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Sep 29, 2025
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fix: remove inference.completion from docs #3589

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e1b750e
fix: remove inference.completion from docs
mattf Sep 28, 2025
b010635
Merge remote-tracking branch 'origin/main' into update-completion-docs
ashwinb Sep 29, 2025
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1 change: 0 additions & 1 deletion docs/docs/references/python_sdk_reference/index.md
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Expand Up @@ -217,7 +217,6 @@ from llama_stack_client.types import (
Methods:

- <code title="post /v1/inference/chat-completion">client.inference.<a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/resources/inference.py">chat_completion</a>(\*\*<a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/types/inference_chat_completion_params.py">params</a>) -> <a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/types/inference_chat_completion_response.py">InferenceChatCompletionResponse</a></code>
- <code title="post /v1/inference/completion">client.inference.<a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/resources/inference.py">completion</a>(\*\*<a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/types/inference_completion_params.py">params</a>) -> <a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/types/inference_completion_response.py">InferenceCompletionResponse</a></code>
- <code title="post /v1/inference/embeddings">client.inference.<a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/resources/inference.py">embeddings</a>(\*\*<a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/types/inference_embeddings_params.py">params</a>) -> <a href="https://github.com/meta-llama/llama-stack-client-python/tree/main/src/llama_stack_client/types/embeddings_response.py">EmbeddingsResponse</a></code>

## VectorIo
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14 changes: 4 additions & 10 deletions docs/getting_started.ipynb
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Expand Up @@ -824,16 +824,10 @@
"\n",
"\n",
"user_input = \"Michael Jordan was born in 1963. He played basketball for the Chicago Bulls. He retired in 2003. Extract this information into JSON for me. \"\n",
"response = client.inference.completion(\n",
" model_id=\"meta-llama/Llama-3.1-8B-Instruct\",\n",
" content=user_input,\n",
" stream=False,\n",
" sampling_params={\n",
" \"strategy\": {\n",
" \"type\": \"greedy\",\n",
" },\n",
" \"max_tokens\": 50,\n",
" },\n",
"response = client.chat.completions.create(\n",
" model=\"meta-llama/Llama-3.1-8B-Instruct\",\n",
" messages=[{\"role\": \"user\", \"content\": user_input}],\n",
" max_tokens=50,\n",
" response_format={\n",
" \"type\": \"json_schema\",\n",
" \"json_schema\": Output.model_json_schema(),\n",
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38 changes: 14 additions & 24 deletions docs/notebooks/nvidia/beginner_e2e/Llama_Stack_NVIDIA_E2E_Flow.ipynb
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Expand Up @@ -706,20 +706,15 @@
" provider_id=\"nvidia\",\n",
")\n",
"\n",
"response = client.inference.completion(\n",
" content=\"Complete the sentence using one word: Roses are red, violets are \",\n",
"response = client.completions.create(\n",
" prompt=\"Complete the sentence using one word: Roses are red, violets are \",\n",
" stream=False,\n",
" model_id=CUSTOMIZED_MODEL_DIR,\n",
" sampling_params={\n",
" \"strategy\": {\n",
" \"type\": \"top_p\",\n",
" \"temperature\": 0.7,\n",
" \"top_p\": 0.9\n",
" },\n",
" \"max_tokens\": 20,\n",
" },\n",
" model=CUSTOMIZED_MODEL_DIR,\n",
" temperature=0.7,\n",
" top_p=0.9,\n",
" max_tokens=20,\n",
")\n",
"print(f\"Inference response: {response.content}\")"
"print(f\"Inference response: {response.choices[0].text}\")"
]
},
{
Expand Down Expand Up @@ -1233,20 +1228,15 @@
" provider_id=\"nvidia\",\n",
")\n",
"\n",
"response = client.inference.completion(\n",
" content=\"Complete the sentence using one word: Roses are red, violets are \",\n",
"response = client.completions.create(\n",
" prompt=\"Complete the sentence using one word: Roses are red, violets are \",\n",
" stream=False,\n",
" model_id=customized_chat_model_dir,\n",
" sampling_params={\n",
" \"strategy\": {\n",
" \"type\": \"top_p\",\n",
" \"temperature\": 0.7,\n",
" \"top_p\": 0.9\n",
" },\n",
" \"max_tokens\": 20,\n",
" },\n",
" model=customized_chat_model_dir,\n",
" temperature=0.7,\n",
" top_p=0.9,\n",
" max_tokens=20,\n",
")\n",
"print(f\"Inference response: {response.content}\")"
"print(f\"Inference response: {response.choices[0].text}\")"
]
},
{
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19 changes: 0 additions & 19 deletions llama_stack/providers/remote/inference/nvidia/NVIDIA.md
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Expand Up @@ -39,25 +39,6 @@ client = LlamaStackAsLibraryClient("nvidia")
client.initialize()
```

### Create Completion

The following example shows how to create a completion for an NVIDIA NIM.

> [!NOTE]
> The hosted NVIDIA Llama NIMs (for example ```meta-llama/Llama-3.1-8B-Instruct```) that have ```NVIDIA_BASE_URL="https://integrate.api.nvidia.com"``` do not support the ```completion``` method, while locally deployed NIMs do.

```python
response = client.inference.completion(
model_id="meta-llama/Llama-3.1-8B-Instruct",
content="Complete the sentence using one word: Roses are red, violets are :",
stream=False,
sampling_params={
"max_tokens": 50,
},
)
print(f"Response: {response.content}")
```

### Create Chat Completion

The following example shows how to create a chat completion for an NVIDIA NIM.
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12 changes: 5 additions & 7 deletions llama_stack/providers/remote/post_training/nvidia/README.md
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Expand Up @@ -140,13 +140,11 @@ client.models.register(
#### 2. Inference with the fine-tuned model

```python
response = client.inference.completion(
content="Complete the sentence using one word: Roses are red, violets are ",
response = client.completions.create(
prompt="Complete the sentence using one word: Roses are red, violets are ",
stream=False,
model_id="test-example-model@v1",
sampling_params={
"max_tokens": 50,
},
model="test-example-model@v1",
max_tokens=50,
)
print(response.content)
print(response.choices[0].text)
```
6 changes: 3 additions & 3 deletions tests/integration/README.md
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Expand Up @@ -178,10 +178,10 @@ Note that when re-recording tests, you must use a Stack pointing to a server (i.

### Basic Test Pattern
```python
def test_basic_completion(llama_stack_client, text_model_id):
response = llama_stack_client.inference.completion(
def test_basic_chat_completion(llama_stack_client, text_model_id):
response = llama_stack_client.inference.chat_completion(
model_id=text_model_id,
content=CompletionMessage(role="user", content="Hello"),
messages=[{"role": "user", "content": "Hello"}],
)

# Test structure, not AI output quality
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