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value | document_id stringlengths 36 36 | chunk_index int64 0 324k | retrieved_at stringclasses 2
values | chunker_version stringclasses 4
values | content_hash stringlengths 15 64 | content stringlengths 50 44.7k | namespace stringclasses 9
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
dd03600c-2455-4d84-98dc-d6bce6e031d2 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 25 | opea-semantic-v1 | 87c356cb900347d9 | The output should be similar to the following:
```bash
NAME ID SIZE MODIFIED
llama3.2:latest a80c4f17acd5 2.0 GB 2 minutes ago | ai_ref_knowledge | OPEA Documentation | The output should be similar to the following:
```bash
NAME ID SIZE MODIFIED
llama3.2:latest a80c4f17acd5 2.0 GB 2 minutes ago | The output should be similar to the following:
```bash
NAME ID SIZE MODIFIED
llama3.2:latest a80c4f17acd5 2.0 GB 2 minutes ago | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
e68aaf26-450f-42a6-bf2e-aec615f3fea3 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 58 | opea-semantic-v1 | ba39597192757318 | ### Ollama Service
Run the command below to use Ollama to generate text for the input prompt. ```bash
curl http://${host_ip}:11434/api/generate -d '{"model": "llama3", "prompt":"What is Deep Learning?"}' | ai_ref_knowledge | OPEA Documentation | ### Ollama Service
Run the command below to use Ollama to generate text for the input prompt. ```bash
curl http://${host_ip}:11434/api/generate -d '{"model": "llama3", "prompt":"What is Deep Learning?"}' | ### Ollama Service
Run the command below to use Ollama to generate text for the input prompt. ```bash
curl http://${host_ip}:11434/api/generate -d '{"model": "llama3", "prompt":"What is Deep Learning?"}' | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
e833aa39-ede2-4a64-9599-801797ed66fa | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 70 | opea-semantic-v1 | 9d7d2f1345e030d9 | ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep/delete_file" \ -d '{"file_path": "nke-10k-2023.pdf"}' \ -H "Content-Type: application/json"
#### Delete all uploaded files and links | ai_ref_knowledge | OPEA Documentation | ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep/delete_file" \ -d '{"file_path": "nke-10k-2023.pdf"}' \ -H "Content-Type: application/json"
#### Delete all uploaded files and links | ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep/delete_file" \ -d '{"file_path": "nke-10k-2023.pdf"}' \ -H "Content-Type: application/json"
#### Delete all uploaded files and links | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f200fe55-e873-4c2a-b79f-580d75ce3903 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 63 | opea-semantic-v1 | 1b91979d1bd9fd29 | of data sources, chunks the data, and embeds each chunk using the embedding microservice. Finally, the embedded vectors are stored in the Redis vector database.
`nke-10k-2023.pdf` is Nike's annual report on a form 10-K. Run this command to download the file:
```bash
wget https://github.com/opea-project/GenAIComps/blob/... | ai_ref_knowledge | OPEA Documentation | of data sources, chunks the data, and embeds each chunk using the embedding microservice. Finally, the embedded vectors are stored in the Redis vector database.
`nke-10k-2023.pdf` is Nike's annual report on a form 10-K. Run this command to download the file:
```bash
wget https://github.com/opea-project/GenAIComps/blob/... | of data sources, chunks the data, and embeds each chunk using the embedding microservice. Finally, the embedded vectors are stored in the Redis vector database.
`nke-10k-2023.pdf` is Nike's annual report on a form 10-K. Run this command to download the file:
```bash
wget https://github.com/opea-project/GenAIComps/blob/... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f3b6ebc9-4f24-44ef-a38e-49cda85a653f | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 37 | opea-semantic-v1 | 1cede6f7de70665c | ::: ::::
### Check Env Variables
After running `docker compose`, check for warning messages for environment variables that are **NOT** set. Address them if needed. | ai_ref_knowledge | OPEA Documentation | ::: ::::
### Check Env Variables
After running `docker compose`, check for warning messages for environment variables that are **NOT** set. Address them if needed. | ::: ::::
### Check Env Variables
After running `docker compose`, check for warning messages for environment variables that are **NOT** set. Address them if needed. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f49d507a-50d6-4e6c-8fab-8eee7d4b6aef | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 16 | opea-semantic-v1 | 25d4bd3f2c9787e8 | follow the instructions to set up Ollama on the PC. This will set the entrypoint needed for the Ollama to work with the ChatQnA example.
#### Install Ollama Service | ai_ref_knowledge | OPEA Documentation | follow the instructions to set up Ollama on the PC. This will set the entrypoint needed for the Ollama to work with the ChatQnA example.
#### Install Ollama Service | follow the instructions to set up Ollama on the PC. This will set the entrypoint needed for the Ollama to work with the ChatQnA example.
#### Install Ollama Service | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f562a4c2-ce34-43dd-935d-69e8db76ca6c | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 65 | opea-semantic-v1 | 9649027fd551da52 | Upload the file: ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep" \ -H "Content-Type: multipart/form-data" \ -F "files=@./nke-10k-2023.pdf"
HTTP links can also be added to the knowledge base. This command adds the opea.dev website. ```bash
curl -X POST "http://${host_ip}:6007/v1/dataprep" \
-H "Content-Type: ... | ai_ref_knowledge | OPEA Documentation | Upload the file: ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep" \ -H "Content-Type: multipart/form-data" \ -F "files=@./nke-10k-2023.pdf"
HTTP links can also be added to the knowledge base. This command adds the opea.dev website. ```bash
curl -X POST "http://${host_ip}:6007/v1/dataprep" \
-H "Content-Type: ... | Upload the file: ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep" \ -H "Content-Type: multipart/form-data" \ -F "files=@./nke-10k-2023.pdf"
HTTP links can also be added to the knowledge base. This command adds the opea.dev website. ```bash
curl -X POST "http://${host_ip}:6007/v1/dataprep" \
-H "Content-Type: ... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f68b5069-0d22-4fae-a324-e70228fc2098 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 66 | opea-semantic-v1 | bee12c5084af5f5a | also be added to the knowledge base. This command adds the opea.dev website. ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep" \ -H "Content-Type: multipart/form-data" \ -F 'link_list=["https://opea.dev"]'
The list of uploaded files can be retrieved using this command:
```bash
curl -X POST "http://${host_ip}:6... | ai_ref_knowledge | OPEA Documentation | also be added to the knowledge base. This command adds the opea.dev website. ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep" \ -H "Content-Type: multipart/form-data" \ -F 'link_list=["https://opea.dev"]'
The list of uploaded files can be retrieved using this command:
```bash
curl -X POST "http://${host_ip}:6... | also be added to the knowledge base. This command adds the opea.dev website. ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep" \ -H "Content-Type: multipart/form-data" \ -F 'link_list=["https://opea.dev"]'
The list of uploaded files can be retrieved using this command:
```bash
curl -X POST "http://${host_ip}:6... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f7644dc9-6d0a-4aae-a040-bbc684e28edd | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 12 | opea-semantic-v1 | 85d6ee71f66ff51a | Set the NGINX port. ```bash # Example: NGINX_PORT=80 export NGINX_PORT=<Nginx_Port>
For machines behind a firewall, set up the proxy environment variables:
```bash
export https_proxy="Your_HTTPs_Proxy"
# Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
export no_proxy=$no_proxy,chatqna-aipc-backend-server,tei-embe... | ai_ref_knowledge | OPEA Documentation | Set the NGINX port. ```bash # Example: NGINX_PORT=80 export NGINX_PORT=<Nginx_Port>
For machines behind a firewall, set up the proxy environment variables:
```bash
export https_proxy="Your_HTTPs_Proxy"
# Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
export no_proxy=$no_proxy,chatqna-aipc-backend-server,tei-embe... | Set the NGINX port. ```bash # Example: NGINX_PORT=80 export NGINX_PORT=<Nginx_Port>
For machines behind a firewall, set up the proxy environment variables:
```bash
export https_proxy="Your_HTTPs_Proxy"
# Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
export no_proxy=$no_proxy,chatqna-aipc-backend-server,tei-embe... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
fc8e72be-ddde-4e47-b044-589fb78dae91 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 59 | opea-semantic-v1 | a694ba90c43c1867 | Run the command below to use Ollama to generate text for the input prompt. ```bash curl http://${host_ip}:11434/api/generate -d '{"model": "llama3", "prompt":"What is Deep Learning?"}'
Ollama service generates text for the input prompt. | ai_ref_knowledge | OPEA Documentation | Run the command below to use Ollama to generate text for the input prompt. ```bash curl http://${host_ip}:11434/api/generate -d '{"model": "llama3", "prompt":"What is Deep Learning?"}'
Ollama service generates text for the input prompt. | Run the command below to use Ollama to generate text for the input prompt. ```bash curl http://${host_ip}:11434/api/generate -d '{"model": "llama3", "prompt":"What is Deep Learning?"}'
Ollama service generates text for the input prompt. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
fdca045e-dc4e-4a7a-94b4-c8b0de17b036 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/aipc.md | unknown | aeb0057b-c949-441a-965a-28121ba1ab77 | 62 | opea-semantic-v1 | 42b49c841d8bc80c | ### Dataprep Microservice
The knowledge base can be updated using the dataprep microservice, which extracts text from a variety of data sources, chunks the data, and embeds each chunk using the embedding microservice. Finally, the embedded vectors are stored in the Redis vector database. | ai_ref_knowledge | OPEA Documentation | ### Dataprep Microservice
The knowledge base can be updated using the dataprep microservice, which extracts text from a variety of data sources, chunks the data, and embeds each chunk using the embedding microservice. Finally, the embedded vectors are stored in the Redis vector database. | ### Dataprep Microservice
The knowledge base can be updated using the dataprep microservice, which extracts text from a variety of data sources, chunks the data, and embeds each chunk using the embedding microservice. Finally, the embedded vectors are stored in the Redis vector database. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
01d31b38-49dc-46e4-91f0-7e1e460f6cc1 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 29 | opea-semantic-v1 | ef56cfdb945eee93 | :::{tab-item} vllm
Run the command below to check whether the LLM service is ready. The output should be "Application startup complete." | ai_ref_knowledge | OPEA Documentation | :::{tab-item} vllm
Run the command below to check whether the LLM service is ready. The output should be "Application startup complete." | :::{tab-item} vllm
Run the command below to check whether the LLM service is ready. The output should be "Application startup complete." | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
0564a024-2d12-4a31-a445-d19049281392 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 15 | opea-semantic-v1 | ac7136a1183c7778 | ### Check Env Variables After running `docker compose`, check for warning messages for environment variables that are **NOT** set. Address them if needed.
::::{tab-set}
:::{tab-item} vllm | ai_ref_knowledge | OPEA Documentation | ### Check Env Variables After running `docker compose`, check for warning messages for environment variables that are **NOT** set. Address them if needed.
::::{tab-set}
:::{tab-item} vllm | ### Check Env Variables After running `docker compose`, check for warning messages for environment variables that are **NOT** set. Address them if needed.
::::{tab-set}
:::{tab-item} vllm | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
06517fb5-9a01-427f-8284-498ec4a02f7f | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 32 | opea-semantic-v1 | df4966b2505632d1 | Run the command below to use the vLLM service to generate text for the input prompt. Sample output is also shown.
```bash
curl http://${host_ip}:8007/v1/completions \
-H "Content-Type: application/json" \
-d '{
"model": "meta-llama/Meta-Llama-3-8B-Instruct",
"prompt": "What is Deep Learning?",
"max_tokens": 32,
"... | ai_ref_knowledge | OPEA Documentation | Run the command below to use the vLLM service to generate text for the input prompt. Sample output is also shown.
