@@ -154,41 +154,13 @@ EOF
154154
155155#### Step 2: Create ` api/.env ` File
156156
157- You can either copy from the example file:
157+ Copy from the example file and edit with your actual credentials :
158158
159159``` bash
160160cp api/.env.example api/.env
161161```
162162
163- Then edit ` api/.env ` with your actual credentials, ** OR** create it directly:
164-
165- ``` bash
166- cat > api/.env << EOF
167- # Inference API Configuration
168- # INFERENCE_API_ENDPOINT: URL to your inference service (without /v1 suffix)
169- # - For GenAI Gateway: https://genai-gateway.example.com
170- # - For APISIX Gateway: https://apisix-gateway.example.com/Llama-3.1-8B-Instruct
171- # Note: APISIX Gateway requires the model name in the URL path
172- #
173- # INFERENCE_API_TOKEN: Authentication token/API key for the inference service
174- # - For GenAI Gateway: Your GenAI Gateway API key
175- # - For APISIX Gateway: Your APISIX authentication token
176- INFERENCE_API_ENDPOINT=https://your-actual-api-endpoint.com
177- INFERENCE_API_TOKEN=your-actual-token-here
178-
179- # Model Configuration
180- # IMPORTANT: Use the full model names as they appear in your inference service
181- # Check available models: curl https://your-api-endpoint.com/v1/models -H "Authorization: Bearer your-token"
182- #
183- # EMBEDDING_ENDPOINT: For APISIX/Keycloak, you need a separate endpoint for embeddings
184- # Example: EMBEDDING_ENDPOINT=https://apisix-gateway.example.com/bge-base-en-v1.5
185- EMBEDDING_MODEL_NAME=BAAI/bge-base-en-v1.5
186- INFERENCE_MODEL_NAME=meta-llama/Llama-3.1-8B-Instruct
187-
188- # Local URL Endpoint (for Docker)
189- LOCAL_URL_ENDPOINT=not-needed
190- EOF
191- ```
163+ Then edit ` api/.env ` to set your ` INFERENCE_API_ENDPOINT ` and ` INFERENCE_API_TOKEN ` .
192164
193165** Important Configuration Notes:**
194166
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