032: Phase 4 US2 — Translate plugin fully async

T022-T028: All translate methods async.
- _llm_async_http.py created (httpx.AsyncClient+asyncio.sleep)
- Old _llm_http.py and preview_llm_client.py preserved (tombstone later)
- superset_executor, preview, executor, run_source, llm_call all async

RATIONALE: httpx.AsyncClient + asyncio.sleep instead of time.sleep.
REJECTED: AsyncOpenAI SDK — doesn't support custom base_url.

backend/src/plugins/translate/preview_executor.py

@@ -18,7 +18,7 @@ from ...core.config_manager import ConfigManager
 from ...core.logger import belief_scope, logger
 from ...core.superset_client import SupersetClient
 from ...models.translate import TranslationJob
-from .preview_llm_client import LLMClient
+from ._llm_async_http import call_openai_compatible
 from .preview_resolve_provider import resolve_provider_model as _resolve_provider_model
 from .preview_response_parser import (
     compute_config_hash as _compute_config_hash,
@@ -38,7 +38,7 @@ class PreviewExecutor:
     # region fetch_sample_rows [TYPE Function]
     # @PURPOSE: Fetch sample rows from Superset dataset for preview.
     # @SIDE_EFFECT  Calls Superset chart data endpoint.
-    def fetch_sample_rows(
+    async def fetch_sample_rows(
         self,
         job: TranslationJob,
         sample_size: int = 10,
@@ -55,7 +55,7 @@ class PreviewExecutor:
                     raise ValueError("No Superset environments configured")
 
             client = SupersetClient(env_config)
-            dataset_detail = client.get_dataset_detail(int(job.source_datasource_id))
+            dataset_detail = await client.get_dataset_detail(int(job.source_datasource_id))
             query_context = client.build_dataset_preview_query_context(
                 dataset_id=int(job.source_datasource_id), dataset_record=dataset_detail,
                 template_params={}, effective_filters=[],
@@ -71,7 +71,7 @@ class PreviewExecutor:
             form_data.pop("query_mode", None)
 
             try:
-                response = client.network.request(
+                response = await client.network.request(
                     method="POST", endpoint="/api/v1/chart/data",
                     data=json.dumps(query_context),
                     headers={"Content-Type": "application/json"},
@@ -85,7 +85,7 @@ class PreviewExecutor:
     # region call_llm [TYPE Function]
     # @PURPOSE: Call the configured LLM provider with a prompt.
     # @SIDE_EFFECT  Makes HTTP call to LLM provider.
-    def call_llm(self, job: TranslationJob, prompt: str, max_tokens: int = 8192) -> str:
+    async def call_llm(self, job: TranslationJob, prompt: str, max_tokens: int = 8192) -> str:
         with belief_scope("PreviewExecutor.call_llm"):
             if not job.provider_id:
                 raise ValueError("Job has no LLM provider configured")
@@ -108,7 +108,7 @@ class PreviewExecutor:
             max_attempts = 2
             for attempt in range(max_attempts):
                 try:
-                    response_text = LLMClient.call_openai_compatible(
+                    content_text, _ = await call_openai_compatible(
                         base_url=provider.base_url, api_key=api_key, model=model,
                         prompt=prompt, provider_type=provider_type,
                         max_tokens=max_tokens * (attempt + 1),
@@ -121,7 +121,7 @@ class PreviewExecutor:
                         continue
                     raise
 
-            return response_text
+            return content_text
     # endregion call_llm
 
     # region delegation_helpers [TYPE Function]