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abidlabs 
posted an update 1 day ago
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1861
HOW TO ADD MCP SUPPORT TO ANY 🤗 SPACE

Gradio now supports MCP! If you want to convert an existing Space, like this one hexgrad/Kokoro-TTS, so that you can use it with Claude Desktop / Cursor / Cline / TinyAgents / or any LLM that supports MCP, here's all you need to do:

1. Duplicate the Space (in the Settings Tab)
2. Upgrade the Gradio sdk_version to 5.28 (in the README.md)
3. Set mcp_server=True in launch()
4. (Optionally) add docstrings to the function so that the LLM knows how to use it, like this:

def generate(text, speed=1):
    """
    Convert text to speech audio.

    Parameters:
        text (str): The input text to be converted to speech.
        speed (float, optional): Playback speed of the generated speech.


That's it! Now your LLM will be able to talk to you 🤯
abidlabs 
posted an update 2 days ago
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2151
Hi folks! Excited to share a new feature from the Gradio team along with a tutorial.

If you don't already know, Gradio is an open-source Python library used to build interfaces for machine learning models. Beyond just creating UIs, Gradio also exposes API capabilities and now, Gradio apps can be launched Model Context Protocol (MCP) servers for LLMs.

If you already know how to use Gradio, there are only two additional things you need to do:
* Add standard docstrings to your function (these will be used to generate the descriptions for your tools for the LLM)
* Set mcp_server=True in launch()


Here's a complete example (make sure you already have the latest version of Gradio installed):


import gradio as gr

def letter_counter(word, letter):
    """Count the occurrences of a specific letter in a word.
    
    Args:
        word: The word or phrase to analyze
        letter: The letter to count occurrences of
        
    Returns:
        The number of times the letter appears in the word
    """
    return word.lower().count(letter.lower())

demo = gr.Interface(
    fn=letter_counter,
    inputs=["text", "text"],
    outputs="number",
    title="Letter Counter",
    description="Count how many times a letter appears in a word"
)

demo.launch(mcp_server=True)



This is a very simple example, but you can add the ability to generate Ghibli images or speak emotions to any LLM that supports MCP. Once you have an MCP running locally, you can copy-paste the same app to host it on [Hugging Face Spaces](https://huggingface.co/spaces/) as well.

All free and open-source of course! Full tutorial: https://www.gradio.app/guides/building-mcp-server-with-gradio
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dn6 
in diffusers/docs-images 4 days ago

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#6 opened 4 days ago by
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linoyts 
posted an update 11 days ago
abidlabs 
posted an update 29 days ago
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3768
JOURNEY TO 1 MILLION DEVELOPERS

5 years ago, we launched Gradio as a simple Python library to let researchers at Stanford easily demo computer vision models with a web interface.

Today, Gradio is used by >1 million developers each month to build and share AI web apps. This includes some of the most popular open-source projects of all time, like Automatic1111, Fooocus, Oobabooga’s Text WebUI, Dall-E Mini, and LLaMA-Factory.

How did we get here? How did Gradio keep growing in the very crowded field of open-source Python libraries? I get this question a lot from folks who are building their own open-source libraries. This post distills some of the lessons that I have learned over the past few years:

1. Invest in good primitives, not high-level abstractions
2. Embed virality directly into your library
3. Focus on a (growing) niche
4. Your only roadmap should be rapid iteration
5. Maximize ways users can consume your library's outputs

1. Invest in good primitives, not high-level abstractions

When we first launched Gradio, we offered only one high-level class (gr.Interface), which created a complete web app from a single Python function. We quickly realized that developers wanted to create other kinds of apps (e.g. multi-step workflows, chatbots, streaming applications), but as we started listing out the apps users wanted to build, we realized what we needed to do:

Read the rest here: https://x.com/abidlabs/status/1907886