37 36 119

Stefano Fiorucci PRO

anakin87

AI & ML interests

Contributing to Haystack LLM framework 🏗️. Language Models: orchestration, post-training, synthetic data...

Articles

🇮🇹🇯🇵🇧🇷 Generating multilingual instruction datasets with Magpie 🐦‍⬛

Oct 21

• 18

Selective fine-tuning of Language Models with Spectrum

Sep 3

• 30

Organizations

Posts 11

Post

1560

Tulu 3 SFT Mixture by AllenAI is a massive, good, multilingual dataset for fine-tuning Language Models.

Unfortunately, it was missing the "language" column.

I added it using the good old fastText.

Check out the dataset here 👉 anakin87/tulu-3-sft-mixture-with-language

Post

380

🐝🐝🐝 𝐀 𝐒𝐰𝐚𝐫𝐦 𝐨𝐟 𝐀𝐠𝐞𝐧𝐭𝐬 𝐰𝐢𝐭𝐡 𝐋𝐥𝐚𝐦𝐚 3.2, 𝐆𝐏𝐓-4𝐨 𝐦𝐢𝐧𝐢 𝐚𝐧𝐝 𝐂𝐥𝐚𝐮𝐝𝐞 3.5 𝐒𝐨𝐧𝐧𝐞𝐭

𝐓𝐋;𝐃𝐑: I reimplemented the Swarm concept using Haystack, but made it work with both open and proprietary models 💫

✍️ blog article: https://haystack.deepset.ai/blog/swarm-of-agents
📓 notebook: https://haystack.deepset.ai/cookbook/swarm

Some time ago OpenAI published Swarm: an educational framework for building multi-agent systems.

Their approach focuses on two main concepts:
・ 𝐑𝐨𝐮𝐭𝐢𝐧𝐞𝐬: Each agent follows specific 📜 instructions and uses 🛠️ tools to execute them.
・ 𝐇𝐚𝐧𝐝𝐨𝐟𝐟𝐬 🤝: Agents can transfer control to one another using tool/function calling.

When I first read these ideas, I thought: 𝘴𝘪𝘮𝘱𝘭𝘦 𝘣𝘶𝘵 𝘱𝘰𝘸𝘦𝘳𝘧𝘶𝘭! And they pair well with the recent unified tool support in Haystack.

🧑‍💻 So, I decided to re-implement these concepts using Haystack, and in just a few lines of code, I had a working prototype.

🆒 Bonus feature: this implementation isn't tied to a single model provider - different agents can be powered by different models!

I replicated the ACME customer service example from the original article, with 3 Agents:
🐝 Triage Agent - Llama 3.2 running on Ollama
🐝 Sales Agent - Anthropic Claude 3.5 Sonnet
🐝 Issues and Repairs Agent - OpenAI GPT-4o mini

Want to see the full implementation and give it a try? Check out the blog post and notebook! ✨

View all posts