update source code

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):
+    # Wrapper for LLAMA2-7B- Chat, Running LLAM2 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 Transformer offers support for various open-source models.
+    # among them popular ones like LLAMA, GPT4All-J, MPT, and Falcon,
+
+    # C Transformers are Python library that provides bindings for transformer models implemented
+    # in C/ C++ using GGML library.
+
+    # https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main
+    llm = CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin',
+                        model_type='llama', config={'max_new_tokens': 256,
+                                                    'temperature': 0.01})
+
+    # Template for building the PROMPT
+    template = """
+    Write an 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', ('Format', '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))

requirements.txt

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+sentence-transformers==2.2.2
+uvicorn==0.24.0.post1
+ctransformers==0.2.27
+fastapi==0.105.0
+ipykernel==6.27.1
+langchain==0.1.0
+python-box==7.1.1