Added large files with LFS

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Llama-Blog-Generation.webm filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,121 @@
+import streamlit as st
+from langchain.prompts import PromptTemplate
+from langchain_community.llms import CTransformers
+import time
+
+# List of blog styles
+BLOG_STYLES = [
+    'Researchers', 
+    'Data Scientist', 
+    'Common People', 
+    'Software Engineers', 
+    'Product Managers', 
+    'Healthcare Professionals', 
+    'Teachers', 
+    'Entrepreneurs', 
+    'Marketers', 
+    'Students'
+]
+
+# Function to get response from LLama 2 model
+def getLLamaResponse(input_text, no_words, blog_style):
+    # Initialize the LLama 2 model
+    llm = CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin',
+                        model_type='llama',
+                        config={'max_new_tokens': 256, 'temperature': 0.01})
+
+    # Define the 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))
+    return response
+
+# Function to generate topics from LLama 2 model
+def generate_topics_from_llama(input_text):
+    # Initialize the LLama 2 model
+    llm = CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin',
+                        model_type='llama',
+                        config={'max_new_tokens': 256, 'temperature': 0.01})
+
+    # Define the prompt template for generating topics
+    topic_template = """
+    Generate a list of blog topics based on the keywords: {input_text}
+    """
+    prompt = PromptTemplate(input_variables=["input_text"], template=topic_template)
+    
+    # Generate the topics from the LLama 2 model
+    topics_response = llm(prompt.format(input_text=input_text))
+    # Split the response into a list of topics
+    topics = topics_response.split('\n')
+    return [topic.strip() for topic in topics if topic.strip()]
+
+# Set up the Streamlit page configuration
+st.set_page_config(page_title="LLAMA 2 Generate Blogs",
+                   page_icon='images/favicon.ico',  # Updated favicon source
+                   layout='centered',
+                   initial_sidebar_state='collapsed')
+
+# Display image using st.image
+st.image('images/ConcertIDC_Logo_Stack.png', width=50, caption='')
+
+# Page header with favicon icon
+st.markdown(
+    """
+    <h1 style="display:flex; align-items:center;">
+        LLAMA 2 Generate Blogs 
+    </h1>
+    """, 
+    unsafe_allow_html=True
+)
+
+# Placeholder for topics and selected topic
+if 'topics' not in st.session_state:
+    st.session_state.topics = []
+
+if 'selected_topic' not in st.session_state:
+    st.session_state.selected_topic = None
+
+# Input field for the blog topic
+input_text = st.text_input("Enter the Blog Topic Keywords")
+
+# Button to generate topics
+generate_topics = st.button("Generate Topics")
+
+# Generate and display topics
+if generate_topics:
+    with st.spinner('Generating topics...'):
+        st.session_state.topics = generate_topics_from_llama(input_text)
+        time.sleep(2)  # Simulate processing time
+
+# Display generated topics in bullet format
+if st.session_state.topics:
+    # st.markdown("### Suggested Topics")
+    # for topic in st.session_state.topics:
+    #     st.markdown(f"- {topic}")
+    
+    # Selection for one of the topics
+    selected_topic = st.selectbox('Select a Topic', st.session_state.topics)
+    st.session_state.selected_topic = selected_topic
+
+    # Optional input field for the number of words
+    no_words = st.text_input('Number of Words (optional)', value='')
+
+    # Dropdown selection for the blog style
+    blog_style = st.selectbox('Writing the blog for', BLOG_STYLES, index=0)
+    
+    # Button to generate the blog content
+    generate_blog = st.button("Generate Blog Content")
+
+    # Display the generated blog response
+    if generate_blog:
+        with st.spinner('Generating blog content...'):
+            if no_words == '':
+                no_words = '500'  # Default to 500 words if not provided
+            response = getLLamaResponse(st.session_state.selected_topic, no_words, blog_style)
+            time.sleep(2)  # Simulate processing time
+            st.write(response)

models/llama-2-7b-chat.ggmlv3.q8_0.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3bfdde943555c78294626a6ccd40184162d066d39774bd2c98dae24943d32cc3
+size 7160799872

requirements.txt

@@ -0,0 +1,6 @@
+sentence-transformers
+uvicorn
+ctransformers
+langchain
+python-box
+streamlit