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manual_slop/src
ed f9b5c9372d feat(grok,llama): add to PROVIDERS; add 11 pricing entries (3 Grok + 8 Llama)
Side concerns for Phase 3:

1. PROVIDERS: src/models.py:56 now includes 'grok' and 'llama' alongside
   the 6 existing vendors. Centralized registry; gui_2.py and
   app_controller.py import from here. State tasks t3.5 and t3.16
   were scoped to gui_2.py/app_controller.py but the actual change
   is at the centralized registry, per the project's single-source-of-
   truth pattern (per src/models.py module docstring and the Phase 5
   audit script audit_no_models_config_io.py which enforces that
   PROVIDERS lives in models.py).

2. cost_tracker.py: added 11 regex pricing entries (3 Grok + 8 Llama):

   Grok (per xAI public pricing):
   - grok-2: 2.00 / 10.00
   - grok-2-vision: 2.00 / 10.00
   - grok-beta: 5.00 / 15.00

   Llama (per Grok's consultation: pricing varies by backend; registry
   entries represent the most common case):
   - llama-3.1-8b-instant: 0.05 / 0.08 (Groq)
   - llama-3.1-70b-versatile: 0.59 / 0.79 (Groq)
   - llama-3.1-405b-reasoning: 3.00 / 3.00 (OpenRouter avg)
   - llama-3.2-1b-preview: 0.04 / 0.04
   - llama-3.2-3b-preview: 0.06 / 0.06
   - llama-3.2-11b-vision-preview: 0.18 / 0.18
   - llama-3.2-90b-vision-preview: 0.90 / 0.90
   - llama-3.3-70b-specdec: 0.59 / 0.79 (Groq)

   (all per 1M tokens, USD; matches the structure of existing entries;
   note: 'llama-3.1', 'llama-3.2', 'llama-3.3' are regex patterns to
   allow future model variants in the same family.)

   Spot check:
   - estimate_cost('grok-2', 1000, 500) = 0.007 (= 0.002 + 0.005)
   - estimate_cost('llama-3.3-70b-specdec', 1000, 500) = 0.000985

3. SKIPPED t3.4 and t3.15 (credentials templates): no
   credentials_template.toml exists in the project (Phase 2 established
   this). The user maintains their own credentials.toml directly.

4. t3.6 and t3.17 (Grok/Llama models in capability registry) were
   completed in Phase 1's initial population of 22 entries
   (commit 6be04bc). Grok has 4 entries (1 wildcard + 3 models);
   Llama has 9 entries (1 wildcard + 8 models). Grok-2-vision has
   vision=True; Llama 3.2-11b/90b vision variants have vision=True.

Verification: 38/38 tests pass in batch.
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