Refactor documentation architecture (#1264)

* Refactor documentation architecture

Split into several `tab` and sections

* Fix Fern's docs.yml after PR review

Thank you Danny!

Co-authored-by: dannysheridan <danny@buildwithfern.com>

* Re-add quickstart in the overview tab

It went missing after a refactoring of the doc architecture

* Documentation writing

* Adapt Makefile to fern documentation

* Do not create overlapping page names in fern documentation

This is causing 500. Thank you to @dsinghvi for the troubleshooting and the help!

* Add a readme to help to understand how fern documentation work and how to add new pages

* Rework the welcome view

Redirects directly users to installation guide with links for people that are not familiar with documentation browsing.

* Simplify the quickstart guide

* PR feedback on installation guide

A ton of refactoring can still be made there

* PR feedback on ingestion

* PR feedback on ingestion splitting

* Rename section on LLM

* Fix missing word in list of LLMs

---------

Co-authored-by: dannysheridan <danny@buildwithfern.com>

fern/docs/pages/manual/configuration.mdx

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+# Configure your private GPT
+
+The configuration of your private GPT server is done thanks to `settings` files (more precisely `settings.yaml`).
+These text files are written using the [YAML](https://en.wikipedia.org/wiki/YAML) syntax.
+
+While privateGPT is distributing safe and universal configuration files, you might want to quickly customize your
+privateGPT, and this can be done using the `settings` files.
+
+This project is defining the concept of **profiles** (or configuration profiles).
+This mechanism, using your environment variables, is giving you the ability to easily switch between
+configuration you've made.
+
+A typical use case of profile is to easily switch between LLM and embeddings.
+To be a bit more precise, you can change the language (to French, Spanish, Italian, English, etc) by simply changing
+the profile you've selected; no code changes required!
+
+PrivateGPT is configured through *profiles* that are defined using yaml files, and selected through env variables.
+The full list of properties configurable can be found in `settings.yaml`.
+
+## How to know which profiles exist
+Given that a profile `foo_bar` points to the file `settings-foo_bar.yaml` and vice-versa, you simply have to look
+at the files starting with `settings` and ending in `.yaml`.
+
+## How to use an existing profiles
+**Please note that the syntax to set the value of an environment variables depends on your OS**.
+You have to set environment variable `PGPT_PROFILES` to the name of the profile you want to use.
+
+For example, on **linux and macOS**, this gives:
+```bash
+export PGPT_PROFILES=my_profile_name_here
+```
+
+Windows Powershell(s) have a different syntax, one of them being:
+```shell
+set PGPT_PROFILES=my_profile_name_here
+```
+If the above is not working, you might want to try other ways to set an env variable in your window's terminal.
+
+---
+
+Once you've set this environment variable to the desired profile, you can simply launch your privateGPT,
+and it will run using your profile on top of the default configuration.
+
+## Reference
+Additional details on the profiles are described in this section
+
+### Environment variable `PGPT_SETTINGS_FOLDER`
+
+The location of the settings folder. Defaults to the root of the project.
+Should contain the default `settings.yaml` and any other `settings-{profile}.yaml`.
+
+### Environment variable `PGPT_PROFILES`
+
+By default, the profile definition in `settings.yaml` is loaded.
+Using this env var you can load additional profiles; format is a comma separated list of profile names.
+This will merge `settings-{profile}.yaml` on top of the base settings file.
+
+For example:
+`PGPT_PROFILES=local,cuda` will load `settings-local.yaml`
+and `settings-cuda.yaml`, their contents will be merged with
+later profiles properties overriding values of earlier ones like `settings.yaml`.
+
+During testing, the `test` profile will be active along with the default, therefore `settings-test.yaml`
+file is required.
+
+### Environment variables expansion
+
+Configuration files can contain environment variables,
+they will be expanded at runtime.
+
+Expansion must follow the pattern `${VARIABLE_NAME:default_value}`.
+
+For example, the following configuration will use the value of the `PORT`
+environment variable or `8001` if it's not set.
+Missing variables with no default will produce an error.
+
+```yaml
+server:
+  port: ${PORT:8001}
+```

fern/docs/pages/manual/ingestion-reset.mdx

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+# Reset Local documents database
+
+When running in a local setup, you can remove all ingested documents by simply
+deleting all contents of `local_data` folder (except .gitignore).
+
+To simplify this process, you can use the command:
+```bash
+make wipe
+```
+
+# Advanced usage
+
+You can actually delete your documents from your storage by using the
+API endpoint `DELETE` in the Ingestion API.