```bash
curl http://${host_ip}:8007/v1/completions \
-H "Content-Type: application/json" \
-d '{
"model": "meta-llama/Meta-Llama-3-8B-Instruct",
"prompt": "What is Deep Learning?",
"max_tokens": 32,
"... | Run the command below to use the vLLM service to generate text for the input prompt. Sample output is also shown.
```bash
curl http://${host_ip}:8007/v1/completions \
-H "Content-Type: application/json" \
-d '{
"model": "meta-llama/Meta-Llama-3-8B-Instruct",
"prompt": "What is Deep Learning?",
"max_tokens": 32,
"... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
09052061-8b73-4984-a646-ff8ea67dbb1f | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 1 | opea-semantic-v1 | 44fccd2fc3cb203d | Intel® Gaudi® AI Accelerators. To quickly learn about OPEA and set up the required hardware and software, follow the instructions in the [Getting Started Guide](../../../getting-started/README.md).
## Overview | ai_ref_knowledge | OPEA Documentation | Intel® Gaudi® AI Accelerators. To quickly learn about OPEA and set up the required hardware and software, follow the instructions in the [Getting Started Guide](../../../getting-started/README.md).
## Overview | Intel® Gaudi® AI Accelerators. To quickly learn about OPEA and set up the required hardware and software, follow the instructions in the [Getting Started Guide](../../../getting-started/README.md).
## Overview | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
0a28ad0e-883a-4865-b752-3c99f6bbdbc2 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 42 | opea-semantic-v1 | 6f0fa08bf82b27d9 | will ensure the megaservice is working properly. ```bash curl http://${host_ip}:8888/v1/chatqna -H "Content-Type: application/json" -d '{ "messages": "What is the revenue of Nike in 2023?" }'
Here is the output for reference:
```bash
data: b'\n'
data: b'An'
data: b'swer'
data: b':'
data: b' In'
data: b' fiscal'
data: b... | ai_ref_knowledge | OPEA Documentation | will ensure the megaservice is working properly. ```bash curl http://${host_ip}:8888/v1/chatqna -H "Content-Type: application/json" -d '{ "messages": "What is the revenue of Nike in 2023?" }'
Here is the output for reference:
```bash
data: b'\n'
data: b'An'
data: b'swer'
data: b':'
data: b' In'
data: b' fiscal'
data: b... | will ensure the megaservice is working properly. ```bash curl http://${host_ip}:8888/v1/chatqna -H "Content-Type: application/json" -d '{ "messages": "What is the revenue of Nike in 2023?" }'
Here is the output for reference:
```bash
data: b'\n'
data: b'An'
data: b'swer'
data: b':'
data: b' In'
data: b' fiscal'
data: b... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
0f437383-cb5a-496d-bc61-8589c0169ae3 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 35 | opea-semantic-v1 | d4f750c741d2f44e | ::: :::{tab-item} TGI
Run the command below to check whether the LLM service is ready. The output should be "INFO text_generation_router::server: router/src/server.rs:2311: Connected" | ai_ref_knowledge | OPEA Documentation | ::: :::{tab-item} TGI
Run the command below to check whether the LLM service is ready. The output should be "INFO text_generation_router::server: router/src/server.rs:2311: Connected" | ::: :::{tab-item} TGI
Run the command below to check whether the LLM service is ready. The output should be "INFO text_generation_router::server: router/src/server.rs:2311: Connected" | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
0fcd8cf6-c213-44b5-b6b1-4182e9601463 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 14 | opea-semantic-v1 | aeaec6f570309f39 | 2. Enable the Guardrails microservice in the pipeline. It will use a TGI Guardrails service.
```bash
docker compose -f compose_guardrails.yaml up -d | ai_ref_knowledge | OPEA Documentation | 2. Enable the Guardrails microservice in the pipeline. It will use a TGI Guardrails service.
```bash
docker compose -f compose_guardrails.yaml up -d | 2. Enable the Guardrails microservice in the pipeline. It will use a TGI Guardrails service.
```bash
docker compose -f compose_guardrails.yaml up -d | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
1348508f-9fab-425c-8bf3-3141d1ff5d58 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 38 | opea-semantic-v1 | 79be3aedfe4193de | Run the command below to use the TGI service to generate text for the input prompt. Sample output is also shown.
```bash
curl http://${host_ip}:8005/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \
-H 'Content-Type: application/json' | ai_ref_knowledge | OPEA Documentation | Run the command below to use the TGI service to generate text for the input prompt. Sample output is also shown.
```bash
curl http://${host_ip}:8005/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \
-H 'Content-Type: application/json' | Run the command below to use the TGI service to generate text for the input prompt. Sample output is also shown.
```bash
curl http://${host_ip}:8005/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \
-H 'Content-Type: application/json' | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
1556a709-a50e-48e3-ac7d-9b2985b9a895 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 6 | opea-semantic-v1 | 2bc9da04fc065a09 | :::{tab-item} vllm
|use case components | Tools | Model | Service Type |
|---------------- |--------------|-----------------------------|-------|
|Data Prep | LangChain | NA | OPEA Microservice |
|VectorDB | Redis | NA | Open source service |
|Embedding | TEI | BAAI/bge-base-en-v1.5 | OPEA Microservice |
|Reranking | T... | ai_ref_knowledge | OPEA Documentation | :::{tab-item} vllm
|use case components | Tools | Model | Service Type |
|---------------- |--------------|-----------------------------|-------|
|Data Prep | LangChain | NA | OPEA Microservice |
|VectorDB | Redis | NA | Open source service |
|Embedding | TEI | BAAI/bge-base-en-v1.5 | OPEA Microservice |
|Reranking | T... | :::{tab-item} vllm
|use case components | Tools | Model | Service Type |
|---------------- |--------------|-----------------------------|-------|
|Data Prep | LangChain | NA | OPEA Microservice |
|VectorDB | Redis | NA | Open source service |
|Embedding | TEI | BAAI/bge-base-en-v1.5 | OPEA Microservice |
|Reranking | T... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
1d3801ae-f122-4ff4-a97f-0ba6829d2ad5 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 30 | opea-semantic-v1 | 73c31e50b72c0282 | Run the command below to check whether the LLM service is ready. The output should be "Application startup complete."
```bash
docker logs vllm-service 2>&1 | grep complete | ai_ref_knowledge | OPEA Documentation | Run the command below to check whether the LLM service is ready. The output should be "Application startup complete."
```bash
docker logs vllm-service 2>&1 | grep complete | Run the command below to check whether the LLM service is ready. The output should be "Application startup complete."
```bash
docker logs vllm-service 2>&1 | grep complete | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
203e1d8b-13aa-4e9d-993f-1c0dcf8313a0 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 3 | opea-semantic-v1 | 83745f224996b08f | 1. Data Prep 2. Embedding 3. Retriever 4. Reranking 5. LLM with vLLM or TGI
This solution is designed to demonstrate the use of Redis vectorDB for RAG and the Meta-Llama-3-8B-Instruct model for LLM inference on Intel® Gaudi® AI Accelerators. The steps will involve setting up Docker containers, using a sample Nike datas... | ai_ref_knowledge | OPEA Documentation | 1. Data Prep 2. Embedding 3. Retriever 4. Reranking 5. LLM with vLLM or TGI
This solution is designed to demonstrate the use of Redis vectorDB for RAG and the Meta-Llama-3-8B-Instruct model for LLM inference on Intel® Gaudi® AI Accelerators. The steps will involve setting up Docker containers, using a sample Nike datas... | 1. Data Prep 2. Embedding 3. Retriever 4. Reranking 5. LLM with vLLM or TGI
This solution is designed to demonstrate the use of Redis vectorDB for RAG and the Meta-Llama-3-8B-Instruct model for LLM inference on Intel® Gaudi® AI Accelerators. The steps will involve setting up Docker containers, using a sample Nike datas... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
216e6e71-429b-44b5-b398-59b823e695e3 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 0 | opea-semantic-v1 | c58dc67336d3da80 | # Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator
This section covers single-node on-prem deployment of the ChatQnA example using the vLLM or TGI LLM service. There are several ways to enable RAG with vectordb and LLM models, but this tutorial will be covering how to build an end-to-end ChatQnA ... | ai_ref_knowledge | OPEA Documentation | # Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator
This section covers single-node on-prem deployment of the ChatQnA example using the vLLM or TGI LLM service. There are several ways to enable RAG with vectordb and LLM models, but this tutorial will be covering how to build an end-to-end ChatQnA ... | # Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator
This section covers single-node on-prem deployment of the ChatQnA example using the vLLM or TGI LLM service. There are several ways to enable RAG with vectordb and LLM models, but this tutorial will be covering how to build an end-to-end ChatQnA ... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
2215f5e4-eefc-4ea4-81be-d63882cf054c | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 8 | opea-semantic-v1 | a3fa1367b653438b | ::: :::{tab-item} TGI
|use case components | Tools | Model | Service Type |
|---------------- |--------------|-----------------------------|-------|
|Data Prep | LangChain | NA | OPEA Microservice |
|VectorDB | Redis | NA | Open source service|
|Embedding | TEI | BAAI/bge-base-en-v1.5 | OPEA Microservice |
|Reranking |... | ai_ref_knowledge | OPEA Documentation | ::: :::{tab-item} TGI
|use case components | Tools | Model | Service Type |
|---------------- |--------------|-----------------------------|-------|
|Data Prep | LangChain | NA | OPEA Microservice |
|VectorDB | Redis | NA | Open source service|
|Embedding | TEI | BAAI/bge-base-en-v1.5 | OPEA Microservice |
|Reranking |... | ::: :::{tab-item} TGI
|use case components | Tools | Model | Service Type |
|---------------- |--------------|-----------------------------|-------|
|Data Prep | LangChain | NA | OPEA Microservice |
|VectorDB | Redis | NA | Open source service|
|Embedding | TEI | BAAI/bge-base-en-v1.5 | OPEA Microservice |
|Reranking |... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
23d66afe-a27f-4218-8701-1f2a25ea5d7b | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 31 | opea-semantic-v1 | 0ee65af333dce812 | ```bash docker logs vllm-service 2>&1 | grep complete
Run the command below to use the vLLM service to generate text for the input prompt. Sample output is also shown. | ai_ref_knowledge | OPEA Documentation | ```bash docker logs vllm-service 2>&1 | grep complete
Run the command below to use the vLLM service to generate text for the input prompt. Sample output is also shown. | ```bash docker logs vllm-service 2>&1 | grep complete
