README.md

metadata

title: Report Writer Agent
emoji: 🏆
colorFrom: indigo
colorTo: green
sdk: gradio
sdk_version: 5.28.0
app_file: app.py
pinned: false
license: mit
short_description: Report Writing Agent by Nader Afshar

Research-Driven Report Writing Agent

🔎 Research Agent

The Research Agent is an autonomous, multi-step research system built using LangGraph, Cohere, and Tavily. It mimics the behavior of a human research assistant — planning, researching, drafting, critiquing, and revising — to produce high-quality research reports on any topic the user provides.

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🧠 What Sets It Apart?

Unlike typical AI content generators, this agent performs real-time research to ensure that reports are grounded in current, verifiable information.

✨ Highlights:

• Uses Cohere’s command-a-03-2025 LLM for language generation, outlining, and critique.
• Uses Tavily to perform real-time, internet-based research (not just LLM memory).
• Produces structured, refined research reports, not informal essays or chatbot replies.
• Streams its research and reasoning process live so users can follow along.

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🧩 How It Works

1. User provides a topic or research question through the UI.
2. The agent:
   • Plans the structure of the research.
   • Conducts multiple web searches via Tavily.
   • Drafts a full report using retrieved content and context.
   • Critiques and revises the report internally.
3. The output includes:
   • A live, streaming log of the research process.
   • A clean, final research report as a separate result.

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⏳ Why It Takes Time

The Research Agent behaves more like a human researcher than a chatbot:

• It may take ~30 seconds before the first visible output, while:
  • Querying the web.
  • Organizing thoughts.
  • Planning the structure.
• It takes 1–2 minutes or more to complete a full research and writing cycle with critique + revision.

🧠 This is intentional: speed is traded for depth, accuracy, and reasoning.

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🖥 Interface

Built with Gradio, the app includes:

• A textbox for entering a topic or question.
• A streaming log of research, planning, and revision steps.
• A final output panel for the completed research report.

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🛠️ Technologies Used

Component	Purpose
LangGraph	Agent state machine + step logic
Cohere LLM	command-a-03-2025 model for text tasks
Tavily Search	Real-time research via web search
LangChain Core	Messaging and prompt orchestration
Gradio	Interactive web interface

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🚀 Getting Started

1. Install dependencies:

   pip install -r requirements.txt