Merge pull request #583 from yashksaini-coder/yash/fix-582

Feature request: Cold Email Generator App

Generative Models/Cold Email generator/.env

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+GROQ_API_KEY=your_groq_api_key

Generative Models/Cold Email generator/README.md

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+# 📧 Cold Mail Generator
+
+A cold email generator for service companies using Groq, Langchain, and Streamlit. This tool allows users to input the URL of a company's careers page, extracting job listings and generating personalized cold emails that include relevant portfolio links sourced from a vector database based on specific job descriptions.
+
+## Features
+
+- Input the URL of a company's careers page.
+- Extract job listings to generate personalized cold emails.
+- Include relevant portfolio links based on job descriptions.
+
+## Usage Example
+
+Imagine a scenario where a software development company can provide dedicated engineers to a major company. This tool facilitates outreach via personalized cold emails.
+
+
+## Set-up
+
+1. **API Key**: Get an API key from [Groq Console](https://console.groq.com/keys) and update the value of `GROQ_API_KEY` in `app/.env` with your created API key.
+
+2. **Install Dependencies**: Install the required Python packages:
+    ```bash
+    pip install -r app/requirements.txt
+    ```
+
+3. **Run the Application**: Start the Streamlit app:
+    ```bash
+    streamlit run app/app.py
+    ```
+
+
+

Generative Models/Cold Email generator/app/app.py

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+import os
+import streamlit as st
+from dotenv import load_dotenv
+from langchain_community.document_loaders import WebBaseLoader
+from langchain_groq import ChatGroq
+from langchain_core.prompts import PromptTemplate
+from langchain_core.output_parsers import JsonOutputParser
+from langchain_core.exceptions import OutputParserException
+import re
+
+
+# Load environment variables
+load_dotenv()
+
+
+def clean_text(text):
+    # Remove HTML tags
+    text = re.sub(r'<[^>]*?>', '', text)
+    # Remove URLs
+    text = re.sub(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', '', text)
+    # Remove special characters
+    text = re.sub(r'[^a-zA-Z0-9 ]', '', text)
+    # Replace multiple spaces with a single space
+    text = re.sub(r'\\s{2,}', ' ', text)
+    # Trim leading and trailing whitespace
+    text = text.strip()
+    # Remove extra whitespace
+    text = ' '.join(text.split())
+    return text
+
+
+# Chain class handling the LLM processing
+class Chain:
+    def __init__(self):
+        self.llm = ChatGroq(temperature=0, groq_api_key=os.getenv("GROQ_API_KEY"), model_name="llama-3.1-70b-versatile")
+
+
+    def extract_jobs(self, cleaned_text):
+        prompt_extract = PromptTemplate.from_template(
+            """
+            ### SCRAPED TEXT FROM WEBSITE:
+            {page_data}
+            ### INSTRUCTION:
+            The scraped text is from the career's page of a website.
+            Acts as a Senior HR manager and Your job is to extract the job postings and return them in JSON format containing the following keys: `role`, `experience`, `skills` and `description`.
+            Only return the valid JSON.
+            ### VALID JSON (NO PREAMBLE):
+            """
+        )
+        chain_extract = prompt_extract | self.llm
+        res = chain_extract.invoke(input={"page_data": cleaned_text})
+        try:
+            json_parser = JsonOutputParser()
+            res = json_parser.parse(res.content)
+        except OutputParserException:
+            raise OutputParserException("Context too big. Unable to parse jobs.")
+        return res if isinstance(res, list) else [res]
+
+
+    def write_mail(self, job, links, user_name, user_about):
+        prompt_email = PromptTemplate.from_template(
+            """
+            ### JOB DESCRIPTION:
+            {job_description}
+
+            ### INSTRUCTION:
+            You are {user_name}. {user_about}
+            Your job is to write a cold email to the client regarding the job mentioned above, describing how you can contribute to fulfilling their needs.
+            Also, add the most relevant ones from the following links to showcase portfolio: {link_list}
+            Do not provide a preamble.
+            ### EMAIL (NO PREAMBLE):
+
+
+            """
+        )
+        chain_email = prompt_email | self.llm
+        res = chain_email.invoke({"job_description": str(job), "link_list": links, "user_name": user_name, "user_about": user_about})
+        return res.content
+
+
+# Portfolio class using temporary in-memory storage
+class Portfolio:
+    def __init__(self):
+        # Initialize a dictionary to store skills and portfolio links temporarily
+        if 'portfolio' not in st.session_state:
+            st.session_state['portfolio'] = []
+
+
+    def add_to_portfolio(self, skills, links):
+        """Add the user's skills and portfolio links to temporary storage."""
+        if skills and links:
+            st.session_state['portfolio'].append({"skills": skills, "links": links})
+
+
+    def query_links(self, required_skills):
+        """Query the temporary storage for relevant links based on provided skills."""
+        if not required_skills:
+            return []
+
+
+        # Find relevant portfolio entries based on skills
+        matched_links = []
+        for entry in st.session_state['portfolio']:
+            portfolio_skills = entry['skills']
+            if any(skill in portfolio_skills for skill in required_skills):
+                matched_links.append(entry['links'])
+
+
+        return matched_links[:2]  # Return up to 2 matched links
+
+
+# Function to create the Streamlit app interface
+def create_streamlit_app(llm, portfolio, clean_text):
+    st.set_page_config(page_title="Cold Email Generator", page_icon="", layout="wide")
+
+
+    st.markdown("""
+    <style>
+        .main {
+            background-color: #121212;
+            color: #e0e0e0;
+            font-family: 'Arial', sans-serif;
+        }
+        .title {
+            text-align: center;
+            color: #e0e0e0;
+            font-size: 2.5em;
+            font-weight: bold;
+        }
+        .subtitle {
+            text-align: center;
+            color: #b0b0b0;
+            font-size: 1.2em;
+        }
+        .container {
+            padding: 20px;
+            max-width: 800px;
+            margin: 0 auto;
+            background-color: #1e1e1e;
+            border-radius: 8px;
+            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.5);
+        }
+        .input-box {
+            margin-bottom: 20px;
+        }
+        .input-box input, .input-box textarea {
+            width: 100%;
+            padding: 10px;
+            border-radius: 5px;
+            border: 1px solid #333;
+            background-color: #2c2c2c;
+            color: #e0e0e0;
+            box-sizing: border-box;
+        }
+        .button {
+            background-color: #007BFF;
+            color: #e0e0e0;
+            padding: 10px 20px;
+            border: none;
+            border-radius: 5px;
+            cursor: pointer;
+            font-size: 1em;
+        }
+        .button:hover {
+            background-color: #0056b3;
+        }
+        .code-block {
+            background-color: #2c2c2c;
+            padding: 10px;
+            border-radius: 5px;
+            color: #e0e0e0;
+        }
+        #MainMenu {visibility: hidden;}
+        footer {visibility: hidden;}
+        header {visibility: hidden;}
+        .stTextInput>div>div>textarea {min-height: 100px;}
+        .stButton>button {background-color: #007BFF;}
+        .stButton>button:hover {background-color: #0056b3;}
+        .footer {
+            text-align: center;
+            color: #e0e0e0;
+            font-size: 1em;
+            margin-top: 20px;
+            padding: 10px;
+            background-color: #333;
+            border-radius: 5px;
+        }
+        .footer a {
+            color: #66b3ff;
+            text-decoration: none;
+        }
+        .footer a:hover {
+            text-decoration: underline;
+        }
+    </style>
+    """, unsafe_allow_html=True)
+
+
+    st.markdown("<div class='title'>Cold Email Generator</div>", unsafe_allow_html=True)
+    st.markdown("<div class='subtitle'>Effortlessly craft professional cold emails for job applications based on job postings.</div>", unsafe_allow_html=True)
+
+
+    st.markdown("<div class='container'>", unsafe_allow_html=True)
+
+
+    user_name = st.text_input("Enter your name:", value=" ")
+    user_about = st.text_area(
+        "Enter a brief description about yourself:",
+        value=" "
+    )
+
+
+    url_input = st.text_input("Enter a Job Post URL:", value=" ")
+
+
+    st.subheader("Enter Your Skills and Portfolio Links")
+    skills_input = st.text_area("Enter your skills (comma separated):", value="")
+    links_input = st.text_area("Enter your portfolio links (comma separated):", value="")
+
+
+    submit_button = st.button("Submit", key='submit_button', help="Click to generate the cold email")
+
+
+    if submit_button:
+        try:
+            skills_list = [skill.strip() for skill in skills_input.split(",")]
+            links_list = [link.strip() for link in links_input.split(",")]
+
+
+            portfolio.add_to_portfolio(skills_list, links_list)
+
+
+            loader = WebBaseLoader([url_input])
+            data = clean_text(loader.load().pop().page_content)
+            jobs = llm.extract_jobs(data)
+
+
+            for job in jobs:
+                job_skills = job.get('skills', [])
+                links = portfolio.query_links(job_skills)
+                email = llm.write_mail(job, links, user_name, user_about)
+                st.markdown(f"<div class='code-block'><pre>{email}</pre></div>", unsafe_allow_html=True)
+
+
+        except Exception as e:
+            st.error(f"An Error Occurred: {e}")
+
+
+    st.markdown("</div>", unsafe_allow_html=True)
+
+
+
+
+# Main function to run the app
+if __name__ == "__main__":
+    chain = Chain()
+    portfolio = Portfolio()
+
+
+    create_streamlit_app(chain, portfolio, clean_text)

Generative Models/Cold Email generator/app/requirements.txt

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+streamlit==1.35.0
+python-dotenv==1.0.0
+langchain-community==0.2.12
+langchain-groq==0.1.9
+langchain-core==0.2.37
+Gunicorn
+beautifulsoup4==4.12.2