Run the command below to use the vLLM service to generate text for the input prompt. Sample output is also shown. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
2a6d7149-406e-47ed-90a7-dbb8071b7958 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 40 | opea-semantic-v1 | 78ed945b01a50f49 | our current AI landscape is much more subtle. In fact, it most often manifests in the forms of algorithms that help recognize the faces of"}
:::
:::: | ai_ref_knowledge | OPEA Documentation | our current AI landscape is much more subtle. In fact, it most often manifests in the forms of algorithms that help recognize the faces of"}
:::
:::: | our current AI landscape is much more subtle. In fact, it most often manifests in the forms of algorithms that help recognize the faces of"}
:::
:::: | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
2c65a660-5460-4c30-9af5-ed04e3036677 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 41 | opea-semantic-v1 | 6ef5de92f36220ca | ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep/delete_file" \ -d '{"file_path": "all"}' \ -H "Content-Type: application/json"
### ChatQnA MegaService
This will ensure the megaservice is working properly. ```bash
curl http://${host_ip}:8888/v1/chatqna -H "Content-Type: application/json" -d '{
"messages": "Wha... | ai_ref_knowledge | OPEA Documentation | ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep/delete_file" \ -d '{"file_path": "all"}' \ -H "Content-Type: application/json"
### ChatQnA MegaService
This will ensure the megaservice is working properly. ```bash
curl http://${host_ip}:8888/v1/chatqna -H "Content-Type: application/json" -d '{
"messages": "Wha... | ```bash curl -X POST "http://${host_ip}:6007/v1/dataprep/delete_file" \ -d '{"file_path": "all"}' \ -H "Content-Type: application/json"
### ChatQnA MegaService
This will ensure the megaservice is working properly. ```bash
curl http://${host_ip}:8888/v1/chatqna -H "Content-Type: application/json" -d '{
"messages": "Wha... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
2da1ef82-c230-457e-bc2d-729b98265862 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 18 | opea-semantic-v1 | 5dbb4783ab55b106 | :::{tab-item} TGI
ubuntu@xeon-vm:~/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi$ docker compose -f compose_tgi.yaml up -d
WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set. Defaulting to a blank string. WARN[0000] The... | ai_ref_knowledge | OPEA Documentation | :::{tab-item} TGI
ubuntu@xeon-vm:~/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi$ docker compose -f compose_tgi.yaml up -d
WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set. Defaulting to a blank string. WARN[0000] The... | :::{tab-item} TGI
ubuntu@xeon-vm:~/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi$ docker compose -f compose_tgi.yaml up -d
WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set. Defaulting to a blank string. WARN[0000] The... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
3186bea9-9dc9-47c7-940b-5e060c65b8c6 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 46 | opea-semantic-v1 | 3b1c3661e2b4fb1d | the port mapping in the `compose.yaml` file as shown below: ```yaml chatqna-gaudi-ui-server: image: opea/chatqna-ui:${TAG:-latest} ... ports: - "YOUR_HOST_PORT:5173" # Change YOUR_HOST_PORT to the desired port
After making this change, rebuild and restart the containers for the change to take effect. | ai_ref_knowledge | OPEA Documentation | the port mapping in the `compose.yaml` file as shown below: ```yaml chatqna-gaudi-ui-server: image: opea/chatqna-ui:${TAG:-latest} ... ports: - "YOUR_HOST_PORT:5173" # Change YOUR_HOST_PORT to the desired port
After making this change, rebuild and restart the containers for the change to take effect. | the port mapping in the `compose.yaml` file as shown below: ```yaml chatqna-gaudi-ui-server: image: opea/chatqna-ui:${TAG:-latest} ... ports: - "YOUR_HOST_PORT:5173" # Change YOUR_HOST_PORT to the desired port
After making this change, rebuild and restart the containers for the change to take effect. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
390fb256-26f7-44bb-8767-35e2e1db8dbf | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 33 | opea-semantic-v1 | 9d9819abecd46205 | ```bash curl http://${host_ip}:8007/v1/completions \ -H "Content-Type: application/json" \ -d '{ "model": "meta-llama/Meta-Llama-3-8B-Instruct", "prompt": "What is Deep Learning?", "max_tokens": 32, "temperature": 0 }'
```bash
{"id":"cmpl-be8e1d681eb045f082a7b26d5dba42ff","object":"text_completion","created":1726269914... | ai_ref_knowledge | OPEA Documentation | ```bash curl http://${host_ip}:8007/v1/completions \ -H "Content-Type: application/json" \ -d '{ "model": "meta-llama/Meta-Llama-3-8B-Instruct", "prompt": "What is Deep Learning?", "max_tokens": 32, "temperature": 0 }'
```bash
{"id":"cmpl-be8e1d681eb045f082a7b26d5dba42ff","object":"text_completion","created":1726269914... | ```bash curl http://${host_ip}:8007/v1/completions \ -H "Content-Type: application/json" \ -d '{ "model": "meta-llama/Meta-Llama-3-8B-Instruct", "prompt": "What is Deep Learning?", "max_tokens": 32, "temperature": 0 }'
```bash
{"id":"cmpl-be8e1d681eb045f082a7b26d5dba42ff","object":"text_completion","created":1726269914... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
399acfdf-46df-49ac-ba1f-98905697d971 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 16 | opea-semantic-v1 | 4c087afc0f251292 | ::::{tab-set} :::{tab-item} vllm
ubuntu@xeon-vm:~/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi$ docker compose -f compose.yaml up -d
WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set. Defaulting to a blank string. WAR... | ai_ref_knowledge | OPEA Documentation | ::::{tab-set} :::{tab-item} vllm
ubuntu@xeon-vm:~/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi$ docker compose -f compose.yaml up -d
WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set. Defaulting to a blank string. WAR... | ::::{tab-set} :::{tab-item} vllm
ubuntu@xeon-vm:~/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi$ docker compose -f compose.yaml up -d
WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set. Defaulting to a blank string. WAR... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
40b3978e-f938-4aa9-84ee-bd6cc82f0b10 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 7 | opea-semantic-v1 | 876ecee33e8f96d6 | | TEI | BAAI/bge-reranker-base | OPEA Microservice | |LLM | vLLM | meta-llama/Meta-Llama-3-8B-Instruct | OPEA Microservice | |UI | | NA | Gateway Service |
:::
:::{tab-item} TGI | ai_ref_knowledge | OPEA Documentation | | TEI | BAAI/bge-reranker-base | OPEA Microservice | |LLM | vLLM | meta-llama/Meta-Llama-3-8B-Instruct | OPEA Microservice | |UI | | NA | Gateway Service |
:::
:::{tab-item} TGI | | TEI | BAAI/bge-reranker-base | OPEA Microservice | |LLM | vLLM | meta-llama/Meta-Llama-3-8B-Instruct | OPEA Microservice | |UI | | NA | Gateway Service |
:::
:::{tab-item} TGI | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
466379e1-5f94-4e23-b117-2d90a910725e | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 5 | opea-semantic-v1 | ca731f79306ceda2 | For machines behind a firewall, set up the proxy environment variables: ```bash export http_proxy="Your_HTTP_Proxy" export https_proxy="Your_HTTPs_Proxy" # Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1" export no_proxy="Your_No_Proxy",chatqna-gaudi-ui-server,chatqna-gaudi-backend-server,dataprep-redis-service,te... | ai_ref_knowledge | OPEA Documentation | For machines behind a firewall, set up the proxy environment variables: ```bash export http_proxy="Your_HTTP_Proxy" export https_proxy="Your_HTTPs_Proxy" # Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1" export no_proxy="Your_No_Proxy",chatqna-gaudi-ui-server,chatqna-gaudi-backend-server,dataprep-redis-service,te... | For machines behind a firewall, set up the proxy environment variables: ```bash export http_proxy="Your_HTTP_Proxy" export https_proxy="Your_HTTPs_Proxy" # Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1" export no_proxy="Your_No_Proxy",chatqna-gaudi-ui-server,chatqna-gaudi-backend-server,dataprep-redis-service,te... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
47a7b86a-9e67-49a3-aa86-16a7009cf695 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 24 | opea-semantic-v1 | ac2973356a0072f3 | 51 seconds 0.0.0.0:6379->6379/tcp, [::]:6379->6379/tcp, 0.0.0.0:8001->8001/tcp, [::]:8001->8001/tcp redis-vector-db b8ecf10c0c2d jaegertracing/all-in-one:latest "/go/bin/all-in-one-…" 55 seconds ago Up 51 seconds 0.0.0.0:4317-4318->4317-4318/tcp, [::]:4317-4318->4317-4318/tcp, 14250/tcp, 0.0.0.0:9411->9411/tcp, [::]:94... | ai_ref_knowledge | OPEA Documentation | 51 seconds 0.0.0.0:6379->6379/tcp, [::]:6379->6379/tcp, 0.0.0.0:8001->8001/tcp, [::]:8001->8001/tcp redis-vector-db b8ecf10c0c2d jaegertracing/all-in-one:latest "/go/bin/all-in-one-…" 55 seconds ago Up 51 seconds 0.0.0.0:4317-4318->4317-4318/tcp, [::]:4317-4318->4317-4318/tcp, 14250/tcp, 0.0.0.0:9411->9411/tcp, [::]:94... | 51 seconds 0.0.0.0:6379->6379/tcp, [::]:6379->6379/tcp, 0.0.0.0:8001->8001/tcp, [::]:8001->8001/tcp redis-vector-db b8ecf10c0c2d jaegertracing/all-in-one:latest "/go/bin/all-in-one-…" 55 seconds ago Up 51 seconds 0.0.0.0:4317-4318->4317-4318/tcp, [::]:4317-4318->4317-4318/tcp, 14250/tcp, 0.0.0.0:9411->9411/tcp, [::]:94... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
50dc3a7e-8772-4af1-a853-a2f3a7385805 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 28 | opea-semantic-v1 | 3ff70ad7ff8142be | take a few minutes to download the model files and complete the warm-up process. Once this is finished, the service will be ready for use.
::::{tab-set} | ai_ref_knowledge | OPEA Documentation | take a few minutes to download the model files and complete the warm-up process. Once this is finished, the service will be ready for use.
::::{tab-set} | take a few minutes to download the model files and complete the warm-up process. Once this is finished, the service will be ready for use.
::::{tab-set} | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
5a3b06c5-82e7-448b-a8d5-1ab9fe917b64 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 22 | opea-semantic-v1 | f6d979c92dcc8336 | -m vllm.ent…" 10 seconds ago Up 9 seconds (health: starting) 0.0.0.0:8007->80/tcp, [::]:8007->80/tcp vllm-gaudi-server 4d7b9aab82b1 redis/redis-stack:7.2.0-v9 "/entrypoint.sh" 10 seconds ago Up 9 seconds 0.0.0.0:6379->6379/tcp, [::]:6379->6379/tcp, 0.0.0.
0:8001->8001/tcp, [::]:8001->8001/tcp redis-vector-db
9e0d0807bb... | ai_ref_knowledge | OPEA Documentation | -m vllm.ent…" 10 seconds ago Up 9 seconds (health: starting) 0.0.0.0:8007->80/tcp, [::]:8007->80/tcp vllm-gaudi-server 4d7b9aab82b1 redis/redis-stack:7.2.0-v9 "/entrypoint.sh" 10 seconds ago Up 9 seconds 0.0.0.0:6379->6379/tcp, [::]:6379->6379/tcp, 0.0.0.
0:8001->8001/tcp, [::]:8001->8001/tcp redis-vector-db
9e0d0807bb... | -m vllm.ent…" 10 seconds ago Up 9 seconds (health: starting) 0.0.0.0:8007->80/tcp, [::]:8007->80/tcp vllm-gaudi-server 4d7b9aab82b1 redis/redis-stack:7.2.0-v9 "/entrypoint.sh" 10 seconds ago Up 9 seconds 0.0.0.0:6379->6379/tcp, [::]:6379->6379/tcp, 0.0.0.
