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albertvillanovaΒ 
posted an update 21 days ago
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Latest smolagents release supports GPT-5: build agents that think, plan, and act.
⚑ Upgrade now and put GPT-5 to work!
albertvillanovaΒ 
posted an update 22 days ago
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πŸš€ smolagents v1.21.0 is here!
Now with improved safety in the local Python executor: dunder calls are blocked!
⚠️ Still, not fully isolated: for untrusted code, use a remote executor instead: Docker, E2B, Wasm.
✨ Many bug fixes: more reliable code.
πŸ‘‰ https://github.com/huggingface/smolagents/releases/tag/v1.21.0
severoΒ 
posted an update about 1 month ago
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Today, three unrelated Slacks popped up at the same time with enthusiastic messages about the new Qwen model.

And all of them mentioned @simonw 's post!

#TopInfluencer
albertvillanovaΒ 
posted an update about 2 months ago
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πŸš€ New in smolagents v1.20.0: Remote Python Execution via WebAssembly (Wasm)

We've just merged a major new capability into the smolagents framework: the CodeAgent can now execute Python code remotely in a secure, sandboxed WebAssembly environment!

πŸ”§ Powered by Pyodide and Deno, this new WasmExecutor lets your agent-generated Python code run safely: without relying on Docker or local execution.

Why this matters:
βœ… Isolated execution = no host access
βœ… No need for Python on the user's machine
βœ… Safer evaluation of arbitrary code
βœ… Compatible with serverless / edge agent workloads
βœ… Ideal for constrained or untrusted environments

This is just the beginning: a focused initial implementation with known limitations. A solid MVP designed for secure, sandboxed use cases. πŸ’‘

πŸ’‘ We're inviting the open-source community to help evolve this executor:
β€’ Tackle more advanced Python features
β€’ Expand compatibility
β€’ Add test coverage
β€’ Shape the next-gen secure agent runtime

πŸ”— Check out the PR: https://github.com/huggingface/smolagents/pull/1261

Let's reimagine what agent-driven Python execution can look like: remote-first, wasm-secure, and community-built.

This feature is live in smolagents v1.20.0!
Try it out.
Break things. Extend it. Give us feedback.
Let's build safer, smarter agents; together πŸ§ βš™οΈ

πŸ‘‰ https://github.com/huggingface/smolagents/releases/tag/v1.20.0

#smolagents #WebAssembly #Python #AIagents #Pyodide #Deno #OpenSource #HuggingFace #AgenticAI
albertvillanovaΒ 
posted an update 2 months ago
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πŸš€ SmolAgents v1.19.0 is live!
This release brings major improvements to agent flexibility, UI usability, streaming architecture, and developer experience: making it easier than ever to build smart, interactive AI agents. Here's what's new:

πŸ”§ Agent Upgrades
- Support for managed agents in ToolCallingAgent
- Context manager support for cleaner agent lifecycle handling
- Output formatting now uses XML tags for consistency

πŸ–₯️ UI Enhancements
- GradioUI now supports reset_agent_memory: perfect for fresh starts in dev & demos.

πŸ”„ Streaming Refactor
- Streaming event aggregation moved off the Model class
- ➑️ Better architecture & maintainability

πŸ“¦ Output Tracking
- CodeAgent outputs are now stored in ActionStep
- βœ… More visibility and structure to agent decisions

πŸ› Bug Fixes
- Smarter planning logic
- Cleaner Docker logs
- Better prompt formatting for additional_args
- Safer internal functions and final answer matching

πŸ“š Docs Improvements
- Added quickstart examples with tool usage
- One-click Colab launch buttons
- Expanded reference docs (AgentMemory, GradioUI docstrings)
- Fixed broken links and migrated to .md format

πŸ”— Full release notes:
https://github.com/huggingface/smolagents/releases/tag/v1.19.0

πŸ’¬ Try it out, explore the new features, and let us know what you build!

#smolagents #opensource #AIagents #LLM #HuggingFace
cfahlgren1Β 
posted an update 2 months ago
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I ran the Anthropic Misalignment Framework for a few top models and added it to a dataset: cfahlgren1/anthropic-agentic-misalignment-results

You can read the reasoning traces of the models trying to blackmail the user and perform other actions. It's very interesting!!

cfahlgren1Β 
posted an update 3 months ago
albertvillanovaΒ 
posted an update 3 months ago
cfahlgren1Β 
posted an update 3 months ago
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Yesterday, we dropped a new conversational viewer for datasets on the hub! πŸ’¬

Actually being able to view and inspect your data is extremely important. This is a big step in making data more accessible and actionable for everyone.

Here's some datasets you can try it out on:
β€’ mlabonne/FineTome-100k
β€’ Salesforce/APIGen-MT-5k
β€’ open-thoughts/OpenThoughts2-1M
β€’ allenai/tulu-3-sft-mixture

Any other good ones?
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albertvillanovaΒ 
posted an update 4 months ago
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New in smolagents v1.16.0:
πŸ” Bing support in WebSearchTool
🐍 Custom functions & executor_kwargs in LocalPythonExecutor
πŸ”§ Streaming GradioUI fixes
🌐 Local web agents via api_base & api_key
πŸ“š Better docs

πŸ‘‰ https://github.com/huggingface/smolagents/releases/tag/v1.16.0
albertvillanovaΒ 
posted an update 4 months ago
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smolagents v1.14.0 is out! πŸš€
πŸ”Œ MCPClient: A sleek new client for connecting to remote MCP servers, making integrations more flexible and scalable.
πŸͺ¨ Amazon Bedrock: Native support for Bedrock-hosted models.
SmolAgents is now more powerful, flexible, and enterprise-ready. πŸ’Ό

