feat: provider modules — ProviderProfile ABC, 33 providers, fetch_models, transport single-path

Introduces providers/ package — single source of truth for every
inference provider. Adding a simple api-key provider now requires one
providers/<name>.py file with zero edits anywhere else.

What this PR ships:
- providers/ package (ProviderProfile ABC + 33 profiles across 4 api_modes)
- ProviderProfile declarative fields: name, api_mode, aliases, display_name,
  env_vars, base_url, models_url, auth_type, fallback_models, hostname,
  default_headers, fixed_temperature, default_max_tokens, default_aux_model
- 4 overridable hooks: prepare_messages, build_extra_body,
  build_api_kwargs_extras, fetch_models
- chat_completions.build_kwargs: profile path via _build_kwargs_from_profile,
  legacy flag path retained for lmstudio/tencent-tokenhub (which have
  session-aware reasoning probing that doesn't map cleanly to hooks yet)
- run_agent.py: profile path for all registered providers; legacy path
  variable scoping fixed (all flags defined before branching)
- Auto-wires: auth.PROVIDER_REGISTRY, models.CANONICAL_PROVIDERS,
  doctor health checks, config.OPTIONAL_ENV_VARS, model_metadata._URL_TO_PROVIDER
- GeminiProfile: thinking_config translation (native + openai-compat nested)
- New tests/providers/ (79 tests covering profile declarations, transport
  parity, hook overrides, e2e kwargs assembly)

Deltas vs original PR (salvaged onto current main):
- Added profiles: alibaba-coding-plan, azure-foundry, minimax-oauth
  (were added to main since original PR)
- Skipped profiles: lmstudio, tencent-tokenhub stay on legacy path (their
  reasoning_effort probing has no clean hook equivalent yet)
- Removed lmstudio alias from custom profile (it's a separate provider now)
- Skipped openrouter/custom from PROVIDER_REGISTRY auto-extension
  (resolve_provider special-cases them; adding breaks runtime resolution)
- runtime_provider: profile.api_mode only as fallback when URL detection
  finds nothing (was breaking minimax /v1 override)
- Preserved main's legacy-path improvements: deepseek reasoning_content
  preserve, gemini Gemma skip, OpenRouter response caching, Anthropic 1M
  beta recovery, etc.
- Kept agent/copilot_acp_client.py in place (rejected PR's relocation —
  main has 7 fixes landed since; relocation would revert them)
- _API_KEY_PROVIDER_AUX_MODELS alias kept for backward compat with existing
  test imports

Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
Closes #14418

tests/providers/test_e2e_wiring.py

@@ -0,0 +1,118 @@
+"""E2E tests: verify _build_kwargs_from_profile produces correct output.
+
+These tests call _build_kwargs_from_profile on the transport directly,
+without importing run_agent (which would cause xdist worker contamination).
+"""
+
+import pytest
+from agent.transports.chat_completions import ChatCompletionsTransport
+from providers import get_provider_profile
+
+
+@pytest.fixture
+def transport():
+    return ChatCompletionsTransport()
+
+
+def _msgs():
+    return [{"role": "user", "content": "hi"}]
+
+
+class TestNvidiaProfileWiring:
+    def test_nvidia_gets_default_max_tokens(self, transport):
+        profile = get_provider_profile("nvidia")
+        kwargs = transport.build_kwargs(
+            model="nvidia/llama-3.1-nemotron-70b-instruct",
+            messages=_msgs(),
+            tools=None,
+            provider_profile=profile,
+            max_tokens=None,
+            max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
+            timeout=300,
+            reasoning_config=None,
+            request_overrides=None,
+            session_id="test",
+            ollama_num_ctx=None,
+        )
+        # NVIDIA profile sets default_max_tokens=16384
+        assert kwargs.get("max_tokens") == 16384
+
+    def test_nvidia_nim_alias(self, transport):
+        profile = get_provider_profile("nvidia-nim")
+        assert profile is not None
+        assert profile.name == "nvidia"
+        assert profile.default_max_tokens == 16384
+
+    def test_nvidia_model_passed(self, transport):
+        profile = get_provider_profile("nvidia")
+        kwargs = transport.build_kwargs(
+            model="nvidia/test-model",
+            messages=_msgs(),
+            tools=None,
+            provider_profile=profile,
+            max_tokens=None,
+            max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
+            timeout=300,
+            reasoning_config=None,
+            request_overrides=None,
+            session_id="test",
+            ollama_num_ctx=None,
+        )
+        assert kwargs["model"] == "nvidia/test-model"
+
+    def test_nvidia_messages_passed(self, transport):
+        profile = get_provider_profile("nvidia")
+        msgs = _msgs()
+        kwargs = transport.build_kwargs(
+            model="nvidia/test",
+            messages=msgs,
+            tools=None,
+            provider_profile=profile,
+            max_tokens=None,
+            max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
+            timeout=300,
+            reasoning_config=None,
+            request_overrides=None,
+            session_id="test",
+            ollama_num_ctx=None,
+        )
+        assert kwargs["messages"] == msgs
+
+
+class TestDeepSeekProfileWiring:
+    def test_deepseek_no_forced_max_tokens(self, transport):
+        profile = get_provider_profile("deepseek")
+        kwargs = transport.build_kwargs(
+            model="deepseek-chat",
+            messages=_msgs(),
+            tools=None,
+            provider_profile=profile,
+            max_tokens=None,
+            max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
+            timeout=300,
+            reasoning_config=None,
+            request_overrides=None,
+            session_id="test",
+            ollama_num_ctx=None,
+        )
+        # DeepSeek has no default_max_tokens
+        assert kwargs["model"] == "deepseek-chat"
+        assert kwargs.get("max_tokens") is None or "max_tokens" not in kwargs
+
+    def test_deepseek_messages_passed(self, transport):
+        profile = get_provider_profile("deepseek")
+        msgs = _msgs()
+        kwargs = transport.build_kwargs(
+            model="deepseek-chat",
+            messages=msgs,
+            tools=None,
+            provider_profile=profile,
+            max_tokens=None,
+            max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
+            timeout=300,
+            reasoning_config=None,
+            request_overrides=None,
+            session_id="test",
+            ollama_num_ctx=None,
+        )
+        assert kwargs["messages"] == msgs