0:8001->8001/tcp, [::]:8001->8001/tcp redis-vector-db
9e0d0807bb... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
5a513bf0-58fe-480a-ad42-89e1d18b4f8c | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 37 | opea-semantic-v1 | b660f22cf14fb802 | ```bash docker logs tgi-service | grep Connected
Run the command below to use the TGI service to generate text for the input prompt. Sample output is also shown. | ai_ref_knowledge | OPEA Documentation | ```bash docker logs tgi-service | grep Connected
Run the command below to use the TGI service to generate text for the input prompt. Sample output is also shown. | ```bash docker logs tgi-service | grep Connected
Run the command below to use the TGI service to generate text for the input prompt. Sample output is also shown. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
5d25f689-3ccf-4e1a-929c-8dde9eec1265 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 21 | opea-semantic-v1 | 20569e1fd3fd1dff | :::{tab-item} vllm
```bash
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS
NAMES
eabb930edad6 opea/nginx:latest "/docker-entrypoint.…" 9 seconds ago Up 8 seconds 0.0.0.0:80->80/tcp, [::]:80->80/tcp
chatqna-gaudi-nginx-server
7e3c16a791b1 opea/chatqna-ui:latest "docker-entrypoint.s…" 9 seconds ago Up 8 seconds 0.0.0.0... | ai_ref_knowledge | OPEA Documentation | :::{tab-item} vllm
```bash
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS
NAMES
eabb930edad6 opea/nginx:latest "/docker-entrypoint.…" 9 seconds ago Up 8 seconds 0.0.0.0:80->80/tcp, [::]:80->80/tcp
chatqna-gaudi-nginx-server
7e3c16a791b1 opea/chatqna-ui:latest "docker-entrypoint.s…" 9 seconds ago Up 8 seconds 0.0.0.0... | :::{tab-item} vllm
```bash
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS
NAMES
eabb930edad6 opea/nginx:latest "/docker-entrypoint.…" 9 seconds ago Up 8 seconds 0.0.0.0:80->80/tcp, [::]:80->80/tcp
chatqna-gaudi-nginx-server
7e3c16a791b1 opea/chatqna-ui:latest "docker-entrypoint.s…" 9 seconds ago Up 8 seconds 0.0.0.0... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
67e69531-756f-487b-ab76-a9d7c8c79818 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 9 | opea-semantic-v1 | 6687fdb902d60828 | | |Reranking | TEI | BAAI/bge-reranker-base | OPEA Microservice | |LLM | TGI | meta-llama/Meta-Llama-3-8B-Instruct|OPEA Microservice | |UI | | NA | Gateway Service |
:::
:::: | ai_ref_knowledge | OPEA Documentation | | |Reranking | TEI | BAAI/bge-reranker-base | OPEA Microservice | |LLM | TGI | meta-llama/Meta-Llama-3-8B-Instruct|OPEA Microservice | |UI | | NA | Gateway Service |
:::
:::: | | |Reranking | TEI | BAAI/bge-reranker-base | OPEA Microservice | |LLM | TGI | meta-llama/Meta-Llama-3-8B-Instruct|OPEA Microservice | |UI | | NA | Gateway Service |
:::
:::: | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
6bb03b33-ad45-4139-af02-b93c756e8bad | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 11 | opea-semantic-v1 | d75ca4e3d66f0272 | Run `docker compose` with the provided YAML file to start all the services mentioned above as containers.
::::{tab-set}
:::{tab-item} vllm | ai_ref_knowledge | OPEA Documentation | Run `docker compose` with the provided YAML file to start all the services mentioned above as containers.
::::{tab-set}
:::{tab-item} vllm | Run `docker compose` with the provided YAML file to start all the services mentioned above as containers.
::::{tab-set}
:::{tab-item} vllm | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
72c9802a-a0f4-44a2-afa6-801ca705bbf7 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 39 | opea-semantic-v1 | be95a56b84ad2f19 | ```bash curl http://${host_ip}:8005/generate \ -X POST \ -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \ -H 'Content-Type: application/json'
```bash
{"generated_text":"Artificial Intelligence (AI) has become a very popular buzzword in the tech industry. While the phrase ... | ai_ref_knowledge | OPEA Documentation | ```bash curl http://${host_ip}:8005/generate \ -X POST \ -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \ -H 'Content-Type: application/json'
```bash
{"generated_text":"Artificial Intelligence (AI) has become a very popular buzzword in the tech industry. While the phrase ... | ```bash curl http://${host_ip}:8005/generate \ -X POST \ -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \ -H 'Content-Type: application/json'
```bash
{"generated_text":"Artificial Intelligence (AI) has become a very popular buzzword in the tech industry. While the phrase ... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
75039ad6-1a65-408f-ab98-af0c21685f0b | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 47 | opea-semantic-v1 | 11f43b37c80ea76e | Navigate to the `docker compose` directory for this hardware platform. ```bash cd $WORKSPACE/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi
To stop and remove all the containers, use the command below:
::::{tab-set} | ai_ref_knowledge | OPEA Documentation | Navigate to the `docker compose` directory for this hardware platform. ```bash cd $WORKSPACE/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi
To stop and remove all the containers, use the command below:
::::{tab-set} | Navigate to the `docker compose` directory for this hardware platform. ```bash cd $WORKSPACE/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi
To stop and remove all the containers, use the command below:
::::{tab-set} | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
7b9bbf60-8fd4-42a7-8b15-a694e41e7053 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 4 | opea-semantic-v1 | 1eae4dc076725a5b | Set the NGINX port. ```bash # Example: NGINX_PORT=80 export NGINX_PORT=<Nginx_Port>
For machines behind a firewall, set up the proxy environment variables:
```bash
export http_proxy="Your_HTTP_Proxy"
export https_proxy="Your_HTTPs_Proxy"
# Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
export no_proxy="Your_No_P... | ai_ref_knowledge | OPEA Documentation | Set the NGINX port. ```bash # Example: NGINX_PORT=80 export NGINX_PORT=<Nginx_Port>
For machines behind a firewall, set up the proxy environment variables:
```bash
export http_proxy="Your_HTTP_Proxy"
export https_proxy="Your_HTTPs_Proxy"
# Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
export no_proxy="Your_No_P... | Set the NGINX port. ```bash # Example: NGINX_PORT=80 export NGINX_PORT=<Nginx_Port>
For machines behind a firewall, set up the proxy environment variables:
```bash
export http_proxy="Your_HTTP_Proxy"
export https_proxy="Your_HTTPs_Proxy"
# Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
export no_proxy="Your_No_P... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
7ec6b50e-e403-4b15-98c9-8dca6ef79838 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 44 | opea-semantic-v1 | f277709da667b020 | ensure the NGINX ervice is working properly. ```bash curl http://${host_ip}:${NGINX_PORT}/v1/chatqna \ -H "Content-Type: application/json" \ -d '{"messages": "What is the revenue of Nike in 2023?"}'
The output will be similar to that of the ChatQnA megaservice. | ai_ref_knowledge | OPEA Documentation | ensure the NGINX ervice is working properly. ```bash curl http://${host_ip}:${NGINX_PORT}/v1/chatqna \ -H "Content-Type: application/json" \ -d '{"messages": "What is the revenue of Nike in 2023?"}'
The output will be similar to that of the ChatQnA megaservice. | ensure the NGINX ervice is working properly. ```bash curl http://${host_ip}:${NGINX_PORT}/v1/chatqna \ -H "Content-Type: application/json" \ -d '{"messages": "What is the revenue of Nike in 2023?"}'
The output will be similar to that of the ChatQnA megaservice. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
7f3d4b9e-6e17-48b7-bb97-b89e84ba8c87 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 20 | opea-semantic-v1 | ef493be5993e2100 | ### Check Container Statuses
Check if all the containers launched via `docker compose` are running i.e. each container's `STATUS` is `Up` and `Healthy`. | ai_ref_knowledge | OPEA Documentation | ### Check Container Statuses
Check if all the containers launched via `docker compose` are running i.e. each container's `STATUS` is `Up` and `Healthy`. | ### Check Container Statuses
Check if all the containers launched via `docker compose` are running i.e. each container's `STATUS` is `Up` and `Healthy`. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
802a9323-16a1-4b44-911c-e9079cb7ef8c | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 45 | opea-semantic-v1 | 3cbde8ef553e61e5 | ## Launch UI
### Basic UI
To access the frontend, open the following URL in a web browser: http://${host_ip}:${NGINX_PORT}. By default, the UI runs on port 5173 internally. A different host port can be used to access the frontend by modifying the port mapping in the `compose.yaml` file as shown below:
```yaml
chatqna-... | ai_ref_knowledge | OPEA Documentation | ## Launch UI
### Basic UI
To access the frontend, open the following URL in a web browser: http://${host_ip}:${NGINX_PORT}. By default, the UI runs on port 5173 internally. A different host port can be used to access the frontend by modifying the port mapping in the `compose.yaml` file as shown below:
```yaml
chatqna-... | ## Launch UI
### Basic UI
To access the frontend, open the following URL in a web browser: http://${host_ip}:${NGINX_PORT}. By default, the UI runs on port 5173 internally. A different host port can be used to access the frontend by modifying the port mapping in the `compose.yaml` file as shown below:
```yaml
chatqna-... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
87a41839-262c-42d8-982e-d84ec5cffc85 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 13 | opea-semantic-v1 | 6c9f0a8c40759bb8 | ```bash docker compose -f compose_tgi.yaml up -d
2. Enable the Guardrails microservice in the pipeline. It will use a TGI Guardrails service. | ai_ref_knowledge | OPEA Documentation | ```bash docker compose -f compose_tgi.yaml up -d
2. Enable the Guardrails microservice in the pipeline. It will use a TGI Guardrails service. | ```bash docker compose -f compose_tgi.yaml up -d
2. Enable the Guardrails microservice in the pipeline. It will use a TGI Guardrails service. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
8d4a7a03-0a73-475c-9b94-8d6a40c78945 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 25 | opea-semantic-v1 | 52e7c9cbf38f8e95 | takes in a string as input, embeds the string into a vector of a specific length determined by the embedding model, and returns this vector.
```bash
curl ${host_ip}:8090/embed \
-X POST \
-d '{"inputs":"What is Deep Learning?"}' \
-H 'Content-Type: application/json' | ai_ref_knowledge | OPEA Documentation | takes in a string as input, embeds the string into a vector of a specific length determined by the embedding model, and returns this vector.
```bash
curl ${host_ip}:8090/embed \
-X POST \
-d '{"inputs":"What is Deep Learning?"}' \
-H 'Content-Type: application/json' | takes in a string as input, embeds the string into a vector of a specific length determined by the embedding model, and returns this vector.
```bash
curl ${host_ip}:8090/embed \
-X POST \
-d '{"inputs":"What is Deep Learning?"}' \
-H 'Content-Type: application/json' | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
9e7468af-dab1-4b5c-bd18-3079f91f9186 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 34 | opea-semantic-v1 | fa08c796d37d4136 | a subset of Machine Learning that is concerned with algorithms inspired by the structure and function of the brain. It is a part of Artificial","logprobs":null,"finish_reason":"length","stop_reason":null}],"usage":{"prompt_tokens":6,"total_tokens":38,"completion_tokens":32}}d
:::
:::{tab-item} TGI | ai_ref_knowledge | OPEA Documentation | a subset of Machine Learning that is concerned with algorithms inspired by the structure and function of the brain. It is a part of Artificial","logprobs":null,"finish_reason":"length","stop_reason":null}],"usage":{"prompt_tokens":6,"total_tokens":38,"completion_tokens":32}}d
:::
:::{tab-item} TGI | a subset of Machine Learning that is concerned with algorithms inspired by the structure and function of the brain. It is a part of Artificial","logprobs":null,"finish_reason":"length","stop_reason":null}],"usage":{"prompt_tokens":6,"total_tokens":38,"completion_tokens":32}}d
:::
:::{tab-item} TGI | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
a5a92609-98d7-443c-ac66-1d63896e88e4 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 36 | opea-semantic-v1 | cf023c1052a4dc81 | Run the command below to check whether the LLM service is ready. The output should be "INFO text_generation_router::server: router/src/server.rs:2311: Connected"
```bash
docker logs tgi-service | grep Connected | ai_ref_knowledge | OPEA Documentation | Run the command below to check whether the LLM service is ready. The output should be "INFO text_generation_router::server: router/src/server.rs:2311: Connected"
```bash
docker logs tgi-service | grep Connected | Run the command below to check whether the LLM service is ready. The output should be "INFO text_generation_router::server: router/src/server.rs:2311: Connected"
```bash
docker logs tgi-service | grep Connected | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
a70b42cf-68c7-4c34-99b4-498ff5a23491 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 2 | opea-semantic-v1 | d7b600e2983280d9 | The OPEA GenAIComps microservices used to deploy a single node vLLM or TGI megaservice solution for ChatQnA are listed below:
1. Data Prep
2. Embedding
3. Retriever
4. Reranking
5. LLM with vLLM or TGI | ai_ref_knowledge | OPEA Documentation | The OPEA GenAIComps microservices used to deploy a single node vLLM or TGI megaservice solution for ChatQnA are listed below:
1. Data Prep
2. Embedding
3. Retriever
4. Reranking
5. LLM with vLLM or TGI | The OPEA GenAIComps microservices used to deploy a single node vLLM or TGI megaservice solution for ChatQnA are listed below:
1. Data Prep
2. Embedding
3. Retriever
4. Reranking
5. LLM with vLLM or TGI | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
cd70dffc-538a-44bd-8fdb-2f9177fff51a | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 19 | opea-semantic-v1 | e62911739dfe6852 | set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set.
