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Sync Core Integrations API reference (meta_llama) on Docusaurus (#9938)

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Co-authored-by: vblagoje <458335+vblagoje@users.noreply.github.com>
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95
docs-website/reference/integrations-api/meta_llama.md
View File

@ -57,7 +57,7 @@ def __init__(*,
streaming_callback: Optional[StreamingCallbackT] = None,
api_base_url: Optional[str] = "https://api.llama.com/compat/v1/",
generation_kwargs: Optional[Dict[str, Any]] = None,
tools: Optional[Union[List[Tool], Toolset]] = None)
tools: Optional[ToolsType] = None)
```
Creates an instance of LlamaChatGenerator. Unless specified otherwise in the `model`, this is for Llama's
@ -86,7 +86,8 @@ Some of the supported parameters:
events as they become available, with the stream terminated by a data: [DONE] message.
- `safe_prompt`: Whether to inject a safety prompt before all conversations.
- `random_seed`: The seed to use for random sampling.
- `tools`: A list of tools for which the model can prepare calls.
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
Each tool should have a unique name.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.to_dict"></a>
@ -102,93 +103,3 @@ Serialize this component to a dictionary.
The serialized component as a dictionary.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.from_dict"></a>
#### MetaLlamaChatGenerator.from\_dict
```python
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "OpenAIChatGenerator"
```
Deserialize this component from a dictionary.
**Arguments**:
- `data`: The dictionary representation of this component.
**Returns**:
The deserialized component instance.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.run"></a>
#### MetaLlamaChatGenerator.run
```python
@component.output_types(replies=list[ChatMessage])
def run(messages: list[ChatMessage],
streaming_callback: Optional[StreamingCallbackT] = None,
generation_kwargs: Optional[dict[str, Any]] = None,
*,
tools: Optional[ToolsType] = None,
tools_strict: Optional[bool] = None)
```
Invokes chat completion based on the provided messages and generation parameters.
**Arguments**:
- `messages`: A list of ChatMessage instances representing the input messages.
- `streaming_callback`: A callback function that is called when a new token is received from the stream.
- `generation_kwargs`: Additional keyword arguments for text generation. These parameters will
override the parameters passed during component initialization.
For details on OpenAI API parameters, see [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
If set, it will override the `tools` parameter provided during initialization.
- `tools_strict`: Whether to enable strict schema adherence for tool calls. If set to `True`, the model will follow exactly
the schema provided in the `parameters` field of the tool definition, but this may increase latency.
If set, it will override the `tools_strict` parameter set during component initialization.
**Returns**:
A dictionary with the following key:
- `replies`: A list containing the generated responses as ChatMessage instances.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.run_async"></a>
#### MetaLlamaChatGenerator.run\_async
```python
@component.output_types(replies=list[ChatMessage])
async def run_async(messages: list[ChatMessage],
streaming_callback: Optional[StreamingCallbackT] = None,
generation_kwargs: Optional[dict[str, Any]] = None,
*,
tools: Optional[ToolsType] = None,
tools_strict: Optional[bool] = None)
```
Asynchronously invokes chat completion based on the provided messages and generation parameters.
This is the asynchronous version of the `run` method. It has the same parameters and return values
but can be used with `await` in async code.
**Arguments**:
- `messages`: A list of ChatMessage instances representing the input messages.
- `streaming_callback`: A callback function that is called when a new token is received from the stream.
Must be a coroutine.
- `generation_kwargs`: Additional keyword arguments for text generation. These parameters will
override the parameters passed during component initialization.
For details on OpenAI API parameters, see [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
If set, it will override the `tools` parameter provided during initialization.
- `tools_strict`: Whether to enable strict schema adherence for tool calls. If set to `True`, the model will follow exactly
the schema provided in the `parameters` field of the tool definition, but this may increase latency.
If set, it will override the `tools_strict` parameter set during component initialization.
