Fix xAI sentiment: use Agent Tools web_search (Live Search deprecated)

xAI returned 410 — search_parameters/Live Search is retired. Route xAI
through the Responses API web_search tool instead (same path as OpenAI):
- OpenAISentimentProvider parametrized with base_url / tool_type / source
- xAI builds it against https://api.x.ai/v1 with the web_search tool
- Drop the dead Live Search code from the generic compatible provider
- Frontend label: "xAI Grok — web search"

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

app/providers/openai_sentiment.py

@@ -55,17 +55,34 @@ VALID_CLASSIFICATIONS = {"bullish", "bearish", "neutral"}
 
 
 class OpenAISentimentProvider:
-    """Fetches sentiment analysis from OpenAI Responses API with live web search."""
+    """Sentiment via the Responses API + web-search tool, with live grounding.
 
-    def __init__(self, api_key: str, model: str = "gpt-4o-mini") -> None:
+    Works against any provider implementing the OpenAI Responses API. OpenAI
+    uses the ``web_search_preview`` tool; xAI Grok uses ``web_search`` at the
+    ``https://api.x.ai/v1`` base URL.
+    """
+
+    def __init__(
+        self,
+        api_key: str,
+        model: str = "gpt-4o-mini",
+        base_url: str | None = None,
+        tool_type: str = "web_search_preview",
+        source: str = "openai",
+    ) -> None:
         if not api_key:
-            raise ProviderError("OpenAI API key is required")
+            raise ProviderError(f"{source} API key is required")
         http_kwargs: dict = {}
         if _CA_BUNDLE and Path(_CA_BUNDLE).exists():
             http_kwargs["verify"] = _CA_BUNDLE
         http_client = httpx.AsyncClient(**http_kwargs)
-        self._client = AsyncOpenAI(api_key=api_key, http_client=http_client)
+        client_kwargs: dict = {"api_key": api_key, "http_client": http_client}
+        if base_url:
+            client_kwargs["base_url"] = base_url
+        self._client = AsyncOpenAI(**client_kwargs)
         self._model = model
+        self._tool_type = tool_type
+        self._source = source
 
     @staticmethod
     def _extract_raw_text(response: object, ticker_context: str) -> str:
@@ -89,12 +106,11 @@ class OpenAISentimentProvider:
             clean = clean[:-3]
         return clean.strip()
 
-    @staticmethod
-    def _normalize_single_result(parsed: dict, ticker: str, citations: list[dict[str, str]]) -> SentimentData:
+    def _normalize_single_result(self, parsed: dict, ticker: str, citations: list[dict[str, str]]) -> SentimentData:
         classification = str(parsed.get("classification", "")).lower()
         if classification not in VALID_CLASSIFICATIONS:
             raise ProviderError(
-                f"Invalid classification '{classification}' from OpenAI for {ticker}"
+                f"Invalid classification '{classification}' from {self._source} for {ticker}"
             )
 
         confidence = int(parsed.get("confidence", 50))
@@ -103,7 +119,8 @@ class OpenAISentimentProvider:
 
         if reasoning:
             logger.info(
-                "OpenAI sentiment for %s: %s (confidence=%d) — %s",
+                "%s sentiment for %s: %s (confidence=%d) — %s",
+                self._source,
                 ticker,
                 classification,
                 confidence,
@@ -114,7 +131,7 @@ class OpenAISentimentProvider:
             ticker=ticker,
             classification=classification,
             confidence=confidence,
-            source="openai",
+            source=self._source,
             timestamp=datetime.now(timezone.utc),
             reasoning=reasoning,
             citations=citations,
@@ -125,7 +142,7 @@ class OpenAISentimentProvider:
         try:
             response = await self._client.responses.create(
                 model=self._model,
-                tools=[{"type": "web_search_preview"}],
+                tools=[{"type": self._tool_type}],
                 instructions="You are a financial sentiment analyst. Always respond with valid JSON only, no markdown fences.",
                 input=_SENTIMENT_PROMPT.format(ticker=ticker),
             )
@@ -172,7 +189,7 @@ class OpenAISentimentProvider:
         try:
             response = await self._client.responses.create(
                 model=self._model,
-                tools=[{"type": "web_search_preview"}],
+                tools=[{"type": self._tool_type}],
                 instructions="You are a financial sentiment analyst. Always respond with valid JSON only, no markdown fences.",
                 input=_SENTIMENT_BATCH_PROMPT.format(tickers_csv=", ".join(normalized)),
             )