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This commit is contained in:
Xi Yan
parent
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2 changed files with 9 additions and 397 deletions
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@ -23,5 +23,6 @@ tgi
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dell-tgi
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dell-tgi
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together
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together
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fireworks
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fireworks
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remote-vllm
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bedrock
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bedrock
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```
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```
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@ -53,9 +53,9 @@ Please see our pages in detail for the types of distributions we offer:
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3. [On-device Distribution](./distributions/ondevice_distro/index.md): If you want to run Llama Stack inference on your iOS / Android device.
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3. [On-device Distribution](./distributions/ondevice_distro/index.md): If you want to run Llama Stack inference on your iOS / Android device.
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### Quick Start Commands
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### Table of Contents
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Once you have decided on the inference provider and distribution to use, use the following quick start commands to get started.
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Once you have decided on the inference provider and distribution to use, use the following guides to get started.
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##### 1.0 Prerequisite
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##### 1.0 Prerequisite
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@ -109,421 +109,32 @@ Access to Single-Node CPU with Fireworks hosted endpoint via API_KEY from [firew
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##### 1.1. Start the distribution
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##### 1.1. Start the distribution
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**(Option 1) Via Docker**
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::::{tab-set}
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:::{tab-item} meta-reference-gpu
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:::{tab-item} meta-reference-gpu
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```
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[Start Meta Reference GPU Distribution](https://llama-stack.readthedocs.io/en/latest/getting_started/distributions/self_hosted_distro/meta-reference-gpu.html)
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$ cd llama-stack/distributions/meta-reference-gpu && docker compose up
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```
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This will download and start running a pre-built Docker container. Alternatively, you may use the following commands:
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```
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docker run -it -p 5000:5000 -v ~/.llama:/root/.llama -v ./run.yaml:/root/my-run.yaml --gpus=all distribution-meta-reference-gpu --yaml_config /root/my-run.yaml
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```
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:::
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:::
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:::{tab-item} vLLM
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:::{tab-item} vLLM
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```
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[Start vLLM Distribution](https://llama-stack.readthedocs.io/en/latest/getting_started/distributions/self_hosted_distro/remote-vllm.html)
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$ cd llama-stack/distributions/remote-vllm && docker compose up
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```
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The script will first start up vLLM server on port 8000, then start up Llama Stack distribution server hooking up to it for inference. You should see the following outputs --
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```
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<TO BE FILLED>
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```
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To kill the server
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```
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docker compose down
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```
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:::
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:::
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:::{tab-item} tgi
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:::{tab-item} tgi
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```
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[Start TGI Distribution](https://llama-stack.readthedocs.io/en/latest/getting_started/distributions/self_hosted_distro/tgi.html)
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$ cd llama-stack/distributions/tgi && docker compose up
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```
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The script will first start up TGI server, then start up Llama Stack distribution server hooking up to the remote TGI provider for inference. You should see the following outputs --
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```
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[text-generation-inference] | 2024-10-15T18:56:33.810397Z INFO text_generation_router::server: router/src/server.rs:1813: Using config Some(Llama)
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[text-generation-inference] | 2024-10-15T18:56:33.810448Z WARN text_generation_router::server: router/src/server.rs:1960: Invalid hostname, defaulting to 0.0.0.0
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[text-generation-inference] | 2024-10-15T18:56:33.864143Z INFO text_generation_router::server: router/src/server.rs:2353: Connected
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INFO: Started server process [1]
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INFO: Waiting for application startup.
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INFO: Application startup complete.
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INFO: Uvicorn running on http://[::]:5000 (Press CTRL+C to quit)
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```
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To kill the server
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```
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docker compose down
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```
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:::
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:::{tab-item} ollama
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```
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$ cd llama-stack/distributions/ollama && docker compose up
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# OR
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$ cd llama-stack/distributions/ollama-gpu && docker compose up
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```
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You will see outputs similar to following ---
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```
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[ollama] | [GIN] 2024/10/18 - 21:19:41 | 200 | 226.841µs | ::1 | GET "/api/ps"
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[ollama] | [GIN] 2024/10/18 - 21:19:42 | 200 | 60.908µs | ::1 | GET "/api/ps"
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INFO: Started server process [1]
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INFO: Waiting for application startup.
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INFO: Application startup complete.
