# Talemate

Roleplay with AI with a focus on strong narration and consistent world and game state tracking.

|![Screenshot 3](docs/img/0.17.0/ss-1.png)|![Screenshot 3](docs/img/0.17.0/ss-2.png)|
|------------------------------------------|------------------------------------------|
|![Screenshot 4](docs/img/0.17.0/ss-4.png)|![Screenshot 1](docs/img/0.19.0/Screenshot_15.png)|
|![Screenshot 2](docs/img/0.19.0/Screenshot_16.png)|![Screenshot 3](docs/img/0.19.0/Screenshot_17.png)|

Supported APIs:
- [OpenAI](https://platform.openai.com/overview)
- [Anthropic](https://www.anthropic.com/)
- [mistral.ai](https://mistral.ai/)
- [Cohere](https://www.cohere.com/)
- [Groq](https://www.groq.com/)
- [Google Gemini](https://console.cloud.google.com/)

Supported self-hosted APIs:
- [KoboldCpp](https://koboldai.org/cpp) ([Local](https://koboldai.org/cpp), [Runpod](https://koboldai.org/runpodcpp), [VastAI](https://koboldai.org/vastcpp), also includes image gen support)
- [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui) (local or with runpod support)
- [LMStudio](https://lmstudio.ai/)

Generic OpenAI api implementations (tested and confirmed working):
- [DeepInfra](https://deepinfra.com/)
- [llamacpp](https://github.com/ggerganov/llama.cpp) with the `api_like_OAI.py` wrapper
- let me know if you have tested any other implementations and they failed / worked or landed somewhere in between

## Core Features

- Multiple AI agents for dialogue, narration, summarization, direction, editing, world state management, character/scenario creation, text-to-speech, and visual generation
- Support for multiple AI clients and APIs
- Long-term memory using ChromaDB and passage of time tracking
- Narrative world state management to reinforce character and world truths
- Creative tools for managing NPCs, AI-assisted character, and scenario creation with template support
- Context management for character details, world information, past events, and pinned information
- Integration with Runpod
- Customizable templates for all prompts using Jinja2
- Modern, responsive UI

# Instructions

Please read the documents in the `docs` folder for more advanced configuration and usage.

- [Quickstart](#quickstart)
    - [Installation](#installation)
        - [Windows](#windows)
        - [Linux](#linux)
        - [Docker](#docker)
    - [Connecting to an LLM](#connecting-to-an-llm)
        - [OpenAI / mistral.ai / Anthropic](#openai--mistralai--anthropic)
        - [Text-generation-webui / LMStudio](#text-generation-webui--lmstudio)
            - [Specifying the correct prompt template](#specifying-the-correct-prompt-template)
            - [Recommended Models](#recommended-models)
        - [DeepInfra via OpenAI Compatible client](#deepinfra-via-openai-compatible-client)
        - [Google Gemini](#google-gemini)
            - [Google Cloud Setup](#google-cloud-setup)
    - [Ready to go](#ready-to-go)
    - [Load the introductory scenario "Infinity Quest"](#load-the-introductory-scenario-infinity-quest)
    - [Loading character cards](#loading-character-cards)
- [Configure for hosting](#configure-for-hosting)
- [Text-to-Speech (TTS)](docs/tts.md)
- [Visual Generation](docs/visual.md)
- [ChromaDB (long term memory) configuration](docs/chromadb.md)
- [Runpod Integration](docs/runpod.md)
- [Prompt template overrides](docs/templates.md)

# Quickstart

## Installation

Post [here](https://github.com/vegu-ai/talemate/issues/17) if you run into problems during installation.

There is also a [troubleshooting guide](docs/troubleshoot.md) that might help.

