Upload app.py

app.py

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+import streamlit as st
+from langchain.prompts import PromptTemplate
+from langchain.llms import CTransformers
+
+#Function to get the response back
+def getLLMResponse(form_input,email_sender,email_recipient,email_style):
+    #llm = OpenAI(temperature=.9, model="text-davinci-003")
+
+    # Wrapper for Llama-2-7B-Chat, Running Llama 2 on CPU
+
+    #Quantization is reducing model precision by converting weights from 16-bit floats to 8-bit integers, 
+    #enabling efficient deployment on resource-limited devices, reducing model size, and maintaining performance.
+
+    #C Transformers offers support for various open-source models, 
+    #among them popular ones like Llama, GPT4All-J, MPT, and Falcon.
+
+
+    #C Transformers is the Python library that provides bindings for transformer models implemented in C/C++ using the GGML library
+
+    llm = CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin',     #https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main
+                    model_type='llama',
+                    config={'max_new_tokens': 256,
+                            'temperature': 0.01})
+    
+    
+    #Template for building the PROMPT
+    template = """
+    Write a email with {style} style and includes topic :{email_topic}.\n\nSender: {sender}\nRecipient: {recipient}
+    \n\nEmail Text:
+    
+    """
+
+    #Creating the final PROMPT
+    prompt = PromptTemplate(
+    input_variables=["style","email_topic","sender","recipient"],
+    template=template,)
+
+  
+    #Generating the response using LLM
+    response=llm(prompt.format(email_topic=form_input,sender=email_sender,recipient=email_recipient,style=email_style))
+    print(response)
+
+    return response
+
+
+st.set_page_config(page_title="Generate Emails",
+                    page_icon='📧',
+                    layout='centered',
+                    initial_sidebar_state='collapsed')
+st.header("Generate Emails 📧")
+
+form_input = st.text_area('Enter the email topic', height=275)
+
+#Creating columns for the UI - To receive inputs from user
+col1, col2, col3 = st.columns([10, 10, 5])
+with col1:
+    email_sender = st.text_input('Sender Name')
+with col2:
+    email_recipient = st.text_input('Recipient Name')
+with col3:
+    email_style = st.selectbox('Writing Style',
+                                    ('Formal', 'Appreciating', 'Not Satisfied', 'Neutral'),
+                                       index=0)
+
+
+submit = st.button("Generate")
+
+#When 'Generate' button is clicked, execute the below code
+if submit:
+    st.write(getLLMResponse(form_input,email_sender,email_recipient,email_style))