Defaulting to a blank string. WARN[0000] /home/ubuntu/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi/compose_tgi.yaml: `version` is ob... | ai_ref_knowledge | OPEA Documentation | set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set.
Defaulting to a blank string. WARN[0000] /home/ubuntu/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi/compose_tgi.yaml: `version` is ob... | set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set.
Defaulting to a blank string. WARN[0000] /home/ubuntu/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi/compose_tgi.yaml: `version` is ob... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
cff77c01-6e43-4d20-a360-8dedc9044e93 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 12 | opea-semantic-v1 | 444c74d520eb6f51 | Follow ONE of the methods below. 1. Use TGI for the LLM backend.
```bash
docker compose -f compose_tgi.yaml up -d | ai_ref_knowledge | OPEA Documentation | Follow ONE of the methods below. 1. Use TGI for the LLM backend.
```bash
docker compose -f compose_tgi.yaml up -d | Follow ONE of the methods below. 1. Use TGI for the LLM backend.
```bash
docker compose -f compose_tgi.yaml up -d | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
e2aa86f4-01bc-43d3-90a7-6290b6778532 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 26 | opea-semantic-v1 | 9bdfb89cc14d33d1 | ```bash curl ${host_ip}:8090/embed \ -X POST \ -d '{"inputs":"What is Deep Learning?"}' \ -H 'Content-Type: application/json'
In this example, the embedding model used is `BAAI/bge-base-en-v1.5`, which has a vector size of 768. Therefore, the output of the curl command is a vector of length 768. | ai_ref_knowledge | OPEA Documentation | ```bash curl ${host_ip}:8090/embed \ -X POST \ -d '{"inputs":"What is Deep Learning?"}' \ -H 'Content-Type: application/json'
In this example, the embedding model used is `BAAI/bge-base-en-v1.5`, which has a vector size of 768. Therefore, the output of the curl command is a vector of length 768. | ```bash curl ${host_ip}:8090/embed \ -X POST \ -d '{"inputs":"What is Deep Learning?"}' \ -H 'Content-Type: application/json'
In this example, the embedding model used is `BAAI/bge-base-en-v1.5`, which has a vector size of 768. Therefore, the output of the curl command is a vector of length 768. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
e8e3b180-f35c-4792-9d95-8f03cab32596 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 43 | opea-semantic-v1 | ea9e5e413118f58c | ### NGINX Service
This will ensure the NGINX ervice is working properly. ```bash
curl http://${host_ip}:${NGINX_PORT}/v1/chatqna \
-H "Content-Type: application/json" \
-d '{"messages": "What is the revenue of Nike in 2023?"}' | ai_ref_knowledge | OPEA Documentation | ### NGINX Service
This will ensure the NGINX ervice is working properly. ```bash
curl http://${host_ip}:${NGINX_PORT}/v1/chatqna \
-H "Content-Type: application/json" \
-d '{"messages": "What is the revenue of Nike in 2023?"}' | ### NGINX Service
This will ensure the NGINX ervice is working properly. ```bash
curl http://${host_ip}:${NGINX_PORT}/v1/chatqna \
-H "Content-Type: application/json" \
-d '{"messages": "What is the revenue of Nike in 2023?"}' | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f16d2ce6-ff48-4fdd-8b8c-8dfaa83177a2 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 17 | opea-semantic-v1 | 4cfe3faa94821353 | set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set.
Defaulting to a blank string. WARN[0000] /home/ubuntu/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi/compose.yaml: `version` is obsole... | ai_ref_knowledge | OPEA Documentation | set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set.
Defaulting to a blank string. WARN[0000] /home/ubuntu/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi/compose.yaml: `version` is obsole... | set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_API_KEY" variable is not set. Defaulting to a blank string. WARN[0000] The "LANGCHAIN_TRACING_V2" variable is not set.
Defaulting to a blank string. WARN[0000] /home/ubuntu/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi/compose.yaml: `version` is obsole... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f23af993-9693-4cef-b4ae-2896eef4daa8 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 23 | opea-semantic-v1 | d5aa6d0dcfb066d7 | ::: :::{tab-item} TGI
```bash
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
353775bfa0dc opea/nginx:latest "/docker-entrypoint.…" 52 seconds ago Up 50 seconds 0.0.0.0:8010->80/tcp, [::]:8010->80/tcp chatqna-gaudi-nginx-server
c4f75d75f18e opea/chatqna-ui:latest "docker-entrypoint.s…" 52 seconds ago Up 50 second... | ai_ref_knowledge | OPEA Documentation | ::: :::{tab-item} TGI
```bash
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
353775bfa0dc opea/nginx:latest "/docker-entrypoint.…" 52 seconds ago Up 50 seconds 0.0.0.0:8010->80/tcp, [::]:8010->80/tcp chatqna-gaudi-nginx-server
c4f75d75f18e opea/chatqna-ui:latest "docker-entrypoint.s…" 52 seconds ago Up 50 second... | ::: :::{tab-item} TGI
```bash
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
353775bfa0dc opea/nginx:latest "/docker-entrypoint.…" 52 seconds ago Up 50 seconds 0.0.0.0:8010->80/tcp, [::]:8010->80/tcp chatqna-gaudi-nginx-server
c4f75d75f18e opea/chatqna-ui:latest "docker-entrypoint.s…" 52 seconds ago Up 50 second... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f7fb89a2-4f05-4eb3-8981-a758b9913e61 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 10 | opea-semantic-v1 | 5876f1f7c7032c24 | models, modify `set_env.sh` before running it. For example, the environment variable `LLM_MODEL_ID` can be changed to another model by specifying the HuggingFace model card ID.
```bash
cd $WORKSPACE/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi
source ./set_env.sh | ai_ref_knowledge | OPEA Documentation | models, modify `set_env.sh` before running it. For example, the environment variable `LLM_MODEL_ID` can be changed to another model by specifying the HuggingFace model card ID.
```bash
cd $WORKSPACE/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi
source ./set_env.sh | models, modify `set_env.sh` before running it. For example, the environment variable `LLM_MODEL_ID` can be changed to another model by specifying the HuggingFace model card ID.
```bash
cd $WORKSPACE/GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi
source ./set_env.sh | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
fffc00dc-7c9b-4a4d-b56f-b2dafc1a84fa | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/gaudi.md | unknown | 657e2302-b8f6-4489-95ef-70858ccbb7dc | 27 | opea-semantic-v1 | b101a7609866845c | ### vLLM and TGI Service
During the initial startup, this service will take a few minutes to download the model files and complete the warm-up process. Once this is finished, the service will be ready for use. | ai_ref_knowledge | OPEA Documentation | ### vLLM and TGI Service
During the initial startup, this service will take a few minutes to download the model files and complete the warm-up process. Once this is finished, the service will be ready for use. | ### vLLM and TGI Service
During the initial startup, this service will take a few minutes to download the model files and complete the warm-up process. Once this is finished, the service will be ready for use. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
06a3671b-f289-4c84-b33c-89c9f6c926ff | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 17 | opea-semantic-v1 | 6f15ac669a512597 | #### Key Components of a Helm Chart
| Component |Description |
| --- | --- |
| `Chart.yaml` | This file contains metadata about the chart such as name, version, and description. |
| `values.yaml` | Overridable configuration values for the Helm chart deployment, used in the chart k8s object templates. |
| `templates/` D... | ai_ref_knowledge | OPEA Documentation | #### Key Components of a Helm Chart
| Component |Description |
| --- | --- |
| `Chart.yaml` | This file contains metadata about the chart such as name, version, and description. |
| `values.yaml` | Overridable configuration values for the Helm chart deployment, used in the chart k8s object templates. |
| `templates/` D... | #### Key Components of a Helm Chart
| Component |Description |
| --- | --- |
| `Chart.yaml` | This file contains metadata about the chart such as name, version, and description. |
| `values.yaml` | Overridable configuration values for the Helm chart deployment, used in the chart k8s object templates. |
| `templates/` D... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
0b43bcbe-607e-4f86-84e2-448e602ec917 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 13 | opea-semantic-v1 | 8b739079b09c4714 | details. | |`kubectl delete -f <path-to-manifest>` | Deletes all the resources in the current namespace, which effectively removes all the managed pods and associated resources.
|
|`kubectl get pods -o wide` | Retrieves a detailed list of all pods in the current namespace, including additional information like IP addre... | ai_ref_knowledge | OPEA Documentation | details. | |`kubectl delete -f <path-to-manifest>` | Deletes all the resources in the current namespace, which effectively removes all the managed pods and associated resources.
|
|`kubectl get pods -o wide` | Retrieves a detailed list of all pods in the current namespace, including additional information like IP addre... | details. | |`kubectl delete -f <path-to-manifest>` | Deletes all the resources in the current namespace, which effectively removes all the managed pods and associated resources.
|
|`kubectl get pods -o wide` | Retrieves a detailed list of all pods in the current namespace, including additional information like IP addre... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
113ce6c0-15f6-420b-834f-81d572b5749a | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 7 | opea-semantic-v1 | c256dae8597ed244 | - **Pods**: Pods are the smallest deployable units created and managed by Kubernetes. A pod typically encapsulates one or more containers where your application runs.
**Verifying Kubernetes Cluster Access with kubectl**
```bash
kubectl get nodes | ai_ref_knowledge | OPEA Documentation | - **Pods**: Pods are the smallest deployable units created and managed by Kubernetes. A pod typically encapsulates one or more containers where your application runs.
**Verifying Kubernetes Cluster Access with kubectl**
```bash
kubectl get nodes | - **Pods**: Pods are the smallest deployable units created and managed by Kubernetes. A pod typically encapsulates one or more containers where your application runs.
