Add request timeout and retry to Gemini extraction backend

A timeout-less generate_content call hung the single-threaded extract worker for ~50 min mid-batch. Set an HTTP timeout (120s) plus 4 retries with backoff, mirroring SparkControl._post; transient 504/read-timeouts now self-heal instead of freezing the run.

signal_engine/extract/backends.py

@@ -10,6 +10,7 @@ A backend exposes: complete_json(messages, max_tokens) -> str  (a JSON object st
 from __future__ import annotations
 
 import logging
+import time
 
 log = logging.getLogger(__name__)
 
@@ -32,31 +33,43 @@ class GeminiBackend:
     API is the eventual scale path; this synchronous form is the drop-in fallback."""
     name = "gemini"
 
-    def __init__(self, api_key: str, model: str = "gemini-2.5-flash") -> None:
+    def __init__(self, api_key: str, model: str = "gemini-2.5-flash", *,
+                 timeout_s: float = 120.0, retries: int = 4) -> None:
         from google import genai  # guarded import; pip install google-genai
+        from google.genai import types
         self._genai = genai
-        self.client = genai.Client(api_key=api_key)
+        self._types = types
+        # http_options.timeout is in MILLISECONDS — without it a stalled request hangs the (single-
+        # threaded) worker forever; one such hang froze a whole batch for ~50 min before this fix.
+        self.client = genai.Client(api_key=api_key,
+                                   http_options=types.HttpOptions(timeout=int(timeout_s * 1000)))
         self.model = model
+        self.retries = retries
 
     def complete_json(self, messages: list[dict], *, max_tokens: int = 4000) -> str:
-        from google.genai import types
+        types = self._types
         system = "\n\n".join(m["content"] for m in messages if m["role"] == "system")
         user = "\n\n".join(m["content"] for m in messages if m["role"] != "system")
-        resp = self.client.models.generate_content(
-            model=self.model,
-            contents=user,
-            config=types.GenerateContentConfig(
-                system_instruction=system or None,
-                temperature=0,
-                max_output_tokens=max_tokens,
-                response_mime_type="application/json",
-                # Gemini 2.5 thinks by default and spends the output budget on reasoning tokens —
-                # it hit MAX_TOKENS with ~3.8k thoughts and a truncated JSON body (0 claims parsed).
-                # Extraction is deterministic, no-CoT (mirrors the local path's enable_thinking=False).
-                thinking_config=types.ThinkingConfig(thinking_budget=0),
-            ),
+        cfg = types.GenerateContentConfig(
+            system_instruction=system or None,
+            temperature=0,
+            max_output_tokens=max_tokens,
+            response_mime_type="application/json",
+            # Gemini 2.5 thinks by default and spends the output budget on reasoning tokens —
+            # it hit MAX_TOKENS with ~3.8k thoughts and a truncated JSON body (0 claims parsed).
+            # Extraction is deterministic, no-CoT (mirrors the local path's enable_thinking=False).
+            thinking_config=types.ThinkingConfig(thinking_budget=0),
         )
-        return resp.text or "{}"
+        for attempt in range(self.retries + 1):
+            try:
+                resp = self.client.models.generate_content(model=self.model, contents=user, config=cfg)
+                return resp.text or "{}"
+            except Exception as e:  # noqa: BLE001 — timeout/5xx/429/network: back off and retry
+                if attempt >= self.retries:
+                    raise
+                sleep = 2.0 * (2 ** attempt)
+                log.warning("Gemini call failed (%s); retry %d/%d in %.0fs", e, attempt + 1, self.retries, sleep)
+                time.sleep(sleep)
 
 
 def from_config(cfg, sc) -> "LocalQwenBackend | GeminiBackend":