**Returns**:
A dictionary with the following key:
- `replies`: A list containing the generated responses as ChatMessage instances.

95
docs-website/reference_versioned_docs/version-2.17/integrations-api/meta_llama.md
View File

@ -57,7 +57,7 @@ def __init__(*,
streaming_callback: Optional[StreamingCallbackT] = None,
api_base_url: Optional[str] = "https://api.llama.com/compat/v1/",
generation_kwargs: Optional[Dict[str, Any]] = None,
tools: Optional[Union[List[Tool], Toolset]] = None)
tools: Optional[ToolsType] = None)
```
Creates an instance of LlamaChatGenerator. Unless specified otherwise in the `model`, this is for Llama's
@ -86,7 +86,8 @@ Some of the supported parameters:
events as they become available, with the stream terminated by a data: [DONE] message.
- `safe_prompt`: Whether to inject a safety prompt before all conversations.
- `random_seed`: The seed to use for random sampling.
- `tools`: A list of tools for which the model can prepare calls.
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
Each tool should have a unique name.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.to_dict"></a>
@ -102,93 +103,3 @@ Serialize this component to a dictionary.
The serialized component as a dictionary.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.from_dict"></a>
#### MetaLlamaChatGenerator.from\_dict
```python
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "OpenAIChatGenerator"
```
Deserialize this component from a dictionary.
**Arguments**:
- `data`: The dictionary representation of this component.
**Returns**:
The deserialized component instance.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.run"></a>
#### MetaLlamaChatGenerator.run
```python
@component.output_types(replies=list[ChatMessage])
def run(messages: list[ChatMessage],
streaming_callback: Optional[StreamingCallbackT] = None,
generation_kwargs: Optional[dict[str, Any]] = None,
*,
tools: Optional[ToolsType] = None,
tools_strict: Optional[bool] = None)
```
Invokes chat completion based on the provided messages and generation parameters.
**Arguments**:
- `messages`: A list of ChatMessage instances representing the input messages.
- `streaming_callback`: A callback function that is called when a new token is received from the stream.
- `generation_kwargs`: Additional keyword arguments for text generation. These parameters will
override the parameters passed during component initialization.
For details on OpenAI API parameters, see [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
If set, it will override the `tools` parameter provided during initialization.
- `tools_strict`: Whether to enable strict schema adherence for tool calls. If set to `True`, the model will follow exactly
the schema provided in the `parameters` field of the tool definition, but this may increase latency.
If set, it will override the `tools_strict` parameter set during component initialization.
**Returns**:
A dictionary with the following key:
- `replies`: A list containing the generated responses as ChatMessage instances.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.run_async"></a>
#### MetaLlamaChatGenerator.run\_async
```python
@component.output_types(replies=list[ChatMessage])
async def run_async(messages: list[ChatMessage],
streaming_callback: Optional[StreamingCallbackT] = None,
generation_kwargs: Optional[dict[str, Any]] = None,
*,
tools: Optional[ToolsType] = None,
tools_strict: Optional[bool] = None)
```
Asynchronously invokes chat completion based on the provided messages and generation parameters.
This is the asynchronous version of the `run` method. It has the same parameters and return values
but can be used with `await` in async code.
**Arguments**:
- `messages`: A list of ChatMessage instances representing the input messages.
- `streaming_callback`: A callback function that is called when a new token is received from the stream.
Must be a coroutine.
- `generation_kwargs`: Additional keyword arguments for text generation. These parameters will
override the parameters passed during component initialization.
For details on OpenAI API parameters, see [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
If set, it will override the `tools` parameter provided during initialization.
- `tools_strict`: Whether to enable strict schema adherence for tool calls. If set to `True`, the model will follow exactly
the schema provided in the `parameters` field of the tool definition, but this may increase latency.
If set, it will override the `tools_strict` parameter set during component initialization.
**Returns**:
A dictionary with the following key:
- `replies`: A list containing the generated responses as ChatMessage instances.