**Verifying Kubernetes Cluster Access with kubectl**
```bash
kubectl get nodes | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
13e672da-914b-42c5-bc5b-b3ac48bcdfa2 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 9 | opea-semantic-v1 | 0553492499d0a7aa | environments, teams, or projects, allowing for finer control over resources and access management. To create a namespace called `chatqa`, use: ```bash kubectl create ns chatqa
When deploying resources (like pods, services, etc.) into your specific namespace, use the `--namespace` flag with `kubectl` commands, or specif... | ai_ref_knowledge | OPEA Documentation | environments, teams, or projects, allowing for finer control over resources and access management. To create a namespace called `chatqa`, use: ```bash kubectl create ns chatqa
When deploying resources (like pods, services, etc.) into your specific namespace, use the `--namespace` flag with `kubectl` commands, or specif... | environments, teams, or projects, allowing for finer control over resources and access management. To create a namespace called `chatqa`, use: ```bash kubectl create ns chatqa
When deploying resources (like pods, services, etc.) into your specific namespace, use the `--namespace` flag with `kubectl` commands, or specif... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
18b5fa31-c860-4577-bb3a-480429431845 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 19 | opea-semantic-v1 | ea985c1cc1ede44d | **Update Dependencies:**
- `scripts/update_dependency.sh` script can be used to ensure that dependencies for `common/` charts are up to date. - `helm dependency update <chart-directory>` command updates the dependencies for the specified chart directory (e.g., `chatqna`) based on the versions specified in its `Chart.ya... | ai_ref_knowledge | OPEA Documentation | **Update Dependencies:**
- `scripts/update_dependency.sh` script can be used to ensure that dependencies for `common/` charts are up to date. - `helm dependency update <chart-directory>` command updates the dependencies for the specified chart directory (e.g., `chatqna`) based on the versions specified in its `Chart.ya... | **Update Dependencies:**
- `scripts/update_dependency.sh` script can be used to ensure that dependencies for `common/` charts are up to date. - `helm dependency update <chart-directory>` command updates the dependencies for the specified chart directory (e.g., `chatqna`) based on the versions specified in its `Chart.ya... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
26e82069-5ecc-4612-a2f8-a5969dec4d2c | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 15 | opea-semantic-v1 | a8f6e9fd72c30213 | ### Using Helm Charts to Deploy
**What is Helm?** Helm is a package manager for Kubernetes, similar to how apt is for Ubuntu. It simplifies deploying and managing Kubernetes applications through Helm charts, which are packages of pre-configured Kubernetes resources. | ai_ref_knowledge | OPEA Documentation | ### Using Helm Charts to Deploy
**What is Helm?** Helm is a package manager for Kubernetes, similar to how apt is for Ubuntu. It simplifies deploying and managing Kubernetes applications through Helm charts, which are packages of pre-configured Kubernetes resources. | ### Using Helm Charts to Deploy
**What is Helm?** Helm is a package manager for Kubernetes, similar to how apt is for Ubuntu. It simplifies deploying and managing Kubernetes applications through Helm charts, which are packages of pre-configured Kubernetes resources. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
3758753f-3e6f-4c43-af7d-ceb6f78c57ce | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 20 | opea-semantic-v1 | 68895d447a3246fc | - `helm dependency update <chart-directory>` command updates the dependencies for the specified chart directory (e.g., `chatqna`) based on the versions specified in its `Chart.yaml` file.
**Helm Install Command:** | ai_ref_knowledge | OPEA Documentation | - `helm dependency update <chart-directory>` command updates the dependencies for the specified chart directory (e.g., `chatqna`) based on the versions specified in its `Chart.yaml` file.
**Helm Install Command:** | - `helm dependency update <chart-directory>` command updates the dependencies for the specified chart directory (e.g., `chatqna`) based on the versions specified in its `Chart.yaml` file.
**Helm Install Command:** | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
3a7f9b7f-2fca-4592-be9a-989ac4e51e0f | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 11 | opea-semantic-v1 | b397af58f19859af | To deploy a pod in the `chatqa` namespace: ```bash kubectl apply -f your-pod-config.yaml --namespace=chatqa
If you want to avoid specifying the namespace with every command, you can set the default namespace for your current context:
```bash
kubectl config set-context --current --namespace=chatqa | ai_ref_knowledge | OPEA Documentation | To deploy a pod in the `chatqa` namespace: ```bash kubectl apply -f your-pod-config.yaml --namespace=chatqa
If you want to avoid specifying the namespace with every command, you can set the default namespace for your current context:
```bash
kubectl config set-context --current --namespace=chatqa | To deploy a pod in the `chatqa` namespace: ```bash kubectl apply -f your-pod-config.yaml --namespace=chatqa
If you want to avoid specifying the namespace with every command, you can set the default namespace for your current context:
```bash
kubectl config set-context --current --namespace=chatqa | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
447718df-0fbf-4166-80fb-95729c85a3a7 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 21 | opea-semantic-v1 | d2f784331bcfb58d | **Helm Install Command:**
- `helm install [RELEASE_NAME] [CHART_NAME]`: This command deploys a Helm chart into your Kubernetes cluster, creating a new release. It is used to set up all the Kubernetes resources specified in the chart and track the version of the deployment. | ai_ref_knowledge | OPEA Documentation | **Helm Install Command:**
- `helm install [RELEASE_NAME] [CHART_NAME]`: This command deploys a Helm chart into your Kubernetes cluster, creating a new release. It is used to set up all the Kubernetes resources specified in the chart and track the version of the deployment. | **Helm Install Command:**
- `helm install [RELEASE_NAME] [CHART_NAME]`: This command deploys a Helm chart into your Kubernetes cluster, creating a new release. It is used to set up all the Kubernetes resources specified in the chart and track the version of the deployment. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
4dc99797-479b-43d3-910e-5260a0563d7d | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 8 | opea-semantic-v1 | 9222c83e4b15bedc | **Verifying Kubernetes Cluster Access with kubectl** ```bash kubectl get nodes
#### Create and Set Namespace
A Kubernetes namespace is a logical division within a cluster that is used to isolate different environments, teams, or projects, allowing for finer control over resources and access management. To create a name... | ai_ref_knowledge | OPEA Documentation | **Verifying Kubernetes Cluster Access with kubectl** ```bash kubectl get nodes
#### Create and Set Namespace
A Kubernetes namespace is a logical division within a cluster that is used to isolate different environments, teams, or projects, allowing for finer control over resources and access management. To create a name... | **Verifying Kubernetes Cluster Access with kubectl** ```bash kubectl get nodes
#### Create and Set Namespace
A Kubernetes namespace is a logical division within a cluster that is used to isolate different environments, teams, or projects, allowing for finer control over resources and access management. To create a name... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
6f3db1c6-9a71-4252-b6bf-79c06924dd7c | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 0 | opea-semantic-v1 | 98d88bd05a250a99 | ## Introduction
Kubernetes is an orchestration platform for managing containerized applications, ideal for deploying microservices based architectures like ChatQnA. It offers robust mechanisms for automating deployment, scaling, and operations of application containers across clusters of hosts. Kubernetes supports diff... | ai_ref_knowledge | OPEA Documentation | ## Introduction
Kubernetes is an orchestration platform for managing containerized applications, ideal for deploying microservices based architectures like ChatQnA. It offers robust mechanisms for automating deployment, scaling, and operations of application containers across clusters of hosts. Kubernetes supports diff... | ## Introduction
Kubernetes is an orchestration platform for managing containerized applications, ideal for deploying microservices based architectures like ChatQnA. It offers robust mechanisms for automating deployment, scaling, and operations of application containers across clusters of hosts. Kubernetes supports diff... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
746f5712-fb86-4d54-ba75-d64b38e30f9c | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 5 | opea-semantic-v1 | c23683d773628273 | configurations by visiting the [GenAI Infrastructure development page](https://opea-project.github.io/latest/GenAIInfra/DEVELOPMENT.html). This page covers all the essential tools and settings needed for effective development within the Kubernetes environment.
**Understanding Kubernetes Deployment Tools and Resources:*... | ai_ref_knowledge | OPEA Documentation | configurations by visiting the [GenAI Infrastructure development page](https://opea-project.github.io/latest/GenAIInfra/DEVELOPMENT.html). This page covers all the essential tools and settings needed for effective development within the Kubernetes environment.
**Understanding Kubernetes Deployment Tools and Resources:*... | configurations by visiting the [GenAI Infrastructure development page](https://opea-project.github.io/latest/GenAIInfra/DEVELOPMENT.html). This page covers all the essential tools and settings needed for effective development within the Kubernetes environment.
**Understanding Kubernetes Deployment Tools and Resources:*... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
7812f9f7-4ee6-4324-b803-8b2ad92763b3 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 10 | opea-semantic-v1 | 6439f68316e433ca | resources (like pods, services, etc.) into your specific namespace, use the `--namespace` flag with `kubectl` commands, or specify the namespace in your resource configuration files.
To deploy a pod in the `chatqa` namespace:
```bash
kubectl apply -f your-pod-config.yaml --namespace=chatqa | ai_ref_knowledge | OPEA Documentation | resources (like pods, services, etc.) into your specific namespace, use the `--namespace` flag with `kubectl` commands, or specify the namespace in your resource configuration files.
To deploy a pod in the `chatqa` namespace:
```bash
kubectl apply -f your-pod-config.yaml --namespace=chatqa | resources (like pods, services, etc.) into your specific namespace, use the `--namespace` flag with `kubectl` commands, or specify the namespace in your resource configuration files.
To deploy a pod in the `chatqa` namespace:
```bash
kubectl apply -f your-pod-config.yaml --namespace=chatqa | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
7b7d0d03-accb-43a6-92c4-1e414e331595 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 18 | opea-semantic-v1 | b50d8534a57e661c | templates. | | `templates/` Directory | Contains YAML templates for Kubernetes objects, typically one file per object type (e.g., deployment.yaml for Deployments, service.yaml for Services).
For more details, refer to the Helm Templates Best Practices. | ai_ref_knowledge | OPEA Documentation | templates. | | `templates/` Directory | Contains YAML templates for Kubernetes objects, typically one file per object type (e.g., deployment.yaml for Deployments, service.yaml for Services).
For more details, refer to the Helm Templates Best Practices. | templates. | | `templates/` Directory | Contains YAML templates for Kubernetes objects, typically one file per object type (e.g., deployment.yaml for Deployments, service.yaml for Services).
For more details, refer to the Helm Templates Best Practices. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
9106f13c-a490-4c03-9712-3ac8908d40d6 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 3 | opea-semantic-v1 | cf57834159e75678 | ### Kubernetes Cluster and Development Environment
**Setting Up the Kubernetes Cluster:** Before beginning deployment for the ChatQnA application, ensure that a Kubernetes cluster is ready. For guidance on setting up your Kubernetes cluster, please refer to the comprehensive setup instructions available at [Kubernetes ... | ai_ref_knowledge | OPEA Documentation | ### Kubernetes Cluster and Development Environment
**Setting Up the Kubernetes Cluster:** Before beginning deployment for the ChatQnA application, ensure that a Kubernetes cluster is ready. For guidance on setting up your Kubernetes cluster, please refer to the comprehensive setup instructions available at [Kubernetes ... | ### Kubernetes Cluster and Development Environment
**Setting Up the Kubernetes Cluster:** Before beginning deployment for the ChatQnA application, ensure that a Kubernetes cluster is ready. For guidance on setting up your Kubernetes cluster, please refer to the comprehensive setup instructions available at [Kubernetes ... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
9ef3ccb8-0280-45e9-946f-2a9251472034 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 22 | opea-semantic-v1 | dafabcdbc1f2f195 | creating a new release. It is used to set up all the Kubernetes resources specified in the chart and track the version of the deployment.
For more detailed instructions and explanations, you can refer to the [official Helm documentation](https://helm.sh/docs/). | ai_ref_knowledge | OPEA Documentation | creating a new release. It is used to set up all the Kubernetes resources specified in the chart and track the version of the deployment.
For more detailed instructions and explanations, you can refer to the [official Helm documentation](https://helm.sh/docs/). | creating a new release. It is used to set up all the Kubernetes resources specified in the chart and track the version of the deployment.
For more detailed instructions and explanations, you can refer to the [official Helm documentation](https://helm.sh/docs/). | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
aaaa540c-be21-4398-903a-e06f646ec173 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 12 | opea-semantic-v1 | c267376bf7e6fab7 | want to avoid specifying the namespace with every command, you can set the default namespace for your current context: ```bash kubectl config set-context --current --namespace=chatqa
Some commonly used kubectl commands and their functions, assuming that you have set your namespace context appropriately are:
|Command |F... | ai_ref_knowledge | OPEA Documentation | want to avoid specifying the namespace with every command, you can set the default namespace for your current context: ```bash kubectl config set-context --current --namespace=chatqa
Some commonly used kubectl commands and their functions, assuming that you have set your namespace context appropriately are:
|Command |F... | want to avoid specifying the namespace with every command, you can set the default namespace for your current context: ```bash kubectl config set-context --current --namespace=chatqa
Some commonly used kubectl commands and their functions, assuming that you have set your namespace context appropriately are:
|Command |F... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
ae56bd69-38c3-487b-b8b9-8bdf1f0355d4 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 23 | opea-semantic-v1 | 118c547cd3666ff3 | For more detailed instructions and explanations, you can refer to the [official Helm documentation](https://helm.sh/docs/).
