app edited

app.py

@@ -0,0 +1,93 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer, pipeline
+from threading import Thread
+
+# Model Initialization
+model_id = "rasyosef/Llama-3.2-180M-Amharic-Instruct"
+
+st.title("Llama 3.2 180M Amharic Chatbot Demo")
+st.write("""
+This chatbot was created using [Llama-3.2-180M-Amharic-Instruct](https://huggingface.co/rasyosef/Llama-3.2-180M-Amharic-Instruct), 
+a finetuned version of the 180 million parameter Llama 3.2 Amharic transformer model.
+""")
+
+# Load the tokenizer and model
+@st.cache_resource
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained(model_id)
+    model = AutoModelForCausalLM.from_pretrained(model_id)
+    llama_pipeline = pipeline(
+        "text-generation",
+        model=model,
+        tokenizer=tokenizer,
+        pad_token_id=tokenizer.pad_token_id,
+        eos_token_id=tokenizer.eos_token_id
+    )
+    return tokenizer, llama_pipeline
+
+tokenizer, llama_pipeline = load_model()
+
+# Generate text
+def generate_response(prompt, chat_history, max_new_tokens):
+    history = []
+
+    # Build chat history
+    for sent, received in chat_history:
+        history.append({"role": "user", "content": sent})
+        history.append({"role": "assistant", "content": received})
+
+    history.append({"role": "user", "content": prompt})
+
+    if len(tokenizer.apply_chat_template(history)) > 512:
+        return "Chat history is too long."
+    else:
+        streamer = TextIteratorStreamer(
+            tokenizer=tokenizer,
+            skip_prompt=True,
+            skip_special_tokens=True,
+            timeout=300.0
+        )
+        thread = Thread(target=llama_pipeline, kwargs={
+            "text_inputs": history,
+            "max_new_tokens": max_new_tokens,
+            "repetition_penalty": 1.15,
+            "streamer": streamer
+        })
+        thread.start()
+
+        generated_text = ""
+        for word in streamer:
+            generated_text += word
+            response = generated_text.strip()
+            yield response
+
+# Streamlit Input and Chat Interface
+st.sidebar.header("Chatbot Configuration")
+max_tokens = st.sidebar.slider("Maximum new tokens", min_value=8, max_value=256, value=64, help="Larger values result in longer responses.")
+
+st.subheader("Chat with the Amharic Chatbot")
+chat_history = st.session_state.get("chat_history", [])
+
+# User Input
+user_input = st.text_input("Your message:", placeholder="Type your message here...")
+
+if st.button("Send"):
+    if user_input:
+        st.session_state.chat_history = st.session_state.get("chat_history", [])
+        st.session_state.chat_history.append((user_input, ""))
+        responses = generate_response(user_input, st.session_state.chat_history, max_tokens)
+
+        # Stream output
+        with st.spinner("Generating response..."):
+            final_response = ""
+            for response in responses:
+                final_response = response
+                st.session_state.chat_history[-1] = (user_input, final_response)
+                st.experimental_rerun()
+
+# Display Chat History
+if "chat_history" in st.session_state:
+    for i, (user_msg, bot_response) in enumerate(st.session_state.chat_history):
+        st.write(f"**User {i+1}:** {user_msg}")
+        st.write(f"**Bot:** {bot_response}")
+