Keeps the ASCII layout map previews, baseline summaries, and state mutation blocks, while cleanly removing Threading & Safety sections and replacing DAG references with SSDL Shape notations.
Add SQLite-style inline docstrings to render_ai_settings_hub, render_agent_tools_panel, and render_diagnostics_panel under simplified granularity per user request. Mark track sqlite_docs_gui_2_20260612 as complete.
The 6 error-classifier functions in ai_client.py, openai_compatible.py,
and qwen_adapter.py now return ErrorInfo (data-oriented) instead of
ProviderError. Each takes a source: str parameter for telemetry
provenance. ProviderError class is still used in production code paths
(Task 3.4) and will be removed in Task 3.7.
Strictly additive: existing _resolve_and_check, read_file, list_directory,
and search_files are unchanged. The new variants return Result[Path] or
Result[str] using the data-oriented ErrorInfo/ErrorKind convention.
The matrix has v2 fields (reasoning, web_search, x_search)
populated for the old vendors (minimax-M2.5/M2.7, grok-*),
but the send functions didn't consult them. This commit
makes the code path actually USE the matrix:
_send_minimax: gate reasoning_extractor on caps.reasoning
(was unconditional; now skipped for non-reasoning models
to avoid useless getattr calls)
_send_grok: populate OpenAICompatibleRequest.extra_body with
search_parameters when caps.web_search or caps.x_search is
True. caps.web_search -> {mode: auto}; caps.x_search ->
{sources: [{type: x}]} per the xAI Live Search spec
OpenAICompatibleRequest: added extra_body field. Wired
through send_openai_compatible (passed as extra_body kwarg
to client.chat.completions.create).
Also fixed 2 latent bugs in _send_minimax surfaced by the
new tests: the function was missing 'tools' variable
(NameError) and 'stream_callback' parameter. These are
pre-existing bugs masked by mock-based tests that don't
exercise the actual call path.
Also cancelled t5_6/7/8 (the invented 'deferred tool-loop
conversion' work). The 3 vendors (anthropic, gemini,
deepseek) use vendor-specific call paths. Their inline
loops are NOT defects. The '3-5 days' / '1-2 weeks'
estimates were made up by the agent. The audit script's
DEFERRED_VENDORS exclusion is permanent.
Tests:
- 2 new grok tests: web_search and x_search populate
extra_body correctly
- 2 new minimax tests: reasoning_extractor used/omitted
based on caps.reasoning
- 122/122 vendor+tool+provider+import-isolation tests pass
(no regressions; +4 new tests this commit)
- 3 audit scripts pass
Phase 5 t5_4 (UI adaptations for 11 v2 fields): the simplest
honest adaptation — render small colored badges for the 11
v2 fields where the active vendor+model supports them. Each
badge has a tooltip showing the field name.
The 11 fields:
reasoning, structured_output, code_execution, web_search,
x_search, file_search, mcp_support, audio, video,
grounding, computer_use
A new module-level function _render_v2_capability_badges(caps)
is added to src/gui_2.py (per the HARD RULE on no new
src/<thing>.py files). It's called from render_provider_panel
right after the existing '[Local]' badge (which uses the
runtime override for caps.local).
What this is NOT: a full UI for the 11 fields (per-field
toggles, panels, attachment buttons). Those are design-heavy
work and need their own track. This change gives the user
visibility into which capabilities the active vendor+model
supports, so they can make informed decisions about which
prompts/features to use.
For example, when the user selects qwen-audio, they'll see:
Provider: qwen [Local] Capabilities [Audio]
Which makes it obvious they can attach audio files.
Tests:
- 2 new tests in tests/test_vendor_capabilities.py:
* All 11 v2 fields are present in the helper (drift guard)
* Helper is a no-op on empty caps (no fields True)
- 118/118 vendor+tool+provider+import-isolation tests pass
(no regressions; +2 new tests this commit)
- 3 audit scripts pass
Updates per-model registry entries to populate the 12 v2
fields where the capability is genuinely supported:
minimax-M2.5/M2.7: reasoning=True (uses reasoning_details)
grok-2-vision: web_search=True, x_search=True (Live Search)
grok-2: web_search=True, x_search=True
grok-beta: web_search=True, x_search=True
llama-3.1-405b: reasoning=True (explicitly in model name)
qwen-long: caching=True (custom long-context chunking)
qwen-audio: audio=True (was 'deferred' in v1 notes)
Adds the runtime override helper:
_apply_runtime_caps_override(app, caps)
-> caps with local=True if app.current_provider=='llama'
AND _llama_base_url contains 'localhost' or '127.0.0.1'
The 'local' flag is the only v2 field that is runtime-state,
not a static per-model property (OpenRouter llama is cloud;
Ollama llama is local — same model name, different backend).
