戒酒的李白
35 lines
1.3 KiB
ReStructuredText
35 lines
1.3 KiB
ReStructuredText
==============
|
|
TopicGPT
|
|
==============
|
|
|
|
TopicGPT integrates the remarkable capabilities of current LLMs such as GPT-3.5 and GPT-4 into topic modeling.
|
|
|
|
While traditional topic models extract topics as simple lists of top-words, such as ["Lion", "Leopard", "Rhino", "Elephant", "Buffalo"], TopicGPT offers rich and dynamic topic representations that can be intuitively understood, extensively investigated and modified in various ways via simple text commands.
|
|
|
|
More specifically, it provides the following core functionalities:
|
|
|
|
- Identification of clusters within document-embeddings and top-word extraction
|
|
- Generation of informative topic descriptions
|
|
- Extraction of detailed information about topics via Retrieval-Augmented-Generation (RAG)
|
|
- Comparison of topics
|
|
- Splitting and combining of identified topics
|
|
- Addition of new topics based on keywords
|
|
- Deletion of topics
|
|
|
|
It is further possible to directly interact with TopicGPT via prompting and without explicitly calling functions - an LLM autonomously decides which functionality to use.
|
|
|
|
Installation Guide
|
|
------------------
|
|
|
|
To install TopicGPT, simply use PyPI:
|
|
|
|
.. code-block:: bash
|
|
|
|
pip install topicgpt
|
|
|
|
GitHub Repository
|
|
-----------------
|
|
|
|
For more details, usage examples, source code, and testing procedures, please visit the TopicGPT GitHub repository: https://github.com/LMU-Seminar-LLMs/TopicGPT
|
|
|