Selfie Personal Server

Quick Start | Releases (+MacOS executables)

Imagine AI that is not just smart, but personal. The Selfie Personal Server turns your data into APIs for text generation and natural language search that can power chatbots, storytelling experiences, games, and more, while keeping you in control of your data.

Selfie is a local-first, open-source project that runs on your device.

Check out the video tour! (recorded using an older version of Selfie)

Core Features

Selfie offers a more personalized interaction between you and the digital world via:

Text Completions: Mix your data into text completions using any OpenAI-compatible tool (like OpenAI SDKs and SillyTavern) or the API.
Simple Data Import: Quickly import any text file, with enhanced support for messaging platform exports.
Use Any LLM: Use local (default) or hosted LLMs from OpenAI, Replicate, etc.
Direct Queries: Search your data with natural language.

Web-Based UI

Selfie comes with a local UI for importing and interacting with your data.

Personalized Chat

Semantic Search

Full API Support

Selfie provides a full API for OpenAI-style text completions and search.

curl -X POST 'http://localhost:8181/v1/chat/completions' \
-H 'Content-Type: application/json' \
-d '{
  "messages": [{"role": "user", "content": "As Alice, what is your proudest garden achievement?"}]
}' | jq '.choices[0].message.content'

# "I grew a 10-pound tomato!"

Jump to API Usage

Quick Start

Choose an installation method that best suits your operating system.

Important: The first time you run Selfie, it will download ~4GB of model weights and may appear to be unresponsive.

MacOS: Running a Downloadable Executable

Choose and download the latest executable for your MacOS based on the processor type:

Apple silicon processors (includes M1, M2, and later models)
Intel processors

Unzip the downloaded file and run the executable to start Selfie.
Right-click on the system tray icon and click Launch UI to open the Selfie UI in your default web browser.

MacOS, Linux: Running the Quick Start Script with Python

To run Selfie using Python, follow these steps:

Ensure Python (version 3.9 or later), Poetry, and Node.js are installed on your system.
Clone the Selfie repository or download the source code for the latest release.
Execute start.sh to run the application.
Right-click on the system tray icon and click Launch UI to open the Selfie UI in your default web browser.

Tip: On MacOS, you can quickly install Poetry and Node.js using Homebrew with the following command: brew install poetry nodejs. Visit Homebrew's website for installation instructions.

If you encounter any issues, refer to the detailed manual installation instructions in the Installation section.

MacOS, Linux, Windows: Manual Installation

Windows users should refer to the detailed installation instructions in the Installation section.

Overview

Selfie's core feature is personalized text generation. You can think of it as middleware that intelligently mixes your data into a request.

A typical request:

Application --prompt--> LLM

A request through Selfie:

Application --prompt--> Selfie --prompt+data--> LLM

On the application side, Selfie exposes text generation APIs, including OpenAI-compatible endpoints.

On the LLM side, Selfie uses tools like LiteLLM and txtai to support forwarding data-augmented requests to your LLM of choice

Installation

For most users, the easiest way to install Selfie is to follow the Quick Start instructions. If that doesn't work, or if you just want to install Selfie manually, follow the detailed instructions below.

Tip: Python 3.11 is recommended.

Manual Installation

Ensure that python 3.9+, poetry, and Node.js are installed.
Clone or download the repository.
In a terminal, navigate to the project directory.
Run ./scripts/build-ui.sh to build the UI and copy it to the server.
Run poetry install to install required Python dependencies.
Optional: Run ./scripts/llama-cpp-python-cublas.sh to enable hardware acceleration (for details, see Scripts).
Run poetry run python -m selfie. The first time you run this, it will download ~4GB of model weights.
- On macOS, you may need to run OMP_NUM_THREADS=1 KMP_DUPLICATE_LIB_OK=TRUE poetry run python -m selfie to avoid OpenMP errors. Read more about OMP_NUM_THREADS here.

If you encounter any issues, you can try running in headless mode: poetry run python -m selfie --headless and opening http://localhost:8181 in your browser.

Note: You can host selfie at a publicly-accessible URL with ngrok. Add your ngrok token (and optionally, ngrok domain) in selfie/.env and run poetry run python -m selfie --share.

Using Docker

You can also run Selfie using Docker. To do so, follow these steps:

Ensure that Docker is installed.
Clone or download selfie repository.
In a terminal, navigate to the project directory.
Run the following commands for the image you want to use (CPU, GPU, or ARM64).

This will start the server and the UI in your browser at http://localhost:8181. Your data will be stored in the data directory. This mounts your Hugging Face cache into the container, so you don't have to download the models again if you already have them.