95
docs-website/reference_versioned_docs/version-2.18/integrations-api/meta_llama.md
View File

@ -57,7 +57,7 @@ def __init__(*,
streaming_callback: Optional[StreamingCallbackT] = None,
api_base_url: Optional[str] = "https://api.llama.com/compat/v1/",
generation_kwargs: Optional[Dict[str, Any]] = None,
tools: Optional[Union[List[Tool], Toolset]] = None)
tools: Optional[ToolsType] = None)
```
Creates an instance of LlamaChatGenerator. Unless specified otherwise in the `model`, this is for Llama's
@ -86,7 +86,8 @@ Some of the supported parameters:
events as they become available, with the stream terminated by a data: [DONE] message.
- `safe_prompt`: Whether to inject a safety prompt before all conversations.
- `random_seed`: The seed to use for random sampling.
- `tools`: A list of tools for which the model can prepare calls.
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
Each tool should have a unique name.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.to_dict"></a>
@ -102,93 +103,3 @@ Serialize this component to a dictionary.
The serialized component as a dictionary.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.from_dict"></a>
#### MetaLlamaChatGenerator.from\_dict
```python
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "OpenAIChatGenerator"
```
Deserialize this component from a dictionary.
**Arguments**:
- `data`: The dictionary representation of this component.
**Returns**:
The deserialized component instance.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.run"></a>
#### MetaLlamaChatGenerator.run
```python
@component.output_types(replies=list[ChatMessage])
def run(messages: list[ChatMessage],
streaming_callback: Optional[StreamingCallbackT] = None,
generation_kwargs: Optional[dict[str, Any]] = None,
*,
tools: Optional[ToolsType] = None,
tools_strict: Optional[bool] = None)
```
Invokes chat completion based on the provided messages and generation parameters.
**Arguments**:
- `messages`: A list of ChatMessage instances representing the input messages.
- `streaming_callback`: A callback function that is called when a new token is received from the stream.
- `generation_kwargs`: Additional keyword arguments for text generation. These parameters will
override the parameters passed during component initialization.
For details on OpenAI API parameters, see [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
If set, it will override the `tools` parameter provided during initialization.
- `tools_strict`: Whether to enable strict schema adherence for tool calls. If set to `True`, the model will follow exactly
the schema provided in the `parameters` field of the tool definition, but this may increase latency.
If set, it will override the `tools_strict` parameter set during component initialization.
**Returns**:
A dictionary with the following key:
- `replies`: A list containing the generated responses as ChatMessage instances.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.run_async"></a>
#### MetaLlamaChatGenerator.run\_async
```python
@component.output_types(replies=list[ChatMessage])
async def run_async(messages: list[ChatMessage],
streaming_callback: Optional[StreamingCallbackT] = None,
generation_kwargs: Optional[dict[str, Any]] = None,
*,
tools: Optional[ToolsType] = None,
tools_strict: Optional[bool] = None)
```
Asynchronously invokes chat completion based on the provided messages and generation parameters.
This is the asynchronous version of the `run` method. It has the same parameters and return values
but can be used with `await` in async code.
**Arguments**:
- `messages`: A list of ChatMessage instances representing the input messages.
- `streaming_callback`: A callback function that is called when a new token is received from the stream.
Must be a coroutine.
- `generation_kwargs`: Additional keyword arguments for text generation. These parameters will
override the parameters passed during component initialization.
For details on OpenAI API parameters, see [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
If set, it will override the `tools` parameter provided during initialization.
- `tools_strict`: Whether to enable strict schema adherence for tool calls. If set to `True`, the model will follow exactly
the schema provided in the `parameters` field of the tool definition, but this may increase latency.
If set, it will override the `tools_strict` parameter set during component initialization.
**Returns**:
A dictionary with the following key:
- `replies`: A list containing the generated responses as ChatMessage instances.

