feat(config): named LLM provider list via env vars, runtime selection

- Config.llm_profiles: LLM_PROVIDERS declares names, each group defined by
  LLM_<NAME>_BASE_URL/_API_KEY/_MODEL (required) and optional _TIMEOUT_SECONDS/
  _MAX_RETRIES/_TEMPERATURE/_EXTRA_BODY; JSON-dict form of LLM_PROVIDERS also
  supported. LLM_PROVIDER selects the active group at runtime; empty/fake =
  offline scripted model
- removed fixed openai/kimi groups (AGENT_LLM_PROVIDER, KIMI_LLM_*)
- validate(): incomplete groups and unknown LLM_PROVIDER fail fast with
  the configured-name list
- OpenAILLMService: http client trust_env from LLM_HTTP_TRUST_ENV (default
  False - local gateways must bypass the Windows system proxy)
- build_llm_service(provider): explicit name or LLM_PROVIDER default
- .env/.env.example: deepseek + kimi groups side by side, switch by
  LLM_PROVIDER=kimi (thinking off via EXTRA_BODY reasoning_effort=none)
- eval probe scripts updated to the new config interface

Verified: 172 unit tests; live calls succeed on both providers
(deepseek 28s, kimi 6.6s, both emitting valid <state> prefixes)

evals/prompt_compare.py

@@ -39,13 +39,13 @@ def main():
             path = args.prompt_dir / (name+'.md')
             return path.read_text(encoding='utf-8') if path.exists() else original_loader(name)
         registry.load_prompt = snapshot_loader
-    if Config.AGENT_BACKEND != 'langgraph' or Config.AGENT_LLM_PROVIDER != 'openai':
+    if Config.AGENT_BACKEND != 'langgraph' or not Config.LLM_PROVIDER or Config.LLM_PROVIDER == 'fake':
         raise SystemExit('Requires langgraph backend and real openai provider')
     args.output_dir.mkdir(parents=True, exist_ok=True)
     cases = load_cases(DEFAULT_CASES_DIR, args.case)
     from src.agent.prompts import load_prompt
     metadata = {
-        'model': Config.LLM_MODEL, 'temperature': Config.LLM_TEMPERATURE,
+        **{k: v for k, v in (Config.llm_profile(Config.LLM_PROVIDER) or {}).items() if k in ('model', 'temperature')},
         'backend': Config.AGENT_BACKEND, 'workers': args.workers,
         'commit': subprocess.check_output(['git', 'rev-parse', 'HEAD'], text=True).strip(),
         'case_hashes': {str(p.relative_to(DEFAULT_CASES_DIR)): sha256(p.read_bytes()).hexdigest()

evals/prompt_probes.py

@@ -63,7 +63,7 @@ async def main(args):
     if args.prompt_dir:
         import src.agent.prompts as registry
         registry.load_prompt = lambda name: (args.prompt_dir / (name+'.md')).read_text(encoding='utf-8')
-    llm = build_llm_service('openai')
+    llm = build_llm_service()
     semaphore = asyncio.Semaphore(4)
     async def run(case):
         async with semaphore:
@@ -107,7 +107,8 @@ async def main(args):
     results = await asyncio.gather(*(run(c) for c in selected))
     from src.core.config import Config
     from src.agent.prompts import load_prompt
-    output = dict(model=Config.LLM_MODEL, temperature=Config.LLM_TEMPERATURE,
+    profile = Config.llm_profile(Config.LLM_PROVIDER) or {}
+    output = dict(model=profile.get('model'), temperature=profile.get('temperature'),
                   execution_mode='runtime' if args.runtime else 'raw_prompt',
                   prompt_hashes={name:sha256(load_prompt(name).encode('utf-8')).hexdigest() for name in (COLLECTION,EXTRACTION)},
                   passed=sum(r['passed'] for r in results), total=len(results), results=results)

evals/time_boundary.py

@@ -26,7 +26,7 @@ def parsed_time(value):
 
 
 async def main(output):
-    llm = build_llm_service('openai')
+    llm = build_llm_service()
     cases = []
     for delay in (75,135):
         cases.append(dict(name=f'anchored_cross_midnight_delay_{delay}',now=ORIGIN+timedelta(minutes=delay),