# generic-RAG-demo

A Sogeti Nederland generic RAG demo

## Getting Started

Please mind due to use of argparse the generic RAG demo can not be launched the usual way chainlit is started. 

```bash
chainlit run generic_rag/app.py  # will not work
```

Instead, the app can be launched and debugged the usual way.

```bash
python generic_rag/app.py -p data  # will work
python generic_rag/app.py --help  # will work and prints command line options
```

## .env file

A .env file needs to be populated to configure API end-points or local back-ends using environment variables.
Currently all required environment variables are defined in code at [backend/models.py](generic_rag/backend/models.py) 
with the exception of the API key variables itself. 
More information about configuring API endpoints for langchain can be found at the following locations.

- [langchain cloud chat model doc](https://python.langchain.com/docs/integrations/chat/)
- [langchain local chat model doc](https://python.langchain.com/docs/how_to/local_llms/) 
- [langchain cloud/local emb model doc](https://python.langchain.com/docs/integrations/text_embedding/)

> for local models we currently use Ollama


An `.env` example is as followed.

```text
# only need 1 backend (azure, google, local, etc)

AZURE_OPENAI_API_KEY="<secret_key>"
AZURE_LLM_ENDPOINT="https://<project_hub>.openai.azure.com"
AZURE_LLM_DEPLOYMENT_NAME="gpt-4"
AZURE_LLM_API_VERSION="2025-01-01-preview"
AZURE_EMB_ENDPOINT="https://<project_hub>.openai.azure.com"
AZURE_EMB_DEPLOYMENT_NAME="text-embedding-3-large"
AZURE_EMB_API_VERSION="2023-05-15"

LOCAL_CHAT_MODEL="llama3.1:8b"
LOCAL_EMB_MODEL="llama3.1:8b"

# google vertex AI does not use API keys but a seperate authentication method
GOOGLE_GENAI_CHAT_MODEL="gemini-2.0-flash"
GOOGLE_GENAI_EMB_MODEL="models/text-embedding-004"
```

## Chainlit starters

Chainlit suggestions (starters) can be set with the `CHAINLIT_STARTERS` environment variable.
The variable should be a JSON array of objects with `label` and `message` properties.
An example is as followed.

```
CHAINLIT_STARTERS=[{"label":"Label 1","message":"Message one."},{"label":"Label 2","message":"Message two."},{"label":"Label 3","message":"Message three."}]
```