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Document review text updates Co-authored-by: Jordan Stephens <[email protected]>
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docs/tutorials/deploying-openai-apps-aws-bedrock-gcp-vertex.mdx

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You need to add a new service that acts as a proxy between your app and the backend LLM provider (Bedrock or Vertex).
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Add **Defang's openai-access-gateway** service:
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Add **Defang's [openai-access-gateway](https://github.com/DefangLabs/openai-access-gateway)** service:
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```diff
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+ llm:
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+ mode: host
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+ environment:
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+ - OPENAI_API_KEY
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+ - GCP_PROJECT_ID
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+ - GCP_REGION
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+ - GCP_PROJECT_ID # if using GCP Vertex AI
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+ - GCP_REGION # if using GCP Vertex AI, AWS_REGION not necessary for Bedrock
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```
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### Notes:
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test: ["CMD", "curl", "-f", "http://localhost:3000/"]
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```
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Now, all OpenAI traffic will route through your gateway service.
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Now, all OpenAI traffic will be routed through your gateway service and onto AWS Bedrock or GCP Vertex.
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---
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:::info
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**Choosing the Right Model**
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- For **AWS Bedrock**, use a Bedrock model ID (e.g., `anthropic.claude-3-sonnet-20240229-v1:0`).
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- For **GCP Vertex AI**, use a full model path (e.g., `google/gemini-2.5-pro-preview-03-25`).
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[See available Vertex models here.](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/call-vertex-using-openai-library#client-setup)
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- For **AWS Bedrock**, use a Bedrock model ID (e.g., `anthropic.claude-3-sonnet-20240229-v1:0`) [See available Bedrock models](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html).
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- For **GCP Vertex AI**, use a full model path (e.g., `google/gemini-2.5-pro-preview-03-25`) [See available Vertex models](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/call-vertex-using-openai-library#client-setup)
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# Complete Example Compose File
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