Explain Default Model in ChatQnA and CodeTrans READMEs (#694)
* explain default model in CodeTrans READMEs Signed-off-by: letonghan <letong.han@intel.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * explain default model in ChatQnA READMEs Signed-off-by: letonghan <letong.han@intel.com> * add required models Signed-off-by: letonghan <letong.han@intel.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Signed-off-by: letonghan <letong.han@intel.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@@ -121,6 +121,18 @@ Currently we support two ways of deploying ChatQnA services with docker compose:
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2. Start services using the docker images `built from source`: [Guide](./docker)
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### Required Models
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By default, the embedding, reranking and LLM models are set to a default value as listed below:
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| Service | Model |
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| --------- | ------------------------- |
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| Embedding | BAAI/bge-base-en-v1.5 |
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| Reranking | BAAI/bge-reranker-base |
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| LLM | Intel/neural-chat-7b-v3-3 |
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Change the `xxx_MODEL_ID` in `docker/xxx/set_env.sh` for your needs.
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### Setup Environment Variable
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To set up environment variables for deploying ChatQnA services, follow these steps:
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@@ -159,6 +159,18 @@ If Guardrails docker image is built, you will find one more image:
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## 🚀 Start MicroServices and MegaService
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### Required Models
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By default, the embedding, reranking and LLM models are set to a default value as listed below:
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| Service | Model |
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| --------- | ------------------------- |
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| Embedding | BAAI/bge-base-en-v1.5 |
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| Reranking | BAAI/bge-reranker-base |
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| LLM | Intel/neural-chat-7b-v3-3 |
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Change the `xxx_MODEL_ID` below for your needs.
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### Setup Environment Variables
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Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below.
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@@ -87,6 +87,18 @@ Then run the command `docker images`, you will have the following 7 Docker Image
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## 🚀 Start MicroServices and MegaService
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### Required Models
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By default, the embedding, reranking and LLM models are set to a default value as listed below:
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| Service | Model |
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| --------- | ------------------------- |
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| Embedding | BAAI/bge-base-en-v1.5 |
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| Reranking | BAAI/bge-reranker-base |
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| LLM | Intel/neural-chat-7b-v3-3 |
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Change the `xxx_MODEL_ID` below for your needs.
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### Setup Environment Variables
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Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below.
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@@ -161,6 +161,18 @@ Then run the command `docker images`, you will have the following 7 Docker Image
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## 🚀 Start Microservices
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### Required Models
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By default, the embedding, reranking and LLM models are set to a default value as listed below:
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| Service | Model |
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| --------- | ------------------------- |
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| Embedding | BAAI/bge-base-en-v1.5 |
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| Reranking | BAAI/bge-reranker-base |
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| LLM | Intel/neural-chat-7b-v3-3 |
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Change the `xxx_MODEL_ID` below for your needs.
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### Setup Environment Variables
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Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below.
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@@ -183,7 +195,7 @@ export your_hf_api_token="Your_Huggingface_API_Token"
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**Append the value of the public IP address to the no_proxy list**
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```
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```bash
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export your_no_proxy=${your_no_proxy},"External_Public_IP"
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```
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@@ -148,6 +148,18 @@ Then run the command `docker images`, you will have the following 7 Docker Image
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## 🚀 Start Microservices
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### Required Models
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By default, the embedding, reranking and LLM models are set to a default value as listed below:
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| Service | Model |
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| --------- | ------------------------- |
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| Embedding | BAAI/bge-base-en-v1.5 |
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| Reranking | BAAI/bge-reranker-base |
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| LLM | Intel/neural-chat-7b-v3-3 |
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Change the `xxx_MODEL_ID` below for your needs.
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### Setup Environment Variables
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Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below.
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@@ -22,6 +22,16 @@ Currently we support two ways of deploying Code Translation services on docker:
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2. Start services using the docker images `built from source`: [Guide](./docker)
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### Required Models
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By default, the LLM model is set to a default value as listed below:
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| Service | Model |
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| ------- | ----------------------------- |
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| LLM | HuggingFaceH4/mistral-7b-grok |
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Change the `LLM_MODEL_ID` in `docker/set_env.sh` for your needs.
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### Setup Environment Variable
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To set up environment variables for deploying Code Translation services, follow these steps:
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@@ -42,9 +42,17 @@ Then run the command `docker images`, you will have the following Docker Images:
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## 🚀 Start Microservices
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### Setup Environment Variables
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### Required Models
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Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below. Notice that the `LLM_MODEL_ID` indicates the LLM model used for TGI service.
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By default, the LLM model is set to a default value as listed below:
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| Service | Model |
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| ------- | ----------------------------- |
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| LLM | HuggingFaceH4/mistral-7b-grok |
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Change the `LLM_MODEL_ID` below for your needs.
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### Setup Environment Variables
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```bash
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export no_proxy=${your_no_proxy}
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@@ -50,9 +50,17 @@ Then run the command `docker images`, you will have the following Docker Images:
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## 🚀 Start Microservices
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### Setup Environment Variables
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### Required Models
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Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below. Notice that the `LLM_MODEL_ID` indicates the LLM model used for TGI service.
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By default, the LLM model is set to a default value as listed below:
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| Service | Model |
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| ------- | ----------------------------- |
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| LLM | HuggingFaceH4/mistral-7b-grok |
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Change the `LLM_MODEL_ID` below for your needs.
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### Setup Environment Variables
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```bash
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export no_proxy=${your_no_proxy}
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@@ -7,9 +7,20 @@ Please install GMC in your Kubernetes cluster, if you have not already done so,
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If you have only Intel Xeon machines you could use the codetrans_xeon.yaml file or if you have a Gaudi cluster you could use codetrans_gaudi.yaml
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In the below example we illustrate on Xeon.
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## Required Models
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By default, the LLM model is set to a default value as listed below:
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|Service |Model |
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|---------|-------------------------|
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|LLM |HuggingFaceH4/mistral-7b-grok|
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Change the `MODEL_ID` in `codetrans_xeon.yaml` for your needs.
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## Deploy the RAG application
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1. Create the desired namespace if it does not already exist and deploy the application
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```bash
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export APP_NAMESPACE=CT
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kubectl create ns $APP_NAMESPACE
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@@ -8,6 +8,16 @@
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> You need to make sure you have created the directory `/mnt/opea-models` to save the cached model on the node where the CodeTrans workload is running. Otherwise, you need to modify the `codetrans.yaml` file to change the `model-volume` to a directory that exists on the node.
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## Required Models
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By default, the LLM model is set to a default value as listed below:
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|Service |Model |
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|---------|-------------------------|
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|LLM |HuggingFaceH4/mistral-7b-grok|
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Change the `MODEL_ID` in `codetrans.yaml` for your needs.
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## Deploy On Xeon
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```bash
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