Upload app.py

app.py

@@ -0,0 +1,56 @@
+import streamlit as st
+from langchain.prompts import PromptTemplate
+from langchain_community.llms import CTransformers
+
+def getLLamaResponse(input_text,no_words,blog_style):
+
+    # LLma Model
+    llm=CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin',
+                      model_type='llama',
+                      config={'max_new_tokens':256,
+                              'temperature':0.01})
+    
+    # Prompt Template
+    # 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(blog_style=blog_style, input_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))
+