### Windows

1. Download and install Python 3.10 or Python 3.11 from the [official Python website](https://www.python.org/downloads/windows/). :warning: python3.12 is currently not supported.
1. Download and install Node.js v20 from the [official Node.js website](https://nodejs.org/en/download/). This will also install npm. :warning: v21 is currently not supported.
1. Download the Talemate project to your local machine. Download from [the Releases page](https://github.com/vegu-ai/talemate/releases).
1. Unpack the download and run `install.bat` by double clicking it. This will set up the project on your local machine.
1. Once the installation is complete, you can start the backend and frontend servers by running `start.bat`.
1. Navigate your browser to http://localhost:8080

### Linux

`python 3.10` or `python 3.11` is required. :warning: `python 3.12` not supported yet. 

`nodejs v19 or v20` :warning: `v21` not supported yet.

1. `git clone https://github.com/vegu-ai/talemate.git`
1. `cd talemate`
1. `source install.sh`
1. Start the backend: `python src/talemate/server/run.py runserver --host 0.0.0.0 --port 5050`.
1. Open a new terminal, navigate to the `talemate_frontend` directory, and start the frontend server by running `npm run serve`.

### Docker

:warning: Some users currently experience issues with missing dependencies inside the docker container, issue tracked at [#114](https://github.com/vegu-ai/talemate/issues/114)

1. `git clone https://github.com/vegu-ai/talemate.git`
1. `cd talemate`
1. `cp config.example.yaml config.yaml`
1. `docker compose up`
1. Navigate your browser to http://localhost:8080

:warning: When connecting local APIs running on the hostmachine (e.g. text-generation-webui), you need to use `host.docker.internal` as the hostname.

#### To shut down the Docker container

Just closing the terminal window will not stop the Docker container. You need to run `docker compose down` to stop the container.

#### How to install Docker

1. Download and install Docker Desktop from the [official Docker website](https://www.docker.com/products/docker-desktop).

# Connecting to an LLM

On the right hand side click the "Add Client" button. If there is no button, you may need to toggle the client options by clicking this button:

![Client options](docs/img/client-options-toggle.png)

![No clients](docs/img/0.21.0/no-clients.png)

## OpenAI / mistral.ai / Anthropic

The setup is the same for all three, the example below is for OpenAI.

If you want to add an OpenAI client, just change the client type and select the appropriate model.

![Add client modal](docs/img/0.21.0/openai-setup.png)

If you are setting this up for the first time, you should now see the client, but it will have a red dot next to it, stating that it requires an API key.

![OpenAI API Key missing](docs/img/0.18.0/openai-api-key-1.png)

Click the `SET API KEY` button. This will open a modal where you can enter your API key.

![OpenAI API Key missing](docs/img/0.21.0/openai-add-api-key.png)

Click `Save` and after a moment the client should have a green dot next to it, indicating that it is ready to go.

![OpenAI API Key set](docs/img/0.18.0/openai-api-key-3.png)

## Text-generation-webui / LMStudio

> :warning: As of version 0.13.0 the legacy text-generator-webui API `--extension api` is no longer supported, please use their new `--extension openai` api implementation instead. 

In the modal if you're planning to connect to text-generation-webui, you can likely leave everything as is and just click Save.

![Add client modal](docs/img/0.21.0/text-gen-webui-setup.png)

### Specifying the correct prompt template

For good results it is **vital** that the correct prompt template is specified for whichever model you have loaded.

Talemate does come with a set of pre-defined templates for some popular models, but going forward, due to the sheet number of models released every day, understanding and specifying the correct prompt template is something you should familiarize yourself with.

If the text-gen-webui client shows a yellow triangle next to it, it means that the prompt template is not set, and it is currently using the default `VICUNA` style prompt template.

![Default prompt template](docs/img/0.21.0/prompt-template-default.png)

Click the two cogwheels to the right of the triangle to open the client settings.

![Client settings](docs/img/0.21.0/select-prompt-template.png)

You can first try by clicking the `DETERMINE VIA HUGGINGFACE` button, depending on the model's README file, it may be able to determine the correct prompt template for you. (basically the readme needs to contain an example of the template)

If that doesn't work, you can manually select the prompt template from the dropdown. 

In the case for `bartowski_Nous-Hermes-2-Mistral-7B-DPO-exl2_8_0` that is `ChatML` - select it from the dropdown and click `Save`.

