Alessandro Risaro

founder @datapizza_ai

[Datapizza AI @datapizza_ai]

Datapizza AI v0.1.0 is live 🔥

Agents are now a first-class component — rebuilt from the ground up: new runner architecture, handoffs, hooks, structured outputs, runtime memory, agent descriptions, and agent-as-tool interoperability.

Also shipping:

→ Persistent MCP sessions + Anthropic client memory bug fix
→ WatsonX, Mistral embedder, and latest Gemini models support
→ Redis cache security fix (now JSON-based)
→ Bug fixes, reliability improvements, expanded test coverage

Docs: https://t.co/RJV7imtT29
GITHUB: https://t.co/dojOf1sOFq

[Beelzebub @BeelzebubLabs]

Catching AI Red Teamers in the Wild 🪤

https://t.co/FNs0nC8xMG

[Clandestine @akaclandestine]

GitHub - beelzebub-labs/azazel: Linux Runtime Security and Forensics using eBPF https://t.co/MaIdTSvm6I

[Datapizza AI @datapizza_ai]

We ran experiments to answer: Is Contextual Retrieval still worth it in 2026? Tested on 3 datasets, with/without rerankers (Cohere v4 Pro, Qwen3 8B).

Here's what we found → https://t.co/qYftRIbCmv

[Nicolò Calcagno @calcagno_nicolo]

https://t.co/dEPMp2PgvI

#madewithdatapizzaai

[Datapizza AI @datapizza_ai]

We’re rolling out a new YouTube playlist with step-by-step tutorials for our open-source framework — and it’s just getting started. 🚀

We’re releasing videos gradually, covering everything from setup to advanced workflows, so you can dive deeper into the architecture as the series evolves.

👉 Start here: https://t.co/gH0p8JhdV5

#opensource #developers #AI #tutorials

[Alessandro Risaro @risooo2]

@datapizza_ai Go

[Datapizza AI @datapizza_ai]

Here are the latest updates from our R&D Lab 🚀

Right now we’re exploring advanced RAG techniques — and for proper evaluation, we need datasets that reflect real-world difficulty.

We tested several public datasets:

📍LegalBench

📍MultiHop-RAG

📍LoCoMo

These have been super helpful starting points for evaluation.

As we applied them to our specific use cases, we realized we needed something more tailored to the GenAI RAG challenges we're focusing on — particularly around domain-specific knowledge and reasoning chains that match our clients' real-world scenarios.

So we built a framework to generate custom evaluation datasets that fit our needs.

We now have two internal domain-heavy evaluation datasets + a public one based on the DnD SRD 5.2.1 that we're sharing with the community.

This is just an initial step, but we're excited about where it's headed. We broke down our approach here:

🔗 Blog post https://t.co/OOYnjntpuW
🔗 GitHub repo https://t.co/sclO2dH4LZ
🔗 Dataset on Hugging Face https://t.co/SK2v9t8tMW

Would love to hear your thoughts, feedback, or ideas on how to improve this!
#RAG #dataset #evaluation #GenAI #framework

[Datapizza AI @datapizza_ai]

🚀 Release v0.0.9 is out!

Here’s what’s new in our open-source framework 👇

New features:

- MCP SUPPORT

Fix:

- Added metadata args on parse method (azure and docling),
- Enhanced OpenAIClient init arguments,

DOCS: https://t.co/gcO9M4Lf5t

GITHUB: https://t.co/dojOf1sOFq

#datapizzaai #opensource #MCP

[Towards Data Science @TDataScience]

Teach an AI agent to execute Python code. @maurodp_ shares a practical example of creating a code execution tool and integrating it into a multi-agent system with Datapizza AI.

https://t.co/Zgar4g9JTY

[Francesco Garavaglia @fgarava83]

🚀! Datapizza AI: framework open source in Python per creare agenti LLM più velocemente. Costruisci chatbot, agenti AI e sistemi multi-agente facilmente. Integrazione con Ollama e OpenAI. Scopri di più! 🍕 https://t.co/KNCv66HJ73

[Alessandro Risaro @risooo2]

@tom_doerr Thx for sharing! 🙌

[Tom Dörr @tom_doerr]

GenAI framework prioritizing control over abstraction

[Alessandro Risaro @risooo2]

@datapizza_ai @pierdd_ 🚀🚀🚀

[Datapizza AI @datapizza_ai]

🚀 Release v0.0.7 is out!

Here’s what’s new in our open-source framework 👇

🔧 Features
- Docling parser: extended to all supported files + flexible OCR configuration

- Bedrock client: now with async support via aioboto3 (and full test coverage)

- New tools
→ web_fetch
→ FileSystem
→ SQLDatabase

- Milvus vectorstore added

Agents: smoother usage & improved UX

🧩 Fixes
- https://t.co/6d0ryt0hCw: accepts list of file paths

- Bedrock async methods: safer error handling

- Node splitter: handles empty cases

- Tool converter & EasyOCR dependency fixes

- Agents: clear user input after first step

- OpenAI client compatibility update (>=2)

💡 Focus of this release: performance, async readiness, and better developer experience.

👉 Full changelog: https://t.co/dojOf1sOFq

#datapizzaai #framework #opensource

[Alessandro Risaro @risooo2]

@datapizza_ai Let’s go! 🚀

[Alessandro Risaro @risooo2]

When people get what Datapizza AI is about without us explaining — that’s the best part.

[Alessandro Risaro @risooo2]

Try it, break it, tell us what you think.
We’re building it together.
👉 https://t.co/Ltq1e0OhfF

[Alessandro Risaro @risooo2]

We’ve tried every GenAI framework out there.

They’re powerful — but too abstract, too rigid, and impossible to debug when something breaks.

[Alessandro Risaro @risooo2]

Launched yesterday.
Already 800+ stars on GitHub.
We didn’t expect that kind of love.