Skip to content
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
228 changes: 228 additions & 0 deletions docs/source/developer-guide/api-change.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,228 @@
# LLM API Change Guide

This guide explains how to modify and manage APIs in TensorRT LLM, focusing on the high-level LLM API.

## Overview

TensorRT LLM provides multiple API levels:

1. **LLM API** - The highest-level API (e.g., the `LLM` class)
2. **PyExecutor API** - The mid-level API (e.g., the `PyExecutor` class)

This guide focuses on the LLM API, which is the primary interface for most users.

## API Types and Stability Guarantees

TensorRT LLM classifies APIs into two categories:

### 1. Committed APIs
- **Stable** and guaranteed to remain consistent across releases
- No breaking changes without major version updates
- Schema stored in: `tests/unittest/api_stability/references_committed/`

### 2. Non-committed APIs
- Under active development and may change between releases
- Marked with a `status` field in the docstring:
- `prototype` - Early experimental stage
- `beta` - More stable but still subject to change
- `deprecated` - Scheduled for removal
- Schema stored in: `tests/unittest/api_stability/references/`
- See [API status documentation](https://nvidia.github.io/TensorRT-LLM/llm-api/reference.html) for complete details

## API Schema Management

All API schemas are:
- Stored as YAML files in the codebase
- Protected by unit tests in `tests/unittest/api_stability/`
- Automatically validated to ensure consistency

## Modifying LLM Constructor Arguments

The LLM class accepts numerous configuration parameters for models, runtime, and other components. These are managed through a Pydantic dataclass called `LlmArgs`.

### Architecture

- The LLM's `__init__` method parameters map directly to `LlmArgs` fields
- `LlmArgs` is an alias for `TorchLlmArgs` (defined in `tensorrt_llm/llmapi/llm_args.py`)
- All arguments are validated and type-checked through Pydantic

### Adding a New Argument

Follow these steps to add a new constructor argument:

#### 1. Add the field to `TorchLlmArgs`

```python
garbage_collection_gen0_threshold: int = Field(
default=20000,
description=(
"Threshold for Python garbage collection of generation 0 objects. "
"Lower values trigger more frequent garbage collection."
),
status="beta" # Required for non-committed arguments
)
```

**Field requirements:**
- **Type annotation**: Required for all fields
- **Default value**: Recommended unless the field is mandatory
- **Description**: Clear explanation of the parameter's purpose
- **Status**: Required for non-committed arguments (`prototype`, `beta`, etc.)

#### 2. Update the API schema

Add the field to the appropriate schema file:

- **Non-committed arguments**: `tests/unittest/api_stability/references/llm_args.yaml`
```yaml
garbage_collection_gen0_threshold:
type: int
default: 20000
status: beta # Must match the status in code
```

- **Committed arguments**: `tests/unittest/api_stability/references_committed/llm_args.yaml`
```yaml
garbage_collection_gen0_threshold:
type: int
default: 20000
# No status field for committed arguments
```

#### 3. Run validation tests

```bash
python -m pytest tests/unittest/api_stability/test_llm_api.py
```

## Modifying LLM Class Methods

Public methods in the LLM class constitute the API surface. All changes must be properly documented and tracked.

### Implementation Details

- The actual implementation is in the `_TorchLLM` class ([llm.py](https://github.com/NVIDIA/TensorRT-LLM/blob/release/1.0/tensorrt_llm/llmapi/llm.py))
- Public methods (not starting with `_`) are automatically exposed as APIs

### Adding a New Method

Follow these steps to add a new API method:

#### 1. Implement the method in `_TorchLLM`

For non-committed APIs, use the `@set_api_status` decorator:

```python
@set_api_status("beta")
def generate_with_streaming(
self,
prompts: List[str],
**kwargs
) -> Iterator[GenerationOutput]:
"""Generate text with streaming output.

Args:
prompts: Input prompts for generation
**kwargs: Additional generation parameters

Returns:
Iterator of generation outputs
"""
# Implementation here
pass
```

For committed APIs, no decorator is needed:

```python
def generate(self, prompts: List[str], **kwargs) -> GenerationOutput:
"""Generate text from prompts."""
# Implementation here
pass
```

#### 2. Update the API schema

Add the method to the appropriate `llm.yaml` file:

**Non-committed API** (`tests/unittest/api_stability/references/llm.yaml`):
```yaml
generate_with_streaming:
status: beta # Must match @set_api_status
parameters:
- name: prompts
type: List[str]
- name: kwargs
type: dict
returns: Iterator[GenerationOutput]
```

**Committed API** (`tests/unittest/api_stability/references_committed/llm.yaml`):
```yaml
generate:
parameters:
- name: prompts
type: List[str]
- name: kwargs
type: dict
returns: GenerationOutput
```

### Modifying Existing Methods

When modifying existing methods:

1. **Non-breaking changes** (adding optional parameters):
- Update the method signature
- Update the schema file
- No status change needed

2. **Breaking changes** (changing required parameters, return types):
- Only allowed for non-committed APIs
- Consider deprecation path for beta APIs
- Update documentation with migration guide

### Best Practices

1. **Documentation**: Always include comprehensive docstrings
2. **Type hints**: Use proper type annotations for all parameters and returns
3. **Testing**: Add unit tests for new methods
4. **Examples**: Provide usage examples in the docstring
5. **Validation**: Run API stability tests before submitting changes

### Running Tests

Validate your changes:

```bash
# Run API stability tests
python -m pytest tests/unittest/api_stability/

# Run specific test for LLM API
python -m pytest tests/unittest/api_stability/test_llm_api.py -v
```

## Common Workflows

### Promoting an API from Beta to Committed

1. Remove the `@set_api_status("beta")` decorator from the method
2. Move the schema entry from `tests/unittest/api_stability/references/` to `tests/unittest/api_stability/references_committed/`
3. Remove the `status` field from the schema
4. Update any documentation referring to the API's beta status

### Deprecating an API

1. Add `@set_api_status("deprecated")` to the method
2. Update the schema with `status: deprecated`
3. Add deprecation warning in the method:
```python
import warnings
warnings.warn(
"This method is deprecated and will be removed in v2.0. "
"Use new_method() instead.",
DeprecationWarning,
stacklevel=2
)
```
4. Document the migration path
1 change: 1 addition & 0 deletions docs/source/index.rst
Original file line number Diff line number Diff line change
Expand Up @@ -83,6 +83,7 @@ Welcome to TensorRT LLM's Documentation!
developer-guide/perf-benchmarking.md
developer-guide/ci-overview.md
developer-guide/dev-containers.md
developer-guide/api-change.md


.. .. toctree::
Expand Down