Adding application and requirements files

app.py

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+import os
+import json
+import gradio as gr
+import google.generativeai as genai
+
+GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
+genai.configure(api_key=GOOGLE_API_KEY)
+
+# Set up the model
+generation_config = {
+  "temperature": 0.9,
+  "top_p": 1,
+  "top_k": 1,
+  "max_output_tokens": 2048,
+}
+
+safety_settings = [
+  {
+    "category": "HARM_CATEGORY_HARASSMENT",
+    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+  },
+  {
+    "category": "HARM_CATEGORY_HATE_SPEECH",
+    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+  },
+  {
+    "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+  },
+  {
+    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+  }
+]
+
+model = genai.GenerativeModel(
+    model_name="gemini-pro",
+    generation_config=generation_config,
+    safety_settings=safety_settings
+)
+
+task_description = " You are an SMS (Short Message Service) reader who reads every message that the short message service centre receives and you need to classify each message among the following categories: {}<div>Let the output be a softmax function output giving the probability of message belonging to each category.</div><div>The sum of the probabilities should be 1</div><div>The output must be in JSON format</div>"
+
+def classify_msg(categories, message):
+    prompt_parts = [
+        task_description.format(categories),
+        f"Message: {message}",
+        "Category: ",
+    ]
+
+    response = model.generate_content(prompt_parts)
+
+    json_response = json.loads(
+        response.text[response.text.find('{'):response.text.rfind('}') + 1]
+    )
+
+    return gr.Label(json_response)
+
+def clear_inputs_and_outputs():
+    return [None, None, None]
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+        <center><h1>Multi-language Text Classifier using Gemini Pro</h1></center> \
+        This space demos SMS and text in general classification using Gemini Pro<br> \
+For the categories, enter a list of words separated by commas<br><br>
+        """
+    )
+    with gr.Row():
+        with gr.Column():
+            with gr.Row():
+                categories = gr.Textbox(label="Categories", placeholder="Input the list of categories as comma separated words")
+            with gr.Row():
+                message = gr.Textbox(label="Message", placeholder="Enter Message")
+            with gr.Row():
+                clr_btn = gr.Button(value="Clear", variant="secondary")
+                csf_btn = gr.Button(value="Classify")
+        with gr.Column():
+            lbl_output = gr.Label(label="Prediction")
+
+    clr_btn.click(
+        fn=clear_inputs_and_outputs,
+        inputs=[],
+        outputs=[categories, message, lbl_output],
+    )
+    csf_btn.click(
+        fn=classify_msg,
+        inputs=[categories, message],
+        outputs=[lbl_output],
+    )
+
+    gr.Examples(
+        examples=[
+            ['Normal, Promotional, Urgent', 'Will you be passing by?'],
+            ['Spam, Ham', 'Plus de 300 % de perte de poids pendant le régime.'],
+            ['Χαρούμενος, Δυστυχισμένος', 'Η εξυπηρέτηση σας ήταν απαίσια'],
+            ['مهم، أقل أهمية ', 'خبر عاجل']
+        ],
+        inputs=[categories, message],
+        outputs=lbl_output,
+        fn=classify_msg,
+        cache_examples=True,
+    )
+
+demo.launch()

requirements.txt

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+google-generativeai