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@sqzrDev sqzrDev released this 28 Apr 14:57
v1.0.2_en
ec78920

BIBIM v1.0.2

Release Date: 2026-04-28

What's New

Multi-Provider LLM Support (BYOK)

You can now choose any of 4 models in Settings — pick the one that fits your account and budget.

Model Provider Sample cost / request Notes
Claude Sonnet 4.6 ⭐ Anthropic ~$0.04 Recommended balance
Claude Opus 4.7 Anthropic ~$0.20 Top quality, agentic tasks
GPT-5.5 OpenAI ~$0.08 Multilingual, strong tooling
Gemini 3.1 Pro Google ~$0.03 Lowest cost, biggest context
  • Each provider has its own key field in Settings (Anthropic / OpenAI / Google).
  • Models without a registered key are greyed out with a tooltip that tells you which key to add.
  • Adding a new key activates that provider's models instantly — no restart needed.
  • Existing 1.0.1 users: your saved Anthropic key migrates automatically. A .bak of the previous config is kept next to it.

API Key Setup Guide Link

A new "📖 View API Key Setup Guide" button at the top of Settings opens a step-by-step Notion guide for getting keys from Anthropic / OpenAI / Google. The link is language-aware (KR or EN).

30–40% Token Reduction

The code-generation pipeline is now substantially leaner — same task, fewer tokens. Typical sessions see ~30–40% input-token reduction, and heavy users (100+ requests/month) save 35–42% on cost.

Highlights:

  • Anthropic prompt caching enabled: cache_control: ephemeral markers on the system prompt + tool definitions. Within the 5-minute cache window, the prefix portion is billed at the cached rate ($0.30/1M — 90% off).
  • Cache-effectiveness telemetry: cache_read_input_tokens and cache_creation_input_tokens are now tracked per call and per session in bibim_v3_debug.txt, including a session cache hit ratio.
  • Roslyn compile retry pruning: previously failed code attempts no longer accumulate across retries. Saves ~700 tokens per retry round.
  • Local RAG slimmed: search_revit_api result verbosity reduced (TopK 5→3, chunk 3000→1200 chars, members 60→30). No effect on code-generation quality.
  • Heuristic planner gate: short greetings/acks ("hi", "ok", "thanks") now skip the planner LLM call entirely — saves ~2,500 tokens per skip.
  • Category question templates extracted: the planner's ~1,800-token category-question library is now a compact checklist.
  • Long-session stabilisation: chat history window 20→10 turns, with dropped turns collapsed into a synthetic recap. Context-length errors down ~70%.
  • Context tools shipped on demand: get_view_info, get_selected_elements, get_element_parameters, get_family_types, get_project_levels are only included when the user message hints at relevant context.
  • FileOutputRules conditional: the ~700-token file-safety block is only attached to actual file-output tasks (PDF/DWG/CSV/etc.), not to in-model edits.

LLM Reliability Improvements

  • Gemini JSON-mode for the planner: responseMimeType: "application/json" is now enforced on Gemini planner calls. Fixes a regression where Gemini's invalid JSON output caused the assistant to dump raw C# code into the chat bubble instead of running the structured task flow.
  • Planner parse-failure retry: if the planner returns malformed JSON, BIBIM retries once with an explicit "your previous response was not valid JSON" nudge. Both attempts must fail before falling back to direct chat.
  • GPT selection-priority rule: when the user uses pointing language ("these doors", "the selection", "이 도어들"), GPT is now explicitly told to use uidoc.Selection.GetElementIds() instead of falling back to a model-wide FilteredElementCollector. Claude already followed this pattern.

Multi-provider hotfixes (caught in real-user testing)

Three latent bugs introduced during the multi-provider work — all three providers were dropping the task → question → codegen flow. Fixed in one go:

  • Anthropic 400 fix: tool_result blocks carried a name field (kept for the Gemini adapter), which Anthropic's strict schema validator rejected, killing the tool loop on the second call onward. AnthropicProvider now strips the field before send.
  • OpenAI 400 fix: OpenAI's Responses API rejects text.format=json_object mode unless an input message contains the literal word "json". Added a one-line [Output format: respond with JSON only…] directive at the end of the planner user message.
  • Gemini model swap: gemini-3.1-pro-preview-customtools (an agent-and-tool-first variant) → gemini-3.1-pro-preview (vanilla). The customtools variant prioritises function-calling output and silently ignored JSON mode in the planner case. Google's own guidance: use vanilla when <50% of requests involve tool calling.
  • Auto-migration: existing configs holding the old -customtools model id are rewritten to vanilla on next launch (.bak backup kept). No manual re-selection in Settings required.

Model selector UX

Each model in the Settings selector now shows a response-speed indicator (⚡) so you can compare at a glance:

  • ⚡⚡⚡ Claude Sonnet 4.6 (fast)
  • ⚡⚡ Claude Opus 4.7, GPT-5.5 (medium)
  • ⚡ Gemini 3.1 Pro (slow — deeper reasoning may take longer)

Hover the ⚡ icon for a localised tooltip.

Loading-State Bug Fix

A 429 / network / billing error from the LLM provider used to leave the chat panel stuck on "Generating response…" forever. Fixed: the progress UI now always clears on error so you can try again or switch models immediately.

Bug Fixes / Improvements

  • Frontend Saved toast now reports the correct provider (Anthropic / OpenAI / Gemini) when multiple keys are saved in sequence.
  • Settings panel scrolls when content overflows on smaller monitors.
  • Cleaner log lines: provider + model + cache hit ratio are now stamped on every LLM call.
  • Streaming chat path no longer drops cache_creation_input_tokens (first-message cache-write cost was previously logged as 0).
  • Removed unused GeminiRagService dead code (local BM25 RAG has been the only RAG since v1.0.1).

Requirements

Source

github.com/SquareZero-Inc/bibim-revit

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