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https://github.com/meta-llama/llama-stack.git
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23210e8679
* docker compose ollama * comment * update compose file * readme for distributions * readme * move distribution folders * move distribution/templates to distributions/ * rename * kill distribution/templates * readme * readme * build/developer cookbook/new api provider * developer cookbook * readme * readme * [bugfix] fix case for agent when memory bank registered without specifying provider_id (#264) * fix case where memory bank is registered without provider_id * memory test * agents unit test * Add an option to not use elastic agents for meta-reference inference (#269) * Allow overridding checkpoint_dir via config * Small rename * Make all methods `async def` again; add completion() for meta-reference (#270) PR #201 had made several changes while trying to fix issues with getting the stream=False branches of inference and agents API working. As part of this, it made a change which was slightly gratuitous. Namely, making chat_completion() and brethren "def" instead of "async def". The rationale was that this allowed the user (within llama-stack) of this to use it as: ``` async for chunk in api.chat_completion(params) ``` However, it causes unnecessary confusion for several folks. Given that clients (e.g., llama-stack-apps) anyway use the SDK methods (which are completely isolated) this choice was not ideal. Let's revert back so the call now looks like: ``` async for chunk in await api.chat_completion(params) ``` Bonus: Added a completion() implementation for the meta-reference provider. Technically should have been another PR :) * Improve an important error message * update ollama for llama-guard3 * Add vLLM inference provider for OpenAI compatible vLLM server (#178) This PR adds vLLM inference provider for OpenAI compatible vLLM server. * Create .readthedocs.yaml Trying out readthedocs * Update event_logger.py (#275) spelling error * vllm * build templates * delete templates * tmp add back build to avoid merge conflicts * vllm * vllm --------- Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com> Co-authored-by: Ashwin Bharambe <ashwin@meta.com> Co-authored-by: Yuan Tang <terrytangyuan@gmail.com> Co-authored-by: raghotham <rsm@meta.com> Co-authored-by: nehal-a2z <nehal@coderabbit.ai>
91 lines
2.7 KiB
Markdown
91 lines
2.7 KiB
Markdown
# Ollama Distribution
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The `llamastack/distribution-ollama` distribution consists of the following provider configurations.
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| **API** | **Inference** | **Agents** | **Memory** | **Safety** | **Telemetry** |
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|----------------- |---------------- |---------------- |---------------------------------- |---------------- |---------------- |
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| **Provider(s)** | remote::ollama | meta-reference | remote::pgvector, remote::chroma | remote::ollama | meta-reference |
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### Start a Distribution (Single Node GPU)
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> [!NOTE]
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> This assumes you have access to GPU to start a Ollama server with access to your GPU.
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```
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$ cd llama-stack/distribution/ollama/gpu
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$ ls
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compose.yaml run.yaml
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$ 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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### Start the Distribution (Single Node CPU)
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> [!NOTE]
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> This will start an ollama server with CPU only, please see [Ollama Documentations](https://github.com/ollama/ollama) for serving models on CPU only.
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```
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$ cd llama-stack/distribution/ollama/cpu
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$ ls
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compose.yaml run.yaml
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$ docker compose up
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```
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### (Alternative) ollama run + llama stack Run
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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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**Via Docker**
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```
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docker run --network host -it -p 5000:5000 -v ~/.llama:/root/.llama -v ./ollama-run.yaml:/root/llamastack-run-ollama.yaml --gpus=all llamastack-local-cpu --yaml_config /root/llamastack-run-ollama.yaml
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```
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Make sure in you `ollama-run.yaml` file, you inference provider is pointing to the correct Ollama endpoint. E.g.
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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://127.0.0.1:14343
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```
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**Via Conda**
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```
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llama stack build --config ./build.yaml
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llama stack run ./gpu/run.yaml
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```
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