95
docs-website/reference_versioned_docs/version-2.19/integrations-api/meta_llama.md
View File

@ -57,7 +57,7 @@ def __init__(*,
streaming_callback: Optional[StreamingCallbackT] = None,
api_base_url: Optional[str] = "https://api.llama.com/compat/v1/",
generation_kwargs: Optional[Dict[str, Any]] = None,
tools: Optional[Union[List[Tool], Toolset]] = None)
tools: Optional[ToolsType] = None)
```
Creates an instance of LlamaChatGenerator. Unless specified otherwise in the `model`, this is for Llama's
@ -86,7 +86,8 @@ Some of the supported parameters:
events as they become available, with the stream terminated by a data: [DONE] message.
- `safe_prompt`: Whether to inject a safety prompt before all conversations.
- `random_seed`: The seed to use for random sampling.
- `tools`: A list of tools for which the model can prepare calls.
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
Each tool should have a unique name.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.to_dict"></a>
@ -102,93 +103,3 @@ Serialize this component to a dictionary.
The serialized component as a dictionary.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.from_dict"></a>
#### MetaLlamaChatGenerator.from\_dict
```python
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "OpenAIChatGenerator"
```
Deserialize this component from a dictionary.
**Arguments**:
- `data`: The dictionary representation of this component.
**Returns**:
The deserialized component instance.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.run"></a>
#### MetaLlamaChatGenerator.run
```python
@component.output_types(replies=list[ChatMessage])
def run(messages: list[ChatMessage],
streaming_callback: Optional[StreamingCallbackT] = None,
generation_kwargs: Optional[dict[str, Any]] = None,
*,
tools: Optional[ToolsType] = None,
tools_strict: Optional[bool] = None)
```
Invokes chat completion based on the provided messages and generation parameters.
**Arguments**:
- `messages`: A list of ChatMessage instances representing the input messages.
- `streaming_callback`: A callback function that is called when a new token is received from the stream.
- `generation_kwargs`: Additional keyword arguments for text generation. These parameters will
override the parameters passed during component initialization.
For details on OpenAI API parameters, see [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
If set, it will override the `tools` parameter provided during initialization.
- `tools_strict`: Whether to enable strict schema adherence for tool calls. If set to `True`, the model will follow exactly
the schema provided in the `parameters` field of the tool definition, but this may increase latency.
If set, it will override the `tools_strict` parameter set during component initialization.
**Returns**:
A dictionary with the following key:
- `replies`: A list containing the generated responses as ChatMessage instances.
<a id="haystack_integrations.components.generators.meta_llama.chat.chat_generator.MetaLlamaChatGenerator.run_async"></a>
#### MetaLlamaChatGenerator.run\_async
```python
@component.output_types(replies=list[ChatMessage])
async def run_async(messages: list[ChatMessage],
streaming_callback: Optional[StreamingCallbackT] = None,
generation_kwargs: Optional[dict[str, Any]] = None,
*,
tools: Optional[ToolsType] = None,
tools_strict: Optional[bool] = None)
```
Asynchronously invokes chat completion based on the provided messages and generation parameters.
This is the asynchronous version of the `run` method. It has the same parameters and return values
but can be used with `await` in async code.
**Arguments**:
- `messages`: A list of ChatMessage instances representing the input messages.
- `streaming_callback`: A callback function that is called when a new token is received from the stream.
Must be a coroutine.
- `generation_kwargs`: Additional keyword arguments for text generation. These parameters will
override the parameters passed during component initialization.
For details on OpenAI API parameters, see [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
If set, it will override the `tools` parameter provided during initialization.
- `tools_strict`: Whether to enable strict schema adherence for tool calls. If set to `True`, the model will follow exactly
the schema provided in the `parameters` field of the tool definition, but this may increase latency.
If set, it will override the `tools_strict` parameter set during component initialization.
**Returns**:
A dictionary with the following key:
- `replies`: A list containing the generated responses as ChatMessage instances.