Getting Started
Check out our Cloud offering at Promptly or follow the instructions below to deploy LLMStack on your own infrastructure.
Prerequisites
Quickstart
Download the latest release from LLMStack's releases page and extract it. Navigate to the extracted directory and create your .env file and update SECRET_KEY, CIPHER_SALT and DATABASE_PASSWORD:
cp .env.prod .env
Run LLMStack using the following command:
./run-llmstack.sh
If you are on Windows, you can use
run-llmstack.batinstead
Once LLMStack is up and ready, it should automatically open your browser and point it to login page on http://localhost:3000. You can also alternatively use docker compose up --pull always to manually start the containers and open http://localhost:3000 to login into the platform. Make sure to wait for the API server to be ready before trying to load LLMStack.
LLMStack comes with a default admin account whose credentials are admin and promptly. Be sure to change the password from admin panel after logging in.
If you are deploying LLMStack on a server, make sure to update ALLOWED_HOSTS and CSRF_TRUSTED_ORIGINS in .env file to include the hostname of your server. Refer to the configuration section for more information.
Instead of downloading the release, you can also clone the repository and run the above commands in the cloned repository.
git clone https://github.com/trypromptly/LLMStack.git
Users of the platform can add their own keys to providers like OpenAI, Cohere, Stability etc., from Settings page. If you want to provide default keys for all the users of your LLMStack instance, you can add them to the .env file. Make sure to restart the containers after adding the keys.
Updating
To update LLMStack to the new release, download the latest release from LLMStack's releases page and extract it. Navigate to the extracted directory, copy the .env file from old installation to here and run the following command:
./run-llmstack.sh
Remember to update POSTGRES_VOLUME, REDIS_VOLUME and WEAVIATE_VOLUME in .env file if you want to persist data across container restarts.
Key Concepts
Processors
Processors are the basic building blocks in LLMStack. These provide the functionality to process the input from user or from a previous processor in a chain, take some action and optionally generate a response. LLMStack comes with a few built-in processors like OpenAI's ChatGPT, Image Generation, Stability's Image Generation etc. You can also create your own processors and add them to LLMStack.
Providers
Providers are the entities that provide the functionality to the processors. For example, OpenAI's ChatGPT processor uses OpenAI's API to generate text. LLMStack comes with a few built-in providers like OpenAI, Cohere, Stability etc. Providers act as namespaces for the processors. You can also create your own providers and add them to LLMStack.
Apps
Apps are the final product of LLMStack. Apps are created by chaining multiple processors together. LLMStack provides a visual editor to create apps. Apps can be shared with other users of LLMStack installation. Apps can be invoked using APIs, from the UI or triggered from Slack, Discord etc.
Datasources
Datasources are used to provide context to LLMs to build applications that can perform tasks on your data. LLMStack allows you to import data from various sources like CSV, PDF, URLs, Youtube etc., and use them in your apps. When a datasource is created, LLMStack chunks the data based on the type, creates embeddings and saves them in a vector database included in the installation. Datasources can also be shared with other users of LLMStack installation in the context of an organization.
Variables
Variables are used in LLMStack to provide dynamic values to the processors. For example, you can use variables to provide the name of the user to the processors. Variables are provided in the form {{name}} where name is the variable name. In App editor, data from previous processors/steps is available as variables and can be used in subsequent processors/steps.
If you have questions, suggestions or need help, feel free to join our Discord server or start a discussion on our Github Discussions page.