Add AI Memory to Jupyter

Enhance Jupyter with long-term AI memory to persist key code cells, queries, and research insights across session.

Try it free

How can I enhance Jupyter with memory?

Pieces infuses Jupyter with long-term memory, allowing you to retain code snippets, data insights, and project context across sessions. Imagine recalling that crucial command or data transformation from weeks ago, directly within your Jupyter environment. Pieces makes it seamless.

What else can Pieces remember?

1

Install & launch PiecesOS

Install and run Pieces OS on your device.

2

Enable Long-Term Memory

Open the PiecesOS menu from your tray and enable Long-Term Memory.

3

Start using memory

Pieces automatically captures code, notebooks, and project metadata from Jupyter, creating an intelligent, searchable memory.

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Capture everything automatically

Pieces automatically captures code, notebooks, and contextual information from Jupyter, ensuring that your valuable work and insights are preserved. You maintain full control over what's captured, with easy opt-out options and robust security measures to protect your data. Pieces respects your privacy and your workflow.

Recall past work with ease

Pieces intelligently stores your Jupyter memories for up to nine months, creating a searchable archive of your projects. You can use time-based queries to quickly locate specific code snippets, data visualizations, or research findings from previous sessions. This means no more wasted time hunting through old notebooks.

Keep context across Jupyter workflows

Pieces helps you navigate your Jupyter history and maintain context across different projects. Easily trace the evolution of your code, understand the rationale behind specific analyses, and leverage past work to accelerate current projects. Pieces helps you build on your existing knowledge.

Best prompts for Add AI Memory to jupyter

Show me the code snippets I saved from my last jupyter session related to image processing.
What were the search queries I ran in jupyter yesterday while working on the sentiment analysis notebook?
Summarize my actions in jupyter last week concerning the 'customer churn' project.
Find the notebook where I experimented with different regularization techniques for my neural network.
List all the jupyter notebooks I opened in the last month that contain the word "TensorFlow".
What were the last 3 code cells I executed in jupyter before closing it yesterday?
Show me the exact code snippet where I fixed the 'IndexError' in my data cleaning script.
Find the notebook where I tried different hyperparameter tuning methods for the random forest model.
What were the different data visualization libraries I used in jupyter last week?
Show me the saved search results from when I was debugging the memory leak in my jupyter notebook.
Create a reusable snippet from the jupyter code cell that performs data normalization.
Summarize the steps I took to install the 'transformers' library in jupyter.
Find the jupyter notebook where I explored different feature engineering techniques.
What were the different versions of pandas I used in jupyter over the past month?
Show me the code snippet where I defined the custom loss function for my neural network.
List all the jupyter notebooks I opened that contain the phrase "gradient descent".
What were the different evaluation metrics I used to assess my machine learning model in jupyter?
Find the jupyter notebook where I compared the performance of different machine learning algorithms.
Show me the code snippet where I handled missing values in my dataset.
What were the different data sources I accessed from jupyter last week?
Create a reusable snippet from the jupyter code cell that performs one-hot encoding.
Summarize the steps I took to connect to the database from my jupyter notebook.
Find the jupyter notebook where I implemented the data pipeline for my project.
What were the different Python packages I imported in jupyter yesterday?
Show me the code snippet where I defined the activation function for my neural network.
List all the jupyter notebooks I opened that contain the word "regression".
What were the different data preprocessing techniques I applied in jupyter last week?
Find the jupyter notebook where I analyzed the time series data.
Show me the code snippet where I calculated the correlation matrix of my dataset.
What were the different command line arguments I used when running my jupyter notebook?
Create a reusable snippet from the jupyter code cell that performs principal component analysis (PCA).
Summarize the steps I took to deploy my machine learning model from jupyter.
Find the jupyter notebook where I built the recommendation system.
What were the different error messages I encountered while running my jupyter notebook last week?
Show me the code snippet where I implemented the cross-validation technique.
List all the jupyter notebooks I opened that contain the word "classification".
What were the different types of plots and charts I generated in jupyter last month?
Find the jupyter notebook where I performed the A/B testing.
Show me the code snippet where I handled outliers in my dataset.
What were the different file formats I used to store my data in jupyter?
Create a reusable snippet from the jupyter code cell that performs text tokenization.
Summarize the steps I took to train my machine learning model in jupyter.
Find the jupyter notebook where I visualized the results of my analysis.
What were the different hardware configurations I used when running my jupyter notebook?
Show me the code snippet where I defined the learning rate scheduler for my neural network.
List all the jupyter notebooks I opened that contain the word "clustering".
What were the different data cleaning operations I performed in jupyter last week?
Find the jupyter notebook where I implemented the natural language processing (NLP) pipeline.
Show me the code snippet where I performed feature selection.
What were the different environment variables I set when running my jupyter notebook?