Continue to [Helm Deployment](./k8s_helm.md) to deploy ChatQnA via Helm. | ai_ref_knowledge | OPEA Documentation | For more detailed instructions and explanations, you can refer to the [official Helm documentation](https://helm.sh/docs/).
Continue to [Helm Deployment](./k8s_helm.md) to deploy ChatQnA via Helm. | For more detailed instructions and explanations, you can refer to the [official Helm documentation](https://helm.sh/docs/).
Continue to [Helm Deployment](./k8s_helm.md) to deploy ChatQnA via Helm. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
bb2c6182-004f-439a-95e9-44d401051caa | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 1 | opea-semantic-v1 | ab915e6d3c68fe13 | can be deployed via `Helm`, a package manager for Kubernetes that simplifies the deployment, management, and versioning of Kubernetes applications using pre-configured templates called charts.
This guide will provide detailed instructions on using Kubernetes and Helm. If you're already familiar with Kubernetes, feel fr... | ai_ref_knowledge | OPEA Documentation | can be deployed via `Helm`, a package manager for Kubernetes that simplifies the deployment, management, and versioning of Kubernetes applications using pre-configured templates called charts.
This guide will provide detailed instructions on using Kubernetes and Helm. If you're already familiar with Kubernetes, feel fr... | can be deployed via `Helm`, a package manager for Kubernetes that simplifies the deployment, management, and versioning of Kubernetes applications using pre-configured templates called charts.
This guide will provide detailed instructions on using Kubernetes and Helm. If you're already familiar with Kubernetes, feel fr... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
c72b7399-06a0-4f49-866c-97a50fddac57 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 6 | opea-semantic-v1 | 5c99405cc2879d4e | **Understanding Kubernetes Deployment Tools and Resources:**
- **kubectl**: This command-line tool allows you to deploy applications, inspect and manage cluster resources, and view logs. For instance, `kubectl apply -f chatqna.yaml` would be used to deploy resources defined in a manifest file. - **Pods**: Pods are the ... | ai_ref_knowledge | OPEA Documentation | **Understanding Kubernetes Deployment Tools and Resources:**
- **kubectl**: This command-line tool allows you to deploy applications, inspect and manage cluster resources, and view logs. For instance, `kubectl apply -f chatqna.yaml` would be used to deploy resources defined in a manifest file. - **Pods**: Pods are the ... | **Understanding Kubernetes Deployment Tools and Resources:**
- **kubectl**: This command-line tool allows you to deploy applications, inspect and manage cluster resources, and view logs. For instance, `kubectl apply -f chatqna.yaml` would be used to deploy resources defined in a manifest file. - **Pods**: Pods are the ... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
cf0c5902-aa23-48f5-9f78-564c89d9c2b3 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 4 | opea-semantic-v1 | 03f11e1940886b9b | a Kubernetes cluster is ready. For guidance on setting up your Kubernetes cluster, please refer to the comprehensive setup instructions available at [Kubernetes Installation Options](https://opea-project.github.io/latest/guide/installation/k8s_install/README.html).
**Development Pre-requisites:** To prepare for the dep... | ai_ref_knowledge | OPEA Documentation | a Kubernetes cluster is ready. For guidance on setting up your Kubernetes cluster, please refer to the comprehensive setup instructions available at [Kubernetes Installation Options](https://opea-project.github.io/latest/guide/installation/k8s_install/README.html).
**Development Pre-requisites:** To prepare for the dep... | a Kubernetes cluster is ready. For guidance on setting up your Kubernetes cluster, please refer to the comprehensive setup instructions available at [Kubernetes Installation Options](https://opea-project.github.io/latest/guide/installation/k8s_install/README.html).
**Development Pre-requisites:** To prepare for the dep... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
cf57fcae-3e18-4f5d-aa81-4d483416edc4 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 16 | opea-semantic-v1 | 0aae7a20b662893e | Kubernetes, similar to how apt is for Ubuntu. It simplifies deploying and managing Kubernetes applications through Helm charts, which are packages of pre-configured Kubernetes resources.
#### Key Components of a Helm Chart | ai_ref_knowledge | OPEA Documentation | Kubernetes, similar to how apt is for Ubuntu. It simplifies deploying and managing Kubernetes applications through Helm charts, which are packages of pre-configured Kubernetes resources.
#### Key Components of a Helm Chart | Kubernetes, similar to how apt is for Ubuntu. It simplifies deploying and managing Kubernetes applications through Helm charts, which are packages of pre-configured Kubernetes resources.
#### Key Components of a Helm Chart | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
cfb429fb-cb51-49ec-a02c-f9c7acc2b811 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 14 | opea-semantic-v1 | f01bc82d3db282ac | application behavior. | |`kubectl get svc` | Lists all services in the current namespace, providing a quick overview of the network services and their status.
### Using Helm Charts to Deploy | ai_ref_knowledge | OPEA Documentation | application behavior. | |`kubectl get svc` | Lists all services in the current namespace, providing a quick overview of the network services and their status.
### Using Helm Charts to Deploy | application behavior. | |`kubectl get svc` | Lists all services in the current namespace, providing a quick overview of the network services and their status.
### Using Helm Charts to Deploy | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
f917cfb7-c9f4-4cce-8ff4-059c5a3678d6 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_getting_started.md | unknown | 8800b226-183a-45ce-97fb-3d350b78f500 | 2 | opea-semantic-v1 | 46581f4190c382b2 | This guide will provide detailed instructions on using Kubernetes and Helm. If you're already familiar with Kubernetes, feel free to skip ahead to [Helm Deployment](./k8s_helm.md)
### Kubernetes Cluster and Development Environment | ai_ref_knowledge | OPEA Documentation | This guide will provide detailed instructions on using Kubernetes and Helm. If you're already familiar with Kubernetes, feel free to skip ahead to [Helm Deployment](./k8s_helm.md)
### Kubernetes Cluster and Development Environment | This guide will provide detailed instructions on using Kubernetes and Helm. If you're already familiar with Kubernetes, feel free to skip ahead to [Helm Deployment](./k8s_helm.md)
### Kubernetes Cluster and Development Environment | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
011067c3-0a84-4a3b-8792-2007a05140b5 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 45 | opea-semantic-v1 | 3249620aebbff77f | This command will display a list of services along with their network-related details such as cluster IP and ports.
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
chatqna ClusterIP 10.108.186.198 <none> 8888/TCP 8m16s
chatqna-chatqna-ui ClusterIP 10.102.80.123 <none> 5173/TCP 8m16s
chatqna-data-prep ClusterIP 10.110.143.... | ai_ref_knowledge | OPEA Documentation | This command will display a list of services along with their network-related details such as cluster IP and ports.
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
chatqna ClusterIP 10.108.186.198 <none> 8888/TCP 8m16s
chatqna-chatqna-ui ClusterIP 10.102.80.123 <none> 5173/TCP 8m16s
chatqna-data-prep ClusterIP 10.110.143.... | This command will display a list of services along with their network-related details such as cluster IP and ports.
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
chatqna ClusterIP 10.108.186.198 <none> 8888/TCP 8m16s
chatqna-chatqna-ui ClusterIP 10.102.80.123 <none> 5173/TCP 8m16s
chatqna-data-prep ClusterIP 10.110.143.... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
014a59a8-c1d3-41d7-8ad1-532da3f1c8b5 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 81 | opea-semantic-v1 | 4042f148dfa2ca12 | curl http://localhost:7000/v1/retrieval \ -X POST \ -d "{\"text\":\"test\",\"embedding\":${your_embedding}}" \ -H 'Content-Type: application/json'
The output of the retriever microservice comprises of a unique ID for the
request, initial query, or the input to the retrieval microservice, a list of top
`n` retrieved doc... | ai_ref_knowledge | OPEA Documentation | curl http://localhost:7000/v1/retrieval \ -X POST \ -d "{\"text\":\"test\",\"embedding\":${your_embedding}}" \ -H 'Content-Type: application/json'
The output of the retriever microservice comprises of a unique ID for the
request, initial query, or the input to the retrieval microservice, a list of top
`n` retrieved doc... | curl http://localhost:7000/v1/retrieval \ -X POST \ -d "{\"text\":\"test\",\"embedding\":${your_embedding}}" \ -H 'Content-Type: application/json'
The output of the retriever microservice comprises of a unique ID for the
request, initial query, or the input to the retrieval microservice, a list of top
`n` retrieved doc... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
02a824fb-5b33-4157-8ae7-7a75eed08f87 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 36 | opea-semantic-v1 | 6437684eb51ff650 | chatqna-redis-vector-db-7f489b6bb6-mvzbw 1/1 Running 0 5m7s chatqna-retriever-usvc-6695979d67-z5jgx 1/1 Running 0 5m7s chatqna-tei-769dc796c-gh5vx 1/1 Running 0 5m7s chatqna-teirerank-54f58c596c-76xqz 1/1 Running 0 5m7s chatqna-tgi-7b5556d46d-pnzph 1/1 Running 0 5m7s
>**Note:** Use `kubectl get pods -o wide` to check t... | ai_ref_knowledge | OPEA Documentation | chatqna-redis-vector-db-7f489b6bb6-mvzbw 1/1 Running 0 5m7s chatqna-retriever-usvc-6695979d67-z5jgx 1/1 Running 0 5m7s chatqna-tei-769dc796c-gh5vx 1/1 Running 0 5m7s chatqna-teirerank-54f58c596c-76xqz 1/1 Running 0 5m7s chatqna-tgi-7b5556d46d-pnzph 1/1 Running 0 5m7s
>**Note:** Use `kubectl get pods -o wide` to check t... | chatqna-redis-vector-db-7f489b6bb6-mvzbw 1/1 Running 0 5m7s chatqna-retriever-usvc-6695979d67-z5jgx 1/1 Running 0 5m7s chatqna-tei-769dc796c-gh5vx 1/1 Running 0 5m7s chatqna-teirerank-54f58c596c-76xqz 1/1 Running 0 5m7s chatqna-tgi-7b5556d46d-pnzph 1/1 Running 0 5m7s
>**Note:** Use `kubectl get pods -o wide` to check t... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
04b5a1e3-967a-46f7-9367-bbe0c5abc348 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 47 | opea-semantic-v1 | f2f4486de8ceaadd | the services running in your Kubernetes cluster from your local machine, you can set up port forwarding with kubectl: ```bash kubectl port-forward svc/[service-name] [local-port]:[service-port] &
Replace `[service-name]`, `[local-port]`, and `[service-port]` with the appropriate values from your services list (as shown... | ai_ref_knowledge | OPEA Documentation | the services running in your Kubernetes cluster from your local machine, you can set up port forwarding with kubectl: ```bash kubectl port-forward svc/[service-name] [local-port]:[service-port] &
Replace `[service-name]`, `[local-port]`, and `[service-port]` with the appropriate values from your services list (as shown... | the services running in your Kubernetes cluster from your local machine, you can set up port forwarding with kubectl: ```bash kubectl port-forward svc/[service-name] [local-port]:[service-port] &
Replace `[service-name]`, `[local-port]`, and `[service-port]` with the appropriate values from your services list (as shown... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
04fb9b31-c3d3-4f69-a5b4-a6703a8127f8 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 26 | opea-semantic-v1 | f11935962b50c85c | ```yaml extraCmdArgs: ["--dtype","bfloat16"]
This configuration ensures that TGI processes LLM operations in bfloat16 precision, enabling lower-precision computations for improved performance and reduced memory usage. Bfloat16 operations are accelerated using Intel® AMX, the built-in AI accelerator on 4th Gen Intel® Xe... | ai_ref_knowledge | OPEA Documentation | ```yaml extraCmdArgs: ["--dtype","bfloat16"]
This configuration ensures that TGI processes LLM operations in bfloat16 precision, enabling lower-precision computations for improved performance and reduced memory usage. Bfloat16 operations are accelerated using Intel® AMX, the built-in AI accelerator on 4th Gen Intel® Xe... | ```yaml extraCmdArgs: ["--dtype","bfloat16"]
This configuration ensures that TGI processes LLM operations in bfloat16 precision, enabling lower-precision computations for improved performance and reduced memory usage. Bfloat16 operations are accelerated using Intel® AMX, the built-in AI accelerator on 4th Gen Intel® Xe... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
05360caa-cf64-4573-8f0d-422acbe70f8b | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 116 | opea-semantic-v1 | a5674570e83b30a4 | The command shows internal IPs for all the nodes in the cluster:
NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME
minikube Ready control-plane 11d v1.31.0 190.128.49.1 <none> Ubuntu 22.04.4 LTS 5.15.0-124-generic docker://27.2.0 | ai_ref_knowledge | OPEA Documentation | The command shows internal IPs for all the nodes in the cluster:
NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME
minikube Ready control-plane 11d v1.31.0 190.128.49.1 <none> Ubuntu 22.04.4 LTS 5.15.0-124-generic docker://27.2.0 | The command shows internal IPs for all the nodes in the cluster:
NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME
minikube Ready control-plane 11d v1.31.0 190.128.49.1 <none> Ubuntu 22.04.4 LTS 5.15.0-124-generic docker://27.2.0 | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
09c4315c-a38b-44bd-9f28-37a65b516fb2 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 55 | opea-semantic-v1 | b18f364169bb0b88 | Which is essentially the following sentence:
OPEA stands for Organization of Public Employees of Alabama. It is a labor union representing public employees in the state of Alabama, working to protect their rights and interests. | ai_ref_knowledge | OPEA Documentation | Which is essentially the following sentence:
OPEA stands for Organization of Public Employees of Alabama. It is a labor union representing public employees in the state of Alabama, working to protect their rights and interests. | Which is essentially the following sentence:
OPEA stands for Organization of Public Employees of Alabama. It is a labor union representing public employees in the state of Alabama, working to protect their rights and interests. | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
09f5c24f-215a-4093-8a84-2c46a8d1e2e3 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 106 | opea-semantic-v1 | 2474538323ad8618 | ### Dataprep Microservice (Advanced) Once you have set up port forward for the dataprep service, you can upload, delete, and list documents.