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INFO: Uvicorn running on http://[::]:5000 (Press CTRL+C to quit)
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[llamastack] | Resolved 12 providers
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[llamastack] | inner-inference => ollama0
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[llamastack] | models => __routing_table__
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[llamastack] | inference => __autorouted__
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```
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To kill the server
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```
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docker compose down
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```
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:::
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:::{tab-item} fireworks
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```
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$ cd llama-stack/distributions/fireworks && docker compose up
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```
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Make sure your `run.yaml` file has the inference provider pointing to the correct Fireworks URL server endpoint. E.g.
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```
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inference:
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- provider_id: fireworks
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provider_type: remote::fireworks
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config:
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url: https://api.fireworks.ai/inference
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api_key: <optional api key>
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```
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:::
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:::{tab-item} together
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```
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$ cd distributions/together && docker compose up
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```
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Make sure your `run.yaml` file has the inference provider pointing to the correct Together URL server endpoint. E.g.
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```
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inference:
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- provider_id: together
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provider_type: remote::together
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config:
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url: https://api.together.xyz/v1
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api_key: <optional api key>
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```
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:::
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::::
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**(Option 2) Via Conda**
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::::{tab-set}
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:::{tab-item} meta-reference-gpu
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1. Install the `llama` CLI. See [CLI Reference](https://llama-stack.readthedocs.io/en/latest/cli_reference/index.html)
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2. Build the `meta-reference-gpu` distribution
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```
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$ llama stack build --template meta-reference-gpu --image-type conda
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```
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3. Start running distribution
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```
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$ llama stack run ~/.llama/distributions/llamastack-meta-reference-gpu/meta-reference-gpu-run.yaml
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```
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Note: If you wish to use pgvector or chromadb as memory provider. You may need to update generated `run.yaml` file to point to the desired memory provider. See [Memory Providers](https://llama-stack.readthedocs.io/en/latest/api_providers/memory_api.html) for more details. Or comment out the pgvector or chromadb memory provider in `run.yaml` file to use the default inline memory provider, keeping only the following section:
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```
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memory:
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- provider_id: faiss-0
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provider_type: faiss
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config:
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kvstore:
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namespace: null
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type: sqlite
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db_path: ~/.llama/runtime/faiss_store.db
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```
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:::
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:::{tab-item} tgi
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1. Install the `llama` CLI. See [CLI Reference](https://llama-stack.readthedocs.io/en/latest/cli_reference/index.html)
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2. Build the `tgi` distribution
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```bash
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llama stack build --template tgi --image-type conda
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```
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3. Start a TGI server endpoint
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4. Make sure in your `run.yaml` file, your `conda_env` is pointing to the conda environment and inference provider is pointing to the correct TGI server endpoint. E.g.
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```
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conda_env: llamastack-tgi
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...
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inference:
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- provider_id: tgi0
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provider_type: remote::tgi
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config:
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url: http://127.0.0.1:5009
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```
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5. Start Llama Stack server
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```bash
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$ llama stack run ~/.llama/distributions/llamastack-tgi/tgi-run.yaml
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```
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Note: If you wish to use pgvector or chromadb as memory provider. You may need to update generated `run.yaml` file to point to the desired memory provider. See [Memory Providers](https://llama-stack.readthedocs.io/en/latest/api_providers/memory_api.html) for more details. Or comment out the pgvector or chromadb memory provider in `run.yaml` file to use the default inline memory provider, keeping only the following section:
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```
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memory:
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- provider_id: faiss-0
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provider_type: faiss
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config:
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kvstore:
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namespace: null
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type: sqlite
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db_path: ~/.llama/runtime/faiss_store.db
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```
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:::
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:::
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:::{tab-item} ollama
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:::{tab-item} ollama
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[Start Ollama Distribution](https://llama-stack.readthedocs.io/en/latest/getting_started/distributions/self_hosted_distro/ollama.html)
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If you wish to separately spin up a Ollama server, and connect with Llama Stack, you may use the following commands.
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#### Start Ollama server.
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- Please check the [Ollama Documentations](https://github.com/ollama/ollama) for more details.
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**Via Docker**
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```
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docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
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```
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**Via CLI**
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```
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ollama run <model_id>
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```
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#### Start Llama Stack server pointing to Ollama server
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Make sure your `run.yaml` file has the inference provider pointing to the correct Ollama endpoint. E.g.
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```
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conda_env: llamastack-ollama
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...
