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Search Results for "optimization"

Found 39 matching component(s)

  • class OneCo_hybrid_RAG

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/OneCo_hybrid_RAG copy.py

    class oneco_hybrid_rag

  • class OneCo_hybrid_RAG_v1

    A class named OneCo_hybrid_RAG

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

    class oneco_hybrid_rag

  • class OneCo_hybrid_RAG_v2

    A class named OneCo_hybrid_RAG

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

    class oneco_hybrid_rag

  • function conversation_example

    Demonstrates a multi-turn conversational RAG system with chat history management, showing how follow-up questions are automatically optimized based on conversation context.

    File: /tf/active/vicechatdev/docchat/example_usage.py

    RAG conversational-ai chat-history multi-turn-conversation context-management

  • function build_document_tree_lazy

    Builds a single-level document tree structure for lazy loading, scanning only immediate children of a target directory without recursively loading subdirectories.

    File: /tf/active/vicechatdev/docchat/app.py

    file-system directory-tree lazy-loading document-management file-browser

  • function api_document_tree

    Flask API endpoint that returns a hierarchical document tree structure from a configured document folder, supporting lazy loading and full expansion modes for efficient navigation and search.

    File: /tf/active/vicechatdev/docchat/app.py

    flask api rest-endpoint document-management tree-structure

  • class DocChatRAG

    Main RAG engine with three operating modes: 1. Basic RAG (similarity search) 2. Extensive (full document retrieval with preprocessing) 3. Full Reading (process all documents)

    File: /tf/active/vicechatdev/docchat/rag_engine.py

    class docchatrag

  • function get_adjusted_top_k

    Calculates an adjusted top_k value for multi-language search operations by multiplying the base value by the number of languages to ensure sufficient results per language.

    File: /tf/active/vicechatdev/docchat/config.py

    multi-language search top-k result-scaling internationalization

  • function test_incremental_indexing

    Comprehensive test function that validates incremental indexing functionality of a document indexing system, including initial indexing, change detection, re-indexing, and force re-indexing scenarios.

    File: /tf/active/vicechatdev/docchat/test_incremental_indexing.py

    testing incremental-indexing document-indexing integration-test file-system

  • class OneCo_hybrid_RAG_v3

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/vice_ai/hybrid_rag_engine.py

    class oneco_hybrid_rag

  • function batch_create_nodes

    Creates multiple Neo4j graph database nodes in batches for improved performance, automatically generating UIDs and timestamps for each node.

    File: /tf/active/vicechatdev/CDocs/db/db_operations.py

    neo4j graph-database batch-processing bulk-insert database

  • function cache_result

    A decorator factory that creates a caching decorator for function results with a configurable time-to-live (TTL). Currently a placeholder implementation that passes through function calls without actual caching.

    File: /tf/active/vicechatdev/CDocs/controllers/__init__.py

    decorator caching performance memoization ttl

  • function test_workflow_progress_structure

    A test function that validates the structure and behavior of a workflow progress tracking system for SQL query processing, including progress states, step transitions, and completion data.

    File: /tf/active/vicechatdev/full_smartstat/test_enhanced_progress.py

    testing workflow progress-tracking sql validation

  • function test_json_serialization

    A test function that validates JSON serialization and deserialization of workflow data structures containing status, progress, and results information.

    File: /tf/active/vicechatdev/full_smartstat/test_enhanced_progress.py

    testing json serialization deserialization workflow

  • function enhanced_sql_workflow

    Flask route handler that initiates an enhanced SQL workflow with iterative optimization, executing data extraction and analysis in a background thread while providing real-time progress tracking.

    File: /tf/active/vicechatdev/full_smartstat/app.py

    flask api-endpoint sql-workflow async-processing background-thread

  • function enhanced_workflow_progress

    Flask route handler that retrieves and returns the current progress status of an enhanced SQL workflow, including step completion, progress percentage, and final results if completed.

    File: /tf/active/vicechatdev/full_smartstat/app.py

    flask api-endpoint progress-tracking workflow status-monitoring

  • class EnhancedSQLWorkflow

    Enhanced SQL workflow with iterative optimization

    File: /tf/active/vicechatdev/full_smartstat/enhanced_sql_workflow.py

    class enhancedsqlworkflow

  • class IterationResult

    A dataclass that encapsulates the complete results of a single iteration in a two-pass process, including table selection, SQL generation, and execution outcomes.

