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Agentic AI research assistant that orchestrates planner, search, writer, and email agents using LLMs to automate web research, generate structured markdown reports, and deliver results via email through a Gradio-based interface.

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AnishNehete/Deep-Research-using-Open-AI

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Deep-Research-using-Open-AI

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🧠 Agentic AI Deep Research Assistant

A modular, end-to-end agent-based research automation system powered by LLMs. This assistant autonomously plans web searches, summarizes findings, writes detailed reports, and emails the result — all from a single user query.

📦 Features

  • 🗺️ Planner Agent: Breaks the query into structured web searches with reasoning.
  • 🔍 Search Agent: Performs web searches and summarizes results concisely.
  • 📝 Writer Agent: Synthesizes findings into a well-formatted markdown report.
  • 📧 Email Agent: Converts reports to HTML and sends via SendGrid.
  • 🌐 Gradio UI: Clean interface to enter queries and track research progress.
  • 🧵 Trace Logging: Generates OpenAI trace links for debugging and transparency.

🚀 Getting Started

1. Clone the repository

git clone https://github.com/AnishNehete/Deep-Research-using-Open-AI/

  1. Install dependencies

pip install -r requirements.txt

  1. Configure environment variables Create a .env file in the root directory:

OPENAI_API_KEY=your_openai_key SENDGRID_API_KEY=your_sendgrid_key

  1. Launch the app

python deep_research.py 🧠 Agent Architecture Agent Name Purpose PlannerAgent Generates 5 web search terms based on the input query SearchAgent Performs search + summarization for each generated term WriterAgent Creates a detailed markdown report with outline and summary EmailAgent Formats the report in HTML and sends it via email

📂 Code Structure File Description deep_research.py Main UI and app launcher using Gradio research_manager.py Controls the full agentic workflow planner_agent.py Query decomposition into web search plan search_agent.py Executes searches and extracts summaries writer_agent.py Converts search findings into a full report email_agent.py Sends reports via SendGrid email service

💡 Example Query

What are the ethical concerns and regulatory frameworks around AI in healthcare? You’ll receive a ~1000 word markdown report with:

A short summary

Full report content

Follow-up research questions

Delivered directly via email

🔐 Security Note All API keys must be stored in the .env file. Do not commit your credentials.

🔧 Future Enhancements Allow user to specify recipient email

Add PDF export support

Save report history to a local or cloud database

👨‍💻 Author Built by Anish Nehete Inspired by Ed Donner Check out his Agentic AI course :)

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Agentic AI research assistant that orchestrates planner, search, writer, and email agents using LLMs to automate web research, generate structured markdown reports, and deliver results via email through a Gradio-based interface.

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