Full release πŸ‘‰ https://github.com/huggingface/smolagents/releases/tag/v1.14.0
#smolagents #LLM #AgenticAI
severoΒ 
posted an update 5 months ago
albertvillanovaΒ 
posted an update 6 months ago
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πŸš€ New smolagents update: Safer Local Python Execution! 🦾🐍

With the latest release, we've added security checks to the local Python interpreter: every evaluation is now analyzed for dangerous builtins, modules, and functions. πŸ”’

Here's why this matters & what you need to know! πŸ§΅πŸ‘‡

1️⃣ Why is local execution risky? ⚠️
AI agents that run arbitrary Python code can unintentionally (or maliciously) access system files, run unsafe commands, or exfiltrate data.

2️⃣ New Safety Layer in smolagents πŸ›‘οΈ
We now inspect every return value during execution:
βœ… Allowed: Safe built-in types (e.g., numbers, strings, lists)
β›” Blocked: Dangerous functions/modules (e.g., os.system, subprocess, exec, shutil)

3️⃣ Immediate Benefits πŸ’‘
- Prevent agents from accessing unsafe builtins
- Block unauthorized file or network access
- Reduce accidental security vulnerabilities

4️⃣ Security Disclaimer ⚠️
🚨 Despite these improvements, local Python execution is NEVER 100% safe. 🚨
If you need true isolation, use a remote sandboxed executor like Docker or E2B.

5️⃣ The Best Practice: Use Sandboxed Execution πŸ”
For production-grade AI agents, we strongly recommend running code in a Docker or E2B sandbox to ensure complete isolation.

6️⃣ Upgrade Now & Stay Safe! πŸš€
Check out the latest smolagents release and start building safer AI agents today.

πŸ”— https://github.com/huggingface/smolagents

What security measures do you take when running AI-generated code? Let’s discuss! πŸ‘‡

#AI #smolagents #Python #Security
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albertvillanovaΒ 
posted an update 6 months ago
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πŸš€ Big news for AI agents! With the latest release of smolagents, you can now securely execute Python code in sandboxed Docker or E2B environments. πŸ¦ΎπŸ”’

Here's why this is a game-changer for agent-based systems: πŸ§΅πŸ‘‡

1️⃣ Security First πŸ”
Running AI agents in unrestricted Python environments is risky! With sandboxing, your agents are isolated, preventing unintended file access, network abuse, or system modifications.

2️⃣ Deterministic & Reproducible Runs πŸ“¦
By running agents in containerized environments, you ensure that every execution happens in a controlled and predictable settingβ€”no more environment mismatches or dependency issues!

3️⃣ Resource Control & Limits 🚦
Docker and E2B allow you to enforce CPU, memory, and execution time limits, so rogue or inefficient agents don’t spiral out of control.

4️⃣ Safer Code Execution in Production 🏭
Deploy AI agents confidently, knowing that any generated code runs in an ephemeral, isolated environment, protecting your host machine and infrastructure.

5️⃣ Easy to Integrate πŸ› οΈ
With smolagents, you can simply configure your agent to use Docker or E2B as its execution backendβ€”no need for complex security setups!

6️⃣ Perfect for Autonomous AI Agents πŸ€–
If your AI agents generate and execute code dynamically, this is a must-have to avoid security pitfalls while enabling advanced automation.

⚑ Get started now: https://github.com/huggingface/smolagents

What will you build with smolagents? Let us know! πŸš€πŸ’‘
albertvillanovaΒ 
posted an update 7 months ago
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πŸš€ Introducing @huggingface Open Deep-ResearchπŸ’₯

In just 24 hours, we built an open-source agent that:
βœ… Autonomously browse the web
βœ… Search, scroll & extract info
βœ… Download & manipulate files
βœ… Run calculations on data

55% on GAIA validation set! Help us improve it!πŸ’‘
https://huggingface.co/blog/open-deep-research
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cfahlgren1Β 
posted an update 7 months ago
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If you haven't seen yet, we just released Inference Providers πŸ”€

> 4 new serverless inference providers on the Hub 🀯
> Use your HF API key or personal key with all providers πŸ”‘
> Chat with Deepseek R1, V3, and more on HF Hub πŸ‹
> We support Sambanova, TogetherAI, Replicate, and Fal.ai πŸ’ͺ

Best of all, we don't charge any markup on top of the provider 🫰 Have you tried it out yet? HF Pro accounts get $2 of free usage for the provider inference.
cfahlgren1Β 
posted an update 8 months ago
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Wow, I just added Langfuse tracing to the Deepseek Artifacts app and it's really nice πŸ”₯

It allows me to visualize and track more things along with the cfahlgren1/react-code-instructions dataset.

It was just added as a one click Docker Space template, so it's super easy to self host πŸ’ͺ
albertvillanovaΒ 
posted an update 8 months ago
cfahlgren1Β 
posted an update 8 months ago
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You'll notice the AI in the SQL Console is much better at working with chatml conversations:

Here's example of unnesting the cfahlgren1/react-code-instructions in less than 10 seconds by asking it. Check it out here: cfahlgren1/react-code-instructions

- "show me the average assistant response length"
- "extract user, system, and assistant messages into separate columns"

It's super easy to work with conversational datasets now with natural language πŸ—£οΈ





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