- Helpers
- Cache
New to Gradio? Start here: Getting Started
See the Release History
To install Gradio from main, run the following command:
pip install https://gradio-builds.s3.amazonaws.com/15ce43720d1611f44e4661c74d604eabe0d04daf/gradio-6.28.0-py3-none-any.whl*Note: Setting share=True in launch() will not work.
Cache
gradio.Cache(···)Description
Thread-safe cache with manual get/set control, injected as a function parameter (add as a default parameter value and Gradio will inject it automatically). Supports per-session isolation so cached data doesn't leak between users, content-aware hashing for ML types (numpy, PIL, pandas), and LRU eviction with memory limits.
Example Usage
import gradio as gr
def generate(prompt, c=gr.Cache(per_session=True)):
hit = c.get(prompt)
if hit is not None:
return hit["result"]
result = llm(prompt)
c.set(prompt, result=result)
return resultInitialization
Parameters
Methods
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gradio.Cache.get(key, ···)Description
Look up a cache entry by key. Returns a dict of stored data, or None on miss. Keys can be any type supported by gr.cache (strings, numbers, numpy arrays, PIL images, etc.).
set
gradio.Cache.set(key, data, ···)Description
Store arbitrary keyword data under a key.
keys
gradio.Cache.keys(···)Description
Return all stored raw keys. Useful for iteration or prefix matching.
clear
gradio.Cache.clear(···)Description
Clear all entries from the cache.