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albertvillanovaย
posted
an
update
5 months ago
albertvillanovaย
posted
an
update
5 months ago
Post
668
๐ smolagents v1.21.0 is here!
Now with improved safety in the local Python executor: dunder calls are blocked!
โ ๏ธ Still, not fully isolated: for untrusted code, use a remote executor instead: Docker, E2B, Wasm.
โจ Many bug fixes: more reliable code.
๐ https://github.com/huggingface/smolagents/releases/tag/v1.21.0
Now with improved safety in the local Python executor: dunder calls are blocked!
โ ๏ธ Still, not fully isolated: for untrusted code, use a remote executor instead: Docker, E2B, Wasm.
โจ Many bug fixes: more reliable code.
๐ https://github.com/huggingface/smolagents/releases/tag/v1.21.0
albertvillanovaย
posted
an
update
6 months ago
Post
792
๐ 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!
๐ง 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:
โ Isolated execution = no host access
โ No need for Python on the user's machine
โ Safer evaluation of arbitrary code
โ Compatible with serverless / edge agent workloads
โ 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. ๐ก
๐ก We're inviting the open-source community to help evolve this executor:
โข Tackle more advanced Python features
โข Expand compatibility
โข Add test coverage
โข Shape the next-gen secure agent runtime
๐ 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 ๐ง โ๏ธ
๐ 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!
๐ง 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:
โ Isolated execution = no host access
โ No need for Python on the user's machine
โ Safer evaluation of arbitrary code
โ Compatible with serverless / edge agent workloads
โ 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. ๐ก
๐ก We're inviting the open-source community to help evolve this executor:
โข Tackle more advanced Python features
โข Expand compatibility
โข Add test coverage
โข Shape the next-gen secure agent runtime
๐ 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 ๐ง โ๏ธ
๐ https://github.com/huggingface/smolagents/releases/tag/v1.20.0
#smolagents #WebAssembly #Python #AIagents #Pyodide #Deno #OpenSource #HuggingFace #AgenticAI
albertvillanovaย
posted
an
update
7 months ago
Post
1820
๐ 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:
๐ง Agent Upgrades
- Support for managed agents in ToolCallingAgent
- Context manager support for cleaner agent lifecycle handling
- Output formatting now uses XML tags for consistency
๐ฅ๏ธ UI Enhancements
- GradioUI now supports reset_agent_memory: perfect for fresh starts in dev & demos.
๐ Streaming Refactor
- Streaming event aggregation moved off the Model class
- โก๏ธ Better architecture & maintainability
๐ฆ Output Tracking
- CodeAgent outputs are now stored in ActionStep
- โ More visibility and structure to agent decisions
๐ Bug Fixes
- Smarter planning logic
- Cleaner Docker logs
- Better prompt formatting for additional_args
- Safer internal functions and final answer matching
๐ 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
๐ Full release notes:
https://github.com/huggingface/smolagents/releases/tag/v1.19.0
๐ฌ 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:
๐ง Agent Upgrades
- Support for managed agents in ToolCallingAgent
- Context manager support for cleaner agent lifecycle handling
- Output formatting now uses XML tags for consistency
๐ฅ๏ธ UI Enhancements
- GradioUI now supports reset_agent_memory: perfect for fresh starts in dev & demos.
๐ Streaming Refactor
- Streaming event aggregation moved off the Model class
- โก๏ธ Better architecture & maintainability
๐ฆ Output Tracking
- CodeAgent outputs are now stored in ActionStep
- โ More visibility and structure to agent decisions
๐ Bug Fixes
- Smarter planning logic
- Cleaner Docker logs
- Better prompt formatting for additional_args
- Safer internal functions and final answer matching
๐ 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
๐ Full release notes:
https://github.com/huggingface/smolagents/releases/tag/v1.19.0
๐ฌ Try it out, explore the new features, and let us know what you build!
#smolagents #opensource #AIagents #LLM #HuggingFace
cfahlgren1ย
posted
an
update
7 months ago
Post
820
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!!
