Create app.py

app.py

@@ -0,0 +1,48 @@
+import streamlit as st
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+
+model_name = "codellama/CodeLlama-7b-Python-hf"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+device = torch.device("cuda" if torch.cuda.is_available() else 'cpu')
+model = model.to(device)
+
+# prompt = st.text_area("Enter your prompt:")
+
+
+# def translate_text(text, source_lang, target_lang):
+#     tokenizer.src_lang = source_lang
+#     encoded_text = tokenizer(text, return_tensors="pt").to(device)
+
+#     generated_tokens = model.generate(**encoded_text, forced_bos_token_id=tokenizer.lang_code_to_id[target_lang])
+
+#     #Decode the output
+#     translated_text = tokenizer.decode(generated_tokens[0], skip_special_tokens=True)
+#     return translated_text
+
+
+st.markdown("### Python Code Helper")
+# source_language = ''
+# target_language = ''
+# source = st.sidebar.selectbox('Source Language', languages)
+# if source:
+#     source_language = lang_dict.get(source)
+#     st.write(source_language)
+
+# target = st.sidebar.selectbox('Target Language', languages)
+# if target:
+#     target_language = lang_dict.get(target)
+#     st.write(target_language)
+
+with st.form(key="myForm"):
+    prompt = st.text_area("Enter your Prompt")
+    submit = st.form_submit_button("Submit", type='primary')
+
+if submit and prompt:
+    with st.spinner("Generating Response"):
+    response = model.invoke(prompt)
+    st.write(response)
+