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>

docs/adr/0004-docx-csv-chunking-strategy.md

@@ -62,6 +62,23 @@ from its model card: 768-dim output, Matryoshka-truncatable down to 256;
 every embedded string — `search_document: ` at ingestion time, `search_query: `
 on the agent's query side (ADR-0003).
 
+> **Amendment — the task prefix is currently not applied.** The `emet`
+> benchmark that selected this model ran *without* any prefix: its Ollama
+> deployment's template is a bare `{{ .Prompt }}` passthrough that injects
+> nothing, which was verified directly against the running endpoint. The
+> prefix is not cosmetic — embedding the same Persian text with and without
+> `search_document: ` yields a cosine of only **0.5741** — so applying it at
+> ingest while the query side omits `search_query: ` would make retrieval
+> *worse* than using neither.
+>
+> Implementation therefore defaults `EMBEDDING_NOMIC_DOCUMENT_PREFIX` to
+> empty, matching the measured configuration, and exposes it as config so the
+> prefixed variant is a one-line experiment rather than a code change. The
+> model card remains the reason to expect prefixing to help; what is missing
+> is evidence on *this* corpus. Turning it on is a paired change — ingest and
+> query must move together — and should be settled by an emet run that
+> measures the pair, not by an unmeasured edit here.
+
 ## Decision
 
 ### Parsing order: structural extraction before chunking