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title: Standard Intelligence | |
emoji: 🌖 | |
colorFrom: yellow | |
colorTo: gray | |
sdk: gradio | |
sdk_version: 4.36.1 | |
app_file: app.py | |
pinned: false | |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
# **The Goal:** | |
**The goal of this tool is to make the an efficient and more focused analysis of the 3gpp contributions** | |
This tool will let you extract the content from the contributions of the 3gpp meetings, query the extracted content (summarize, does it talk about 5g?, …) and categories each contribution in your own personalized categories. | |
You’ll then have the possibility to generate charts to have a more simplified and visual overview of the documents. And you’ll also the possibility to code in your own functions and filters on the generated | |
# **Tabs** | |
![image/png](https://cdn-uploads.huggingface.co/production/uploads/65def87dea58a4f451de6ffa/PSDPtLqWjm93s6J4Qivva.png) | |
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# File extraction | |
This part aims to extract the most relevant content and information about every contribution from a 3gpp meeting | |
- ### Link search | |
Links can be searched directly within the interface. | |
- ### Filtering by document status | |
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. | |
- ### Example | |
![image/png](https://cdn-uploads.huggingface.co/production/uploads/65def87dea58a4f451de6ffa/4K0bM2hTmPjcZEb3n_Fs6.png) | |
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# Ask LLM | |
This section utilizes Large Language Models (LLMs) to query rows in an Excel file. | |
- ### Source columns | |
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. | |
- ### Destination column | |
This is just the name of the column in which the ansewer to your query will be written | |
- ### Prompt | |
This is the prompt you give to the LLM to interact with your source query | |
- ### Choose your LLM | |
This makes it possible to chose the LLM you want for your specific need. | |
- ### Filters | |
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) | |
- ### Example | |
# Classification by topic | |
- ### Source columns | |
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. | |
- ### Categories | |
You can define your own categories here | |
- ### Example | |
# Personalised chart generation | |
- ### Source columns | |
You select 2 column names and it generates a dimensional graph | |
- ### Categories | |
- ### Example | |
# Meeting Report (charts) | |
- ### Overall review | |
- ### By Expert | |
- ### By Company | |
- ### Example |