Show me the code snippets I saved from my last jupyter session related to image processing.
What were the search queries I ran in jupyter yesterday while working on the sentiment analysis notebook?
Summarize my actions in jupyter last week concerning the 'customer churn' project.
Find the notebook where I experimented with different regularization techniques for my neural network.
List all the jupyter notebooks I opened in the last month that contain the word "TensorFlow".
What were the last 3 code cells I executed in jupyter before closing it yesterday?
Show me the exact code snippet where I fixed the 'IndexError' in my data cleaning script.
Find the notebook where I tried different hyperparameter tuning methods for the random forest model.
What were the different data visualization libraries I used in jupyter last week?
Show me the saved search results from when I was debugging the memory leak in my jupyter notebook.
Create a reusable snippet from the jupyter code cell that performs data normalization.
Summarize the steps I took to install the 'transformers' library in jupyter.
Find the jupyter notebook where I explored different feature engineering techniques.
What were the different versions of pandas I used in jupyter over the past month?
Show me the code snippet where I defined the custom loss function for my neural network.
List all the jupyter notebooks I opened that contain the phrase "gradient descent".
What were the different evaluation metrics I used to assess my machine learning model in jupyter?
Find the jupyter notebook where I compared the performance of different machine learning algorithms.
Show me the code snippet where I handled missing values in my dataset.
What were the different data sources I accessed from jupyter last week?
Create a reusable snippet from the jupyter code cell that performs one-hot encoding.
Summarize the steps I took to connect to the database from my jupyter notebook.
Find the jupyter notebook where I implemented the data pipeline for my project.
What were the different Python packages I imported in jupyter yesterday?
Show me the code snippet where I defined the activation function for my neural network.
List all the jupyter notebooks I opened that contain the word "regression".
What were the different data preprocessing techniques I applied in jupyter last week?
Find the jupyter notebook where I analyzed the time series data.
Show me the code snippet where I calculated the correlation matrix of my dataset.
What were the different command line arguments I used when running my jupyter notebook?
Create a reusable snippet from the jupyter code cell that performs principal component analysis (PCA).
Summarize the steps I took to deploy my machine learning model from jupyter.
Find the jupyter notebook where I built the recommendation system.
What were the different error messages I encountered while running my jupyter notebook last week?
Show me the code snippet where I implemented the cross-validation technique.
List all the jupyter notebooks I opened that contain the word "classification".
What were the different types of plots and charts I generated in jupyter last month?
Find the jupyter notebook where I performed the A/B testing.
Show me the code snippet where I handled outliers in my dataset.
What were the different file formats I used to store my data in jupyter?
Create a reusable snippet from the jupyter code cell that performs text tokenization.
Summarize the steps I took to train my machine learning model in jupyter.
Find the jupyter notebook where I visualized the results of my analysis.
What were the different hardware configurations I used when running my jupyter notebook?
Show me the code snippet where I defined the learning rate scheduler for my neural network.
List all the jupyter notebooks I opened that contain the word "clustering".
What were the different data cleaning operations I performed in jupyter last week?
Find the jupyter notebook where I implemented the natural language processing (NLP) pipeline.
Show me the code snippet where I performed feature selection.
What were the different environment variables I set when running my jupyter notebook?

DOWNLOAD FOR FREE

Never lose track of your work again. Try AI Memory

Talk to us

Try it free

DOWNLOAD FOR FREE

Never lose track of your work again. Try AI Memory

Talk to us

Get started

DOWNLOAD FOR FREE

Never lose track of your work again. Try AI Memory

Talk to us

Get started