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inference:
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- provider_id: ollama0
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provider_type: remote::ollama
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config:
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url: http://127.0.0.1:11434
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```
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```
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llama stack build --template ollama --image-type conda
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llama stack run ~/.llama/distributions/llamastack-ollama/ollama-run.yaml
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```
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Note: If you wish to use pgvector or chromadb as memory provider. You may need to update generated `run.yaml` file to point to the desired memory provider. See [Memory Providers](https://llama-stack.readthedocs.io/en/latest/api_providers/memory_api.html) for more details. Or comment out the pgvector or chromadb memory provider in `run.yaml` file to use the default inline memory provider, keeping only the following section:
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```
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memory:
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- provider_id: faiss-0
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provider_type: faiss
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config:
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kvstore:
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namespace: null
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type: sqlite
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db_path: ~/.llama/runtime/faiss_store.db
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```
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:::
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:::{tab-item} fireworks
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```bash
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llama stack build --template fireworks --image-type conda
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# -- modify run.yaml to a valid Fireworks server endpoint
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llama stack run ./run.yaml
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```
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Make sure your `run.yaml` file has the inference provider pointing to the correct Fireworks URL server endpoint. E.g.
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```
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conda_env: llamastack-fireworks
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...
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inference:
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- provider_id: fireworks
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provider_type: remote::fireworks
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config:
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url: https://api.fireworks.ai/inference
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api_key: <optional api key>
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```
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:::
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:::
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:::{tab-item} together
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:::{tab-item} together
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[Start Together Distribution](https://llama-stack.readthedocs.io/en/latest/getting_started/distributions/self_hosted_distro/together.html)
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```bash
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llama stack build --template together --image-type conda
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# -- modify run.yaml to a valid Together server endpoint
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llama stack run ~/.llama/distributions/llamastack-together/together-run.yaml
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```
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Make sure your `run.yaml` file has the inference provider pointing to the correct Together URL server endpoint. E.g.
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```
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conda_env: llamastack-together
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...
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inference:
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- provider_id: together
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provider_type: remote::together
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config:
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url: https://api.together.xyz/v1
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api_key: <optional api key>
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```
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:::
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::::
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##### 1.2 (Optional) Update Model Serving Configuration
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::::{tab-set}
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||||||
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:::{tab-item} meta-reference-gpu
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||||||
You may change the `config.model` in `run.yaml` to update the model currently being served by the distribution. Make sure you have the model checkpoint downloaded in your `~/.llama`.
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```
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inference:
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- provider_id: meta0
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provider_type: inline::meta-reference
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config:
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model: Llama3.2-11B-Vision-Instruct
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quantization: null
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torch_seed: null
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max_seq_len: 4096
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max_batch_size: 1
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```
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Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints.
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:::
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||||||
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:::{tab-item} tgi
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To serve a new model with `tgi`, change the docker command flag `--model-id <model-to-serve>`.
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|
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This can be done by edit the `command` args in `compose.yaml`. E.g. Replace "Llama-3.2-1B-Instruct" with the model you want to serve.
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```
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command: ["--dtype", "bfloat16", "--usage-stats", "on", "--sharded", "false", "--model-id", "meta-llama/Llama-3.2-1B-Instruct", "--port", "5009", "--cuda-memory-fraction", "0.3"]
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```
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or by changing the docker run command's `--model-id` flag
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```
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docker run --rm -it -v $HOME/.cache/huggingface:/data -p 5009:5009 --gpus all ghcr.io/huggingface/text-generation-inference:latest --dtype bfloat16 --usage-stats on --sharded false --model-id meta-llama/Llama-3.2-1B-Instruct --port 5009
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```
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Make sure your `run.yaml` file has the inference provider pointing to the TGI server endpoint serving your model.
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```
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inference:
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- provider_id: tgi0
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provider_type: remote::tgi
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config:
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url: http://127.0.0.1:5009
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```
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```
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Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints.
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||||||
:::
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||||||
|
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||||||
:::{tab-item} ollama
|
|
||||||
You can use ollama for managing model downloads.
|
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||||||
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```
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ollama pull llama3.1:8b-instruct-fp16
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ollama pull llama3.1:70b-instruct-fp16
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```
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||||||
> Please check the [OLLAMA_SUPPORTED_MODELS](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers.remote/inference/ollama/ollama.py) for the supported Ollama models.
