceed with generative AI response
+    return mistral_response(text)
+
+
+# Gradio interface styling and layout with ChatGPT-like theme
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="green", neutral_hue="slate")) as chatbot_interface:
+    gr.Markdown("# 🐔 Poultry Management Chatbot")
     gr.Markdown(
-        "Upload an image of poultry fecal matter or describe symptoms to get a diagnosis and advice."
+        "This chatbot can help you manage your poultry with conversational AI. Upload an image of poultry fecal matter for disease detection or just ask questions!"
     )
 
     with gr.Row():
         with gr.Column(scale=1):
             fecal_image = gr.Image(
-                label="Upload Image of Poultry Feces",
+                label="Upload Image of Poultry Feces (Optional)",
                 type="numpy",
                 elem_id="image-upload",
                 show_label=True,
             )
         with gr.Column(scale=2):
-            symptom_text = gr.Textbox(
-                label="Describe Symptoms or Ask a Question",
-                placeholder="Enter symptoms of the poultry...",
+            user_input = gr.Textbox(
+                label="Type your question or chat with the assistant",
+                placeholder="Ask a question about poultry management...",
                 lines=3,
-                elem_id="symptom-textbox",
+                elem_id="user-input",
             )
 
     output_box = gr.Textbox(
-        label="Diagnosis and Advice",
-        placeholder="The diagnosis and advice will appear here...",
+        label="Response",
+        placeholder="The response will appear here...",
         interactive=False,
-        lines=6,
+        lines=10,
         elem_id="output-box",
     )
 
@@ -180,11 +170,11 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="green", neutral_hue="slate")) a
         elem_id="submit-button"
     )
     submit_button.click(
-        fn=generate_combined_response,
-        inputs=[fecal_image, symptom_text],
+        fn=chatbot_response,
+        inputs=[fecal_image, user_input],
         outputs=[output_box],
     )
 
 # Launch the Gradio interface
 if __name__ == "__main__":
-    diagnosis_interface.launch(debug=True, share=True)
+    chatbot_interface.launch(debug=True, share=True)