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Search Results for "diagram"

Found 18 matching component(s)

  • function generate_neo4j_schema_report

    Generates a comprehensive schema report of a Neo4j graph database, including node labels, relationships, properties, constraints, indexes, and sample data, outputting multiple file formats (JSON, HTML, Python snippets, Cypher examples).

    File: /tf/active/vicechatdev/neo4j_schema_report.py

    neo4j graph-database schema-analysis database-introspection documentation-generation

  • function generate_diagram_data

    Transforms Neo4j schema information into a structured format suitable for graph visualization, creating separate node and edge data structures.

    File: /tf/active/vicechatdev/neo4j_schema_report.py

    graph-visualization schema-processing neo4j data-transformation diagram-generation

  • function generate_html_report

    Generate HTML report from schema info

    File: /tf/active/vicechatdev/neo4j_schema_report.py

    function generate_html_report

  • class CompactResponseFormatter

    A formatter class that converts verbose LLM responses into compact, symbol-rich text optimized for e-ink displays by using Unicode symbols, mathematical notation, and abbreviated formatting.

    File: /tf/active/vicechatdev/e-ink-llm/compact_formatter.py

    formatting text-processing e-ink display-optimization compact-notation

  • class LLMHandler

    Handles OpenAI LLM interactions with optimized prompts for analyzing handwritten and drawn content, providing comprehensive responses with optional hybrid graphics integration.

    File: /tf/active/vicechatdev/e-ink-llm/llm_handler.py

    openai llm gpt-4 image-analysis handwriting-recognition

  • function create_instruction_diagram

    Generates a sample instructional diagram image showing step-by-step coffee making instructions with text, lines, shapes, and an arrow pointing to a coffee maker illustration.

    File: /tf/active/vicechatdev/e-ink-llm/demo.py

    image-generation PIL Pillow diagram instructions

  • function run_demo

    Orchestrates a complete demonstration of an E-Ink LLM Assistant by creating three sample handwritten content files (question, instruction diagram, math problem) and processing each through an AI pipeline.

    File: /tf/active/vicechatdev/e-ink-llm/demo.py

    async demo e-ink llm handwriting

  • class HybridResponseHandler

    Orchestrates the complete workflow for generating hybrid PDF documents that combine LLM text responses with dynamically generated graphics (charts, diagrams, illustrations).

    File: /tf/active/vicechatdev/e-ink-llm/hybrid_response_handler.py

    pdf-generation hybrid-content graphics-generation async document-assembly

  • class HybridPromptEnhancer

    A utility class that enhances LLM prompts by adding instructions and formatting guidelines to encourage hybrid text+graphics responses with embedded graphic placeholders.

    File: /tf/active/vicechatdev/e-ink-llm/hybrid_response_handler.py

    prompt-engineering llm graphics hybrid-output text-enhancement

  • function demo_graphics_generation

    Demonstrates the generation of three types of graphics (bar chart, process diagram, and mathematical illustration) using the GraphicsGenerator class with e-ink optimized styling.

    File: /tf/active/vicechatdev/e-ink-llm/demo_hybrid_mode.py

    demo graphics-generation async visualization chart

  • function demo_hybrid_response

    Demonstrates end-to-end hybrid response processing by converting an LLM response containing text and graphics placeholders into a formatted PDF document.

    File: /tf/active/vicechatdev/e-ink-llm/demo_hybrid_mode.py

    demo hybrid-response pdf-generation graphics-processing async

  • function demo_placeholder_parsing

    Demonstrates the parsing of graphics placeholders embedded in text by extracting and displaying placeholder metadata including type, description, ID, and parameters.

    File: /tf/active/vicechatdev/e-ink-llm/demo_hybrid_mode.py

    demo testing placeholder-parsing graphics text-processing

  • class ConversationContextManager

    Advanced conversation context manager that analyzes conversation history, extracts topics, builds reference maps, and generates contextual intelligence for multi-turn conversations.

    File: /tf/active/vicechatdev/e-ink-llm/conversation_context.py

    conversation-management context-analysis topic-extraction reference-tracking conversation-intelligence

  • function test_placeholder_parsing

    A unit test function that validates the placeholder parsing functionality of the HybridResponseHandler class by testing its ability to extract and parse graphic placeholders from formatted text.

    File: /tf/active/vicechatdev/e-ink-llm/test_hybrid_mode.py

    testing unit-test placeholder-parsing text-processing graphics

  • class GraphicType

    An enumeration class that defines the types of graphics that can be generated in the system.

    File: /tf/active/vicechatdev/e-ink-llm/graphics_generator.py

    enum enumeration graphics types constants

  • class DiagramGenerator

    A class that generates various types of diagrams including flowcharts, process flows, and network diagrams using matplotlib and networkx, returning base64-encoded PNG images.

    File: /tf/active/vicechatdev/e-ink-llm/graphics_generator.py

    diagram-generation visualization flowchart network-diagram matplotlib

  • class IllustrationGenerator

    A class that generates educational illustrations and technical drawings for mathematical and scientific concepts using matplotlib and programmatic rendering.

    File: /tf/active/vicechatdev/e-ink-llm/graphics_generator.py

    illustration educational graphics matplotlib visualization

  • class GraphicsGenerator

    GraphicsGenerator is a coordinator class that orchestrates the generation of different types of graphics (charts, diagrams, illustrations, and sketches) by delegating to specialized generator classes.

    File: /tf/active/vicechatdev/e-ink-llm/graphics_generator.py

    graphics visualization coordinator async chart-generation

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