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fix: notebook vision inference (#1423)

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# What does this PR do?

- update to use library client throughout 

cc @jeffxtang 

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
```
pytest -v -s --nbval-lax ./docs/getting_started.ipynb
```

[//]: # (## Documentation)
This commit is contained in:
Xi Yan 2025-03-06 13:40:21 -08:00 • committed by GitHub
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@ -141,7 +141,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 18,
"id": "E1UFuJC570Tk", "id": "E1UFuJC570Tk",
"metadata": { "metadata": {
"colab": { "colab": {
@ -326,54 +326,108 @@
" type: sqlite\n", " type: sqlite\n",
"models:\n", "models:\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct\n", " model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct-Turbo\n", " provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct\n", " model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct-Turbo\n", " provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-FP8\n", " model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-FP8\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-Turbo\n", " provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct\n", " model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct-Turbo\n", " provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct\n", " model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct-Turbo\n", " provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct\n", " model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct-Turbo\n", " provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct\n", " model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct-Turbo\n", " provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Meta-Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n", " model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n", " provider_model_id: meta-llama/Meta-Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n", "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-11B-Vision-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-11B-Vision-Turbo\n",
"- metadata: <span style=\"font-weight: bold\">{}</span>\n",
" model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-11B-Vision\n", " model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-11B-Vision\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
@ -473,6 +527,9 @@
" - config: <span style=\"font-weight: bold\">{}</span>\n", " - config: <span style=\"font-weight: bold\">{}</span>\n",
" provider_id: model-context-protocol\n", " provider_id: model-context-protocol\n",
" provider_type: remote::model-context-protocol\n", " provider_type: remote::model-context-protocol\n",
" - config: <span style=\"font-weight: bold\">{}</span>\n",
" provider_id: wolfram-alpha\n",
" provider_type: remote::wolfram-alpha\n",
" vector_io:\n", " vector_io:\n",
" - config:\n", " - config:\n",
" kvstore:\n", " kvstore:\n",
@ -504,6 +561,10 @@
" mcp_endpoint: null\n", " mcp_endpoint: null\n",
" provider_id: code-interpreter\n", " provider_id: code-interpreter\n",
" toolgroup_id: builtin::code_interpreter\n", " toolgroup_id: builtin::code_interpreter\n",
"- args: null\n",
" mcp_endpoint: null\n",
" provider_id: wolfram-alpha\n",
" toolgroup_id: builtin::wolfram_alpha\n",
"vector_dbs: <span style=\"font-weight: bold\">[]</span>\n", "vector_dbs: <span style=\"font-weight: bold\">[]</span>\n",
"version: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>\n", "version: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>\n",
"\n", "\n",
@ -530,54 +591,108 @@
" type: sqlite\n", " type: sqlite\n",
"models:\n", "models:\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct\n", " model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct-Turbo\n", " provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct\n", " model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct-Turbo\n", " provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-FP8\n", " model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-FP8\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-Turbo\n", " provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct\n", " model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct-Turbo\n", " provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct\n", " model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct-Turbo\n", " provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct\n", " model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct-Turbo\n", " provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct\n", " model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct-Turbo\n", " provider_model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Meta-Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n", " model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
