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Yiorgis Gozadinos 2025-10-20 19:22:25 +03:00
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# Tutorial
This tutorial quickstart instructions for getting familiar with `haiku.rag`. This tutorial is indented for people who are familiar with command line and Python, but not different AI ecosystem tools.
This tutorial quickstart instructions for getting familiar with `haiku.rag`. This tutorial is intended for people who are familiar with command line and Python, but not different AI ecosystem tools.
The tutorial covers:
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- Adding and retrieving items
- Inspecting the database
The tutorial uses OpenAI API service - no local installation needed and will work on computers with any amount of RAM and GPU. The OpenAI API is pay-as-you-go, so you need to top it up at least up top ~$5 when creating the API key.
The tutorial uses OpenAI API service - no local installation needed and will work on computers with any amount of RAM and GPU. The OpenAI API is pay-as-you-go, so you need to top it up with at least ~$5 when creating the API key.
## Introduction
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```shell
# Python 3.12+ needed
uv install haiku.rag
uv pip install haiku.rag
```
Configure your OpenAI API key and embeddings model.
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- OpenAI translates the free form text to RAG embedding vectors needed for the retrieval
- The vector values will be stored in a local database
Now you can view your [LanceDB](<(https://lancedb.com/) database, and the embeddings it is configured for:
Now you can view your [LanceDB](https://lancedb.com/) database, and the embeddings it is configured for:
```shell
haiku-rag info
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Now we can use OpenAI LLMs to retrieve information from our embeddings database.
In this example, we connect to a remote OpenAI API.
Mak
Behind the scenes [pydantic-ai](https://ai.pydantic.dev/) query is created
using `OpenAIChatModel.request()`.
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## Complex documents
Haiku RAG can also handle types beyond plain text..
Haiku RAG can also handle types beyond plain text.
Here we add research papers about Python from [arxiv](https://arxiv.org/search/?query=python&searchtype=all&source=header) using URL retriever.
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David Georg Reichelt from Lancaster University wrote a paper titled "Interoperability From OpenTelemetry to Kieker: Demonstrated as Export from the Astronomy Shop." In his work, he indicates that there is a structural difference between Kiekers synchronous traces and OpenTelemetrys asynchronous traces, leading to limited compatibility between the two systems. This highlights the challenges of interoperability in observability frameworks.
```
We can also add offline files, like PDFs. Here we add a local file to ensure OpenAI does not cheat - a file we know that should not very well known in Internet:
We can also add offline files, like PDFs. Here we add a local file to ensure OpenAI does not cheat - a file we know that should not be very well known in Internet:
```shell
# This static file is supplied in haiku.rag repo
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## Configuration
See [Configuration page](./configuration.md) for more information about configurait
See [Configuration page](./configuration.md) for more information about configuration
For the available environment variable config options see [config.py](https://github.com/ggozad/haiku.rag/blob/main/src/haiku/rag/config.py).