# API Reference

This document provides detailed API documentation for the main components of LLMPromptKit.

## PromptManager

The `PromptManager` class is the core component for managing prompts.

```python
from llmpromptkit import PromptManager
```

### Methods

#### `__init__(storage_path=None)`
- **Description**: Initialize a new PromptManager.
- **Parameters**:
  - `storage_path` (str, optional): Path to store prompts. Defaults to "~/llmpromptkit_storage".

#### `create(content, name, description='', tags=None, metadata=None)`
- **Description**: Create a new prompt.
- **Parameters**:
  - `content` (str): The prompt text with optional variables in {variable_name} format.
  - `name` (str): Name of the prompt.
  - `description` (str, optional): Description of the prompt.
  - `tags` (list of str, optional): Tags for categorization.
  - `metadata` (dict, optional): Additional metadata.
- **Returns**: `Prompt` object.

#### `get(prompt_id)`
- **Description**: Get a prompt by ID.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt.
- **Returns**: `Prompt` object or None if not found.

#### `update(prompt_id, content=None, name=None, description=None, tags=None, metadata=None)`
- **Description**: Update a prompt.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt to update.
  - `content` (str, optional): New prompt text.
  - `name` (str, optional): New name.
  - `description` (str, optional): New description.
  - `tags` (list of str, optional): New tags.
  - `metadata` (dict, optional): New metadata.
- **Returns**: Updated `Prompt` object.

#### `delete(prompt_id)`
- **Description**: Delete a prompt.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt to delete.
- **Returns**: True if deleted, False otherwise.

#### `list_all()`
- **Description**: List all prompts.
- **Returns**: List of `Prompt` objects.

#### `search_by_tags(tags, match_all=False)`
- **Description**: Search prompts by tags.
- **Parameters**:
  - `tags` (list of str): Tags to search for.
  - `match_all` (bool, optional): If True, prompt must have all tags.
- **Returns**: List of matching `Prompt` objects.

## VersionControl

The `VersionControl` class manages prompt versions.

```python
from llmpromptkit import VersionControl
```

### Methods

#### `__init__(prompt_manager)`
- **Description**: Initialize the version control system.
- **Parameters**:
  - `prompt_manager` (PromptManager): A PromptManager instance.

#### `commit(prompt_id, commit_message, metadata=None)`
- **Description**: Create a new version of a prompt.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt.
  - `commit_message` (str): Message describing the changes.
  - `metadata` (dict, optional): Additional version metadata.
- **Returns**: Version number (int).

#### `list_versions(prompt_id)`
- **Description**: List all versions of a prompt.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt.
- **Returns**: List of version objects.

#### `get_version(prompt_id, version_number)`
- **Description**: Get a specific version of a prompt.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt.
  - `version_number` (int): The version number.
- **Returns**: Version data.

#### `checkout(prompt_id, version_number)`
- **Description**: Revert a prompt to a specific version.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt.
  - `version_number` (int): The version to revert to.
- **Returns**: Updated `Prompt` object.

#### `diff(prompt_id, version1, version2)`
- **Description**: Compare two versions of a prompt.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt.
  - `version1` (int): First version number.
  - `version2` (int): Second version number.
- **Returns**: Diff object.

## PromptTesting

The `PromptTesting` class provides testing capabilities.

```python
from llmpromptkit import PromptTesting
```

### Methods

#### `__init__(prompt_manager)`
- **Description**: Initialize the testing system.
- **Parameters**:
  - `prompt_manager` (PromptManager): A PromptManager instance.

#### `create_test_case(prompt_id, input_vars, expected_output=None, name=None, description=None)`
- **Description**: Create a test case for a prompt.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt to test.
  - `input_vars` (dict): Variables to substitute in the prompt.
  - `expected_output` (str, optional): Expected response.
  - `name` (str, optional): Test case name.
  - `description` (str, optional): Test case description.
- **Returns**: Test case object.

#### `run_test_case(test_case_id, llm_callback)`
- **Description**: Run a test case.
- **Parameters**:
  - `test_case_id` (str): The ID of the test case.
  - `llm_callback` (callable): Function to call LLM.
- **Returns**: Test result.

#### `run_all_tests(prompt_id, llm_callback)`
- **Description**: Run all tests for a prompt.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt.
  - `llm_callback` (callable): Function to call LLM.
- **Returns**: List of test results.

#### `ab_test(prompt_id_a, prompt_id_b, test_cases, llm_callback, metrics=None)`
- **Description**: Run A/B tests comparing two prompts.
- **Parameters**:
  - `prompt_id_a` (str): First prompt ID.
  - `prompt_id_b` (str): Second prompt ID.
  - `test_cases` (list): Test cases to run.
  - `llm_callback` (callable): Function to call LLM.
  - `metrics` (list, optional): Metrics to compare.
- **Returns**: A/B test results.

## Evaluator

The `Evaluator` class handles prompt evaluation.

```python
from llmpromptkit import Evaluator
```

### Methods

#### `__init__(prompt_manager)`
- **Description**: Initialize the evaluator.
- **Parameters**:
  - `prompt_manager` (PromptManager): A PromptManager instance.

#### `register_metric(metric)`
- **Description**: Register a new evaluation metric.
- **Parameters**:
  - `metric` (EvaluationMetric): The metric to register.

#### `evaluate_prompt(prompt_id, inputs, llm_callback, expected_outputs=None, metric_names=None)`
- **Description**: Evaluate a prompt with the given inputs and metrics.
- **Parameters**:
  - `prompt_id` (str): The ID of the prompt.
  - `inputs` (list): List of input dictionaries.
  - `llm_callback` (callable): Function to call LLM.
  - `expected_outputs` (list, optional): Expected outputs.
  - `metric_names` (list, optional): Metrics to use.
- **Returns**: Evaluation results.

## PromptTemplate

The `PromptTemplate` class provides advanced templating.

```python
from llmpromptkit import PromptTemplate
```

### Methods

#### `__init__(template_string)`
- **Description**: Initialize a template.
- **Parameters**:
  - `template_string` (str): Template with variables, conditionals, and loops.

#### `render(**variables)`
- **Description**: Render the template with given variables.
- **Parameters**:
  - `variables` (dict): Variables to substitute.
- **Returns**: Rendered string.

## EvaluationMetric

The `EvaluationMetric` is the base class for evaluation metrics.

```python
from llmpromptkit import EvaluationMetric
```

### Methods

#### `__init__(name, description=None)`
- **Description**: Initialize a metric.
- **Parameters**:
  - `name` (str): Metric name.
  - `description` (str, optional): Metric description.

#### `compute(generated_output, expected_output=None, **kwargs)`
- **Description**: Compute the metric score.
- **Parameters**:
  - `generated_output` (str): Output from LLM.
  - `expected_output` (str, optional): Expected output.
  - `**kwargs`: Additional parameters.
- **Returns**: Score (float between 0 and 1).

### Built-in Metrics

- `ExactMatchMetric`: Scores exact matches between generated and expected output.
- `ContainsKeywordsMetric`: Scores based on keyword presence.
- `LengthMetric`: Scores based on output length.

```python
from llmpromptkit import ExactMatchMetric, ContainsKeywordsMetric, LengthMetric
```