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57 changes: 18 additions & 39 deletions mkdocs/index.md
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# 👋 Hello, dear

The Cheshire Cat is an open-source, hackable and production-ready framework that allows developing intelligent personal
AI agents on top of [Large Language Models](framework/cat-components/llm.md) (LLM).

```
"Every adventure requires a first step".
(Alice's Adventures in Wonderland - Lewis Carroll)
```

## Quick links

<div class="grid cards" markdown>

- &#127939; __Onboarding__

---

Take your first step with hands-on examples!

[Get started now](quickstart/introduction.md){ .md-button }

- &#128268; __Plugins__

---

Dive into advanced concepts to develop and publish your plugin!

[Plugin documentation](plugins/plugins.md){ .md-button }

- &#129693; __Hooks__
<div class="grid" markdown>

---

Explore all the available hooks to customize the Cat!
[&#127939; Get started now](quickstart/installation-configuration.md){ .md-button }
[&#129693; Available Hooks](plugins/hooks.md#available-hooks){ .md-button }

[Available Hooks](plugins/hooks.md#available-hooks){ .md-button }
[&#128268; Plugin documentation](plugins/plugins.md){ .md-button }

- &#128640; __Deploy__

---

Ready-to-use setup to deploy your assistant!

[Docker Compose examples](production/administrators/docker-compose.md){ .md-button }
[&#128640; Docker Compose examples](production/administrators/docker-compose.md){ .md-button }

</div>

## Cheshire Cat Features

The Cheshire Cat is an open-source, hackable and production-ready framework that allows developing intelligent personal
AI assistant agents on top of [Large Language Models](framework/cat-components/llm.md) (LLM).

<div class="grid cards" markdown>

Expand All @@ -56,53 +33,55 @@ AI assistant agents on top of [Large Language Models](framework/cat-components/l

Chat with the Cat and interact with its endpoints!

[:octicons-arrow-right-24: Python API](production/network/clients.md)
[Client libs](production/network/clients.md){ .md-button }
[Endpoints](production/network/http-endpoints.md){ .md-button }

- &#128640; __Extendable via plugins in Python__

---

Write your first plugin, your imagination is the limit!

[:octicons-arrow-right-24: Write your first plugin](quickstart/prepare-plugin.md)
[Write your first plugin](quickstart/prepare-plugin.md){ .md-button }

- &#127757; __Language model agnostic__

---

Easily choose from a plenty of models to use!

[:octicons-arrow-right-24: compatible-models](production/administrators/docker-compose.md#compatible-models)
[Compatible Models](production/administrators/docker-compose/#cat-ollama){ .md-button }

- &#128220; __Can ingest documents__

---

Ground the model based on your knowledge base!

[:octicons-arrow-right-24: Retrieval Augmented Generation](framework/llm-concepts/rag.md)
[Retrieval Augmented Generation](framework/llm-concepts/rag.md){ .md-button }

- &#128024; __Local Long term memory__

---

Make use of a persistent memory across restarts!

[:octicons-arrow-right-24: Cat's Long Term Memory](framework/cat-components/memory/long_term_memory.md)
[Cat's Long Term Memory](framework/cat-components/memory/long_term_memory.md){ .md-button }

- &#128011; __100% dockerized__

---

Setup the Cat in the blink of an eye with the pre-built docker image!

[:octicons-arrow-right-24: Installation](quickstart/installation-configuration.md)
[Installation](quickstart/installation-configuration.md){ .md-button }

</div>

## Get in touch with us

[:fontawesome-brands-discord: Discord](https://discord.gg/bHX5sNFCYU){ .md-button .md-button--primary } &#128072;
[:fontawesome-brands-discord: Discord](https://discord.gg/bHX5sNFCYU){ .md-button }

Join our Discord community where you can
connect with other developers and ask for support to the contributors or directly to the Cat &#128570;
mentioning `@Cheshire Cat AI`.
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20 changes: 15 additions & 5 deletions mkdocs/production/administrators/docker-compose.md
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To facilitate, speed up, and standardize the Cat's user experience, the Cat lives inside a Docker container.
To facilitate, speed up, and standardize the Cat's user experience, the Cat lives inside a Docker container. This allows for maximum power, flexibility and portability, but requires a little understanding from you on [how docker works](https://docs.docker.com/get-started/).


## Cat standalone
Expand All @@ -19,20 +19,26 @@ services:
## Cat + Ollama
The cat is agnostic, meaning You can attach your preferred llm and embedder model/provider. The Cat supports the most used ones, but you can increase the number of models/providers by [plugins](../../plugins/hooks.md/#__tabbed_1_5), here is a list of the main ones:
The Cat is model agnostic, meaning you can attach your preferred LLM and embedder model/provider. The Cat supports the most used ones, but you can increase the number of models/providers by [plugins](../../plugins/hooks.md/#__tabbed_1_5), here is a list of the main ones:
1. OpenAI and Azure OpenAI
2. Cohere
3. Ollama (LLM model only)
3. Ollama
4. HuggingFace TextInference API (LLM model only)
5. Google Gemini
6. Qdrant FastEmbed (Embedder model only)
7. (custom via plugin)
If you want a setup Cat + Ollama, here an example `compose.yml`:
Let's see a full local setup for Cat + Ollama.
To make this work properly, be sure your docker engine can see the GPU via [NVIDIA docker](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html).
As an alternative you can install Ollama directly on your machine and making the Cat aware of it in the Ollama LLM settings, inserting your local network IP or using `host.docker.internal`.

Example `compose.yml`:

```yaml
services:
cheshire-cat-core:
image: ghcr.io/cheshire-cat-ai/core:latest
container_name: cheshire_cat_core
Expand Down Expand Up @@ -64,10 +70,14 @@ services:
capabilities: [gpu]
```

For a solid local embedder, choose one from the FastEmbed list.
The Cat will download the embedder in `cat/data` and will use it to embed text.
Congratulations, you are now free from commercial LLM providers.

## Cat + Qdrant

By default the Core uses an embedded version of [Qdrant](https://qdrant.tech/), based on SQLite.
It is highly recommended to connect the Cat to a full Qdrant instance to increase performance and capacity!
It is highly recommended to connect the Cat to a full Qdrant instance to increase performance and scalability!

```yaml
services:
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image: ghcr.io/cheshire-cat-ai/core:latest
container_name: cheshire_cat_core
ports:
- ${CORE_PORT:-1865}:80
- 1865:80
volumes:
- ./static:/app/cat/static
- ./plugins:/app/cat/plugins
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2 changes: 2 additions & 0 deletions mkdocs/quickstart/introduction.md
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# Introduction

There are a few things you need to know about the Cheshire Cat. If you are eager to launch and start hacking, jump to the [installation page](installation-configuration.md), but please be sure to return here.

The Cheshire Cat is a ready-to-use AI micro-framework.
Once installed and connected to a Language Model (LLM), it can be queried through APIs.
These APIs return the responses provided by the LLM.
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# &#128268; Preparing a Plugin
# &#128268; Your first Plugin

Plugins are packages of `Tools` and `Hooks`.
You don't distribute a `Tool` or a `Hook` directly, you will distribute a Plugin containing them.
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5 changes: 5 additions & 0 deletions mkdocs/stylesheets/extra.css
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color: black;
}

/* Buttons */
[data-md-color-scheme="custom"] .md-button {
color: #666;
}

[data-md-color-scheme="custom"] .md-typeset a {
font-weight: 700;
}
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