You can read the reasoning traces of the models trying to blackmail the user and perform other actions. It's very interesting!!
cfahlgren1ย
posted
an
update
7 months ago
Post
409
Really nice to see AllenAI drop the Reward-Bench-2 dataset and leaderboard from their new paper all on the hub! ๐
allenai/reward-bench
allenai/reward-bench-2
allenai/reward-bench-2-results
Great work @natolambert , allenai and others!! ๐ค
allenai/reward-bench
allenai/reward-bench-2
allenai/reward-bench-2-results
Great work @natolambert , allenai and others!! ๐ค
albertvillanovaย
posted
an
update
8 months ago
Post
744
New in smolagents v1.17.0:
- Structured generation in CodeAgent ๐งฑ
- Streamable HTTP MCP support ๐
- Agent.run() returns rich RunResult ๐ฆ
Smarter agents, smoother workflows.
Try it now: https://github.com/huggingface/smolagents/releases/tag/v1.17.0
- Structured generation in CodeAgent ๐งฑ
- Streamable HTTP MCP support ๐
- Agent.run() returns rich RunResult ๐ฆ
Smarter agents, smoother workflows.
Try it now: https://github.com/huggingface/smolagents/releases/tag/v1.17.0
cfahlgren1ย
posted
an
update
8 months ago
Post
1731
Yesterday, we dropped a new conversational viewer for datasets on the hub! ๐ฌ
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:
โข mlabonne/FineTome-100k
โข Salesforce/APIGen-MT-5k
โข open-thoughts/OpenThoughts2-1M
โข allenai/tulu-3-sft-mixture
Any other good ones?
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:
โข mlabonne/FineTome-100k
โข Salesforce/APIGen-MT-5k
โข open-thoughts/OpenThoughts2-1M
โข allenai/tulu-3-sft-mixture
Any other good ones?
albertvillanovaย
posted
an
update
8 months ago
Post
2609
New in smolagents v1.16.0:
๐ Bing support in WebSearchTool
๐ Custom functions & executor_kwargs in LocalPythonExecutor
๐ง Streaming GradioUI fixes
๐ Local web agents via api_base & api_key
๐ Better docs
๐ https://github.com/huggingface/smolagents/releases/tag/v1.16.0
๐ Bing support in WebSearchTool
๐ Custom functions & executor_kwargs in LocalPythonExecutor
๐ง Streaming GradioUI fixes
๐ Local web agents via api_base & api_key
๐ Better docs
๐ https://github.com/huggingface/smolagents/releases/tag/v1.16.0
albertvillanovaย
posted
an
update
9 months ago
Post
2891
smolagents v1.14.0 is out! ๐
๐ MCPClient: A sleek new client for connecting to remote MCP servers, making integrations more flexible and scalable.
๐ชจ Amazon Bedrock: Native support for Bedrock-hosted models.
SmolAgents is now more powerful, flexible, and enterprise-ready. ๐ผ
Full release ๐ https://github.com/huggingface/smolagents/releases/tag/v1.14.0
#smolagents #LLM #AgenticAI
๐ MCPClient: A sleek new client for connecting to remote MCP servers, making integrations more flexible and scalable.
๐ชจ Amazon Bedrock: Native support for Bedrock-hosted models.
SmolAgents is now more powerful, flexible, and enterprise-ready. ๐ผ
Full release ๐ https://github.com/huggingface/smolagents/releases/tag/v1.14.0
#smolagents #LLM #AgenticAI
Post
2034
Need to convert CSV to Parquet?
Use https://www.chatdb.ai/tools/csv-to-parquet-converter. It does the job instantly.
@cfahlgren1 provides many other tools on his website. Approved and bookmarked!
Use https://www.chatdb.ai/tools/csv-to-parquet-converter. It does the job instantly.
