monish563/NU-KIOSK-API
0
1"""2Core package for the CS Kiosk prototype.3 4The project follows a modular layout inspired by Satyrn:5 6- ``backend.data``: catalog registry, data sources, and utilities.7- ``backend.tools``: analytic blueprints, analysis engine, conversation runtime helpers.8- ``backend.providers``: LLM clients/adapters and shared responders.9"""10 11from .data import (12 DataCatalog,13 EntityRecords,14 RelationshipDefinition,15 load_default_catalog,16 DataSource,17 CSVSource,18 FeedListSource,19 default_sources,20 canonicalize_name,21 generate_name_variants,22 tokenize_name,23)24from .tools import (25 Blueprint,26 BlueprintResult,27 AnalysisContext,28 Fact,29 FacultyByTopicBlueprint,30 LocationBlueprint,31 CenterBlueprint,32 AdvisorshipBlueprint,33 StaffSupportBlueprint,34 UpcomingEventsBlueprint,35 OfficeHoursBlueprint,36 PersonLookupBlueprint,37 AnalysisEngine,38)39from .providers import (40 BaseLLM,41 ChatMessage,42 LLMResponse,43 ProviderConfig,44 ToolCall,45 EchoProvider,46 OpenAIChat,47 ClaudeProvider,48 GeminiGenerative,49)50from .responders import Responder, LLMResponder51from . import mcp52 53__all__ = [54 # Data layer55 "DataCatalog",56 "EntityRecords",57 "RelationshipDefinition",58 "load_default_catalog",59 "DataSource",60 "CSVSource",61 "FeedListSource",62 "default_sources",63 "canonicalize_name",64 "generate_name_variants",65 "tokenize_name",66 # Tools layer67 "Blueprint",68 "BlueprintResult",69 "AnalysisContext",70 "Fact",71 "FacultyByTopicBlueprint",72 "LocationBlueprint",73 "CenterBlueprint",74 "AdvisorshipBlueprint",75 "StaffSupportBlueprint",76 "UpcomingEventsBlueprint",77 "OfficeHoursBlueprint",78 "PersonLookupBlueprint",79 "AnalysisEngine",80 # LLM layer81 "BaseLLM",82 "ChatMessage",83 "LLMResponse",84 "ProviderConfig",85 "ToolCall",86 "EchoProvider",87 "OpenAIChat",88 "ClaudeProvider",89 "GeminiGenerative",90 "Responder",91 "LLMResponder",92 "mcp",93]94