Add Advanced Self Hosting Section, Improve Self Hosting, OpenAI Proxy Docs

- Add instructions for self-hosted users with info, warning boxes to
  avoid, fix common issues when setting up Khoj server
- Create new Advanced Self Hosting section
  - Extract Advanced Self-Hosting Sections from the Advanced Page and
    move them to separate Pages under Advanced Self Hosting section
- Improve OpenAI Proxy Docs
  - Put Ollama setup as a section under OpenAI API Proxy page instead
    of a separate page
  - Add Section to use Khoj with chat model from LM Studio
  - Update LiteLLM docs to use chat model from LM Studio

documentation/docs/miscellaneous/advanced.md

@@ -4,14 +4,6 @@ sidebar_position: 3
 
 # Advanced Usage
 
-## Search across Different Languages (Self-Hosting)
-To search for notes in multiple, different languages, you can use a [multi-lingual model](https://www.sbert.net/docs/pretrained_models.html#multi-lingual-models).<br />
-For example, the [paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2) supports [50+ languages](https://www.sbert.net/docs/pretrained_models.html#:~:text=we%20used%20the%20following%2050%2B%20languages), has good search quality and speed. To use it:
-1. Manually update the search config in server's admin settings page. Go to [the search config](http://localhost:42110/server/admin/database/searchmodelconfig/). Either create a new one, if none exists, or update the existing one. Set the bi_encoder to `sentence-transformers/multi-qa-MiniLM-L6-cos-v1` and the cross_encoder to `mixedbread-ai/mxbai-rerank-xsmall-v1`.
-2. Regenerate your content index from all the relevant clients. This step is very important, as you'll need to re-encode all your content with the new model.
-
-Note: If you use a search model that expects a prefix (e.g [mixedbread-ai/mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1)) to the query (or docs) string before encoding. Update the `bi_encoder_query_encode_config` field with `{prompt: <prefix-prompt>}`. Eg. `{prompt: "Represent this query for searching documents"}`. You can pass a valid JSON object that the SentenceTransformer `encode` function accepts
-
 ## Query Filters
 
 Use structured query syntax to filter entries from your knowledge based used by search results or chat responses.
@@ -32,25 +24,3 @@ Use structured query syntax to filter entries from your knowledge based used by
     - containing dates from the year *1984*
     - excluding words *"big"* and *"brother"*
     - that best match the natural language query *"what is the meaning of life?"*
-
-## Use OpenAI compatible LLM API Server (Self Hosting)
-Use this if you want to use non-standard, open or commercial, local or hosted LLM models for Khoj chat
-1. Setup your desired chat LLM by installing an OpenAI compatible LLM API Server like [LiteLLM](https://docs.litellm.ai/docs/proxy/quick_start), [llama-cpp-python](https://github.com/abetlen/llama-cpp-python?tab=readme-ov-file#openai-compatible-web-server)
-2. Set environment variable `OPENAI_API_BASE="<url-of-your-llm-server>"` before starting Khoj
-3. Add ChatModelOptions with `model-type` `OpenAI`, and `chat-model` to anything (e.g `gpt-3.5-turbo`) during [Config](/get-started/setup#3-configure)
-   - *(Optional)* Set the `tokenizer` and `max-prompt-size` relevant to the actual chat model you're using
-
-#### Sample Setup using LiteLLM and Mistral API
-
-```shell
-# Install LiteLLM
-pip install litellm[proxy]
-
-# Start LiteLLM and use Mistral tiny via Mistral API
-export MISTRAL_API_KEY=<MISTRAL_API_KEY>
-litellm --model mistral/mistral-tiny --drop_params
-
-# Set OpenAI API Base to LiteLLM server URL and start Khoj
-export OPENAI_API_BASE='http://localhost:8000'
-khoj --anonymous-mode
-```