| {"smolagents": {"cdate": "2025-03-14 16:04:17.000743", "name": "DuckDuckGoSearchTool", "data": "## Search Results\n\n[smolagents: a barebones library for agents. Agents write ... - GitHub](https://github.com/huggingface/smolagents)\nsmolagents is a library that enables you to run powerful agents in a few lines of code. It supports CodeAgents that write actions as Python code snippets, and integrates with various tools and models from Hugging Face Hub and other providers.\n\n[smolagents - Hugging Face](https://huggingface.co/docs/smolagents/index)\nsmolagents is a library that lets you create powerful agents with any LLM, including Code Agents. Learn how to use it with guides, tutorials and examples on the Hugging Face documentation.\n\n[Smolagents : Huggingface AI Agent Framework](https://smolagents.org/)\nSmolagents is a minimalist and efficient framework for creating and running AI agents with large language models. Learn how to use code agents, tools, and the Hugging Face Hub to build powerful and versatile agents for various tasks.\n\n[Agents - Guided tour - Smolagents](https://smolagents.org/docs/agents-guided-tour/)\nSmolagents lets you create agents that can use text-generation models and tools to solve tasks. Learn how to initialize, run, and customize agents with different models, tools, and options.\n\n[Building good Smolagents - Smolagents](https://smolagents.org/docs/building-good-smolagents/)\nSmolagents is a framework for creating agents that can perform tasks using natural language and external tools. Learn best practices for simplifying workflows, improving information flow, and debugging agents with LLMs.\n\n[Introducing smolagents , a simple library to build agents - Hugging Face](https://huggingface.co/blog/smolagents)\nsmolagents is a simple library that unlocks agentic capabilities for language models. It allows LLMs to write actions in code, such as calling external tools or executing loops, to solve real-world tasks.\n\n[Introduction to Agents - Hugging Face](https://huggingface.co/docs/smolagents/conceptual_guides/intro_agents)\nsmolagents documentation Introduction to Agents. smolagents Search documentation. Get started. \ud83e\udd17 Agents Guided tour. Tutorials. Building good agents \ud83d\udcca Inspect your agent runs using telemetry \ud83d\udee0\ufe0f Tools - in-depth guide \ud83d\udee1\ufe0f Secure code execution \ud83d\udcda Manage your agent's memory. Conceptual guides ...\n\n[smolagents/README.md at main \u00b7 huggingface/smolagents - GitHub](https://github.com/huggingface/smolagents/blob/main/README.md)\nsmolagents is a Python library that lets you create agents that can perform tasks using natural language and various tools. It supports code agents, model-agnostic agents, modality-agnostic agents, and tool-agnostic agents.\n\n[smolagents \u00b7 PyPI](https://pypi.org/project/smolagents/)\nsmolagents is a library that enables you to run powerful agents in a few lines of code. It offers: Simplicity: the logic for agents fits in ~1,000 lines of code (see agents.py).We kept abstractions to their minimal shape above raw code! \ud83e\uddd1\u200d\ud83d\udcbb First-class support for Code Agents.Our CodeAgent writes its actions in code (as opposed to \"agents being used to write code\").\n\n[SmolAgents. SmolAgents from HuggingFace | by Cobus Greyling | Feb, 2025 ...](https://cobusgreyling.medium.com/smolagents-7a4bf7712814)\nHugging Face launched SmolAgents with a clear mission: to democratise the creation of sophisticated agentic systems by prioritising simplicity and reducing technical overhead.. Unlike more complex frameworks, which often involve intricate architectures, SmolAgents intentionally strips away unnecessary layers of abstraction. The library emphasises lightweight efficiency without sacrificing ..."}, "What is smolagents?": {"cdate": "2025-03-14 18:08:58.593568", "name": "DuckDuckGoSearchTool", "data": "## Search Results\n\n[smolagents - Hugging Face](https://huggingface.co/docs/smolagents/index)\nsmolagents. This library is the simplest framework out there to build powerful agents! By the way, wtf are \"agents\"? We provide our definition in this page, where you'll also find tips for when to use them or not (spoilers: you'll often be better off without agents).\n\n[Smolagents : Huggingface AI Agent Framework](https://smolagents.org/)\n\ud83e\udd17 Smolagents is a minimalist AI agent framework developed by the Hugging Face team, crafted to enable developers to deploy robust agents with just a few lines of code. Embracing simplicity and efficiency, smolagents empowers large language models (LLMs) to interact seamlessly with the real world.\n\n[Introducing smolagents , a simple library to build agents - Hugging Face](https://huggingface.co/blog/smolagents)\nsmolagents is the successor to transformers.agents, and will be replacing it as transformers.agents gets deprecated in the future. Building an agent To build an agent, you need at least two elements: tools: a list of tools the agent has access to;\n\n[smolagents: a barebones library for agents. Agents write ... - GitHub](https://github.com/huggingface/smolagents)\nsmolagents is a library that enables you to run powerful agents in a few lines of code. It offers: Simplicity: the logic for agents fits in ~1,000 lines of code (see agents.py).We kept abstractions to their minimal shape above raw code! \ud83e\uddd1\u200d\ud83d\udcbb First-class support for Code Agents.Our CodeAgent writes its actions in code (as opposed to \"agents being used to write code\").\n\n[What are SmolAgents?: A Easy Guide With Code Examples](https://analyticsiksha.com/smolagents-by-hugging-face-a-comprehensive-guide/)\nIn the evolving world of artificial intelligence, Hugging Face has once again pushed the boundaries of innovation with its latest release: SmolAgents. SmolAgents - This lightweight, efficient, and versatile framework for building and running AI agents is designed to simplify complex workflows, making AI-powered solutions more accessible than ...\n\n[SmolAgents by Hugging Face: Build AI Agents in Under 30 Lines](https://www.analyticsvidhya.com/blog/2025/01/smolagents/)\nSmolAgents is an innovative library designed to simplify the creation and execution of powerful agents. Developed by Hugging Face, it stands out for its minimalist approach, with the entire agent logic encapsulated in approximately 1,000 lines of code. This streamlined design ensures ease of use while maintaining robust functionality.\n\n[Agents - Guided tour - Smolagents](https://smolagents.org/docs/agents-guided-tour/)\nfrom smolagents import tool @tool def model_download_tool(task: str) -> str: \"\"\" This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub. It returns the name of the checkpoint.\n\n[HuggingFace smolagents: The best Multi-Agent framework so far?](https://medium.com/data-science-in-your-pocket/huggingface-smolagents-the-best-multi-agent-framework-so-far-313178ef3c2e)\nWhat are smolagents? Smolagents is a newly launched agent framework by Hugging Face, designed to simplify the creation of intelligent agents that leverage large language models (LLMs).\n\n[smolagents\u2014Simplifying AI Agent Development](https://smolagents.org/smolagents-simplifying-ai-agent-development/)\nWhat is smolagents? smolagents is an open-source, lightweight AI agent library that allows developers to create powerful agents with minimal code. With a core codebase of approximately 1,000 lines in agents.py, smolagents reduces unnecessary abstractions, making the development process straightforward and accessible.By focusing on simplicity and efficiency, smolagents enables LLMs to interact ...\n\n[Getting Started with Smolagents](https://debuggercafe.com/smolagents/)\nWe have three Python files: app.py, tool.py, tool_config.py. The primary code resides in the tool.py file. This contains a class to generate the image and is a subclass of the Tool class.. The app.py file just imports the class and launches the Gradio demo.. And finally, the tool_config.py file is what tells the load_tool function that this is a tool and how to use it."}} |