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2827
Latest smolagents release supports GPT-5: build agents that think, plan, and act.
⚡ Upgrade now and put GPT-5 to work!
⚡ Upgrade now and put GPT-5 to work!
AI & ML interests
🤗 Hugging Face x 🌸 BigScience initiative to create open source community resources for LAMs.
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albertvillanova
posted
an
update
2 days ago
albertvillanova
posted
an
update
4 days ago
Post
257
🚀 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.
👉 https://github.com/huggingface/smolagents/releases/tag/v1.21.0
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.
👉 https://github.com/huggingface/smolagents/releases/tag/v1.21.0
alielfilali01
posted
an
update
9 days ago
Post
426
Guys WTH is "yofo-*" ???
Most OpenAI staff associated with the openai/gpt-oss-68911959590a1634ba11c7a4 release are affiliated to dozens of yofo orgs ...
i.e
yofo-wildflower
Some HF folks as well 👀
Most OpenAI staff associated with the openai/gpt-oss-68911959590a1634ba11c7a4 release are affiliated to dozens of yofo orgs ...
i.e
yofo-wildflower
Some HF folks as well 👀
albertvillanova
posted
an
update
about 1 month ago
Post
595
🚀 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!
🔧 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:
✅ Isolated execution = no host access
✅ No need for Python on the user's machine
✅ Safer evaluation of arbitrary code
✅ Compatible with serverless / edge agent workloads
✅ 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. 💡
💡 We're inviting the open-source community to help evolve this executor:
• Tackle more advanced Python features
• Expand compatibility
• Add test coverage
• Shape the next-gen secure agent runtime
🔗 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 🧠⚙️
👉 https://github.com/huggingface/smolagents/releases/tag/v1.20.0
#smolagents #WebAssembly #Python #AIagents #Pyodide #Deno #OpenSource #HuggingFace #AgenticAI
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!
🔧 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:
✅ Isolated execution = no host access
✅ No need for Python on the user's machine
✅ Safer evaluation of arbitrary code
✅ Compatible with serverless / edge agent workloads
✅ 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. 💡
💡 We're inviting the open-source community to help evolve this executor:
• Tackle more advanced Python features
• Expand compatibility
• Add test coverage
• Shape the next-gen secure agent runtime
🔗 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 🧠⚙️
👉 https://github.com/huggingface/smolagents/releases/tag/v1.20.0
#smolagents #WebAssembly #Python #AIagents #Pyodide #Deno #OpenSource #HuggingFace #AgenticAI
louisbrulenaudet
posted
an
update
about 1 month ago
Post
2794
Because hackathons are often the starting point for many AI projects, I've created a Python-backend template incorporating my feedback to streamline collaboration and urgent deployments 🏎️
Within a year, I had the opportunity to participate in hackathons organized by Mistral, OpenAI, and DeepMind and this GitHub template is structured around several fundamental building blocks and recommendations I offer developers eager to participate in their first hackathon, whether as part of a team or individually. Its emphasis is on rapid setup and deployment through:
- uv as a package manager, simplifying usage via a series of pre-configured make commands.
- FastAPI for API management, structured in a modular architecture designed to minimize branch conflicts during merges to main branches (using minimal health-check and ping routes to verify Docker’s proper execution and backend accessibility on the local network).
- Pydantic for validation and type handling, which simplifies debugging and enhances understanding of data objects.
- A set of custom instructions tailored for agents (Cline and GitHub Copilot), aimed at improving overall comprehension of the application and optimizing the vibe-coding experience.
This template includes unit tests with a 100% success rate and test coverage, as well as a minimal CI file ensuring that the FastAPI application runs correctly. Thus, merging code that breaks the server into production becomes impossible ⛔️
In general, I would reiterate an essential piece of advice: your two main adversaries are branch conflicts—particularly when the same file is modified concurrently within a brief period, especially if your architecture isn’t built for scalability—and deployment issues under urgent circumstances ⏱️
Link to GitHub: https://github.com/louisbrulenaudet/hackathon-backend
Simply issue these commands and you can ship your code at the speed of light:
Within a year, I had the opportunity to participate in hackathons organized by Mistral, OpenAI, and DeepMind and this GitHub template is structured around several fundamental building blocks and recommendations I offer developers eager to participate in their first hackathon, whether as part of a team or individually. Its emphasis is on rapid setup and deployment through:
- uv as a package manager, simplifying usage via a series of pre-configured make commands.
- FastAPI for API management, structured in a modular architecture designed to minimize branch conflicts during merges to main branches (using minimal health-check and ping routes to verify Docker’s proper execution and backend accessibility on the local network).
- Pydantic for validation and type handling, which simplifies debugging and enhances understanding of data objects.
- A set of custom instructions tailored for agents (Cline and GitHub Copilot), aimed at improving overall comprehension of the application and optimizing the vibe-coding experience.
This template includes unit tests with a 100% success rate and test coverage, as well as a minimal CI file ensuring that the FastAPI application runs correctly. Thus, merging code that breaks the server into production becomes impossible ⛔️
In general, I would reiterate an essential piece of advice: your two main adversaries are branch conflicts—particularly when the same file is modified concurrently within a brief period, especially if your architecture isn’t built for scalability—and deployment issues under urgent circumstances ⏱️
Link to GitHub: https://github.com/louisbrulenaudet/hackathon-backend
Simply issue these commands and you can ship your code at the speed of light:
make init
make dev
albertvillanova
posted
an
update
about 2 months ago
Post
1665
🚀 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:
🔧 Agent Upgrades
- Support for managed agents in ToolCallingAgent
- Context manager support for cleaner agent lifecycle handling
- Output formatting now uses XML tags for consistency
🖥️ UI Enhancements
- GradioUI now supports reset_agent_memory: perfect for fresh starts in dev & demos.
