As of end of Phase 4, only _send_minimax has a working tool-call loop.
Phase 3 (Grok, Llama) and Phase 2 (Qwen) entry points are single-shot;
they call send_openai_compatible once and return without executing
tool_calls. If the user notices 'tool execution doesn't work for
Qwen/Grok/Llama' after Phase 5 ships, the fix is to lift the tool
loop into a shared run_with_tool_loop() helper that wraps
send_openai_compatible. The 4 existing vendors (_send_anthropic /
_send_gemini / _send_gemini_cli / _send_deepseek) already have the
same inline duplication, so the lift would also help those.
This is a follow-up track, not in scope for qwen_llama_grok_integration_20260606.
Grok's own recommendation (consulted 2026-06-11):
'xAI (Grok) | xAI official OpenAI-compatible (https://api.x.ai/v1) |
Fully compatible and clean. Supports Grok-2 + Grok-2-Vision. No
meaningful unique native surface lost by using the compatible
endpoint.'
This REVERSES the earlier 'xAI native' correction. The OpenAI-
compatible approach for Grok is the canonical full-featured path;
the implementation in Phase 3 (OpenAI SDK with base_url=https://api.x.ai/v1
+ send_openai_compatible helper) is correct as-is.
Updates to the spec:
1. §3.1.1: replaced the 'use xAI native' decision with the confirmed
per-vendor table. Qwen=Native, Grok=OpenAI-Compatible (per Grok's
own confirmation), MiniMax=OpenAI-Compatible, DeepSeek=OpenAI-
Compatible, Ollama=OpenAI-Compatible-in-v1 (native in v2),
Meta Llama API=Native (new 4th backend, follow-up), Gemini=Native
(follow-up), Anthropic=Native (follow-up). Also added Grok's
recommended v2 matrix field expansion: audio, video, grounding,
computer_use, local, reasoning/extended_thinking, web_search,
x_search, code_execution, file_search, mcp_support, structured_output.
2. §4.3: reverted from 'Grok via xAI (Native REST API)' back to
'Grok via xAI (OpenAI-Compatible) - confirmed 2026-06-11'. The
implementation does NOT need a native refactor; the OpenAI SDK
at https://api.x.ai/v1 is the canonical approach. Removed the
earlier 'caching: true' entry from the registry (since the
OpenAI-compat shim doesn't expose prompt_cache_key) and the
'no persistent client' state struct (back to the OpenAI SDK
pattern).
3. §13.1.B: renamed from 'Native Vendor APIs' to 'Llama Native APIs
(Ollama native + Meta Llama API)' and removed the Grok native
refactor item (Grok says OpenAI-compat is fine). Kept the Ollama
native + Meta Llama API items + matrix expansion. Clarified that
Grok tests do NOT need rewriting; only Llama tests get 2 more
(native Ollama, Meta Llama API).
Net effect: the Phase 3 work that just shipped (Grok+Llama Green
using OpenAI-compat shim) is CORRECT as-is. The implementation
matches Grok's actual recommendation. No code rollback needed.
Three additions to the spec, per the user's architectural correction
in this session:
1. NEW section 3.1.1: 'Architectural principle: Use the best API per
vendor' — explains why the OpenAI-compatible shim loses vendor-
specific features (xAI: prompt_cache_key, reasoning_effort, server-
side tools, cost_in_usd_ticks; Ollama: think param, images array,
thinking field, structured outputs) and states the principle:
'use each vendor's native SDK or REST API when one exists, falling
back to OpenAI-compatible only when no native option exists.'
Also notes that the capability matrix IS the aggregate tracker;
future native features go into the matrix, and the GUI filters
based on it (no per-vendor UI branches).
2. UPDATED section 4.3 (Grok): 'Grok via xAI (Native REST API)' — was
'OpenAI-Compatible'. Now specifies two native endpoints
(/v1/chat/completions and /v1/responses), the native features that
matter, the updated capability registry (caching=true for Grok
via prompt_cache_key), and a 'Phase 3 placeholder behavior' note
that this track's Phase 3 ships the OpenAI-compatible Grok as a
placeholder. The native refactor is deferred to follow-up B.
3. UPDATED section 13.1: added follow-up track B 'Native Vendor APIs
(post-OpenAI-compatible-placeholder)' which documents:
- Grok → xAI native REST
- Llama (Ollama) → native /api/chat
- Llama (Meta Llama API) → new 4th backend (deferred pending
verification of Meta's API spec; llama.developer.meta.com/docs/overview
returned 400 on fetch this session)
- Capability matrix expansion (web_search, x_search, code_execution,
file_search, mcp_support, reasoning_effort, structured_output)
- Test rewrites (mock requests.post instead of chat.completions.create)
This is a docs-only commit; no code changes. The Phase 3 Green work
continues with the OpenAI-compatible approach as planned in the
existing Red tests (t3.3 Grok + t3.14 Llama), and the follow-up track
B handles the native refactor when prioritized.
