mmar-mapi 1.7.4

Common pure/IO utilities for multi-modal architectures team

mmar-mapi

Multimodal architectures Maestro API — common pure/IO utilities for multi-modal architectures team.

Installation

pip install mmar-mapi

Overview

A Python library providing foundational utilities for building conversational AI systems, with particular focus on medical/healthcare applications.

Core Features

• Chat Management: Framework for managing conversations with flexible message types
• File Storage: Resource management with deduplication support
• Document Processing: Content extraction from various document types
• LLM Integration: Interfaces for Large Language Model communication
• XML Parsing: Utilities for medical diagnostic data

Quick Start

from mmar_mapi import Chat, HumanMessage, AIMessage, make_content

# Create a chat session
chat = Chat(
    context=Context(session_id="session-123", user_id="user-456"),
    messages=[
        HumanMessage(content=make_content("Hello, AI!")),
        AIMessage(content=make_content("How can I help you today?"))
    ]
)

from mmar_mapi import FileStorage, ResourceId

# Store and retrieve files
storage = FileStorage()
resource_id = storage.upload(b"file content")
content = storage.download(resource_id)

Main Modules

Chat System (mmar_mapi.models.chat)

• Chat — Conversation container with context and messages
• HumanMessage, AIMessage, MiscMessage — Message types
• Content — Flexible content supporting text, resources, commands, and widgets
• Widget — UI components for interactive conversations

File Storage (mmar_mapi.file_storage)

• FileStorageAPI — Abstract interface for file operations
• FileStorage — Implementation with deduplication
• FileStorageBasic — Simple file access without storage
• ResourceId — Type-safe resource identifiers

Models (mmar_mapi.models)

• TrackInfo, DomainInfo — Track and domain categorization
• DiagnosticsXMLTagEnum, MTRSXMLTagEnum, UncertaintyXMLTagEnum — Medical XML tags

Utilities (mmar_mapi.utils)

• make_session_id() — Generate unique session identifiers
• chunked() — Split iterables into chunks
• XMLParser — XML processing utilities

Services (mmar_mapi.services)

Service APIs for integrating with external systems:

LLM Hub (llm_hub.py)

• LLMHubAPI — Interface for LLM communication
• LLMCallProps — Call configuration
• LLMPayload — Message payload with attachments
• LLMResponseExt — Extended response format

Document Extractor (document_extractor.py)

• DocumentExtractorAPI — Extract content from documents
• DocExtractionSpec — Extraction configuration
• ExtractedTable, ExtractedPicture, ExtractedPageImage — Extraction results

Chat Manager (chat_manager.py)

• ChatManagerAPI — Manage domains, tracks, and chat responses

Text Processing (text_generator.py, text_processor.py)

• TextGeneratorAPI — Generate text from chat
• TextProcessorAPI — Process text with chat context

Content Interpreter (content_interpreter.py)

• ContentInterpreterAPI — Interpret content resources
• ContentInterpreterRemoteAPI — Remote content interpretation
• ContentInterpreterRemoteResponse — Remote response format

Additional Services

• BinaryClassifiersAPI — Binary text classification
• TranslatorAPI — Language translation
• CriticAPI — Text evaluation
• TextExtractorAPI — Extract text from resources