@cfahlgren1 provides many other tools on his website. Approved and bookmarked!
albertvillanovaย
posted
an
update
10 months ago
Post
4195
๐ New smolagents update: Safer Local Python Execution! ๐ฆพ๐
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. ๐
Here's why this matters & what you need to know! ๐งต๐
1๏ธโฃ Why is local execution risky? โ ๏ธ
AI agents that run arbitrary Python code can unintentionally (or maliciously) access system files, run unsafe commands, or exfiltrate data.
2๏ธโฃ New Safety Layer in smolagents ๐ก๏ธ
We now inspect every return value during execution:
โ Allowed: Safe built-in types (e.g., numbers, strings, lists)
โ Blocked: Dangerous functions/modules (e.g., os.system, subprocess, exec, shutil)
3๏ธโฃ Immediate Benefits ๐ก
- Prevent agents from accessing unsafe builtins
- Block unauthorized file or network access
- Reduce accidental security vulnerabilities
4๏ธโฃ Security Disclaimer โ ๏ธ
๐จ Despite these improvements, local Python execution is NEVER 100% safe. ๐จ
If you need true isolation, use a remote sandboxed executor like Docker or E2B.
5๏ธโฃ The Best Practice: Use Sandboxed Execution ๐
For production-grade AI agents, we strongly recommend running code in a Docker or E2B sandbox to ensure complete isolation.
6๏ธโฃ Upgrade Now & Stay Safe! ๐
Check out the latest smolagents release and start building safer AI agents today.
๐ https://github.com/huggingface/smolagents
What security measures do you take when running AI-generated code? Letโs discuss! ๐
#AI #smolagents #Python #Security
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. ๐
Here's why this matters & what you need to know! ๐งต๐
1๏ธโฃ Why is local execution risky? โ ๏ธ
AI agents that run arbitrary Python code can unintentionally (or maliciously) access system files, run unsafe commands, or exfiltrate data.
2๏ธโฃ New Safety Layer in smolagents ๐ก๏ธ
We now inspect every return value during execution:
โ Allowed: Safe built-in types (e.g., numbers, strings, lists)
โ Blocked: Dangerous functions/modules (e.g., os.system, subprocess, exec, shutil)
3๏ธโฃ Immediate Benefits ๐ก
- Prevent agents from accessing unsafe builtins
- Block unauthorized file or network access
- Reduce accidental security vulnerabilities
4๏ธโฃ Security Disclaimer โ ๏ธ
๐จ Despite these improvements, local Python execution is NEVER 100% safe. ๐จ
If you need true isolation, use a remote sandboxed executor like Docker or E2B.
5๏ธโฃ The Best Practice: Use Sandboxed Execution ๐
For production-grade AI agents, we strongly recommend running code in a Docker or E2B sandbox to ensure complete isolation.
6๏ธโฃ Upgrade Now & Stay Safe! ๐
Check out the latest smolagents release and start building safer AI agents today.
๐ https://github.com/huggingface/smolagents
What security measures do you take when running AI-generated code? Letโs discuss! ๐
#AI #smolagents #Python #Security
albertvillanovaย
posted
an
update
10 months ago
Post
4101
๐ Big news for AI agents! With the latest release of smolagents, you can now securely execute Python code in sandboxed Docker or E2B environments. ๐ฆพ๐
Here's why this is a game-changer for agent-based systems: ๐งต๐
1๏ธโฃ Security First ๐
Running AI agents in unrestricted Python environments is risky! With sandboxing, your agents are isolated, preventing unintended file access, network abuse, or system modifications.
2๏ธโฃ Deterministic & Reproducible Runs ๐ฆ
By running agents in containerized environments, you ensure that every execution happens in a controlled and predictable settingโno more environment mismatches or dependency issues!
3๏ธโฃ Resource Control & Limits ๐ฆ
Docker and E2B allow you to enforce CPU, memory, and execution time limits, so rogue or inefficient agents donโt spiral out of control.
4๏ธโฃ Safer Code Execution in Production ๐ญ
Deploy AI agents confidently, knowing that any generated code runs in an ephemeral, isolated environment, protecting your host machine and infrastructure.