New track for prior-session sepia tint:
- 3 new theme slots (prior_session_bg, prior_session_tint, prior_session_amount)
- per-palette state dict mirroring _brightness/_contrast/_gamma
- apply_prior_tint helper (float-only math per user requirement)
- 6 prior-session render sites wrapped (2 bubble_vendor swaps + 4 tint wraps)
- Theme Settings panel slider with persistence
Code-block tonemap fix is OUT OF SCOPE (upstream imgui_bundle 1.92.5
API only exposes 4-value PaletteId enum, no per-instance struct).
See spec §1.1.1 and design doc 'Honest constraint' section.
These were authored at track start but missed by the final-state
commit. They are the brief 1-2 page design intent and executable
plan for the docs sync track. The closing report at
docs/reports/docs_sync_test_era_20260610.md summarizes the actual
17-commit execution.
- state.toml: status active->completed, all 25 tasks marked complete
with commit SHAs, all 4 phases checkpointed
- metadata.json: status active->shipped, 17-commit list, all 9
verification criteria flipped to DONE
The user said (verbatim): "On number 1. I love the idea and definitely
see poitental." This commit creates a full track that promotes the
ASCII-sketch UX ideation workflow
(docs/reports/ascii_sketch_ux_workflow_20260608.md, 340 lines) to
a real track with a concrete first target.
The track complements (does not replace) the existing
manual_ux_validation_20260302 track (which is a general UX review
track; this 2026-06-08 track is *focused* on the ASCII-sketch
workflow specifically).
Files (5 total, ~52KB, 12,000+ words):
- spec.md (186 lines, 9 sections) - track design, 5 open
questions, first target analysis, SSDL cross-reference
- plan.md (~280 lines, 4 phases, 21 tasks) - TDD-style with
WHERE/WHAT/HOW/SAFETY annotations
- metadata.json (~120 lines) - structured metadata, 5 open
questions with defaults, 5 SSDL principles available
- state.toml (~95 lines) - per-task tracking + phase status
- index.md (~50 lines) - track context + related docs
Key design decisions captured:
1. Two distinct vocabularies are conflated at first glance:
- GUI ASCII (the workflow) for panel sketches
- SSDL (computational shapes digest) for internal code sketches
Spec §2.6 makes the distinction explicit; both are useful for
this track (GUI ASCII for Phase 2 design; SSDL for Phase 3
internal refactoring documentation).
2. The 5 open questions from the workflow report (Q1 vocabulary,
Q2 comparison policy, Q3 storage location, Q4 tooling,
Q5 frequency) are documented with sensible defaults in
spec.md §2.1-2.5 and metadata.json. The user can override
any of them; defaults pre-stage the work.
3. First target is src/gui_2.py:3770 render_discussion_entry
(Discussion Hub per-entry panel). Rationale:
- Most-edited surface (every AI/user message)
- User has strong opinions (per nagent_review_20260608 3 rounds
of corrections)
- 23-op matrix A1-A7 is the source of truth
- ImGui layout maps cleanly to ASCII
- SSDL defusing techniques can guide the internal refactoring
4. 4 phases: 1=resolve 5 questions, 2=execute workflow on first
target (1-3 ASCII rounds), 3=implement per design contract
(TDD with 7 test files for A1-A7 operations),
4=document the pattern + propose 5-7 next targets.
Cross-references added throughout:
- docs/reports/computational_shapes_ssdl_digest_20260608.md
(the SSDL digest, with explicit "this is a different vocabulary
for a different purpose" note in spec §2.6)
- docs/reports/ascii_sketch_ux_workflow_20260608.md (the workflow)
- docs/guide_discussions.md (the 23-op matrix A1-A7)
- conductor/tracks/nagent_review_20260608/ (the source of the
user's editable-discussion corrections)
- conductor/tracks/manual_ux_validation_20260302/ (complementary
general UX review track)
- conductor/tracks/chunkification_optimization_20260608_PLACEHOLDER/
(the contingency track; referenced in spec §2.6 SSDL cross-ref)
No code modified. Track is active; Phase 1 (5 user-questions) is
the current phase. User-confirmed worth doing in the prior turn.