The override uses dataclasses.replace() to mutate the
frozen dataclass. Implemented in src/gui_2.py (per the
HARD RULE on no new src/*.py files).
The override is wired into App._get_active_capabilities()
so the GUI sees caps.local=True when the active backend
is Ollama and caps.local=False otherwise.
Also: cost panel in src/gui_2.py (per-tier + session-total
columns) now renders 'Free (local)' when caps.local=True
(both the per-tier cost column and the session-total line).
This is t3_7 (moved from Phase 3 per the user's request;
naturally belongs after t4_1 which adds caps.local).
Tests:
- 3 new tests in tests/test_vendor_capabilities.py:
* per-model population (reasoning, audio, caching, vision)
* runtime override for llama+localhost
* runtime override does NOT touch other vendors
- 107/107 vendor+tool+provider+import-isolation tests pass
(no regressions; +4 new tests this commit)
- 3 audit scripts pass
When the active vendor+model has caps.local=True (per the
v2 capability matrix), the provider panel now shows a green
' [Local]' badge next to the provider combo. The tooltip
shows the Ollama base URL (when the active provider is
llama; otherwise the bare 'Local backend' tooltip).
Implements t4_4 of qwen_llama_grok_followup_20260611
Phase 4. Future use: Phase 4 t3_7 (moved from Phase 3)
will use caps.local to render 'Free (local)' in the cost
column.
The badge uses theme.get_color('status_success') (same
green used by C_IN / C_NUM / other 'success' indicators).
Renders inside the existing render_provider_panel function
at src/gui_2.py:2308.
Verification:
- import src.gui_2 OK (no syntax errors)
- 44/44 vendor+capability+provider tests pass (no regressions)
- 4 audit scripts pass
When _llama_base_url is localhost/127.0.0.1, _send_llama now
calls _send_llama_native (the native /api/chat adapter)
instead of the OpenAI-compat path. The native adapter
supports Ollama's vendor-specific fields: think, images,
thinking.
Functions added (in src/ai_client.py, per the naming
convention HARD RULE on no new src/*.py files):
ollama_chat(model, messages, *, think='low', images=None,
tools=None, base_url=OLLAMA_DEFAULT_BASE_URL)
-> dict[str, Any]
_send_llama_native(md_content, user_message, base_dir,
file_items=None, discussion_history='',
stream=False, ...callbacks) -> str
OLLAMA_DEFAULT_BASE_URL: str = 'http://localhost:11434'
Implementation notes:
- requests loaded via _require_warmed('requests') (local
scope; preserves startup_speedup_20260606 invariant that
heavy SDKs are warmed on _io_pool, not imported at module
level)
- _send_llama dispatches based on 'localhost' in
_llama_base_url (same check already used by
_get_llama_cost_tracking at line 2500)
- Removed orphan def stub at the old _send_llama body (the
dead 'def _build_llama_request' that was overwritten by
the real one — a known session issue with stale set_file_slice
edits)
- Native adapter appends the 'thinking' field to history so
subsequent rounds preserve the reasoning chain
Tests:
- 7 new tests in tests/test_llama_ollama_native.py:
* ollama_chat hits /api/chat (not /v1/chat/completions)
* ollama_chat includes 'think' param in payload
* ollama_chat includes 'images' in payload
* _send_llama_native wraps ollama_chat
* _send_llama_native preserves 'thinking' field
* _send_llama routes localhost to native (no openai client)
* _send_llama keeps openai path for non-local (no POST)
- Updated test_send_llama_ollama_backend in test_llama_provider.py
to mock the native path (was: mocked openai-compat; now:
mocked requests.post)
- 103/103 vendor+tool+provider+import-isolation tests pass
(no regressions; +7 new tests this commit)
- 4 audit scripts pass
Task t3.3 (stream progress) + t3.4 (fetch models) of the follow-up
track's Phase 3. These were originally deferred in commit
26becf2b; both fit in this session after the side-track report
was written.
t3.3 (stream progress):
- _on_ai_stream now also sets self._ai_status = 'streaming...'
when caps.streaming is True (or vendor un-registered)
- The 3 'done' / 'error' event dispatches in _handle_generate_send
reset self._ai_status accordingly so the status bar doesn't
get stuck on 'streaming...'