fern/docs/pages/manual/ingestion.mdx

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+# Ingesting & Managing Documents
+
+The ingestion of documents can be done in different ways:
+
+* Using the `/ingest` API
+* Using the Gradio UI
+* Using the Bulk Local Ingestion functionality (check next section)
+
+## Bulk Local Ingestion
+
+When you are running PrivateGPT in a fully local setup, you can ingest a complete folder for convenience (containing
+pdf, text files, etc.)
+and optionally watch changes on it with the command:
+
+```bash
+make ingest /path/to/folder -- --watch
+```
+
+To log the processed and failed files to an additional file, use:
+
+```bash
+make ingest /path/to/folder -- --watch --log-file /path/to/log/file.log
+```
+
+After ingestion is complete, you should be able to chat with your documents
+by navigating to http://localhost:8001 and using the option `Query documents`,
+or using the completions / chat API.
+
+## Ingestion troubleshooting
+
+Are you running out of memory when ingesting files?
+
+To do not run out of memory, you should ingest your documents without the LLM loaded in your (video) memory.
+To do so, you should change your configuration to set `llm.mode: mock`.
+
+In other words, you should update your `settings.yaml` (or your custom configuration file) to set the
+following **before** ingesting your documents:
+```yaml
+llm:
+  mode: mock
+```
+
+Once your documents are ingested, you can set the `llm.mode` value back to `local` (or your previous custom value).
+
+You can also use the existing `PGPT_PROFILES=mock` that will set the `llm.mode` to `mock` for you.
+
+## Supported file formats
+
+privateGPT by default supports all the file formats that contains clear text (for example, `.txt` files, `.html`, etc.).
+However, these text based file formats as only considered as text files, and are not pre-processed in any other way.
+
+It also supports the following file formats:
+* `.hwp`
+* `.pdf`
+* `.docx`
+* `.pptx`
+* `.ppt`
+* `.pptm`
+* `.jpg`
+* `.png`
+* `.jpeg`
+* `.mp3`
+* `.mp4`
+* `.csv`
+* `.epub`
+* `.md`
+* `.mbox`
+* `.ipynb`
+* `.json`
+
+**Please note the following nuance**: while `privateGPT` supports these file formats, it **might** require additional
+dependencies to be installed in your python's virtual environment.
+For example, if you try to ingest `.epub` files, `privateGPT` might fail to do it, and will instead display an
+explanatory error asking you to download the necessary dependencies to install this file format.
+
+
+**Other file formats might work**, but they will be considered as plain text
+files (in other words, they will be ingested as `.txt` files).

fern/docs/pages/manual/llms.mdx

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+## Running the Server
+
+PrivateGPT supports running with different LLMs & setups.
+
+### Local models
+
+Both the LLM and the Embeddings model will run locally.
+
+Make sure you have followed the *Local LLM requirements* section before moving on.
+
+This command will start PrivateGPT using the `settings.yaml` (default profile) together with the `settings-local.yaml`
+configuration files. By default, it will enable both the API and the Gradio UI. Run:
+
+```bash
+PGPT_PROFILES=local make run
+```
+
+or
+
+```bash
+PGPT_PROFILES=local poetry run python -m private_gpt
+```
+
+When the server is started it will print a log *Application startup complete*.
+Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API
+using Swagger UI.
+
+### Using OpenAI
+
+If you cannot run a local model (because you don't have a GPU, for example) or for testing purposes, you may
+decide to run PrivateGPT using OpenAI as the LLM and Embeddings model.
+
+In order to do so, create a profile `settings-openai.yaml` with the following contents:
+
+```yaml
+llm:
+  mode: openai
+
+openai:
+  api_key: <your_openai_api_key>  # You could skip this configuration and use the OPENAI_API_KEY env var instead
+```
+
+And run PrivateGPT loading that profile you just created:
+
+`PGPT_PROFILES=openai make run`
+
+or
+
+`PGPT_PROFILES=openai poetry run python -m private_gpt`
+
+When the server is started it will print a log *Application startup complete*.
+Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API.
+You'll notice the speed and quality of response is higher, given you are using OpenAI's servers for the heavy
+computations.
+
+### Using AWS Sagemaker
+
+For a fully private & performant setup, you can choose to have both your LLM and Embeddings model deployed using Sagemaker.
+
+Note: how to deploy models on Sagemaker is out of the scope of this documentation.
+
+In order to do so, create a profile `settings-sagemaker.yaml` with the following contents (remember to
+update the values of the llm_endpoint_name and embedding_endpoint_name to yours):
+
+```yaml
+llm:
+  mode: sagemaker
+
+sagemaker:
+  llm_endpoint_name: huggingface-pytorch-tgi-inference-2023-09-25-19-53-32-140
+  embedding_endpoint_name: huggingface-pytorch-inference-2023-11-03-07-41-36-479
+```
+
+And run PrivateGPT loading that profile you just created:
+
+`PGPT_PROFILES=sagemaker make run`
+
+or
+
+`PGPT_PROFILES=sagemaker poetry run python -m private_gpt`
+
+When the server is started it will print a log *Application startup complete*.
+Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API.