" provider_id: together\n", " provider_id: together\n",
" provider_model_id: meta-llama/Meta-Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n", " provider_model_id: meta-llama/Meta-Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-11B-Vision-Turbo\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n",
" provider_id: together\n",
" provider_model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-11B-Vision-Turbo\n",
"- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-11B-Vision\n", " model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-11B-Vision\n",
" model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n", " model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
" - llm\n", " - llm\n",
@ -677,6 +792,9 @@
" - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n", " - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" provider_id: model-context-protocol\n", " provider_id: model-context-protocol\n",
" provider_type: remote::model-context-protocol\n", " provider_type: remote::model-context-protocol\n",
" - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
" provider_id: wolfram-alpha\n",
" provider_type: remote::wolfram-alpha\n",
" vector_io:\n", " vector_io:\n",
" - config:\n", " - config:\n",
" kvstore:\n", " kvstore:\n",
@ -708,6 +826,10 @@
" mcp_endpoint: null\n", " mcp_endpoint: null\n",
" provider_id: code-interpreter\n", " provider_id: code-interpreter\n",
" toolgroup_id: builtin::code_interpreter\n", " toolgroup_id: builtin::code_interpreter\n",
"- args: null\n",
" mcp_endpoint: null\n",
" provider_id: wolfram-alpha\n",
" toolgroup_id: builtin::wolfram_alpha\n",
"vector_dbs: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n", "vector_dbs: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
"version: \u001b[32m'2'\u001b[0m\n", "version: \u001b[32m'2'\u001b[0m\n",
"\n" "\n"
@ -4098,7 +4220,7 @@
"source": [ "source": [
"## 4. Image Understanding with Llama 3.2\n", "## 4. Image Understanding with Llama 3.2\n",
"\n", "\n",
"Below is a complete example of using Together's Llama Stack 0.1 server at https://llama-stack.together.ai to ask Llama 3.2 questions about an image." "Below is a complete example of to ask Llama 3.2 questions about an image."
] ]
}, },
{ {
@ -4106,14 +4228,12 @@
"id": "82e381ec", "id": "82e381ec",
"metadata": {}, "metadata": {},
"source": [ "source": [
"### 4.1 Setup and helpers\n", "### 4.1 Setup and helpers\n"
"\n",
"Below we install the Llama Stack client 0.1, download the example image, define two image helpers, and set Llama Stack Together server URL and Llama 3.2 model name.\n"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 1,
"id": "44e05e16", "id": "44e05e16",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -4123,7 +4243,7 @@
"text": [ "text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\n", " % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n", " Dload Upload Total Spent Left Speed\n",
"100 275k 100 275k 0 0 780k 0 --:--:-- --:--:-- --:--:-- 780k\n" "100 275k 100 275k 0 0 905k 0 --:--:-- --:--:-- --:--:-- 906k\n"
] ]
} }
], ],
@ -4133,32 +4253,13 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 20,
"id": "469750f7",
"metadata": {},
"outputs": [],
"source": [
"# NBVAL_SKIP\n",
"from PIL import Image\n",
"import matplotlib.pyplot as plt\n",
"\n",
"def display_image(path):\n",
" img = Image.open(path)\n",
" plt.imshow(img)\n",
" plt.axis('off')\n",
" plt.show()\n",
"\n",
"display_image(\"Llama_Repo.jpeg\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a2c1e1c2", "id": "a2c1e1c2",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"import base64\n", "import base64\n",
"vision_model_id = \"meta-llama/Llama-3.2-11B-Vision-Instruct\"\n",
"\n", "\n",
"def encode_image(image_path):\n", "def encode_image(image_path):\n",
" with open(image_path, \"rb\") as image_file:\n", " with open(image_path, \"rb\") as image_file:\n",
@ -4167,19 +4268,6 @@
" return base64_url" " return base64_url"
] ]
}, },
{
"cell_type": "code",
"execution_count": null,
"id": "c565f99e",
"metadata": {},
"outputs": [],
"source": [
"from llama_stack_client import LlamaStackClient\n",
"\n",
"LLAMA_STACK_API_TOGETHER_URL=\"https://llama-stack.together.ai\"\n",
"LLAMA32_11B_INSTRUCT = \"meta-llama/Llama-3.2-11B-Vision-Instruct\""
]
},
{ {
"cell_type": "markdown", "cell_type": "markdown",
"id": "7737cd41", "id": "7737cd41",
@ -4192,55 +4280,44 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 21,
"id": "d7914894", "id": "d7914894",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"There are three llamas in the image. The llama in the middle is purple, the llama on the left is white, and the llama on the right is also white, but it is wearing a blue party hat. Therefore, there are two different colors of llama in the image: purple and white.\n"
]
}
],
"source": [ "source": [
"from llama_stack_client.lib.inference.event_logger import EventLogger\n", "response = client.inference.chat_completion(\n",
"\n", " messages=[\n",
