Create app.py file

app.py

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+!pip install keras_nlp kaggle gradio tensorflow
+!pip install huggingface_hub
+
+#importing libraries
+import keras_nlp
+import os
+import tensorflow as tf
+import kagglehub
+
+
+#Loading the model from kaggle
+#For safety, add this to kaggle or google secrets
+os.environ['KAGGLE_USERNAME'] = 'ayomidezulkazeem' #username
+os.environ['KAGGLE_KEY'] = '245a313b018fe8355198d9c48413b991' #kaggle_key
+
+
+# Download latest version
+path = kagglehub.model_download("ayomidezulkazeem/hydrosense/keras/gemma-hydrosense-instruct-2b")
+
+print("Path to model files:", path)
+print("Model path:", path)
+
+
+model_path = path
+gemma_lm = keras_nlp.models.GemmaCausalLM.from_preset(model_path)
+
+
+
+import gradio as gr
+import time
+from huggingface_hub import InferenceClient
+import os
+
+custom_css = """
+@import url('https://fonts.googleapis.com/css2?family=Edu+AU+VIC+WA+NT+Dots:[email protected]&family=Give+You+Glory&family=Sofia&family=Sunshiney&family=Vujahday+Script&display=swap');
+.gradio-container, .gradio-container * {
+     font-family: "Playfair Display", serif;
+  font-optical-sizing: auto;
+  font-weight: <weight>;
+  font-style: normal;
+}
+"""
+js = """
+function refresh() {
+    const url = new URL(window.location);
+    if (url.searchParams.get('__theme') === 'light') {
+        url.searchParams.set('__theme', 'light');
+        window.location.href = url.href;
+    }
+}
+"""
+
+
+previous_sessions = []
+memory = [{}]
+
+
+
+def inference(prompt_text):
+  prompt_text = prompt_text
+  generated_text = gemma_lm.generate(prompt_text)
+
+  #Apply post-processing
+  formatted_output = post_process_output(prompt_text, generated_text)
+  print(formatted_output)
+
+  #adding a bit of delay
+  time.sleep(1)
+  result = formatted_output
+  sessions = add_session(prompt_text)
+  return result, sessions
+
+
+def remember(prompt, result):
+    global memory
+    # Store the session as a dictionary
+    session = {'prompt': prompt, 'result': result}
+    memory.append(session)
+
+    # Update previous_sessions for display
+    session_display = [f"Q: {s['prompt']} \nA: {s['result']}" for s in memory]
+    
+    return "\n\n".join(session_display)  # Return formatted sessions as a string
+
+
+def add_session(prompt_text):
+    global previous_sessions
+    session_name = ' '.join(prompt_text.split()[:5])
+    
+    if session_name and session_name not in previous_sessions:
+        previous_sessions.append(session_name)
+        
+    return "\n".join(previous_sessions)  # Return only the session logs as a string
+
+
+def clear_sessions():
+    global previous_sessions
+    previous_sessions.clear()
+    return "\n".join(previous_sessions)
+
+def clear_fields():
+    return "", ""  # Return empty strings to clear the prompt and output fields
+
+
+with gr.Blocks(theme='gradio/soft', css=custom_css) as demo:
+    gr.Markdown("<center><h1>HydroFlow LLM Demo</h1></center>")
+    gr.Markdown("<center><h3><i><em>Ask me anything on Wastewater or Stormwater!</em></i></h3></center>")
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("## Previous Sessions")
+            session_list = gr.Textbox(label="Sessions", value="\n".join(previous_sessions), interactive=False, lines=4, max_lines=20)
+            add_button = gr.Button("New Session")
+            clear_session = gr.Button("Clear Session")
+
+        with gr.Column(scale=2):
+            output = gr.Textbox(label="Result", lines=5, max_lines=20)
+            prompt = gr.Textbox(label="Enter your Prompt here", max_lines=20)
+            
+            with gr.Row():
+                generate_btn = gr.Button("Generate Answer", variant="primary", size="sm")
+                reset_btn = gr.Button("Clear Content", variant="secondary", size="sm", elem_id="primary")
+
+
+    generate_btn.click(
+        fn=inference,
+        inputs=[prompt],
+        outputs=[output, session_list],
+    )
+
+    prompt.submit(
+        fn=inference,
+        inputs=[prompt],
+        outputs=[output, session_list],
+    )
+
+    reset_btn.click(
+        lambda: ("", ""),
+        inputs=None,
+        outputs=[prompt, output]
+    )
+
+
+    # Button to clear the prompt and output fields
+    add_button.click(
+        fn=clear_fields,  # Only call the clear_fields function
+        inputs=None,      # No inputs needed
+        outputs=[prompt, output]  # Clear the prompt and output fields
+)
+
+
+    clear_session.click(
+        fn=clear_sessions,
+        inputs=None,
+        outputs=[session_list]
+    )
+
+demo.launch(share=True)