Thread by @_avichawla

Let's build a multi-agent internet research assistant with OpenAI Swarm & Llama 3.2 (100% local):

Before we begin, here's what we're building!

The app takes a user query, searches the web for it, and turns it into a well-crafted article.

Tool stack:
- @ollama for running LLMs locally.
- @OpenAI Swarm for multi-agent orchestration.
- @Streamlit for the UI.

The architecture diagram below illustrates the key components (agents/tools) & how they interact with each other!

Let's implement it now!

Agent 1: Web search and tool use

The web-search agent takes a user query and then uses the DuckDuckGo search tool to fetch results from the internet.

Agent 2: Research Analyst

The role of this agent is to analyze and curate the raw search results and make them ready to use for the content writer agent.

Agent 3: Technical Writer

The role of a technical writer is to use the curated results and turn them into a polished, publication-ready article.

Create a workflow

Now that we have all our agents and tools ready, it's time to put them together and create a workflow.

Here's how we do it:

The Chat interface

Finally we create a Streamlit UI to provide a chat interface for our application.

Done!

That's a wrap!

If you enjoyed this tutorial:

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