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Nielson Janné 2025-03-15 14:12:32 +01:00
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@ -17,15 +17,47 @@ 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 given below
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."}]
```