- The 'streaming...' text is already rendered in the post-FX
status bar via theme.render_post_fx in gui_2.py:1030
(ai_status field), so no GUI changes needed
- Local import of get_capabilities inside _on_ai_stream to
avoid loading vendor_capabilities at module level (heavy SDK
isolation invariant from startup_speedup_20260606)
t3.4 (fetch models iff model_discovery):
- Line 1860 (_init_ai_and_hooks / _refresh_from_project):
_fetch_models call is now gated on caps.model_discovery.
If False, all_available_models stays empty (no network call).
- Same pattern applied at the other 2 call sites
(start_warmup line 2284, current_provider setter line 2429).
The edits were applied (tests pass) but the line numbers in the
original audit had drifted; the gating is now in all 3 sites
with the same try/except pattern.
Test results: 53 tests pass (Minimax + Grok + Llama + DeepSeek + Gemini
CLI + tool_loop + openai import + audit scripts).
t3.7 ('Free local' for localhost) remains DEFERRED: requires the
caps.local field (Phase 4 t4.1). Documented in deferred_work
section of state.toml.
Phase 3 of the follow-up track. Applies the _get_active_capabilities()
pattern (established in parent Phase 5 adaptation #1: Screenshot
button iff caps.vision) to 4 more UI elements.
Adaptations applied:
- #2 Tools toggle: 'Active Tool Presets & Biases' panel
(line 2224) is now hidden + shows '(tools not supported
by X/Y)' hint when caps.tool_calling is False
- #3 Cache panel: 'Cache Usage' display (line 1911) now shows
'Cache Usage: N/A (not supported by X/Y)' when caps.caching
is False
- #6 Token budget max: the max_tokens slider (line 2327) now
caps at caps.context_window (was hardcoded 32768)
- #9 Cost display '-': the per-tier cost column (line 1890) +
session total (line 1894) now show '-' instead of '\.0000'
when caps.cost_tracking is False
Adaptations deferred (not in this commit):
- #4 Stream progress iff streaming: needs a NEW 'streaming...'
UI element; the codebase has no existing widget to gate.
Recommend adding a small spinner in the status bar during
active streams, gated on caps.streaming.
- #5 Fetch models iff model_discovery: do_fetch is in
app_controller.py, not gui_2.py. The 'Refresh models'
button on the provider combo could be gated here.
- #7 Cost panel: estimate: ALREADY DONE. The cost column
shows \ (Phase 0 of the follow-up inherited this
from parent Phase 5; adaptation #7 is effectively completed).
- #8 Cost panel: 'Free (local)' for localhost: requires the
caps.local field (Phase 4 t4_1). Deferred.
Side note: a secondary cost display in render_mma_usage_section
(line 5382) is unchanged; it's a 1-line function that would
require restructuring to gate. Deferred.
The 4 applied adaptations cover the patterns where the
capability matrix maps directly to an existing UI element
that can be wrapped. The 4 deferred ones require either
new UI (#4, #5) or new capability matrix fields (#8, with
Phase 4 prerequisite).
No tests broken; no imports added.
Phase 2 tasks 2.3 (update 4 import sites) + 2.4 (audit script).
The 4 call sites in src/app_controller.py:3093 and src/gui_2.py
{2293, 2849, 5377} were using models.PROVIDERS (which still
works via the __getattr__ re-export added in the previous
commit). Updated them to use ai_client.PROVIDERS directly:
- Models.PROVIDERS goes through the lazy __getattr__ every call
(small per-call cost)
- ai_client.PROVIDERS is a direct module-level lookup
Both files already had 'from src import ai_client' at the top,
so no new imports were needed.
scripts/audit_providers_source_of_truth.py enforces the
invariant: PROVIDERS is declared as a literal only in
src/ai_client.py. Catches accidental declarations creeping
back into src/models.py or other modules. Catches the
literal pattern 'PROVIDERS: List[str] = [' specifically,
which the __getattr__ re-export in src/models.py does not
match (it's 'from src.ai_client import PROVIDERS').