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|
||||||
|
|
||||||
|
|
||||||
To serve a new model with `ollama`
|
|
||||||
```
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|
||||||
ollama run <model_name>
|
|
||||||
```
|
|
||||||
|
|
||||||
To make sure that the model is being served correctly, run `ollama ps` to get a list of models being served by ollama.
|
|
||||||
```
|
|
||||||
$ ollama ps
|
|
||||||
|
|
||||||
NAME ID SIZE PROCESSOR UNTIL
|
|
||||||
llama3.1:8b-instruct-fp16 4aacac419454 17 GB 100% GPU 4 minutes from now
|
|
||||||
```
|
|
||||||
|
|
||||||
To verify that the model served by ollama is correctly connected to Llama Stack server
|
|
||||||
```
|
|
||||||
$ llama-stack-client models list
|
|
||||||
+----------------------+----------------------+---------------+-----------------------------------------------+
|
|
||||||
| identifier | llama_model | provider_id | metadata |
|
|
||||||
+======================+======================+===============+===============================================+
|
|
||||||
| Llama3.1-8B-Instruct | Llama3.1-8B-Instruct | ollama0 | {'ollama_model': 'llama3.1:8b-instruct-fp16'} |
|
|
||||||
+----------------------+----------------------+---------------+-----------------------------------------------+
|
|
||||||
```
|
|
||||||
:::
|
|
||||||
|
|
||||||
:::{tab-item} together
|
|
||||||
Use `llama-stack-client models list` to check the available models served by together.
|
|
||||||
|
|
||||||
```
|
|
||||||
$ llama-stack-client models list
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| identifier | llama_model | provider_id | metadata |
|
|
||||||
+==============================+==============================+===============+============+
|
|
||||||
| Llama3.1-8B-Instruct | Llama3.1-8B-Instruct | together0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.1-70B-Instruct | Llama3.1-70B-Instruct | together0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.1-405B-Instruct | Llama3.1-405B-Instruct | together0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.2-3B-Instruct | Llama3.2-3B-Instruct | together0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.2-11B-Vision-Instruct | Llama3.2-11B-Vision-Instruct | together0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.2-90B-Vision-Instruct | Llama3.2-90B-Vision-Instruct | together0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
```
|
|
||||||
:::
|
:::
|
||||||
|
|
||||||
:::{tab-item} fireworks
|
:::{tab-item} fireworks
|
||||||
Use `llama-stack-client models list` to check the available models served by Fireworks.
|
[Start Fireworks Distribution](https://llama-stack.readthedocs.io/en/latest/getting_started/distributions/self_hosted_distro/fireworks.html)
|
||||||
```
|
|
||||||
$ llama-stack-client models list
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| identifier | llama_model | provider_id | metadata |
|
|
||||||
+==============================+==============================+===============+============+
|
|
||||||
| Llama3.1-8B-Instruct | Llama3.1-8B-Instruct | fireworks0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.1-70B-Instruct | Llama3.1-70B-Instruct | fireworks0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.1-405B-Instruct | Llama3.1-405B-Instruct | fireworks0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.2-1B-Instruct | Llama3.2-1B-Instruct | fireworks0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.2-3B-Instruct | Llama3.2-3B-Instruct | fireworks0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.2-11B-Vision-Instruct | Llama3.2-11B-Vision-Instruct | fireworks0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
| Llama3.2-90B-Vision-Instruct | Llama3.2-90B-Vision-Instruct | fireworks0 | {} |
|
|
||||||
+------------------------------+------------------------------+---------------+------------+
|
|
||||||
```
|
|
||||||
:::
|
:::
|
||||||
|
|
||||||
::::
|
::::
|
||||||
|
|
||||||
|
|
||||||
##### Troubleshooting
|
##### Troubleshooting
|
||||||
- If you encounter any issues, search through our [GitHub Issues](https://github.com/meta-llama/llama-stack/issues), or file an new issue.
|
- If you encounter any issues, search through our [GitHub Issues](https://github.com/meta-llama/llama-stack/issues), or file an new issue.
|
||||||
- Use `--port <PORT>` flag to use a different port number. For docker run, update the `-p <PORT>:<PORT>` flag.
|
- Use `--port <PORT>` flag to use a different port number. For docker run, update the `-p <PORT>:<PORT>` flag.
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue