Automated Messaging Bot & LinkedIn Candidate Screening Bot
Budget: $1,500 – $3,000 USD
Bot 1: Automated Messaging Bot
Objective:
Create a bot that integrates with Instagram, Facebook Messenger, and WhatsApp to respond to incoming messages automatically based on predefined instructions and data.
Requirements:
1. Platform Integration:
Connect the bot to the APIs of Instagram, Facebook Messenger, and WhatsApp.
Ensure the bot complies with the platforms' API policies, including rate limits and message types.
2. LLM Integration:
Use a Large Language Model (e.g., ChatGPT, Claude) to process incoming messages and generate responses.
The bot should send the generated response back to the user on the respective platform.
3. Configuration:
Allow me to provide predefined instructions and data for the bot.
Include an interface or simple method to update these instructions easily.
4. Automation:
The bot should work in real-time, processing incoming messages as they arrive.
5. Scalability:
Ensure the system is robust and capable of handling multiple simultaneous conversations.
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Bot 2: LinkedIn Candidate Screening Bot
Objective:
Develop a bot that uses the LinkedIn API to find and evaluate new candidates based on predefined parameters.
Requirements:
1. API Integration:
Connect to the LinkedIn API to access candidate data.
Ensure the bot filters out previously reviewed candidates and focuses only on new ones.
2. Parameter-Based Search:
Allow me to set specific search parameters (e.g., industry: healthcare, skills, location, experience level).
The bot should process candidate descriptions and evaluate whether they meet the criteria.
3. Automated Evaluation:
Use an LLM or a predefined rule-based system to evaluate candidates based on my provided parameters.
Provide a simple output (e.g., a list of matching candidates with a "match score" or summary).
4. Data Delivery:
Save matching candidate data in a structured format (e.g., CSV, JSON).
Optionally, provide notifications for new matches.
5. Efficiency:
Avoid redundant data downloads by tracking and ignoring previously processed candidates.
Objective:
Create a bot that integrates with Instagram, Facebook Messenger, and WhatsApp to respond to incoming messages automatically based on predefined instructions and data.
Requirements:
1. Platform Integration:
Connect the bot to the APIs of Instagram, Facebook Messenger, and WhatsApp.
Ensure the bot complies with the platforms' API policies, including rate limits and message types.
2. LLM Integration:
Use a Large Language Model (e.g., ChatGPT, Claude) to process incoming messages and generate responses.
The bot should send the generated response back to the user on the respective platform.
3. Configuration:
Allow me to provide predefined instructions and data for the bot.
Include an interface or simple method to update these instructions easily.
4. Automation:
The bot should work in real-time, processing incoming messages as they arrive.
5. Scalability:
Ensure the system is robust and capable of handling multiple simultaneous conversations.
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Bot 2: LinkedIn Candidate Screening Bot
Objective:
Develop a bot that uses the LinkedIn API to find and evaluate new candidates based on predefined parameters.
Requirements:
1. API Integration:
Connect to the LinkedIn API to access candidate data.
Ensure the bot filters out previously reviewed candidates and focuses only on new ones.
2. Parameter-Based Search:
Allow me to set specific search parameters (e.g., industry: healthcare, skills, location, experience level).
The bot should process candidate descriptions and evaluate whether they meet the criteria.
3. Automated Evaluation:
Use an LLM or a predefined rule-based system to evaluate candidates based on my provided parameters.
Provide a simple output (e.g., a list of matching candidates with a "match score" or summary).
4. Data Delivery:
Save matching candidate data in a structured format (e.g., CSV, JSON).
Optionally, provide notifications for new matches.
5. Efficiency:
Avoid redundant data downloads by tracking and ignoring previously processed candidates.
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