Interactive workflows for generating AI intelligence reports from real-world data sources using GPT models
Project description
Developing
Requirements
-
Python 3.11 or 3.12 (Download)
-
uv (Download)
-
wkhtmltopdf (used to generate PDF reports)
-
Windows: (Download)
-
Linux:
sudo apt-get install wkhtmltopdf -
macOS:
curl -L https://github.com/wkhtmltopdf/packaging/releases/download/0.12.6-2/wkhtmltox-0.12.6-2.macos-cocoa.pkg -O installer -pkg wkhtmltox-0.12.6-2.macos-cocoa.pkg -target ~ -
Running the app
GPT settings
You can configure your OpenAI access when running the app via Settings page, or using environment variables.
Default values:
OPENAI_API_MODEL="gpt-4.1-mini"
OPENAI_TYPE="OpenAI" ## Other option available: Azure OpenAI
AZURE_AUTH_TYPE="Azure Key" # if OPENAI_TYPE==Azure OpenAI
DEFAULT_EMBEDDING_MODEL = "text-embedding-3-small"
OpenAI
OPENAI_API_KEY=<OPENAI_API_KEY>
Azure OpenAI
OPENAI_TYPE="Azure OpenAI"
AZURE_OPENAI_VERSION=2023-12-01-preview
AZURE_OPENAI_ENDPOINT="https://<ENDPOINT>.azure.com/"
OPENAI_API_KEY=<AZURE_OPENAI_API_KEY>
#If Azure OpenAI using Managed Identity:
AZURE_AUTH_TYPE="Managed Identity"
Running locally
Windows: Search and open the app Windows Powershell on Windows start menu
Linux and Mac: Open Terminal
For any OS:
Navigate to the folder where you cloned this repo.
Use cd + the path to the folder. For example:
cd C:\Users\user01\projects\intelligence-toolkit
Run uv sync --extra dev and wait for the packages installation.
Run the app:
Run uv run poe run_streamlit, and it will automatically open the app in your default browser in localhost:8081
Use the API
You can also replicate the examples in your own environment running pip install intelligence-toolkit or uv add intelligence-toolkit.
See the documentation and an example of how to run the code with your data to obtain results without the need to run the UI.
Running with docker
Recommended configuration:
- Minimum disk space: 8GB
- Minimum memory: 4GB
Download, install and then open docker app: https://www.docker.com/products/docker-desktop/
Then, open a terminal:
Windows: Search and open the app Windows Powershell on Windows start menu
Linux and Mac: Open Terminal
For any OS:
Navigate to the folder where you cloned this repo.
Use cd + the path to the folder. For example:
cd C:\Users\user01\projects\intelligence-toolkit
Build the container:
docker build . -t intelligence-toolkit
Once the build is finished, run the docker container:
-
via terminal:
docker run -d --name intelligence-toolkit -p 80:80 intelligence-toolkit
Open localhost:80
Note that docker might sleep and you might need to start it again. Open Docker Desktop, in the left menu click on Container and press play on intelligence-toolkit.
Lifecycle Scripts
For Lifecycle scripts it utilizes uv and poethepoet to manage build scripts.
Available scripts are:
uv run poe test_unit- This will execute unit tests on api.uv run poe test_smoke- This will execute smoke tests on api.uv run poe check- This will perform a suite of static checks across the package, including:- formatting
- documentation formatting
- linting
- security patterns
- type-checking
uv run poe fix- This will apply any available auto-fixes to the package. Usually this is just formatting fixes.uv run poe fix_unsafe- This will apply any available auto-fixes to the package, including those that may be unsafe.uv run poe format- Explicitly run the formatter across the package.
Project details
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