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FinanceAgent/docker_compose/amd/gpu/rocm/README.md

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Some HuggingFace resources, such as some models, are only accessible if you have an access token. If you do not already have a HuggingFace access token, you can create one by first creating an account by following the steps provided at [HuggingFace](https://huggingface.co/) and then generating a [user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token).
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### Deploy the Services Using Docker Compose
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#### 3.1 Launch vllm endpoint
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In the context of deploying a Finance Agent pipeline on an AMD GPU platform, we can pick and choose different large language model serving frameworks. The table below outlines the various configurations that are available as part of the application.
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| File | Description |
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| ---------------------------------------- | ------------------------------------------------------------------------------------------ |
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| [compose.yaml](./compose.yaml) | Default compose to run agent service |
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| [compose_vllm.yaml](./compose_vllm.yaml) | The LLM Service serving framework is vLLM. |
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| [dataprep_compose.yaml](./dataprep_compose.yaml) | Compose file to run Data Prep service such as Redis vector DB, Re-rancer and Embeder |
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| File | Description |
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| ------------------------------------------------ | ------------------------------------------------------------------------------------ |
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| [compose.yaml](./compose.yaml) | Default compose to run agent service |
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| [compose_vllm.yaml](./compose_vllm.yaml) | The LLM Service serving framework is vLLM. |
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| [dataprep_compose.yaml](./dataprep_compose.yaml) | Compose file to run Data Prep service such as Redis vector DB, Re-rancer and Embedder |
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## How to interact with the agent system with UI
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