Add a walkthrough guide of the toolkit

docs/walkthrough/walkthrough.md

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+
+
+<p align="center">
+  <img src="assets/toolkit.png" width="200px" height="200px" />
+  <h1 align="center" >Toolkit Guide</h1>
+</p>
+
+Cohere Toolkit is a collection of plug-in pre-built components enabling customers to quickly build and deploy **production** level RAG applications. Principles of the toolkit is that it is:
+
+- Quick and simple to set up a light weight version
+- Quick and simple to configure for your needs
+- Quick and simple to deploy for production usage
+- Quick and simple to contribute through open source
+- Quick and simple to set up on any cloud provider
+
+<h2>Initial Set Up</h2>
+
+When you first set up the toolkit by running one of the following commands:
+- `docker run -e COHERE_API_KEY='>>YOUR_API_KEY<<' -p 8000:8000 -p 4000:4000 ghcr.io/cohere-ai/cohere-toolkit:latest` 
+- Or cloning:
+  - `git clone https://github.com/cohere-ai/cohere-toolkit.git`
+  - `cd cohere-toolkit`
+  - `make first-run`
+
+The default configuration of the toolkit is: 
+
+<img src="assets/default_set_up.png"  />
+
+On top of this the toolkit offers many configurable components  
+
+<img src="assets/whole_set_up.png"  />
+
+Below we will go through each of these components including the prebuilt options and how to plug in your own. 
+
+
+
+<p align="center">
+  <img src="assets/interfaces.png" width="100px" height="100px" />
+  <h1 align="center" >Interfaces</h1>
+</p>
+
+Interfaces are applications on top of the backend API this could be anything from a website, workflows, a bot etc. 
+
+Pre-built interfaces which your can customize to your needs include:
+- Chat UI (Coral)
+
+- SlackBot
+
+To add your own: 
+
+- You can add your own interface at `src/interfaces/{custom_frontend}`, which calls into the backend API at env variable NEXT_PUBLIC_API_HOSTNAME. 
+- You can test the API calls needed to the backend with the postman collection. 
+
+<p align="center">
+  <img src="assets/tools.png" width="100px" height="100px" />
+  <h1 align="center" >Tools</h1>
+</p>
+
+Tools can be any function, data provider, connector, vector store, third-party app, LangChain tool/retriever, llamaIndex integration, OpenSearch integration of your choosing. 
+
+Pre-built tools which your can customize to your needs include:
+- Calculator
+- Web Search
+- Python Interpreter 
+- Files
+
+To add your own we have a [detailed guide here](../custom_tool_guides/tool_guide.md) and the main steps are:
+
+- Add your tool file at `src/backend/tools/{custom_tool_name}` (for open source contributions add to the community folder)
+- The tool needs to implement a `call` function
+- Then add the config of the tool to `src/backend/config/tools.py`
+- You can then view the tool in the chat UI or for customer interfaces add the tool to the API request to use it. 
+
+Coming soon: Support for tools that require authentication. 
+
+<p align="center">
+  <img src="assets/model_providers.png" width="100px" height="100px" />
+  <h1 align="center" >Model Providers</h1>
+</p>
+
+There is no required connection to cohere's platform. You can plug in any model provider to use Cohere's models including local models. A model provider is a service which allows you to make requests to Cohere's models. 
+
+Pre-built model providers which your can customize to your needs include:
+- Cohere Platform
+- Azure 
+- AWS (Bedrock and Sagemaker)
+- Local Models (with raw prompting)
+  - Hugging Face
+
+We have a [detailed guide for these model providers here](../command_model_providers.md).
+
+To add your own:
+- Add a file to `src/backend/model_deployments/{custom_provider}`
+- Implement the `.chat()` function 
+- Add your model config at `src/backend/config/deployments.py`
+
+<p align="center">
+  <img src="assets/flows.png" width="100px" height="100px" />
+  <h1 align="center" >Flows</h1>
+</p>
+
+A "flow" is the main orchestration piece of the toolkit. We have a default chat flow at `src/backend/chat/custom/custom.py` which handles calling the tools and models. 
+
+Additionally there is an experimental LangChain flow which uses raw prompting at `src/backend/chat/custom/langchain.py`.
+
+You would add your own flow at `src/backend/chat/customer/{flow_name}` or customize the current ones if you wanted to experiment with a large new feature such as adding video or image elements. 
+
+<p align="center">
+  <img src="assets/auth.png" width="100px" height="100px" />
+  <h1 align="center" >Authentication</h1>
+</p>
+
+Authentication is the piece that enables multiple user's to use your application. If you don't enable any authentication piece by default there is only one user. 
+
+Pre-built authentication which your can customize to your needs include:
+- Basic (password+username)
+- Google OAuth  
+- OIDC 
+
+We have a [detailed guide for auth here](../auth_guide.md). Note authentication is currently under development. 
+
+<p align="center">
+  <img src="assets/cloud_deploys.png" width="100px" height="100px" />
+  <h1 align="center" >Cloud Deployment</h1>
+</p>
+
+Cloud Deployment's are options for you to deploy your application to a cloud. We have detailed instructions and one click deployment options for cloud providers. 
+
+Pre-built cloud deployments which your can customize to your needs include:
+- Google Cloud Provider (GCP)
+- Azure 
+- AWS
+- K8s support
+
+We have a [detailed guide for each cloud deployment here](../service_deployments.md). 
+
+<p align="center">
+  <img src="assets/memory.png" width="100px" height="100px" />
+  <h1 align="center" >Memory (Storage)</h1>
+</p>
+
+The toolkit stores history of conversations to improve next turn generations. It stores these turns in a PostgreSQL database. It is possible to switch this out for a database that you prefer. There is also an option with no storage. 
+
+<p align="center">
+  <img src="assets/analytics.png" width="100px" height="100px" />
+  <h1 align="center" >Analytics</h1>
+</p>
+
+Currently in development.