Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Initialize the model
+model_name = "sarvamai/sarvam-2b-v0.5"
+pipe = pipeline("text-generation", model=model_name, device=0)
+
+# Supported languages
+LANGUAGES = ["English", "Bengali", "Gujarati", "Hindi", "Kannada", "Malayalam", "Marathi", "Oriya", "Punjabi", "Tamil", "Telugu"]
+
+def chatbot(message, history, language):
+    # Prepare the prompt
+    prompt = f"Conversation in {language}:\n"
+    for human, ai in history:
+        prompt += f"Human: {human}\nAI: {ai}\n"
+    prompt += f"Human: {message}\nAI:"
+
+    # Generate response
+    response = pipe(prompt, max_new_tokens=100, temperature=0.7, repetition_penalty=1.1)[0]['generated_text']
+    
+    # Extract only the AI's response
+    ai_response = response.split("AI:")[-1].strip()
+    
+    return ai_response
+
+# Create the Gradio interface
+iface = gr.ChatInterface(
+    chatbot,
+    additional_inputs=[
+        gr.Dropdown(choices=LANGUAGES, label="Select Language", value="English")
+    ],
+    title="Multilingual Indian Chatbot",
+    description="Chat in multiple Indian languages using the sarvam-2b model.",
+    examples=[
+        ["Hello, how are you?", "English"],
+        ["नमस्ते, आप कैसे हैं?", "Hindi"],
+        ["வணக்கம், எப்படி இருக்கிறீர்கள்?", "Tamil"],
+    ],
+    theme="soft"
+)
+
+# Launch the interface
+iface.launch()