Spaces:
Sleeping
title: Standard Intelligence
emoji: 🌖
colorFrom: yellow
colorTo: gray
sdk: gradio
sdk_version: 4.19.2
app_file: app.py
pinned: false
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
Tabs
File extraction
This part aims to extract the most relevant content and information about every contribution from a 3gpp meeting
Links can be searched directly within the interface.
If you want the download and extraction to go faster it is recommended that you use this functionnality. It makes sure that the documents are pre-filtered making it possible to download only the documents with a certain status, removing those which may be considered unnecessary.
Ask LLM
This section utilizes Large Language Models (LLMs) to query rows in an Excel file.
After giving an excel file, the columns of the excel file are suggested here as Source Columns. Only the content of the source columns you chose, will be given to the LLM.
This is just the name of the column in which the ansewer to your query will be written
This is the prompt you give to the LLM to interact with your source query
This makes it possible to chose the LLM you want for your specific need.
If you don't to waste your LLM's tokens on rows that aren't in your interest, you can filter your excel by specific words to only query the rows with the chosen words (It will look for the words only in the columns you specify)
Classification by topic
After giving an excel file, the columns of the excel file are suggested here as Source Columns. Only the content of the source columns you chose, will be used the classify the document in a category.
Personalised chart generation
After giving an excel file, the columns of the excel file are suggested here as Source Columns. Only the content of the source columns you chose, will be used the classify the document in a category.
Meeting Report (charts)
After giving an excel file, the columns of the excel file are suggested here as Source Columns. Only the content of the source columns you chose, will be used the classify the document in a category.