DeepTutor v1.3.6 Release Notes

Release Date: 2026.05.03

v1.3.6 focuses on making model routing explicit across DeepTutor. Users can
choose configured LLM profiles from chat and TutorBot flows, runtime services
resolve those choices without leaking provider secrets, and RAG/knowledge-base
index handling is more defensive when persisted embeddings are invalid.

Highlights

Catalog-Based Model Selection

• Chat can target a configured model - unified chat turns now carry a
  profile_id and model_id selection through the WebSocket payload, session
  preferences, turn snapshots, and regenerate flows.
• Settings exposes safe LLM options - the new settings options endpoint
  returns display-ready provider/model choices while omitting credentials and
  connection secrets from the response.
• Runtime model overrides are scoped per turn - selected profiles are
  resolved through the provider catalog for the active request without writing
  temporary choices back to disk or changing global defaults.
• Model-selector UI is shared - chat and TutorBot screens use the same
  configured-model selector, with localized labels and system-default handling.

TutorBot Model Control

• Bots can persist model selections - TutorBot create/update flows now accept
  llm_selection, validate it against the configured catalog, and store it with
  each bot.
• Running bots can reload their LLM - changing a bot's model updates the
  active agent loop instead of requiring a full bot restart.
• Recent bot history is steadier - TutorBot history assembly now sorts by
  message timestamp with stable tie-breaking before taking the latest context.
• Bot chat route changes are cleaner - the web chat page cancels in-flight
  bot requests and resets transient reasoning state when switching bots.

RAG and Knowledge Reliability

• Invalid vectors trigger rebuilds - re-indexing no longer treats a matching
  document signature as reusable when the existing vector store fails embedding
  validation.
• Full rebuilds use fresh version directories - complete knowledge-base
  rebuilds write to a new flat index version while leaving failed old storage
  available for inspection.
• RAG tool logs can stream to clients - retrieval runs can forward captured
  INFO-level process logs as raw tool events when an event sink is available.
• Knowledge health checks recognize bad embeddings - invalid persisted
  vectors are surfaced earlier instead of producing opaque search failures.

Provider and Launch Fixes

• OpenAI Responses token limits are normalized - Responses API calls now map
  chat-style max_completion_tokens and max_tokens to max_output_tokens,
  fixing the SDK error reported for newer OpenAI models in #437.
• Azure and OpenAI-compatible paths share the mapping - both streaming and
  non-streaming Responses API routes use the same conversion helper.
• Launch ports come from .env and environment variables - setup and launch
  helpers now keep backend/frontend port behavior aligned around the project
  .env file instead of the older runtime settings JSON.

Web UX Polish

• Skill names validate before save - the Skills editor slugifies names,
  flags invalid input inline, and prevents silent API failures for uppercase
  letters, spaces, underscores, or other unsupported characters.
• Skill editor modals are opaque across themes - the editor now uses the
  page background token, avoiding text bleed-through in translucent themes.
• Space navigation is easier to scan - Space mini-navigation, notebook,
  question-bank, skills, and session-list spacing were tightened with clearer
  card and divider treatment.

Tests

• Added model-selection service tests for safe option listing, active markers,
  invalid profile/model rejection, and non-mutating catalog overrides.
• Added unified WebSocket turn-runtime tests for persisted LLM selections,
  invalid selections, model switching, snapshots, and regenerate behavior.
• Added TutorBot API and manager tests for llm_selection persistence,
  validation, runtime reload, and default-model behavior.
• Added settings, provider-runtime, and LLM-config tests for scoped catalog
  selection and per-turn config precedence.
• Added RAG and knowledge-router tests for invalid vector stores, re-index
  rebuild decisions, and storage version resolution.
• Added OpenAI Responses converter tests for token-limit aliases, precedence,
  None filtering, and input immutability.
• Added frontend slug tests for skill-name normalization and validation.

Upgrade Notes

• Chat and TutorBot clients that want explicit model routing should send
  llm_selection as { "profile_id": "...", "model_id": "..." }. Omitting it
  continues to use the configured system default.
• TutorBot configuration files may now contain llm_selection. Existing bot
  configs without that field continue to load, and legacy model values remain
  usable as model-name overrides.
• Launch ports should be configured in .env or process environment variables
  (BACKEND_PORT / FRONTEND_PORT). The old data/user/settings/env.json
  port block is no longer used as a launch-port source.
• Knowledge bases with stale or invalid persisted vectors may rebuild on the
  next re-index even when document signatures have not changed.
• Skill names are now normalized and validated as lowercase slugs of up to 64
  characters using letters, numbers, and hyphens.

Full Changelog: v1.3.5...v1.3.6