Create app.py

app.py

@@ -0,0 +1,69 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+from PIL import Image
+import os
+
+
+from dotenv import load_dotenv
+load_dotenv()
+
+if not api_key:
+    st.error("Hugging Face API key is not set. Please check your .env file or environment variables.")
+
+# App title and description
+st.title("I am Your GrowBuddy 🌱")
+st.write("Let me help you start gardening. Let's grow together!")
+
+def load_model():
+    try:
+        tokenizer = AutoTokenizer.from_pretrained("KhunPop/Gardening")
+        model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b")
+        return tokenizer, model
+    except Exception as e:
+        st.error(f"Failed to load model: {e}")
+        return None, None
+
+tokenizer, model = load_model()
+
+if not tokenizer or not model:
+    st.stop()
+
+# Default to CPU
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+if model is not None:
+    model = model.to(device)
+
+if "messages" not in st.session_state.keys():
+    st.session_state.messages = [
+        {"role": "assistant", "content": "Hello there! How can I help you with gardening today?"}
+    ]
+
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.write(message["content"])
+
+def generate_response(prompt):
+    try:
+        inputs = tokenizer(prompt, return_tensors="pt").to(device)  # Ensure inputs are moved to the device (CPU)
+        outputs = model.generate(**inputs, max_new_tokens=150, temperature=0.7)
+        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        return response
+    except Exception as e:
+        st.error(f"Error during text generation: {e}")
+        return "Sorry, I couldn't process your request."
+
+user_input = st.chat_input("Type your gardening question here:")
+
+if user_input:
+    # Display user message
+    with st.chat_message("user"):
+        st.write(user_input)
+
+with st.chat_message("assistant"):
+        with st.spinner("I'm gonna tell you..."):
+            response = generate_response(user_input)
+            st.write(response)
+
+st.session_state.messages.append({"role": "user", "content": user_input})
+st.session_state.messages.append({"role": "assistant", "content": response})