Add Knowledge Base via HTTP Links: | ai_ref_knowledge | OPEA Documentation | ### Dataprep Microservice (Advanced) Once you have set up port forward for the dataprep service, you can upload, delete, and list documents.
Add Knowledge Base via HTTP Links: | ### Dataprep Microservice (Advanced) Once you have set up port forward for the dataprep service, you can upload, delete, and list documents.
Add Knowledge Base via HTTP Links: | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
0e14f6e8-4872-4454-8d95-a853264fbe4b | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 87 | opea-semantic-v1 | 4d1055a3fecb9899 | Overview\nOPEA Overview\nOPEA (Open Platform for Enterprise AI) is a framework that enables the creation and evaluation\nof open, multi-provider, robust, and composable generative AI (GenAI) solutions.
It harnesses\nthe best innovations across the ecosystem while keeping enterprise-level needs front and\ncenter.\nOPEA ... | ai_ref_knowledge | OPEA Documentation | Overview\nOPEA Overview\nOPEA (Open Platform for Enterprise AI) is a framework that enables the creation and evaluation\nof open, multi-provider, robust, and composable generative AI (GenAI) solutions.
It harnesses\nthe best innovations across the ecosystem while keeping enterprise-level needs front and\ncenter.\nOPEA ... | Overview\nOPEA Overview\nOPEA (Open Platform for Enterprise AI) is a framework that enables the creation and evaluation\nof open, multi-provider, robust, and composable generative AI (GenAI) solutions.
It harnesses\nthe best innovations across the ecosystem while keeping enterprise-level needs front and\ncenter.\nOPEA ... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
11430fd6-b2c9-40bb-8ba9-55eed760291c | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 29 | opea-semantic-v1 | 58460cdd43002fc6 | is writable. > > Another option is to use k8s persistent volume to share the model data files. For more information see [Using Persistent Volume](https://github.com/opea-project/GenAIInfra/blob/main/helm-charts/README.md#using-persistent-volume).
## Deploy the use case
The `helm install` command will initiate all the a... | ai_ref_knowledge | OPEA Documentation | is writable. > > Another option is to use k8s persistent volume to share the model data files. For more information see [Using Persistent Volume](https://github.com/opea-project/GenAIInfra/blob/main/helm-charts/README.md#using-persistent-volume).
## Deploy the use case
The `helm install` command will initiate all the a... | is writable. > > Another option is to use k8s persistent volume to share the model data files. For more information see [Using Persistent Volume](https://github.com/opea-project/GenAIInfra/blob/main/helm-charts/README.md#using-persistent-volume).
## Deploy the use case
The `helm install` command will initiate all the a... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
118f7aa9-2715-4673-a11d-6349b9bf4057 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 12 | opea-semantic-v1 | 26bc3b1cd2de81ea | ### HF Token The example can utilize model weights from HuggingFace.
Setup your [HuggingFace](https://huggingface.co/) account and generate
[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). | ai_ref_knowledge | OPEA Documentation | ### HF Token The example can utilize model weights from HuggingFace.
Setup your [HuggingFace](https://huggingface.co/) account and generate
[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). | ### HF Token The example can utilize model weights from HuggingFace.
Setup your [HuggingFace](https://huggingface.co/) account and generate
[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
12b7c1ba-4f8e-4158-a684-00e99698ed83 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 79 | opea-semantic-v1 | 47a896ee7c492a28 | Check the vector dimension of your embedding model and set `your_embedding` dimension equal to it.
export your_embedding=$(python3 -c "import random; embedding = [random.uniform(-1, 1) for _ in range(768)]; print(embedding)") | ai_ref_knowledge | OPEA Documentation | Check the vector dimension of your embedding model and set `your_embedding` dimension equal to it.
export your_embedding=$(python3 -c "import random; embedding = [random.uniform(-1, 1) for _ in range(768)]; print(embedding)") | Check the vector dimension of your embedding model and set `your_embedding` dimension equal to it.
export your_embedding=$(python3 -c "import random; embedding = [random.uniform(-1, 1) for _ in range(768)]; print(embedding)") | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
16679b7c-0d50-49e7-9b32-57623d494c93 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 73 | opea-semantic-v1 | 21bc705396178ed2 | in a string as input, embeds the string into a vector of a specific length determined by the embedding model and returns this embedded vector.
curl http://localhost:6006/embed \
-X POST \
-d '{"inputs":"What is Deep Learning?"}' \
-H 'Content-Type: application/json' | ai_ref_knowledge | OPEA Documentation | in a string as input, embeds the string into a vector of a specific length determined by the embedding model and returns this embedded vector.
curl http://localhost:6006/embed \
-X POST \
-d '{"inputs":"What is Deep Learning?"}' \
-H 'Content-Type: application/json' | in a string as input, embeds the string into a vector of a specific length determined by the embedding model and returns this embedded vector.
curl http://localhost:6006/embed \
-X POST \
-d '{"inputs":"What is Deep Learning?"}' \
-H 'Content-Type: application/json' | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
19a1304b-ebb0-403a-8d83-f5eb6ccadc4a | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 89 | opea-semantic-v1 | 8e5af88e80e3cf50 | systems around performance, features,\ntrustworthiness and enterprise-grade readiness\nOPEA Project Architecture\nOPEA uses microservices to create high-quality GenAI applications for enterprises, simplifying\nthe scaling and deployment process for production.
These microservices leverage a service\ncomposer that assem... | ai_ref_knowledge | OPEA Documentation | systems around performance, features,\ntrustworthiness and enterprise-grade readiness\nOPEA Project Architecture\nOPEA uses microservices to create high-quality GenAI applications for enterprises, simplifying\nthe scaling and deployment process for production.
These microservices leverage a service\ncomposer that assem... | systems around performance, features,\ntrustworthiness and enterprise-grade readiness\nOPEA Project Architecture\nOPEA uses microservices to create high-quality GenAI applications for enterprises, simplifying\nthe scaling and deployment process for production.
These microservices leverage a service\ncomposer that assem... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
1e04d329-588d-4b42-a064-da26acec9ca3 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 41 | opea-semantic-v1 | a060e8789c4129be | show 'Running', describe the pod using the name from the above table. In our example the pod name is chatqna-tgi-778bb6598f-cv5cg. ```bash kubectl describe pod chatqna-tgi-778bb6598f-cv5cg
Or check logs using:
```bash
kubectl logs chatqna-tgi-778bb6598f-cv5cg | ai_ref_knowledge | OPEA Documentation | show 'Running', describe the pod using the name from the above table. In our example the pod name is chatqna-tgi-778bb6598f-cv5cg. ```bash kubectl describe pod chatqna-tgi-778bb6598f-cv5cg
Or check logs using:
```bash
kubectl logs chatqna-tgi-778bb6598f-cv5cg | show 'Running', describe the pod using the name from the above table. In our example the pod name is chatqna-tgi-778bb6598f-cv5cg. ```bash kubectl describe pod chatqna-tgi-778bb6598f-cv5cg
Or check logs using:
```bash
kubectl logs chatqna-tgi-778bb6598f-cv5cg | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
1fe6465e-d953-4af3-94ae-c0ad32e348c8 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 117 | opea-semantic-v1 | 211e917c718a2f9c | NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME minikube Ready control-plane 11d v1.31.0 190.128.49.1 <none> Ubuntu 22.04.4 LTS 5.15.0-124-generic docker://27.2.0
When using a NodePort, all the nodes in the cluster will be listening at the specified port, which is `30304`... | ai_ref_knowledge | OPEA Documentation | NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME minikube Ready control-plane 11d v1.31.0 190.128.49.1 <none> Ubuntu 22.04.4 LTS 5.15.0-124-generic docker://27.2.0
When using a NodePort, all the nodes in the cluster will be listening at the specified port, which is `30304`... | NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME minikube Ready control-plane 11d v1.31.0 190.128.49.1 <none> Ubuntu 22.04.4 LTS 5.15.0-124-generic docker://27.2.0
When using a NodePort, all the nodes in the cluster will be listening at the specified port, which is `30304`... | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation | |
20496071-b99e-47c4-80c5-207ce05fbe61 | OPEA Documentation | file://datasets/opea-docs/tutorial/ChatQnA/deploy/k8s_helm.md | unknown | f8424b32-9e7e-493f-9934-cad335b62634 | 24 | opea-semantic-v1 | 44c393f013dd6d35 | # "chatqna" here refers to the directory name that contains the Helm # chart for the ChatQnA application helm dependency update chatqna
To use the bfloat16 data type for the LLM in TGI, modify the `values.yaml` file located in `GenAIInfra/helm-charts/common/tgi/`. Uncomment or add the following line: | ai_ref_knowledge | OPEA Documentation | # "chatqna" here refers to the directory name that contains the Helm # chart for the ChatQnA application helm dependency update chatqna
To use the bfloat16 data type for the LLM in TGI, modify the `values.yaml` file located in `GenAIInfra/helm-charts/common/tgi/`. Uncomment or add the following line: | # "chatqna" here refers to the directory name that contains the Helm # chart for the ChatQnA application helm dependency update chatqna
To use the bfloat16 data type for the LLM in TGI, modify the `values.yaml` file located in `GenAIInfra/helm-charts/common/tgi/`. Uncomment or add the following line: | opea, enterprise-ai, genai, docs, P1 | OPEA Documentation |
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