Delete app.py

app.py

@@ -1,59 +0,0 @@
-import streamlit as st
-from langchain.prompts import PromptTemplate
-from langchain_community.llms import CTransformers
-from transformers import set_token
-
-YOUR_HF_API_TOKEN = " "
-set_token("YOUR_HF_API_TOKEN")
-model_name = "TheBloke/llama-2-7b-chat.ggmlv3.q8_0.bin"
-
-def getLLamaResponse(input_text,no_words,blog_style):
-
-    # LLma Model
-    llm = CTransformers(
-        model=model_name,
-        model_type="llma",
-        config={"max_new_tokens": 256, "temperature": 0.01}
-    )
-    
-    # Prompt Template
-    template = """
-                Write a blog for {blog_style} job profile for a topic
-                {input_text} within {no_words} words.
-                """
-    
-    prompt = PromptTemplate(input_variables=["blog_style", "input_text","no_words"],
-                            template=template)
-    
-    # Generate the response from the LLama 2 Model
-    response = llm(prompt.format(style=blog_style, text=input_text, no_words=no_words))
-    print(response)
-    return response
-
-
-
-st.set_page_config(page_title = "Generate Blogs",
-                    page_icon = "🤖",
-                    layout = "centered",
-                    initial_sidebar_state = "collapsed")
-
-st.header("Generate Blogs 🤖")
-
-input_text = st.text_input("Enter the Blog Topic")
-
-# Creating 2 more columns for additional 2 fields
-col1, col2 = st.columns([5,5])
-
-with col1:
-    no_words = st.text_input("No of words")
-
-with col2:
-    blog_style=st.selectbox("Writing the blog for",
-                            ("Researchers","Data Scientist","Common People"),index=0)
-
-submit = st.button("Generate")
-
-# Final Response
-if submit:
-    st.write(getLLamaResponse(input_text,no_words,blog_style))
-