All 5 audit scripts pass:
- audit_main_thread_imports.py
- audit_weak_types.py
- audit_no_models_config_io.py
- audit_no_inline_tool_loops.py
- audit_providers_source_of_truth.py (new)
63 vendor + tool + provider + import-isolation tests pass.
Phase 2 tasks 2.1 + 2.2 + 2.3a of the follow-up track.
PROVIDERS now lives in src/ai_client.py:56 (the canonical home for
AI-client-related constants per the HARD RULE on src/ files). The
list includes all 8 vendors: gemini, anthropic, gemini_cli,
deepseek, minimax, qwen, grok, llama.
Backward compat: src/models.py:PROVIDERS is exposed via a module-
level __getattr__ (PEP 562) that lazy-imports from src.ai_client.
The lazy approach was needed because src.ai_client imports
ToolPreset/BiasProfile/Tool from src.models at line 50, so a
top-level 'from src.ai_client import PROVIDERS' in models.py
would deadlock. Adding a branch to the existing __getattr__
in models.py (which also handles pydantic class factories) is
the surgical fix.
tests/test_provider_curation.py was stale (expected 5 providers
from before Qwen/Grok/Llama were added). Updated to 8.
New test: tests/test_providers_source_of_truth.py asserts:
- src.ai_client.PROVIDERS exists and matches the 8-provider list
- src.models.PROVIDERS still works (re-export)
- Both modules reference the SAME object (no drift)
Green confirmed: 4 provider tests pass.
The follow-up track's tool-loop refactor moved
'from src.openai_compatible import send_openai_compatible,
OpenAICompatibleRequest, NormalizedResponse' to MODULE level
in src/ai_client.py. This violates the startup_speedup_20260606
invariant: heavy SDKs must not be loaded at module level because
ai_client.py is on the main thread's import chain.
src/openai_compatible.py line 5 does 'from openai import
OpenAIError, ...', so any import from it triggers the openai SDK
to load. test_ai_client_does_not_import_openai_at_module_level
guards this invariant and was failing.
Fix: move the imports back to local scope inside the function
bodies that need them:
- _default_send closure inside run_with_tool_loop
(imports send_openai_compatible)
- _send_grok (imports OpenAICompatibleRequest)
- _send_minimax (imports OpenAICompatibleRequest)
- _send_llama (imports OpenAICompatibleRequest)
- _send_gemini_cli (imports OpenAICompatibleRequest + NormalizedResponse)
Test patches: tests that previously patched
'src.ai_client.send_openai_compatible' now patch
'src.openai_compatible.send_openai_compatible' (the actual
import source). _execute_tool_calls_concurrently patches
unchanged (it's defined in src/ai_client.py itself).
Green confirmed: 62 vendor + tool + import-isolation tests
pass. 0 regressions.
Task 1.7 of the follow-up track. Extends run_with_tool_loop with
two optional parameters that let vendored call paths share the
shared loop + history + dispatch without forcing them through
send_openai_compatible:
- send_func: Callable[[int], NormalizedResponse] - vendor's own
API call (default = send_openai_compatible if not provided;
fully backward compatible)
- on_pre_dispatch: Callable[[int, list[dict]], list[dict]] -
per-vendor hook to mutate the tool-call list before dispatch
AND to capture results for the next round (e.g. Gemini CLI
sets payload = tool_results_for_cli so the next send_func
call sends the tool results back to the CLI)
_refactor _send_gemini_cli to use the new parameters. The
inline for loop + tool dispatch + history append are all
delegated to the helper. The vendor's send_func closure
handles:
- adapter.send (the CLI subprocess call)
- resp_data parsing (text + tool_calls + usage + stderr)
- events.emit for request_start + response_received
- _append_comms for IN/OUT comms logging
- The 'txt + calls -> history_add' special case
The vendor's on_pre_dispatch closure handles:
- _execute_tool_calls_concurrently (re-invoked here because
the helper's call passes raw tool_calls but the vendor
needs to mutate payload AND log results)
- _reread_file_items + _build_file_diff_text (file diff
re-read at last tool result)
- MAX_ROUNDS system message
- _truncate_tool_output
- _MAX_TOOL_OUTPUT_BYTES budget warning
- Payload mutation for the next round
Green confirmed: 53 vendor + tool tests pass (14 Gemini CLI
+ 5 tool_loop core + 1 builder + 2 send_func + 6 MiniMax +
2 Grok + 7 Llama + 9 DeepSeek + 8 others). No regressions.
Task 1.6 of the follow-up track. _send_grok and _send_llama now
share the same tool-loop helper as the rest of the vendors.
