Create app.py

app.py

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+import streamlit as st
+
+#from langchain_openai import OpenAI
+#from langchain.llms import HuggingFaceEndpoint
+from langchain_community.llms import HuggingFaceEndpoint
+
+#When deployed on huggingface spaces, this values has to be passed using Variables & Secrets setting, as shown in the video :)
+#import os
+#os.environ["OPENAI_API_KEY"] = "sk-PLfFwPq6y24234234234FJ1Uc234234L8hVowXdt"
+
+#Function to return the response
+def load_answer(question):
+    # "text-davinci-003" model is depreciated, so using the latest one https://platform.openai.com/docs/deprecations
+    #llm = OpenAI(model_name="gpt-3.5-turbo-instruct",temperature=0)
+    llm = HuggingFaceEndpoint(repo_id="mistralai/Mistral-7B-Instruct-v0.2", Temperature=0.9)
+    #Last week langchain has recommended to use invoke function for the below please :)
+    answer=llm.invoke(question)
+    return answer
+
+
+#App UI starts here
+st.set_page_config(page_title="Sentiment Analysis", page_icon=":robot:")
+st.header("Sentiment Analysis")
+
+#Gets the user input
+def get_text():
+    input_text = st.text_input("You:", "Pls Write Your Something.......")
+    if input_text.isalpha():
+        st.write(text, 'string', )
+    else:
+        st.write('Please type in a string Only')
+    return input_text
+
+user_input=get_text()
+response = load_answer(user_input)
+
+submit = st.button('Generate')  
+
+#If generate button is clicked
+if submit:
+
+    st.subheader("Answer:")
+
+    st.write(response)