CPU Image

./docker/build.sh cpu 

docker run -p 8181:8181 \
  --name selfie-cpu \
  -v $(pwd)/data:/selfie/data \
  -v $HOME/.cache/huggingface:/root/.cache/huggingface \
  selfie:cpu

Nvidia GPU Image

./docker/build.sh gpu 

docker run -p 8181:8181 \
  --name selfie-gpu \
  -v $(pwd)/data:/selfie/data \
  -v $HOME/.cache/huggingface:/root/.cache/huggingface \
  --gpus all \
  --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \
  selfie:gpu

MacOS ARM64 Image

Disclaimer:

This Docker container is designed to run on a wide range of architectures, including Apple's M1 and M2 chips. However, due to current limitations with Docker on macOS, direct access to Metal APIs is not available for containers. As a result, applications requiring intensive graphics processing may experience reduced performance compared to running natively on macOS. This setup is recommended for development and testing purposes only. Running it on a native machine is recommended for better performance.

We're continuously exploring ways to improve performance and compatibility.

 ./docker/build.sh arm64

docker run -p 8181:8181 \
  --name selfie-arm64 \
  -v $(pwd)/data:/selfie/data \
  -v $HOME/.cache/huggingface:/root/.cache/huggingface \
  selfie:arm64

Setting Up Selfie

Selfie comes with a web-based UI that you can use to import your data and interact with it.

Import Your Data

Selfie supports importing text data, with special processing for certain data formats, like chat logs from WhatsApp and ChatGPT.

Note: You can try the example files in the example-chats directory if you want to try a specific data format that you don't have ready for import.

To import data into Selfie:

Open the Add Data Page: Access the UI and locate the Add Data section.
Select Data Source: Choose the type of data you are uploading (e.g., WhatsApp, Text Files). Choose the type that most closely matches your data format.
Configure and Submit: Complete the required fields and submit the form.

Support for new types of data can be added by creating new data connectors in selfie/connectors/ (instructions here, please contribute!).

Note: Ensure you obtain consent from participants in the chats you wish to export.

Interact With Your Data

Now you are ready to interact with your data!

The Playground page includes a chat interface and a search feature. Write an LLM persona by entering a name and bio, and try interacting with your data through conversation. You can also search your data for specific topics under Search.

Now you are ready to use the Selfie API!

API Usage Guide

To quickly see your API in action, try viewing this link in your web browser:

http://localhost:8181/v1/index_documents/summary?topic=travel.

Detailed API documentation is available here.

How Text Completions Work

By default, Selfie augments text completions with local models using llama.cpp and a local txtai embeddings database.

OpenAI-supported parameters like messages, temperature, max_tokens, etc., should all work out of the box, with some special considerations:

model should be a local path, HuggingFace model name, or LiteLLM model name, depending on the method you choose.

You can also include special parameters to direct Selfie in how your request should be handled:

method: The method to use for text generation. Options are llama.cpp for running local model files directly (e.g., .gguf files), and litellm for everything else.
api_base: The base URL of an OpenAI-compatible API to use for text generation, e.g. if you want to host a local model with another tool.
api_key: The API key required by your API at api_base.
disable_augmentation: Set to true to generate text without data augmentation.

Examples and more details are provided in the next sections.

Using Selfie With Local Models

Selfie uses txtai to download local models and run them with llama.cpp. In completion requests, specify the llama.cpp method, or leave it off as the default, and ensure that your model is defined correctly, as a local path or HuggingFace model, according to txtai's documentation.

{
  "prompt": "What is the meaning of life?",
  "method": "llama.cpp",
  "model": "~/models/dolphin-2.6-mistral-7b-dpo.Q5_K_M.gguf"
}

or

{
  "prompt": "What is the meaning of life?",
  "method": "llama.cpp",
  "model": "TheBloke/dolphin-2.6-mistral-7B-dpo-GGUF/dolphin-2.6-mistral-7b-dpo.Q5_K_M.gguf"
}

You can even use a local Open-AI compatible API (LiteLLM OpenAI-Compatible Endpoints docs).

{
  "method": "litellm",
  "api_base": "http://localhost:5000/v1",
  "api_key": "none"
}

Method is optional and defaults to litellm when api_base is specified.

Using Selfie with Hosted Models

Selfie can use hosted model providers through litellm. In completion requests, specify the litellm method (optional) and ensure that your model is prefixed correctly according to litellm's documentation for your provider.

{
  "method": "litellm",
  "model": "replicate/llama-2-70b-chat:2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf"
}

In general, you need an API key for your provided loaded into your environment. A quick way to do that is to specify it when you start the server: REPLICATE_API_KEY=replicatekey python -m selfie.

