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This project aims to leverage large language models (LLMs) to automate the process of identifying potential candidates on LinkedIn and sending personalized invitation messages. The goal is to streamline the outreach process and increase the chances of successful connections and engagements.

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BennyDanielT/AI-Outreach-Agent

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AI-Outreach-Agent

This project aims to leverage large language models (LLMs) to automate the process of identifying potential candidates on LinkedIn and sending personalized invitation messages. The goal is to streamline the outreach process and increase the chances of successful connections and engagements.

How do I install and test the application?

Prerequisites

  • pip
  • python >= 3.12
  • poetry
  • groq API key (You can also use Ollama to serve models locally and utilize them but groq is significantly faster)
  1. Clone the repository with git clone https://github.com/BennyDanielT/AI-Outreach-Agent.git
  2. Ensure you have poetry installed in your machine, if not, execute pip install poetry
  3. Install the dependencies with poetry install
  4. Obtain your groq api key on groq console
  5. Obtain the your Serper API key on Serper
  6. Obtain a Google API key and Google Programmable Search Engine API Key
  7. Rename the .env.example file to .env and Update the key values with the keys obtained in the previous steps
  8. Run the application with poetry run ai_outreach_crew
  9. View the results in the terminal
  10. Modify the inputs in main.py to test different example

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This project aims to leverage large language models (LLMs) to automate the process of identifying potential candidates on LinkedIn and sending personalized invitation messages. The goal is to streamline the outreach process and increase the chances of successful connections and engagements.

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