I added using Local LLM using wtih streamlit. I share the model link.

README.md

@@ -16,7 +16,8 @@ Current examples include:
 - LangChain Quickstart
 - LangChain PromptTemplate
 - Chat with user feedback
-
+- local-LLm (Firstly download the model from HuggingFace, dont need API key)
+   https://huggingface.co/BashitAli/llama-2-7b-chat.ggmlv3.q5_K_M
 ## Demo App
 
 [![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://llm-examples.streamlit.app/)

pages/local-LLm.py

@@ -0,0 +1,46 @@
+import streamlit as st
+from langchain.prompts import PromptTemplate
+from langchain.llms import CTransformers
+
+
+
+def getLlamaResponse(input_text, no_words, category):
+    llm = CTransformers(model = 'model/path', 
+                        model_type = 'model_type', # using llama from share link
+                        config={'max_new_tokens': 256,
+                                'temperature': 0.01})
+
+
+    template = """Write a  {category} on {input_text} in less than {no_words} word"""
+
+    prompt = PromptTemplate(input_variables = ["input_text", "no_words", "category"],
+                            template = template)
+
+
+    respone = llm(prompt.format(category=category,input_text=input_text,no_words=no_words))
+    print(respone)
+    return respone
+
+
+
+st.set_page_config(page_title = "Content-Creater",
+                    layout='centered',
+                    initial_sidebar_state = "collapsed")
+
+
+
+input_text = st.text_input("Write your creative words")
+
+col1,col2 = st.columns([5,5])
+
+with col1:
+    no_words = st.text_input('Number of words')
+with col2:
+    category = st.selectbox("category",
+                              ('Essays', 'Poem', 'Joke', 'Blog'),
+                              index=0)
+
+submit = st.button("Start")
+
+if submit:
+    st.write(getLlamaResponse(input_text, no_words, category))