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54 lines
3.3 KiB
Markdown
54 lines
3.3 KiB
Markdown
---
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sidebar_position: 3
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---
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# Advanced Usage
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## Search across Different Languages (Self-Hosting)
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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 />
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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:
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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 `cross-encoder/ms-marco-MiniLM-L-6-v2`.
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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.
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## Query Filters
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Use structured query syntax to filter entries from your knowledge based used by search results or chat responses.
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- **Word Filter**: Get entries that include/exclude a specified term
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- Entries that contain term_to_include: `+"term_to_include"`
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- Entries that contain term_to_exclude: `-"term_to_exclude"`
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- **Date Filter**: Get entries containing dates in YYYY-MM-DD format from specified date (range)
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- Entries from April 1st 1984: `dt:"1984-04-01"`
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- Entries after March 31st 1984: `dt>="1984-04-01"`
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- Entries before April 2nd 1984 : `dt<="1984-04-01"`
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- **File Filter**: Get entries from a specified file
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- Entries from incoming.org file: `file:"incoming.org"`
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- Combined Example
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- `what is the meaning of life? file:"1984.org" dt>="1984-01-01" dt<="1985-01-01" -"big" -"brother"`
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- Adds all filters to the natural language query. It should return entries
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- from the file *1984.org*
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- containing dates from the year *1984*
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- excluding words *"big"* and *"brother"*
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- that best match the natural language query *"what is the meaning of life?"*
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## Use OpenAI compatible LLM API Server (Self Hosting)
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Use this if you want to use non-standard, open or commercial, local or hosted LLM models for Khoj chat
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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)
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2. Set environment variable `OPENAI_API_BASE="<url-of-your-llm-server>"` before starting Khoj
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3. Add ChatModelOptions with `model-type` `OpenAI`, and `chat-model` to anything (e.g `gpt-4`) during [Config](/get-started/setup#3-configure)
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- *(Optional)* Set the `tokenizer` and `max-prompt-size` relevant to the actual chat model you're using
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#### Sample Setup using LiteLLM and Mistral API
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```shell
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# Install LiteLLM
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pip install litellm[proxy]
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# Start LiteLLM and use Mistral tiny via Mistral API
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export MISTRAL_API_KEY=<MISTRAL_API_KEY>
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litellm --model mistral/mistral-tiny --drop_params
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# Set OpenAI API Base to LiteLLM server URL and start Khoj
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export OPENAI_API_BASE='http://localhost:8000'
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khoj --anonymous-mode
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```
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