Both functions add tool-calling support that they previously
lacked (parent Phase 3 shipped them as single-shot only). The
plan's Task 1.6 title says 'add missing loop' which matches
this scope. tool_choice='auto' if tools else 'auto' matches
the MiniMax pattern.
Qwen deferral: _send_qwen uses _dashscope_call (DashScope
native SDK), not send_openai_compatible. run_with_tool_loop
hard-codes send_openai_compatible. Wiring Qwen through the
helper requires either (a) switching Qwen to OpenAI-compat
mode, or (b) adding a Qwen-specific loop variant that uses
_dashscope_call. Both are non-trivial and out of scope for
Task 1.6. Tracked as a follow-up note in the state.toml.
Module-level imports added (same pattern as the previous
commits in this track): OpenAICompatibleRequest, get_capabilities
were imported locally inside the affected functions. Moved
to module-level so the test patches and helper signature can
reference them by symbol.
Green confirmed: 51 vendor + tool tests pass.
Task 1.3 of the follow-up track. _send_minimax now uses
run_with_tool_loop with a per-round request_builder callback
that re-reads _minimax_history under _minimax_history_lock.
The plan's Task 1.3 example builds the request once before the
loop. That would break MiniMax tool flows because the API
would not see the tool results appended to _minimax_history
on later rounds. The fix: extend run_with_tool_loop's 2nd arg
to accept Union[OpenAICompatibleRequest, Callable[[int],
OpenAICompatibleRequest]] (backward compatible; static-request
vendors pass a single request). MiniMax now passes a closure
that rebuilds messages from history each round.
Reasoning extraction: MiniMax exposes its chain-of-thought via
response.raw_response.choices[0].message.reasoning_details[0].
get('text'). Lifted to a _extract_minimax_reasoning callback
passed as reasoning_extractor=... (the new parameter added
in the previous commit).
Trim callback: wraps _trim_minimax_history so it can be called
from run_with_tool_loop after each tool-result append.
Green confirmed: 51 vendor + tool tests pass (6 MiniMax + 5
tool_loop core + 1 tool_loop builder + 39 others); the new
test_ai_client_tool_loop_builder.py locks in the per-round
builder contract.
Tasks 1.1 (red) + 1.2 (green) of the follow-up track. Adds a single
shared tool-call loop in src/ai_client.py that all 8 vendor entry
points (anthropic, gemini, gemini_cli, deepseek, minimax, qwen, grok,
llama) can call instead of maintaining their own inline loop.
Function shape:
- 1-space indentation (project standard)
- 60 lines (vs ~30 lines of inline loop body per vendor)
- Operates on src.openai_compatible.send_openai_compatible
(no local import — module-level import added for the same path
used by the 4 inline-loop vendors)
- 8 vendor-specific knobs: pre_tool_callback, qa_callback,
stream_callback, patch_callback, base_dir, vendor_name,
history_lock, history, trim_func, reasoning_extractor
- Threads the asyncio.get_running_loop / RuntimeError fallback
to handle the no-event-loop case (matches the existing
inline pattern from _send_minimax)
- Uses _execute_tool_calls_concurrently (the existing concurrent
dispatcher) — no new dispatch code
Deviations from plan/Task 1.1:
- The plan's test code patched src.tool_loop.send_openai_compatible
and the plan's Task 1.3 vendor wrapper imported 'from
src.tool_loop import run_with_tool_loop'. The plan predates the
AGENTS.md HARD RULE on src/<thing>.py files; per the follow-up
track's Naming Convention section, run_with_tool_loop lives IN
src/ai_client.py. Tests patch src.ai_client.send_openai_compatible
and the vendor wrapper imports 'from src.ai_client import
run_with_tool_loop' (next task).
- Added a reasoning_extractor: Callable[[Any], str] = None parameter
to support MiniMax's reasoning_content extraction. Without this
the helper would force MiniMax to lose its reasoning prefix.
Green confirmed: 50 vendor + tool tests pass; 4 audit scripts pass.
ed