From f020257fbe58e4feac099e2ef3b86b811ee715ef Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Nielson=20Jann=C3=A9?= <nielsonj@gmail.com>
Date: Sat, 15 Mar 2025 14:12:32 +0100
Subject: [PATCH] Update readme with .env information

---
 README.md | 38 +++++++++++++++++++++++++++++++++++---
 1 file changed, 35 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 6ca699e..d7fa337 100644
--- a/README.md
+++ b/README.md
@@ -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."}]
-
 ```