Spaces:
Sleeping
Sleeping
First model version
Browse files- README.md +4 -4
- app.py +103 -0
- backend.py +27 -0
- llm.py +55 -0
- pages/1_β€οΈ_Chat_Page.py +8 -0
- pages/2_π_Templates_Page.py +6 -0
- requirements.txt +4 -0
README.md
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---
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title: Cold Email
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emoji:
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colorFrom:
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colorTo: red
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sdk: streamlit
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sdk_version: 1.
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app_file: app.py
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pinned: false
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---
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---
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title: Cold Email Part One
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emoji: π
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colorFrom: red
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colorTo: red
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sdk: streamlit
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sdk_version: 1.38.0
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app_file: app.py
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pinned: false
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---
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app.py
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import streamlit as st
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import pandas as pd
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import traceback
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import backend
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st.set_page_config(page_title="Cold Email Generator", layout="wide",initial_sidebar_state='collapsed')
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def main():
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try:
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# ------------------------------------- Custom CSS -------------------------------------------------------------
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st.markdown(
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"""
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<style>
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.css-1d391kg { /* Adjust this class based on your Streamlit version */
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padding-left: 10px;
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padding-right: 10px;
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}
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</style>
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""",
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unsafe_allow_html=True
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)
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# --------------------------------------------------------------------------------------------------
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st.header("Cold Email Generator")
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split_screen_col1, split_screen_col2 = st.columns(2)
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# Input fields
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with split_screen_col1:
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industry_col, recipient_col = st.columns(2)
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with industry_col:
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industry = st.text_input("Industry")
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with recipient_col:
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recipient_role = st.text_input("Recipient Name")
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details_col1, details_col2 = st.columns(2)
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with details_col1:
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details_type = st.radio("Select Details Type", ["Personal Details", "Company Details"])
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with details_col2:
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name = st.text_input("Senders Name")
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designation = ""
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company_name = ""
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if details_type == "Personal Details":
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designation = st.text_input("Designation/Role")
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else:
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company_name = st.text_input("Company Name")
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designation = st.text_input("Designation/Role")
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tone = st.selectbox("Tone", ["Formal", "Casual", "Friendly", "Professional"])
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context = st.text_area("Context")
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is_generate_clicked = st.button("Generate Email")
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with split_screen_col2:
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if is_generate_clicked :
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generated_email = backend.collect_context_for_email(industry,recipient_role, tone, context, details_type, name, designation, company_name)
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st.session_state.edited_email = st.text_area("Generated Email", value = generated_email, height=300, disabled=False)
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st.session_state.is_generate_clicked = True
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else:
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st.text_area("Generated Email", height=300, disabled=True)
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# Edit and Send button
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if st.button("Completed Editing"):
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st.session_state.is_cmp_editing_clicked = True
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st.markdown("---")
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if st.session_state.get("is_cmp_editing_clicked") and st.session_state.get("is_generate_clicked") :
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st.subheader("Chat to refine your email")
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email_col1, email_col2 = st.columns(2)
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with email_col1:
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sender_email = st.text_input("Sender's Email")
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with email_col2:
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receiver_email = st.text_input("Receiver's Email")
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subject = st.text_input("Subject")
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st.text_area("Generated Email", value=st.session_state.edited_email, height=300, disabled=False)
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is_send_clicked = ""
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if st.session_state.get("is_cmp_editing_clicked") :
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is_send_clicked = st.button("Send Email")
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if is_send_clicked:
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st.subheader("All done, real-time email sending will be implemented in part2 π ")
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except Exception as err:
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traceback.print_exc()
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print(err)
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if __name__ == "__main__":
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main()
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backend.py
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import llm
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import traceback
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def collect_context_for_email(industry, rec_name, tone, context, details_type, name, designation, company_name =""):
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try:
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print("number of calls")
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user_input = {
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"industry": industry,
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"recipient_name": rec_name,
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"tone": tone,
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"context": context,
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"details_type": details_type,
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"name": name,
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"designation": designation,
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"company_name": company_name
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}
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llm_output = llm.chat_with_groq(user_input)
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return llm_output
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except Exception as err:
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traceback.print_exc()
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print(err)
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llm.py
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# Default
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import os
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from groq import Groq
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import traceback
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client = Groq(
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# This is the default and can be omitted
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api_key=os.environ.get("GROQ_API_KEY"),
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)
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def chat_with_groq(user_input, additional_info=None):
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try:
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template_prompt = f"""
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You are a professional email writer who specialises in writing cold email.
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Generate a cold email to {user_input['recipient_name']} based on the following information:
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Industry: {user_input['industry']}
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Tone: {user_input['tone']}
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Context: {user_input['context']}
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Senders Name: {user_input['name']}
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Designation: {user_input['designation']}
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Incorporate all information and write a compelling email.
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"""
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# test purposes:
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# return template_prompt
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chat_completion = client.chat.completions.create(
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messages=[
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{
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"role": "system",
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"content": "You are an expert email writer specializing in cold emails.",
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},
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{
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"role": "user",
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"content": template_prompt,
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}
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],
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model="mixtral-8x7b-32768",
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)
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generated_email = chat_completion.choices[0].message.content
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return generated_email
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except Exception as err:
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traceback.print_exc()
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print(err)
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pages/1_β€οΈ_Chat_Page.py
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import streamlit as st
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import pandas as pd
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import traceback
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import llm
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st.header("To be implemented in part 2")
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pages/2_π_Templates_Page.py
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import streamlit as st
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import pandas as pd
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import traceback
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import llm
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st.header("To be implemented in part 2")
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requirements.txt
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streamlit
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pandas
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groq
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python-dotenv
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