| Name | sigmund JSON |
| Version |
0.30.0
JSON |
| download |
| home_page | None |
| Summary | AI-based chatbot that provides sensible answers based on documentation |
| upload_time | 2025-02-07 11:18:42 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
ai
chatbot
llm
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# Sigmund AI
Copyright 2023-2025 Sebastiaan Mathôt
A Python library and web app for an LLM-based chatbot with two main modes:
- __OpenSesame expert__: answers questions about OpenSesame based on documentation
- __Research assistant__: a general purpose chatbot with several tools that are mainly useful for research
Features:
- __Privacy__: all messages and uploaded attachments are encrypted so that no-one can listen in on your conversation
- __Knowledge__ (in OpenSesame mode): access to documentation
- __Continuous conversation__: conversations are summarized w hen they become too long to fit into the prompt
- __Tool use__ (in research-assistant mode):
- __Code execution__: ability to execute Python and R code
- __Google Scholar search__: ability to search for articles on Google Scholar
- __Attachments__: ability to read attachments
- __Download__: ability to download pages and files as attachments
- __Image generation__: ability to generate images
Sigmund is not a large language model itself. Rather it uses third-party models. Currently, models from [OpenAI](https://openai.com), [Anthropic](https://www.anthropic.com/), and [Mistral](https://mistral.ai/) are supported. API keys from these respective providers are required.
## What can Sigmund do? And how does Sigmund work?
For a description of how Sigmund works, see: <https://sigmundai.eu/about>. This page describes the default configuration.
## Configuration
See `sigmund/config.py` for configuration instructions.
## Dependencies
For Python dependencies, see `pyproject.toml`. In addition to these, `pandoc` is required for the ability to read attachments, and a local `redis` server needs to run for persistent data between sessions.
## Running (development)
Download the source code, and in the folder of the source code execute the following:
```
# Specify API keys for model providers. Even when using Anthropic (Claude) or
# Mistral, an OpenAI key is provided when document search is enabled
export OPENAI_API_KEY="your key here"
export ANTHROPIC_API_KEY="your key here"
export MISTRAL_API_KEY="your key here"
pip install . # install dependencies
python index_library.py # build library (documentation) index
python app.py # start the app
```
Next, access the app (by default) through:
```
http://127.0.0.1:5000/
```
## Running (production)
In production, the server is generally not run by directly calling the app. There are many ways to run a Flask app in production. One way is to use gunicorn to start the app, and then use an nginx web server as a proxy that reroutes requests to the app. When taking this route, make sure to set up nginx with a large `client_max_body_size` (to allow attachment uploading) and disable `proxy_cache` and `proxy_buffering` (to allow status messages to be streamed while Sigmund is answering).
## License
Sigmund is distributed under the terms of the GNU General Public License 3. The full license should be included in the file `COPYING`, or can be obtained from:
- <http://www.gnu.org/licenses/gpl.txt>
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