# chat-ollama

**Repository Path**: gengxf0505/chat-ollama

## Basic Information

- **Project Name**: chat-ollama
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-04-14
- **Last Updated**: 2024-04-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ChatOllama

`ChatOllama` is an open source chatbot based on LLMs. It supports a wide range of language models including:

- Ollama served models
- OpenAI
- Azure OpenAI
- Anthropic

`ChatOllama` supports multiple types of chat:

- Free chat with LLMs
- Chat with LLMs based on knowledge base

`ChatOllama` feature list:
- Ollama models management
- Knowledge bases management
- Chat
- Commercial LLMs API keys management

## Join Our Community

If you are a user, contributor, or even just new to `ChatOllama`, you are more than welcome to join our community on Discord by clicking the [invite link](https://discord.gg/TjhZGYv5pC).

If you are a contributor, the channel `technical-discussion` is for you, where we discuss technical stuff.

If you have any issue in `ChatOllama` usage, please report to channel `customer-support`. We will help you out as soon as we can.

## Quick Start

As a user of `ChatOllama`, please walk through the document below, to make sure you get all the components up and running before starting using `ChatOllama`.

### Supported Vector Databases

`ChatOllama` supported 2 types of vector databases: Milvus and Chroma.

Please refer to the `.env.example` for how to work with your vector database setup.

```
# Supported values: chroma, milvus
VECTOR_STORE=chroma
CHROMADB_URL=http://localhost:8000
MILVUS_URL=http://localhost:19530
```

By default `ChatOllama` is using Chroma. If you'd like to use Milvus, set `VECTOR_STORE` to `milvus` and specify the corresponding URL. It works both in the development server and Docker containers.

### Use with Nuxt 3 Development Server

If you'd like to run with the latest code base and apply changes as needed, you can clone this repository and follow the steps below.

1. Install and run Ollama server

    You will need an Ollama server running. Follow the installation guide of [Ollama](https://github.com/ollama/ollama). By default, it's running on http://localhost:11434.    

2. Install Chroma

    Please refer to [https://docs.trychroma.com/getting-started](https://docs.trychroma.com/getting-started) for Chroma installation.

    We recommend you run it in a docker container:

    ```bash
    #https://hub.docker.com/r/chromadb/chroma/tags

    docker pull chromadb/chroma
    docker run -d -p 8000:8000 chromadb/chroma
    ```
    Now, ChromaDB is running on http://localhost:8000

3. ChatOllama Setup

    Now, we can complete the necessary setup to run ChatOllama.

    3.1 Copy the `.env.example` file to `.env` file:

    ```bash
    cp .env.example .env
    ```

    3.2 Make sure to install the dependencies:

    ```bash
    # npm
    npm install

    # pnpm
    pnpm install

    # yarn
    yarn install

    # bun
    bun install
    ```

    3.3 Run a migration to create your database tables with Prisma Migrate

    ```bash
    # npm
    npm run prisma-migrate

    # pnpm
    pnpm prisma-migrate

    # yarn
    yarn prisma-migrate

    # bun
    bun run prisma-migrate
    ```

4. Launch Development Server

    > Make sure both __[Ollama Server](#ollama-server)__ and __[ChromaDB](#install-chromadb-and-startup)__ are running.

    Start the development server on `http://localhost:3000`:

    ```bash
    # npm
    npm run dev

    # pnpm
    pnpm dev

    # yarn
    yarn dev

    # bun
    bun run dev
    ```

### Use with Docker

This is the easist way to use `ChatOllama`.

The only thing you need is a copy of [docker-compose.yaml](./docker-compose.yaml). Please download it and execute the command below to launch `ChatOllama`.

```shell
$ docker compose up
```

As `ChatOllama` is running within a docker container, you should set Ollama server to `http://host.docker.internal:11434` in the Settings section, assuming your Ollama server is running locally with default port.

Make sure you initialize the SQLite database as below if you are launching the dockerized `ChatOllama` for the first time:

```shell
$ docker compose exec chatollama npx prisma migrate dev
```
#### Prerequisites for knowledge bases
When using KnowledgeBases, we need a valid embedding model in place. It can be one of the models downloaded by Ollama or from 3rd party service provider for example, OpenAI.

**Ollama Managed Embedding Model**

We recommand you download `nomic-embed-text` model for embedding purpose.

You can do so on Models page http://localhost:3000/models, or via CLI as below if you are using Docker.

```shell
# In the folder of docker-compose.yaml

$ docker compose exec ollama ollama pull nomic-embed-text:latest
```

**OpenAI Embedding Model**

If you prefer to use OpenAI, please make sure you set a valid OpenAI API Key in Settings, and fill with one of the OpenAI embedding models listed below:

- `text-embedding-3-large`
- `text-embedding-3-small`
- `text-embedding-ada-002`

#### Data Storage with Docker Containers

There are 2 types of data storage, vector data and relational data. See the summary below and for more details, please refer to [docker-compose.yaml](./docker-compose.yaml) for the settings.

##### Vector data

With `docker-compose.yaml`, a dockerized Chroma database is run side by side with `ChatOllama`. The data is persisted in a docker volume.

##### Relational data

The relational data including knowledge base records and their associated files are stored in a SQLite database file persisted and mounted from `~/.chatollama/chatollama.sqlite`.

## Developers Guide

As ChatOllama is still under active development, features, interfaces and database schema may be changed. Please follow the instructions below in your every `git pull` to make sure your dependencies and database schema are always in sync.

1. Install the latest dependencies
    - `npm install` OR
    - `pnpm install`
2. Prisma migrate
    - `pnpm run prisma-migrate` OR
    - `npm run prisma-migrate`

## Change logs:

Here we summarize what's done and released in our day-to-day development.

### 03/10/2024

1. Instructions data will be stored in SQLite database.
2. `vueuse` is introduced for storage management.