Create app.py

app.py

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+
+
+import streamlit as st
+from langchain import HuggingFaceHub
+from apikey import apikey
+from langchain import PromptTemplate, LLMChain
+import os
+
+# Set Hugging Face Hub API token
+# Make sure to store your API token in the `apikey_hungingface.py` file
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = apikey 
+
+# Set up the language model using the Hugging Face Hub repository
+repo_id = "tiiuae/falcon-7b-instruct"
+llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.3, "max_new_tokens": 2000})
+
+# Set up the prompt template
+template = """
+I'm an artificial intelligence assistant.
+I give you helpful, detailed, and polite answers to your questions
+Question: {question}\n\nAnswer: Hmmmm, ok let's think step by step."""
+prompt = PromptTemplate(template=template, input_variables=["question"])
+llm_chain = LLMChain(prompt=prompt, llm=llm)
+
+# Create the Streamlit app
+def main():
+    
+    st.title("savbot - your helpful assistant <3 by srini")
+
+    # Get user input
+    question = st.text_input("what's up?")
+
+    # Generate the response
+    if st.button("help me out!"):
+        with st.spinner("here you go......"):
+            response = llm_chain.run(question)
+        st.success(response)
+
+if __name__ == "__main__":
+    main()