    File: /tf/active/vicechatdev/full_smartstat/two_pass_sql_workflow.py

    dataclass result-container iteration-tracking sql-execution query-generation

  • class StatisticalAnalysisService

    Main service for statistical analysis orchestration

    File: /tf/active/vicechatdev/full_smartstat/services.py

    class statisticalanalysisservice

  • class SQLQueryGenerator

    Generates SQL queries based on user requests and database schema

    File: /tf/active/vicechatdev/full_smartstat/sql_query_generator.py

    class sqlquerygenerator

  • function demonstrate_sql_workflow_v1

    Demonstrates the enhanced SQL workflow for the SmartStat system by loading configurations, initializing the SQL query generator, testing natural language to SQL conversion, and displaying schema analysis.

    File: /tf/active/vicechatdev/full_smartstat/demo_enhanced_sql_workflow.py

    demonstration testing sql-generation natural-language-processing database-schema

  • function get_dbo_establishment_with_references_municipalities_reference_municipalities

    Retrieves Reference_Municipalities nodes from a Neo4j graph database that are connected to a specific dbo_Establishment node via a REFERENCES_MUNICIPALITIES relationship.

    File: /tf/active/vicechatdev/neo4j_schema/neo4j_python_snippets.py

    neo4j graph-database cypher-query relationship-traversal establishment

  • function demonstrate_sql_workflow

    Demonstrates the enhanced SQL workflow for the SmartStat system by loading configurations, initializing SQL query generator, testing natural language to SQL conversion, and displaying schema analysis.

    File: /tf/active/vicechatdev/smartstat/demo_enhanced_sql_workflow.py

    demonstration sql-generation natural-language-processing database-schema testing

  • function group_select

    Recursively groups a list of key tuples into a nested dictionary structure to optimize indexing operations by avoiding duplicate key lookups.

    File: /tf/active/vicechatdev/patches/util.py

    data-structures optimization indexing grouping recursion

  • class ndmapping_groupby

    A parameterized function class that performs groupby operations on NdMapping objects, automatically using pandas for improved performance when available, falling back to pure Python implementation otherwise.

    File: /tf/active/vicechatdev/patches/util.py

    groupby data-processing ndmapping pandas multi-dimensional

  • function cross_index

    Efficiently indexes into a Cartesian product of iterables without materializing the full product, using a linear index to retrieve the corresponding tuple of values.

    File: /tf/active/vicechatdev/patches/util.py

    cartesian-product indexing combinatorics memory-efficient itertools-alternative

  • class OneCo_hybrid_RAG_v4

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/datacapture_backup_16072025/OneCo_hybrid_RAG.py

    class oneco_hybrid_rag

  • class OneCo_hybrid_RAG_v5

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/data_capture_backup_18072025/OneCo_hybrid_RAG.py

    class oneco_hybrid_rag

  • function validate_schema

    Validates that a Neo4j database schema is correctly configured by checking for required constraints, node labels, and indexes.

    File: /tf/active/vicechatdev/CDocs single class/db/schema_manager.py

    neo4j database schema-validation graph-database constraints

  • class Document_v1

    Document class represents a reMarkable document file, extending the Item class to provide document-specific operations like content extraction, uploading, and rendering with annotations.

    File: /tf/active/vicechatdev/rmcl/items.py

    document remarkable pdf epub annotation

  • 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 HybridPDFGenerator

    A class that generates hybrid PDF documents combining formatted text content with embedded graphics, optimized for e-ink displays.

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

    pdf-generation document-creation reportlab hybrid-content graphics-embedding

  • class RemarkableEInkProcessor

    Enhanced E-Ink LLM Processor that extends EInkLLMProcessor with reMarkable Cloud integration, enabling file processing from both local directories and reMarkable Cloud storage.

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

    e-ink llm file-processing remarkable cloud-integration

  • 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

  • function main_v68

    Async entry point for an E-Ink LLM Assistant that processes handwritten/drawn content using AI vision models, supporting local files, reMarkable Cloud, and OneDrive integration.

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

    async cli entry-point file-processing ai-vision

  • 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_improvement_comparison

    A demonstration function that displays a before-and-after comparison of response formatting improvements, showing the evolution from verbose to compact, symbol-rich formatting optimized for e-ink displays.

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

    demonstration comparison formatting e-ink console-output

  • class EInkStyler

    A utility class providing styling configurations and color palettes optimized for e-ink displays with high contrast and minimal grayscale variations.

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

    e-ink styling visualization matplotlib color-palette

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