"async def run_main(image_path: str, prompt):\n", " {\n",
" client = LlamaStackClient(\n", " \"role\": \"user\",\n",
" base_url=LLAMA_STACK_API_TOGETHER_URL,\n", " \"content\": [\n",
" )\n", " {\n",
"\n", " \"type\": \"image\",\n",
" message = {\n", " \"image\": {\n",
" \"role\": \"user\",\n", " \"url\": {\n",
" \"content\": [\n", " \"uri\": encode_image(\"Llama_Repo.jpeg\")\n",
" {\n", " }\n",
" \"type\": \"image\",\n", " }\n",
" \"image\": {\n", " },\n",
" \"url\": {\n", " {\n",
" \"uri\": encode_image(image_path)\n", " \"type\": \"text\",\n",
" }\n", " \"text\": \"How many different colors are those llamas? What are those colors?\",\n",
" }\n", " }\n",
" },\n", " ]\n",
" {\n", " }\n",
" \"type\": \"text\",\n", " ],\n",
" \"text\": prompt,\n", " model_id=vision_model_id,\n",
" }\n", " stream=False,\n",
" ]\n", ")\n",
" }\n",
"\n", "\n",
" response = client.inference.chat_completion(\n", "print(response.completion_message.content)"
" messages=[message],\n",
" model_id=LLAMA32_11B_INSTRUCT,\n",
" stream=False,\n",
" )\n",
"\n",
" print(response.completion_message.content.lower().strip())"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4ee09b97",
"metadata": {},
"outputs": [],
"source": [
"await run_main(\"Llama_Repo.jpeg\",\n",
" \"How many different colors are those llamas?\\\n",
" What are those colors?\")"
] ]
}, },
{ {
@ -4255,68 +4332,65 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 19,
"id": "f9a83275", "id": "f9a83275",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33minference> \u001b[0m\u001b[33mThere\u001b[0m\u001b[33m are\u001b[0m\u001b[33m three\u001b[0m\u001b[33m different\u001b[0m\u001b[33m colors\u001b[0m\u001b[33m of\u001b[0m\u001b[33m ll\u001b[0m\u001b[33mamas\u001b[0m\u001b[33m in\u001b[0m\u001b[33m the\u001b[0m\u001b[33m image\u001b[0m\u001b[33m.\u001b[0m\u001b[33m The\u001b[0m\u001b[33m first\u001b[0m\u001b[33m llama\u001b[0m\u001b[33m on\u001b[0m\u001b[33m the\u001b[0m\u001b[33m left\u001b[0m\u001b[33m is\u001b[0m\u001b[33m white\u001b[0m\u001b[33m,\u001b[0m\u001b[33m the\u001b[0m\u001b[33m second\u001b[0m\u001b[33m llama\u001b[0m\u001b[33m in\u001b[0m\u001b[33m the\u001b[0m\u001b[33m middle\u001b[0m\u001b[33m is\u001b[0m\u001b[33m purple\u001b[0m\u001b[33m,\u001b[0m\u001b[33m and\u001b[0m\u001b[33m the\u001b[0m\u001b[33m third\u001b[0m\u001b[33m llama\u001b[0m\u001b[33m on\u001b[0m\u001b[33m the\u001b[0m\u001b[33m right\u001b[0m\u001b[33m is\u001b[0m\u001b[33m white\u001b[0m\u001b[33m with\u001b[0m\u001b[33m a\u001b[0m\u001b[33m blue\u001b[0m\u001b[33m party\u001b[0m\u001b[33m hat\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
"\u001b[30m\u001b[0m"
]
}
],
"source": [ "source": [
"from llama_stack_client.lib.agents.agent import Agent\n",
"from llama_stack_client.lib.agents.event_logger import EventLogger\n",
"from llama_stack_client.types.agent_create_params import AgentConfig\n", "from llama_stack_client.types.agent_create_params import AgentConfig\n",
"\n", "\n",
"async def run_main(image_path, prompt):\n", "agent_config = AgentConfig(\n",
" base64_image = encode_image(image_path)\n", " model=vision_model_id,\n",
" instructions=\"You are a helpful assistant\",\n",
" enable_session_persistence=False,\n",
" toolgroups=[],\n",
")\n",
"\n", "\n",
" client = LlamaStackClient(\n", "agent = Agent(client, agent_config)\n",
" base_url=LLAMA_STACK_API_TOGETHER_URL,\n", "session_id = agent.create_session(\"test-session\")\n",
" )\n",
"\n", "\n",
" agent_config = AgentConfig(\n", "response = agent.create_turn(\n",
" model=LLAMA32_11B_INSTRUCT,\n", " messages=[{\n",
" instructions=\"You are a helpful assistant\",\n", " \"role\": \"user\",\n",
" enable_session_persistence=False,\n", " \"content\": [\n",
" toolgroups=[],\n", " {\n",
" )\n", " \"type\": \"image\",\n",
"\n", " \"image\": {\n",
" agent = Agent(client, agent_config)\n", " \"url\": {\n",
" session_id = agent.create_session(\"test-session\")\n", " \"uri\": encode_image(\"Llama_Repo.jpeg\")\n",
"\n", " }\n",
" response = agent.create_turn(\n",
" messages=[{\n",
" \"role\": \"user\",\n",
" \"content\": [\n",
" {\n",
" \"type\": \"image\",\n",
" \"image\": {\n",
" \"url\": {\n",
" \"uri\": encode_image(image_path)\n",
" }\n",
" }\n",
" },\n",
" {\n",
" \"type\": \"text\",\n",
" \"text\": prompt,\n",
" }\n", " }\n",
" ]\n", " },\n",
" }],\n", " {\n",
" session_id=session_id,\n", " \"type\": \"text\",\n",
" )\n", " \"text\": \"How many different colors are those llamas? What are those colors?\",\n",
" }\n",
" ]\n",
" }],\n",
" session_id=session_id,\n",
")\n",
"\n", "\n",
" for log in EventLogger().log(response):\n", "for log in EventLogger().log(response):\n",
" log.print()" " log.print()\n",
" "
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"id": "15d0098b", "id": "f3352379",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": []
"await run_main(\"Llama_Repo.jpeg\",\n",
" \"How many different colors are those llamas?\\\n",
" What are those colors?\")"
]
} }
], ],
"metadata": { "metadata": {