![Client settings](docs/img/0.21.0/selected-prompt-template.png)

### Recommended Models 

Any of the top models in any of the size classes here should work well (i wouldn't recommend going lower than 7B):

[https://oobabooga.github.io/benchmark.html](https://oobabooga.github.io/benchmark.html)

## DeepInfra via OpenAI Compatible client

You can use the OpenAI compatible client to connect to [DeepInfra](https://deepinfra.com/).

![DeepInfra](docs/img/0.21.0/deepinfra-setup.png)

```
API URL: https://api.deepinfra.com/v1/openai
```

Models on DeepInfra that work well with Talemate:

- [mistralai/Mixtral-8x7B-Instruct-v0.1](https://deepinfra.com/mistralai/Mixtral-8x7B-Instruct-v0.1) (max context 32k, 8k recommended)
- [cognitivecomputations/dolphin-2.6-mixtral-8x7b](https://deepinfra.com/cognitivecomputations/dolphin-2.6-mixtral-8x7b) (max context 32k, 8k recommended)
- [lizpreciatior/lzlv_70b_fp16_hf](https://deepinfra.com/lizpreciatior/lzlv_70b_fp16_hf) (max context 4k)

## Google Gemini

### Google Cloud Setup

Unlike the other clients the setup for Google Gemini is a bit more involved as you will need to set up a google cloud project and credentials for it.

Please follow their [instructions for setup](https://cloud.google.com/vertex-ai/docs/start/client-libraries) - which includes setting up a project, enabling the Vertex AI API, creating a service account, and downloading the credentials.

Once you have downloaded the credentials, copy the JSON file into the talemate directory. You can rename it to something that's easier to remember, like `my-credentials.json`.

### Add the client

![Google Gemini](docs/img/0.25.0/google-add-client.png)

The `Disable Safety Settings` option will turn off the google reponse validation for what they consider harmful content. Use at your own risk.

### Conmplete the google cloud setup in talemate

![Google Gemini](docs/img/0.25.0/google-setup-incomplete.png)

Click the `SETUP GOOGLE API CREDENTIALS` button that will appear on the client.

The google cloud setup modal will appear, fill in the path to the credentials file and select a location that is close to you.

![Google Gemini](docs/img/0.25.0/google-cloud-setup.png)

Click save and after a moment the client should have a green dot next to it, indicating that it is ready to go.

![Google Gemini](docs/img/0.25.0/google-ready.png)

## Ready to go

You will know you are good to go when the client and all the agents have a green dot next to them.

![Ready to go](docs/img/0.21.0/ready-to-go.png)

## Load the introductory scenario "Infinity Quest"

Generated using talemate creative tools, mostly used for testing / demoing.

You can load it (and any other talemate scenarios or save files) by expanding the "Load" menu in the top left corner and selecting the middle tab. Then simple search for a partial name of the scenario you want to load and click on the result.

![Load scenario location](docs/img/load-scene-location.png)

## Loading character cards

Supports both v1 and v2 chara specs.

Expand the "Load" menu in the top left corner and either click on "Upload a character card" or simply drag and drop a character card file into the same area.

![Load character card location](docs/img/load-card-location.png)

Once a character is uploaded, talemate may actually take a moment because it needs to convert it to a talemate format and will also run additional LLM prompts to generate character attributes and world state.

Make sure you save the scene after the character is loaded as it can then be loaded as normal talemate scenario in the future.

## Configure for hosting

By default talemate is configured to run locally. If you want to host it behind a reverse proxy or on a server, you will need create some environment variables in the `talemate_frontend/.env.development.local` file

Start by copying `talemate_frontend/example.env.development.local` to `talemate_frontend/.env.development.local`.

Then open the file and edit the `ALLOWED_HOSTS` and  `VUE_APP_TALEMATE_BACKEND_WEBSOCKET_URL` variables.

```sh
ALLOWED_HOSTS=example.com
# wss if behind ssl, ws if not
VUE_APP_TALEMATE_BACKEND_WEBSOCKET_URL=wss://example.com:5050
```
