Revise model choice for managed LLM samples

samples/managed-llm-provider/README.md

@@ -43,10 +43,11 @@ For this sample, you will need to provide the following [configuration](https://
 > Note that if you are using the 1-click deploy option, you can set these values as secrets in your GitHub repository and the action will automatically deploy them for you.
 
 ### `MODEL`
-The Model ID of the LLM you are using for your application. For example, `anthropic.claude-3-haiku-20240307-v1:0`.
+The Model ID of the LLM you are using for your application. For example, `ai/claude3-haiku`. 
 ```bash
 defang config set MODEL
 ```
+For more about model mapping, please see our [Model Mapping documentation](https://docs.defang.io/docs/concepts/managed-llms/openai-access-gateway#model-mapping). 
 
 ## Deployment
 

samples/managed-llm-provider/compose.yaml

@@ -8,7 +8,7 @@ services:
     restart: always
     environment:
       - ENDPOINT_URL=http://llm/api/v1/chat/completions   # endpoint to the Provider Service
-      - MODEL=anthropic.claude-3-haiku-20240307-v1:0   # LLM model ID used in the Provider Service
+      - MODEL=ai/claude3-haiku  # LLM model ID used in the Provider Service
     healthcheck:
       test: ["CMD", "python3", "-c", "import sys, urllib.request; urllib.request.urlopen(sys.argv[1]).read()", "http://localhost:8000/"]
       interval: 30s

samples/managed-llm/README.md

@@ -46,10 +46,11 @@ For this sample, you will need to provide the following [configuration](https://
 > Note that if you are using the 1-click deploy option, you can set these values as secrets in your GitHub repository and the action will automatically deploy them for you.
 
 ### `MODEL`
-The Model ID of the LLM you are using for your application. For example, `anthropic.claude-3-haiku-20240307-v1:0`.
+The Model ID of the LLM you are using for your application. For example, `ai/claude3-haiku`. 
 ```bash
 defang config set MODEL
 ```
+For more about model mapping, please see our [Model Mapping documentation](https://docs.defang.io/docs/concepts/managed-llms/openai-access-gateway#model-mapping). 
 
 ## Deployment
 

samples/managed-llm/compose.yaml

@@ -8,7 +8,7 @@ services:
     restart: always
     environment:
       - ENDPOINT_URL=http://llm/api/v1/chat/completions   # endpoint to the gateway service
-      - MODEL=anthropic.claude-3-haiku-20240307-v1:0  # LLM model ID used for the gateway
+      - MODEL=ai/claude3-haiku  # LLM model ID used for the gateway
       - OPENAI_API_KEY=FAKE_TOKEN   # the actual value will be ignored when using the gateway, but it should match the one in the llm service
     healthcheck:
       test: ["CMD", "python3", "-c", "import sys, urllib.request; urllib.request.urlopen(sys.argv[1]).read()", "http://localhost:8000/"]