feat(ingestion): add bounded, benchmark-aligned embedding execution

Why:
- Plan 001 Phase 4 needs batched, concurrency-bounded embedding wired into
  the inline upload path, with process-wide capacity/timeout/chunk-limit
  guards (ADR-0017).
- The BM25 analyzer and dense-model config are ported from the `emet`
  evaluation lab, which benchmarked them against the real Farsi corpus
  (bm25-fa-norm-stop; nomic-embed-text-v2-moe at 768-dim; text-embedding-3-large
  at native 3072-dim), closing open items in ADR-0001/ADR-0005.

Changes:
- New: embedding ports, orchestration (embed_chunks), request-bounds
  helpers, and dense/sparse adapters (analyzers.py, bm25.py,
  openai_compatible.py).
- upload.py now parses/chunks/embeds inline behind INGESTION_MAX_CONCURRENCY
  (503), INGESTION_TIMEOUT_SECONDS (504), and the chunk-count ceiling (413);
  every failure path still writes a terminal job row.
- Lifespan builds and warms both dense embedders at startup (fail-soft) and
  creates the sparse embedder and concurrency semaphore.
- httpx moves from dev to main dependencies (adapters use it directly).

Impact:
- Qdrant point upserts are still Phase 5 -- chunks_indexed stays 0.
- New EMBEDDING_* env vars documented in .env.example; safe defaults.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

tests/conftest.py

@@ -12,12 +12,22 @@ from src.main import create_app
 
 @pytest.fixture
 def settings() -> Settings:
+    # Every external dependency points at a closed port so unit tests never
+    # reach real infrastructure. For the embedders this matters twice over:
+    # the real defaults are a colleague's Ollama box and OpenAI's paid API,
+    # and ADR-0016 forbids routine runs calling either. Connection-refused is
+    # immediate, so the lifespan's fail-soft warm-up costs nothing here --
+    # and these tests passing at all is what proves it is fail-soft.
     return Settings(
         postgres={"host": "127.0.0.1", "port": 1},
         minio={"endpoint": "127.0.0.1:1"},
         ingestion={"timeout_seconds": 1.0},
         qdrant={"url": "http://127.0.0.1:1"},
         app={"readiness_check_timeout_seconds": 0.5},
+        embedding={
+            "nomic": {"base_url": "http://127.0.0.1:1/v1", "timeout_seconds": 0.5},
+            "openai": {"base_url": "http://127.0.0.1:1/v1", "timeout_seconds": 0.5},
+        },
     )