Streamlit¶
Installation¶
(mypy310) lkk@Alienware-LKKi7G8:~/Developer$ pip install streamlit
(mypy310) lkk@Alienware-LKKi7G8:~/Developer$ streamlit hello #run demo in browser
streamlit run your_script.py [-- script args]
“st.write()”: which can be used to write anything from text to tables. Streamlit supports “magic commands,” which means you don’t have to use st.write() at all!
- Scripts use the Streamlit cache to avoid recomputing expensive functions, so updates happen very fast
“st.cache_data” is the recommended way to cache computations that return data
“st.cache_resource” is the recommended way to cache global resources like ML models or database connections – unserializable objects that you don’t want to load multiple times.
Streamlit apps can contain multiple pages, which are defined in separate .py files in a pages folder.
References¶
Run a Streamlit App with Google Colab Notebook: https://alphasec.io/run-a-streamlit-app-with-google-colab-notebook/
https://github.com/mmz-001/knowledge_gpt/tree/main
https://alphasec.io/prototype-langchain-flows-visually-with-langflow/
https://alphasec.io/persistent-ai-chat-bots-with-langchain-and-steamship/
https://alphasec.io/deploy-your-own-ai-chat-bot-using-openai-and-vercel/
https://www.langchain.com/ LangChain is a framework for developing applications powered by language models.
conda install langchain -c conda-forge pip install langchain[llms] pip install openai https://python.langchain.com/docs/get_started/quickstart