The user's third correction this session changed the framing
from "build a stateful C extension" to "wait for a hard constraint,
then build a request/response blob pipeline." This commit creates
a 1-page contingency document (no plan.md, no implementation)
that captures:
- The threshold: "only worth it under a hard constraint that
no existing Python package can solve"
- The shape when activated: subprocess-launch C11 binary with
request/response blob wire format (NOT stateful CPython C
extension)
- The 2 cited candidates (markdown parsing into aggregate markdown,
context snapshot processing) are NOT currently bottlenecks per
src/aggregate.py:380-454 (pure-Python string concat, zero
third-party markdown deps in pyproject.toml:6-27) and
src/history.py:1-141 (bounded ~500KB at 100-snapshot capacity,
debounced)
- The SSDL digest's Technique 5 "Assume-away (Xar)" in §2.2 +
"Xar-style chunked arrays" recommendation in §5.2 pre-support
this track
Files (4 total, 227+ lines of contingency document):
- conductor/tracks/chunkification_optimization_20260608_PLACEHOLDER/spec.md
- conductor/tracks/chunkification_optimization_20260608_PLACEHOLDER/metadata.json
- conductor/tracks/chunkification_optimization_20260608_PLACEHOLDER/state.toml
- conductor/tracks/chunkification_optimization_20260608_PLACEHOLDER/index.md
Cross-references added:
- docs/reports/computational_shapes_ssdl_digest_20260608.md (the
SSDL digest is the theoretical foundation; explicitly cited in
the spec's §6.1 "SSDL alignment" and in metadata.json external)
- docs/reports/c11_python_interop_assessment_20260608.md (the v1+v2
assessment; explicitly cited in spec's §6 See Also)
No code modified. Track does NOT appear in the active queue
of conductor/tracks.md; appears in the Backlog / Contingency
section as a reference, not a commitment.
Activation criteria (per metadata.json):
1. Profiling shows a real bottleneck in a target code path
2. The bottleneck cannot be solved with existing Python packages
3. The user explicitly approves activation
Without all 3, this track stays deferred. Default action is don't.
The user specified that the code_path_audit_20260607 track should run
AFTER the 4 foundational tracks complete (qwen_llama_grok,
data_oriented_error_handling, data_structure_strengthening,
mcp_architecture_refactor). This commit formalizes that timing
and grounds the audit's analytical framing in the 5 sources loaded
into context on 2026-06-08.
3 surgical additions to the spec/plan, no task changes:
1. Post-4-tracks timing (new section in spec.md §"Timing", plus
a "Timing" callout in plan.md's opening):
- The 4 tracks will significantly reshape src/ai_client.py,
src/mcp_client.py, src/app_controller.py, and
src/type_aliases.py
- Running the audit on pre-refactor code would produce a
report that's stale on day 1
- The post-4-tracks timing ensures the audit grounds
optimization decisions for the *resulting* architecture
- Pre-flight check: verify all 4 tracks are [x] completed
in conductor/tracks.md before starting this track
2. Analytical framing (new section in spec.md §"Analytical Framing
(5-source lens)"):
- Maps each of the 5 sources (Fleury taxonomy + Fleury
combinatoric + Muratori Big OOPs + Reece Assuming + user's
chunk ideation) to specific audit-time heuristics
- 4 concrete heuristics: effective-codepath count,
entity-hierarchy fingerprint, assumed-too-much detector,
chunkification candidates
- The heuristics shape REPORT INTERPRETATION, not the
static cost model (which stays data-grounded in
EXPENSIVE_THRESHOLD + per-class weights)
3. See Also cross-references in spec.md (6 new entries):
- nagent_review Pitfalls #2 and #4 (provider history
globals + stateful singleton)
- wo84LFzx5nI Big OOPs transcript (full text, 4310
segments, 200KB; loaded 2026-06-08)
- i-h95QIGchY Assuming transcript (full text, 3719
segments, 162KB; loaded 2026-06-08)
- ed_chunk_data_structures_20260523.md (5-image archive
of user's chunk ideation, 19KB; saved 2026-06-08)
- computational_shapes_ssdl_digest_20260608.md (the SSDL
digest that synthesizes the 4-source computational-shapes
thinking; the audit's tree/mermaid outputs ARE
computational-shape visualizations)
4. tracks.md entry updated to include the spec/plan links and
a brief status note that the audit is post-4-tracks.
5. plan.md has a "Timing" callout at the top stating the 4
tracks must ship before the plan executes.
No code modified. The audit's tasks (Phases 1-6) are unchanged
in structure; the new sections only add analytical context
and timing constraints.