🤖 Self-hosted, community-driven, local OpenAI-compatible API with Keycloak Auth Flak app as frontend. 🏠
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FlaskAI/examples/query_data/README.md

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# Data query example
This example makes use of [Llama-Index](https://gpt-index.readthedocs.io/en/stable/getting_started/installation.html) to enable question answering on a set of documents.
It loosely follows [the quickstart](https://gpt-index.readthedocs.io/en/stable/guides/primer/usage_pattern.html).
## Requirements
For this in order to work, you will need a model compatible with the `llama.cpp` backend. This is will not work with gpt4all.
The example uses `WizardLM`. Edit the config files in `models/` accordingly to specify the model you use (change `HERE`).
You will also need a training data set. Copy that over `data`.
## Setup
Start the API:
```bash
# Clone LocalAI
git clone https://github.com/go-skynet/LocalAI
cd LocalAI/examples/query_data
# Copy your models, edit config files accordingly
# start with docker-compose
docker-compose up -d --build
```
### Create a storage:
```bash
export OPENAI_API_BASE=http://localhost:8080/v1
export OPENAI_API_KEY=sk-
python store.py
```
After it finishes, a directory "storage" will be created with the vector index database.
## Query
```bash
export OPENAI_API_BASE=http://localhost:8080/v1
export OPENAI_API_KEY=sk-
python query.py
```