swarmauri_base 0.10.0

This repository includes base classes and mixins for the Swarmauri framework.

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Swarmauri Base

Getting Started

Installing Swarmauri Base from pypi

To start developing with the Core Library, include it as a module in your Python project. Ensure you have Python 3.10 or later installed.

pip install swarmauri-base

Example Usage:

# Example of using the base class
from swarmauri_base.llms.LLMBase import LLMBase

class MyConcreteClass(LLMBase):
    
    pass

Features

agents

• AgentBase.py: Base class for agents.
• AgentConversationMixin.py: Mixin for conversation capabilities.
• AgentRetrieveMixin.py: Mixin for retrieval functionalities.
• AgentSystemContextMixin.py: Mixin for system context.
• AgentToolMixin.py: Mixin for tool integration.
• AgentVectorStoreMixin.py: Mixin for vector store functionalities.

chains

• ChainBase.py: Base class for chains.
• ChainContextBase.py: Base class for chain context.
• ChainStepBase.py: Base class for chain steps.
• PromptContextChainBase.py: Base class for prompt context chains.

chunkers

• ChunkerBase.py: Base class for chunkers.

conversations

• ConversationBase.py: Base class for conversations.
• ConversationSystemContextMixin.py: Mixin for system context in conversations.

dataconnectors

• DataConnectorBase.py: Base class for data connectors.

distances

• DistanceBase.py: Base class for distance calculations.
• VisionDistanceBase.py: Base class for vision distance calculations.

documents

• DocumentBase.py: Base class for documents.

document_stores

• DocumentStoreBase.py: Base class for document stores.
• DocumentStoreRetrieveBase.py: Base class for document retrieval.

embeddings

• EmbeddingBase.py: Base class for embeddings.
• VisionEmbeddingBase.py: Base class for vision embeddings.

factories

• FactoryBase.py: Base class for factories.

image_gens

• ImageGenBase.py: Base class for image generation.

llms

• LLMBase.py: Base class for large language models.

logging

• HandlerBase.py: Base class for logging handlers.
• LoggerBase.py: Base class for loggers.

measurements

• MeasurementAggregateMixin.py: Mixin for measurement aggregation.
• MeasurementBase.py: Base class for measurements.
• MeasurementCalculateMixin.py: Mixin for measurement calculations.
• MeasurementThresholdMixin.py: Mixin for measurement thresholds.

messages

• MessageBase.py: Base class for messages.

ocrs

• OCRBase.py: Base class for OCR functionalities.

parsers

• ParserBase.py: Base class for parsers.

pipelines

• PipelineBase.py: Base class for pipelines.

prompts

• PromptBase.py: Base class for prompts.
• PromptGeneratorBase.py: Base class for prompt generators.
• PromptMatrixBase.py: Base class for prompt matrices.

prompt_templates

• PromptTemplateBase.py: Base class for prompt templates.

schema_converters

• SchemaConverterBase.py: Base class for schema converters.

service_registries

• ServiceRegistryBase.py: Base class for service registries.

state

• StateBase.py: Base class for state management.

stt

• STTBase.py: Base class for speech-to-text functionalities.

swarms

• SwarmBase.py: Base class for swarm intelligence.

task_mgmt_strategies

• TaskMgmtStrategyBase.py: Base class for task management strategies.

toolkits

• ToolkitBase.py: Base class for toolkits.

tool_llms

• ToolLLMBase.py: Base class for tools for large language models.

tools

• ParameterBase.py: Base class for parameters.
• ToolBase.py: Base class for tools.

transports

• TransportBase.py: Base class for transports.

tts

• TTSBase.py: Base class for text-to-speech functionalities.

vectors

• VectorBase.py: Base class for vectors.

vector_stores

• VectorStoreBase.py: Base class for vector stores.
• VectorStoreCloudMixin.py: Mixin for cloud vector stores.
• VectorStorePersistentMixin.py: Mixin for persistent vector stores.
• VectorStoreRetrieveMixin.py: Mixin for vector store retrieval.
• VectorStoreSaveLoadMixin.py: Mixin for saving and loading vector stores.
• VisionVectorStoreBase.py: Base class for vision vector stores.

vlms

• VLMBase.py: Base class for visual language models.

Contributing

Contributions are welcome! If you'd like to add a new feature, fix a bug, or improve documentation, kindly go through the contributions guidelines first.