Vanilla Text Generation

Add disable_augmentation: true to your request body to generate text without data augmentation.

{
  "prompt": "What is the meaning of life?",
  "method": "llama.cpp",
  "model": "~/models/dolphin-2.6-mistral-7b-dpo.Q5_K_M.gguf",
  "disable_augmentation": true
}

Integration Recipes

Selfie can be used to augment text generation in a variety of applications. Here are some examples.

Powering the OpenAI SDK

The OpenAI SDK is a popular way to access OpenAI's text generation models. You can use Selfie to augment the text completions that the SDK generates simply by setting the apiBase and apiKey parameters.

import OpenAI from 'openai';

const openai = new OpenAI({
  baseURL: 'http://localhost:8181/v1',
  apiKey: ''
});

const chatCompletion = await openai.chat.completions.create({
  messages: [
    { role: 'system', content: `Write Alice's next reply.` },
    { role: 'user', content: 'What are your favorite snacks?' },
  ]
});

console.log(chatCompletion.choices[0].message.content);

// "I enjoy Bahn Mi and Vietnamese coffee."

Powering SillyTavern

SillyTavern is a self-hosted application that allows you to chat/roleplay with characters that you create. You can use Selfie to give SillyTavern characters some awareness of your data.

Install and run SillyTavern.
Configure a custom chat completion source as http://localhost:8181. You can customize the model by setting API parameters for method and model in Additional Parameters.
Create a character, customize the text generation settings, etc.
Chat with your character to see that it is aware of your data:

You can even tell Selfie to use an OpenAI-compatible API for the LLM that it augments:

Note that model is empty: We pass an extra parameter, instruct_mode, for text-generation-webui.

Note: some OpenAI-compatible APIs may not properly handle SillyTavern's use of multiple system messages and non-alternating user/assistant messages (like text-generation-webui). A text-generation-webui workaround is described here.

Scripts

The scripts directory contains a variety of scripts for setting up Selfie. Here's a brief overview of each script:

build-ui.sh

To build the UI, run ./scripts/build-ui.sh.

llama-cpp-python-cublas.sh

To install llama.cpp with hardware acceleration for better performance, run ./scripts/llama-cpp-python-cublas.sh.

Alternatively, you can build llama-cpp-python manually with the flags of your choice by following the instructions.

Experimental Features

Selfie is a work in progress. Here are some features that are not yet fully supported.

Building an Executable

To build an executable for your platform:

Run poetry run pip install pyinstaller. (pyinstaller is not compatible with Python >3.12 so it is not included by default)
Run poetry run pyinstaller selfie.spec --noconfirm.
Start the built service with ./dist/selfie/selfie.

Contributing

Selfie is a community project. We welcome contributions of all kinds, including bug reports, feature requests, and pull requests. Please see the contributing guide for more information.

Community

Join the Vana Discord server to chat with the community and get help with Selfie.

Provide feedback

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README.md

README.md

Selfie Personal Server

Core Features

Web-Based UI

Full API Support

Quick Start

MacOS: Running a Downloadable Executable

MacOS, Linux: Running the Quick Start Script with Python

MacOS, Linux, Windows: Manual Installation

Overview

Installation

Using Docker

CPU Image

Nvidia GPU Image

MacOS ARM64 Image

Setting Up Selfie

Import Your Data

Interact With Your Data

API Usage Guide

How Text Completions Work

Using Selfie With Local Models

Using Selfie with Hosted Models

Vanilla Text Generation

Integration Recipes

Powering the OpenAI SDK

Powering SillyTavern

Scripts

build-ui.sh

llama-cpp-python-cublas.sh

Experimental Features

Building an Executable

Contributing

Community

Files

README.md

Latest commit

History

README.md

File metadata and controls

Selfie Personal Server

Core Features

Web-Based UI

Full API Support

Quick Start

MacOS: Running a Downloadable Executable

MacOS, Linux: Running the Quick Start Script with Python

MacOS, Linux, Windows: Manual Installation

Overview

Installation

Using Docker

CPU Image

Nvidia GPU Image

MacOS ARM64 Image

Setting Up Selfie

Import Your Data

Interact With Your Data

API Usage Guide

How Text Completions Work

Using Selfie With Local Models

Using Selfie with Hosted Models

Vanilla Text Generation

Integration Recipes

Powering the OpenAI SDK

Powering SillyTavern

Scripts

build-ui.sh

llama-cpp-python-cublas.sh

Experimental Features

Building an Executable

Contributing

Community