Problem The problem is, that when doing a multi-upload using the file uploader widget, some files can fail sometimes (even though they are below the file size limit), see screenshot: I tried uploading 13 files with ~12MB each. 7 failed a...
command = f'"{python_path}" -m streamlit run "{script_path}"' # 执行命令 result = subprocess.run(command, shell=True) if result.returncode != 0: print("脚本运行出错。") # 实例化并运行应用 if __name__ == "__main__": # 指定您的脚本路径 script_path = abs_path("w...
uploaded_files = st.file_uploader("Choose photos to upload", accept_multiple_files=True, type=['png', 'jpeg', 'jpg']) st.set_option('deprecation.showfileUploaderEncoding', False) # Enabling the automatic file decoder submit_button = st.button(label='Upload Photos') # Submit button pic_...
multiple(boolean; defaultFalse): Allow dropping multiple files. className(string; optional): HTML class name of the component. className_active(string; optional): HTML class name of the component while active. className_reject(string; optional): HTML class name of the component if rejected. ...
# Allow multiple files to be uploaded multiple=False, ) drag_drop = dcc.Upload( id='drag-drop-uploader', children=[ html.Img(src="assets/demos/img_template.jpg", style=MAIN_IMG_STYLE), html.P('Drag and drop to upload an image.', className="form-text text-muted", id='drag-drop-...
# import streamlit as st # import os # import google.generativeai as genai # genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) # # Function to load Gemini Pro model and get responses # model = genai.GenerativeModel("gemini-pro") # chat = model.start_chat(history=[]) # def ...
Run the application using Streamlit: streamlit run app.py Usage Upload Documents: Use the interface to upload multiple PDF documents. Ask Questions: Enter your questions in the provided text box. Get Answers: The chatbot processes the documents and provides relevant answers based on the content....
Upload a multiple page PDF and generate a quiz with multiple options. For each page 2 questions will be generated. This leverage Langchain library to abstract the LLM (Large Language Model) calls. The UI is based on Streamlit Will generate the following interractive quiz questions: Pre-requisit...
streamlit run app.py Open your web browser and go to http://localhost:8501 (or the URL provided by Streamlit). Usage Select a local language model from the dropdown menu. Upload one or more PDF files using the file uploader. Click the "Submit & Process" button to process the PDFs....
$ poetry shell $ streamlit run app.py 🐳 Run the app using Docker 💽 Build image $ docker compose build 🏃️ Run the app $ docker compose up Access to http://localhost:8501. 🌐 Deploy to Streamlit Cloud You can fork this repository and deploy the app to https://share.stre...