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update .env.example and README
Signed-off-by: gopal-raj-suresh <gopal.raj.dummugudupu@cloud2labs.com>
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sample_solutions/RAGChatbot/README.md

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#### Step 2: Create `api/.env` File
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You can either copy from the example file:
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Copy from the example file and edit with your actual credentials:
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```bash
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cp api/.env.example api/.env
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```
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Then edit `api/.env` with your actual credentials, **OR** create it directly:
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```bash
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cat > api/.env << EOF
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# Inference API Configuration
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# INFERENCE_API_ENDPOINT: URL to your inference service (without /v1 suffix)
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# - For GenAI Gateway: https://genai-gateway.example.com
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# - For APISIX Gateway: https://apisix-gateway.example.com/Llama-3.1-8B-Instruct
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# Note: APISIX Gateway requires the model name in the URL path
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#
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# INFERENCE_API_TOKEN: Authentication token/API key for the inference service
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# - For GenAI Gateway: Your GenAI Gateway API key
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# - For APISIX Gateway: Your APISIX authentication token
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INFERENCE_API_ENDPOINT=https://your-actual-api-endpoint.com
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INFERENCE_API_TOKEN=your-actual-token-here
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# Model Configuration
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# IMPORTANT: Use the full model names as they appear in your inference service
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# Check available models: curl https://your-api-endpoint.com/v1/models -H "Authorization: Bearer your-token"
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#
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# EMBEDDING_ENDPOINT: For APISIX/Keycloak, you need a separate endpoint for embeddings
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# Example: EMBEDDING_ENDPOINT=https://apisix-gateway.example.com/bge-base-en-v1.5
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EMBEDDING_MODEL_NAME=BAAI/bge-base-en-v1.5
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INFERENCE_MODEL_NAME=meta-llama/Llama-3.1-8B-Instruct
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# Local URL Endpoint (for Docker)
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LOCAL_URL_ENDPOINT=not-needed
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EOF
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```
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Then edit `api/.env` to set your `INFERENCE_API_ENDPOINT` and `INFERENCE_API_TOKEN`.
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**Important Configuration Notes:**
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sample_solutions/RAGChatbot/api/.env.example

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# APISIX Gateway Endpoints
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# Uncomment and set these when using APISIX Gateway:
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# IMPORTANT: Use exact APISIX route paths:
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# Example routes: /bge-base-en-v1.5-vllmcpu/* and /Llama-3.1-8B-Instruct-vllmcpu/*
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# INFERENCE_API_ENDPOINT=https://api.example.com/Llama-3.1-8B-Instruct-vllmcpu
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# EMBEDDING_API_ENDPOINT=https://api.example.com/bge-base-en-v1.5-vllmcpu
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# Example routes: /bge-base-en-v1.5/* and /Llama-3.1-8B-Instruct/*
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# INFERENCE_API_ENDPOINT=https://api.example.com/Llama-3.1-8B-Instruct
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# EMBEDDING_API_ENDPOINT=https://api.example.com/bge-base-en-v1.5
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# Local URL Endpoint (only needed for non-public domains)
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# If using a local domain like api.example.com mapped to localhost:

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