fern/docs/pages/manual/ui.mdx

@@ -0,0 +1,39 @@
+## Gradio UI user manual
+
+Gradio UI is a ready to use way of testing most of PrivateGPT API functionalities.
+
+![Gradio PrivateGPT](https://lh3.googleusercontent.com/drive-viewer/AK7aPaD_Hc-A8A9ooMe-hPgm_eImgsbxAjb__8nFYj8b_WwzvL1Gy90oAnp1DfhPaN6yGiEHCOXs0r77W1bYHtPzlVwbV7fMsA=s1600)
+
+### Execution Modes
+
+It has 3 modes of execution (you can select in the top-left):
+
+* Query Docs: uses the context from the
+  ingested documents to answer the questions posted in the chat. It also takes
+  into account previous chat messages as context.
+    * Makes use of `/chat/completions` API with `use_context=true` and no
+      `context_filter`.
+* Search in Docs: fast search that returns the 4 most related text
+  chunks, together with their source document and page.
+    * Makes use of `/chunks` API with no `context_filter`, `limit=4` and
+      `prev_next_chunks=0`.
+* LLM Chat: simple, non-contextual chat with the LLM. The ingested documents won't
+  be taken into account, only the previous messages.
+    * Makes use of `/chat/completions` API with `use_context=false`.
+
+### Document Ingestion
+
+Ingest documents by using the `Upload a File` button. You can check the progress of
+the ingestion in the console logs of the server.
+
+The list of ingested files is shown below the button.
+
+If you want to delete the ingested documents, refer to *Reset Local documents
+database* section in the documentation.
+
+### Chat
+
+Normal chat interface, self-explanatory ;)
+
+You can check the actual prompt being passed to the LLM by looking at the logs of
+the server. We'll add better observability in future releases.

fern/docs/pages/manual/vectordb.mdx

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+## Vectorstores
+PrivateGPT supports [Chroma](https://www.trychroma.com/), [Qdrant](https://qdrant.tech/) as vectorstore providers. Chroma being the default.
+
+### Qdrant configuration
+
+To enable Qdrant, set the `vectorstore.database` property in the `settings.yaml` file to `qdrant` and install the `qdrant` extra.
+
+```bash
+poetry install --extras qdrant
+```
+
+By default Qdrant tries to connect to an instance at `http://localhost:3000`.
+
+Qdrant settings can be configured by setting values to the `qdrant` property in the `settings.yaml` file.
+
+The available configuration options are:
+| Field        | Description |
+|--------------|-------------|
+| location     | If `:memory:` - use in-memory Qdrant instance. If `str` - use it as a `url` parameter.|
+| url          | Either host or str of 'Optional[scheme], host, Optional[port], Optional[prefix]'. Eg. `http://localhost:6333` |
+| port         | Port of the REST API interface. Default: `6333` |
+| grpc_port    | Port of the gRPC interface. Default: `6334` |
+| prefer_grpc  | If `true` - use gRPC interface whenever possible in custom methods. |
+| https        | If `true` - use HTTPS(SSL) protocol.|
+| api_key      | API key for authentication in Qdrant Cloud.|
+| prefix       | If set, add `prefix` to the REST URL path. Example: `service/v1` will result in `http://localhost:6333/service/v1/{qdrant-endpoint}` for REST API.|
+| timeout      | Timeout for REST and gRPC API requests. Default: 5.0 seconds for REST and unlimited for gRPC |
+| host         | Host name of Qdrant service. If url and host are not set, defaults to 'localhost'.|
+| path         | Persistence path for QdrantLocal. Eg. `local_data/private_gpt/qdrant`|
+| force_disable_check_same_thread         | Force disable check_same_thread for QdrantLocal sqlite connection, defaults to True.|