🔄 Streaming Refactor
- Streaming event aggregation moved off the Model class
- ➡️ Better architecture & maintainability
📦 Output Tracking
- CodeAgent outputs are now stored in ActionStep
- ✅ More visibility and structure to agent decisions
🐛 Bug Fixes
- Smarter planning logic
- Cleaner Docker logs
- Better prompt formatting for additional_args
- Safer internal functions and final answer matching
📚 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
🔗 Full release notes:
https://github.com/huggingface/smolagents/releases/tag/v1.19.0
💬 Try it out, explore the new features, and let us know what you build!
#smolagents #opensource #AIagents #LLM #HuggingFace
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:
🔧 Agent Upgrades
- Support for managed agents in ToolCallingAgent
- Context manager support for cleaner agent lifecycle handling
- Output formatting now uses XML tags for consistency
🖥️ UI Enhancements
- GradioUI now supports reset_agent_memory: perfect for fresh starts in dev & demos.
🔄 Streaming Refactor
- Streaming event aggregation moved off the Model class
- ➡️ Better architecture & maintainability
📦 Output Tracking
- CodeAgent outputs are now stored in ActionStep
- ✅ More visibility and structure to agent decisions
🐛 Bug Fixes
- Smarter planning logic
- Cleaner Docker logs
- Better prompt formatting for additional_args
- Safer internal functions and final answer matching
📚 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
🔗 Full release notes:
https://github.com/huggingface/smolagents/releases/tag/v1.19.0
💬 Try it out, explore the new features, and let us know what you build!
#smolagents #opensource #AIagents #LLM #HuggingFace
louisbrulenaudet
posted
an
update
about 2 months ago
Post
1167
🌐 Clinical Trials Dataset now available on Hugging Face! 🧬
I’ve just released a comprehensive, ML-ready dataset featuring 500,000+ clinical trial records sourced directly from ClinicalTrials.gov for biomedical NLP, healthcare analytics, and clinical research applications 🤗
I wanted to produce the most complete and up-to-date dump with all raw data partially flattened to simplify extraction, self-querying and processing.
Do you have any ideas about what we can do with it? Using descriptions to enhance specialized embedding models?
louisbrulenaudet/clinical-trials
I’ve just released a comprehensive, ML-ready dataset featuring 500,000+ clinical trial records sourced directly from ClinicalTrials.gov for biomedical NLP, healthcare analytics, and clinical research applications 🤗
I wanted to produce the most complete and up-to-date dump with all raw data partially flattened to simplify extraction, self-querying and processing.
Do you have any ideas about what we can do with it? Using descriptions to enhance specialized embedding models?
louisbrulenaudet/clinical-trials
[bot] Conversion to Parquet
#2 opened about 2 months ago
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parquet-converter
davanstrien
posted
an
update
2 months ago
Post
3363
Inspired by Hugging Face's official MCP server, I've developed a complementary tool that exposes my semantic search API to enhance discovery across the HF platform.
Key capabilities:
- AI-powered semantic search for models and datasets
- Parameter count analysis via safetensors metadata
- Trending content discovery
- Find similar models/datasets functionality
- 11 tools total for enhanced ecosystem navigation
The semantic search goes beyond simple keyword matching, understanding context and relationships between different models and datasets.
Example query: "Find around 10 reasoning Hugging Face datasets published in 2025 focusing on topics other than maths and science. Show a link and a short summary for each dataset." (results in video!)
https://github.com/davanstrien/hub-semantic-search-mcp
Key capabilities:
- AI-powered semantic search for models and datasets
- Parameter count analysis via safetensors metadata
- Trending content discovery
- Find similar models/datasets functionality
- 11 tools total for enhanced ecosystem navigation
The semantic search goes beyond simple keyword matching, understanding context and relationships between different models and datasets.
Example query: "Find around 10 reasoning Hugging Face datasets published in 2025 focusing on topics other than maths and science. Show a link and a short summary for each dataset." (results in video!)
https://github.com/davanstrien/hub-semantic-search-mcp
- 1 reply
marianna13
authored
4
papers
2 months ago
Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models
Paper
•
2406.02061
•
Published
•
2
DataComp-LM: In search of the next generation of training sets for language models
Paper
•
2406.11794
•
Published
•
54
OpenThoughts: Data Recipes for Reasoning Models
Paper
•
2506.04178
•
Published
•
44
Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets
Paper
•
2506.04598
•
Published
•
6
storytracer
authored
a
paper
2 months ago
alielfilali01
authored
a
paper
3 months ago
albertvillanova
posted
an
update
3 months ago
Post
670
New in smolagents v1.17.0:
- Structured generation in CodeAgent 🧱
- Streamable HTTP MCP support 🌐
- Agent.run() returns rich RunResult 📦
Smarter agents, smoother workflows.
Try it now: https://github.com/huggingface/smolagents/releases/tag/v1.17.0
- Structured generation in CodeAgent 🧱
- Streamable HTTP MCP support 🌐
- Agent.run() returns rich RunResult 📦
Smarter agents, smoother workflows.
Try it now: https://github.com/huggingface/smolagents/releases/tag/v1.17.0
Zaid
authored
4
papers
3 months ago
Masader: Metadata Sourcing for Arabic Text and Speech Data Resources
Paper
•
2110.06744
•
Published
Arabic Stable LM: Adapting Stable LM 2 1.6B to Arabic
Paper
•
2412.04277
•
Published
Rephrasing natural text data with different languages and quality levels for Large Language Model pre-training
Paper
•
2410.20796
•
Published
Ashaar: Automatic Analysis and Generation of Arabic Poetry Using Deep Learning Approaches
Paper
•
2307.06218
•
Published