This documentation page is also available as an interactive notebook. You can launch the notebook in
Kaggle or Colab, or download it for use with an IDE or local Jupyter installation, by clicking one of the
above links.
Pixeltable’s Mistral AI integration enables you to access Mistral’s LLM
and other models via the Mistral AI API.
Prerequisites
Important notes
- Mistral AI usage may incur costs based on your Mistral AI plan.
- Be mindful of sensitive data and consider security measures when
integrating with external services.
First you’ll need to install required libraries and enter a Mistral AI
API key.
Now let’s create a Pixeltable directory to hold the tables for our demo.
Connected to Pixeltable database at: postgresql+psycopg://postgres:@/pixeltable?host=/Users/asiegel/.pixeltable/pgdata
Created directory ‘mistralai_demo’.
<pixeltable.catalog.dir.Dir at 0x3195333d0>
Messages
Create a Table: In Pixeltable, create a table with columns to represent
your input data and the columns where you want to store the results from
Mistral.
Created table ‘chat’.
Added 0 column values with 0 errors in 0.01 s
No rows affected.
Added 0 column values with 0 errors in 0.01 s
No rows affected.
Inserted 1 row with 0 errors in 2.31 s (0.43 rows/s)
Learn more
To learn more about advanced techniques like RAG operations in
Pixeltable, check out the RAG Operations in
Pixeltable
tutorial.
If you have any questions, don’t hesitate to reach out.