5๏ธโฃ Easy to Integrate ๐ ๏ธ
With smolagents, you can simply configure your agent to use Docker or E2B as its execution backendโno need for complex security setups!
6๏ธโฃ Perfect for Autonomous AI Agents ๐ค
If your AI agents generate and execute code dynamically, this is a must-have to avoid security pitfalls while enabling advanced automation.
โก Get started now: https://github.com/huggingface/smolagents
What will you build with smolagents? Let us know! ๐๐ก
Here's why this is a game-changer for agent-based systems: ๐งต๐
1๏ธโฃ Security First ๐
Running AI agents in unrestricted Python environments is risky! With sandboxing, your agents are isolated, preventing unintended file access, network abuse, or system modifications.
2๏ธโฃ Deterministic & Reproducible Runs ๐ฆ
By running agents in containerized environments, you ensure that every execution happens in a controlled and predictable settingโno more environment mismatches or dependency issues!
3๏ธโฃ Resource Control & Limits ๐ฆ
Docker and E2B allow you to enforce CPU, memory, and execution time limits, so rogue or inefficient agents donโt spiral out of control.
4๏ธโฃ Safer Code Execution in Production ๐ญ
Deploy AI agents confidently, knowing that any generated code runs in an ephemeral, isolated environment, protecting your host machine and infrastructure.
5๏ธโฃ Easy to Integrate ๐ ๏ธ
With smolagents, you can simply configure your agent to use Docker or E2B as its execution backendโno need for complex security setups!
6๏ธโฃ Perfect for Autonomous AI Agents ๐ค
If your AI agents generate and execute code dynamically, this is a must-have to avoid security pitfalls while enabling advanced automation.
โก Get started now: https://github.com/huggingface/smolagents
What will you build with smolagents? Let us know! ๐๐ก
cfahlgren1ย
authored
a
paper
11 months ago
albertvillanovaย
posted
an
update
11 months ago
Post
4192
๐ Introducing
@huggingface
Open Deep-Research๐ฅ
In just 24 hours, we built an open-source agent that:
โ Autonomously browse the web
โ Search, scroll & extract info
โ Download & manipulate files
โ Run calculations on data
55% on GAIA validation set! Help us improve it!๐ก
https://huggingface.co/blog/open-deep-research
In just 24 hours, we built an open-source agent that:
โ Autonomously browse the web
โ Search, scroll & extract info
โ Download & manipulate files
โ Run calculations on data
55% on GAIA validation set! Help us improve it!๐ก
https://huggingface.co/blog/open-deep-research
cfahlgren1ย
posted
an
update
11 months ago
Post
2351
If you haven't seen yet, we just released Inference Providers ๐
> 4 new serverless inference providers on the Hub ๐คฏ
> Use your HF API key or personal key with all providers ๐
> Chat with Deepseek R1, V3, and more on HF Hub ๐
> We support Sambanova, TogetherAI, Replicate, and Fal.ai ๐ช
Best of all, we don't charge any markup on top of the provider ๐ซฐ Have you tried it out yet? HF Pro accounts get $2 of free usage for the provider inference.
> 4 new serverless inference providers on the Hub ๐คฏ
> Use your HF API key or personal key with all providers ๐
> Chat with Deepseek R1, V3, and more on HF Hub ๐
> We support Sambanova, TogetherAI, Replicate, and Fal.ai ๐ช
Best of all, we don't charge any markup on top of the provider ๐ซฐ Have you tried it out yet? HF Pro accounts get $2 of free usage for the provider inference.
cfahlgren1ย
posted
an
update
12 months ago
Post
1786
Wow, I just added Langfuse tracing to the Deepseek Artifacts app and it's really nice ๐ฅ
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 ๐ช
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 ๐ช
albertvillanovaย
posted
an
update
about 1 year ago
Post
2224
Discover all the improvements in the new version of Lighteval: https://huggingface.co/docs/lighteval/
cfahlgren1ย
posted
an
update
about 1 year ago
Post
2277
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 ๐ฃ๏ธ
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 ๐ฃ๏ธ