Create app.py

app.py

@@ -0,0 +1,42 @@
+import streamlit as st
+import os
+
+from langchain import PromptTemplate, HuggingFaceHub, LLMChain
+
+st.title("Generating Response with HuggingFace Models")
+st.markdown("## Model: `facebook/blenderbot-1B-distill`")
+
+def get_response(question: str) -> dict:
+    """
+    Generate a response to a given question using the Blenderbot Large Language Model.
+
+    Args:
+        question (str): The question to be answered.
+
+    Returns:
+        dict: A dictionary containing the response text and metadata.
+    """
+    template = """Question: {question}
+
+    Answer: Let's think step by step."""
+
+    prompt = PromptTemplate(template=template, input_variables=["question"])
+
+    llm_chain = LLMChain(prompt=prompt, 
+                        llm=HuggingFaceHub(repo_id="facebook/blenderbot-1B-distill", 
+                                            model_kwargs={"temperature":0, 
+                                                        "max_length":64}))
+
+    response = llm_chain.invoke(question)
+
+    return response
+
+question = st.text_area("Enter your question here...")
+
+if st.button("Get Response") and question:
+    with st.spinner("Generating Response..."):
+        answer = get_response(question)
+    if answer is not None:
+        st.success('Great! Response generated successfully')
+        st.write(answer)
+        st.write(answer["text"])