feat: add Requesty as a model provider

Add Requesty (https://requesty.ai), an OpenAI-compatible LLM router, as a
model provider by mirroring the existing OpenRouter integration.

Backend:
- app/services/requesty_model_normalizer.py: normalizes Requesty's /v1/models
  catalogue, mapping its flat capability booleans (supports_tool_calling/
  supports_vision/supports_image_generation) and context_window field onto the
  shared normalized shape (Requesty differs from OpenRouter's architecture +
  supported_parameters + context_length layout)
- provider_registry.py: Requesty ProviderSpec (OpenAI-compatible, base URL
  https://router.requesty.ai/v1, REQUESTY_API_KEY bearer auth)
- model_connection_service.py: key verification + live model discovery
- quality_score.py: Requesty score entry
- unit tests mirroring the OpenRouter normalizer coverage

Frontend:
- Requesty provider icon + registration, metadata entry, and base-url hint

Signed-off-by: Thibault Jaigu <thibault.jaigu@gmail.com>

surfsense_backend/app/services/requesty_model_normalizer.py

@@ -0,0 +1,123 @@
+"""Shared Requesty model normalization.
+
+Requesty (https://router.requesty.ai) is an OpenAI-compatible LLM router.
+Its ``/v1/models`` catalogue carries richer, Requesty-specific capability
+metadata than a generic OpenAI-compatible ``/models`` response, so keep all
+Requesty filtering and capability extraction here -- mirroring
+``openrouter_model_normalizer`` -- so GLOBAL catalogue generation and BYOK
+discovery agree.
+
+Unlike OpenRouter, Requesty exposes capabilities as flat booleans
+(``supports_tool_calling`` / ``supports_reasoning`` / ``supports_vision`` /
+``supports_image_generation``) rather than an ``architecture`` block plus a
+``supported_parameters`` array, and it reports context size as
+``context_window`` rather than ``context_length``. This module maps those
+fields onto the same normalized shape the rest of the backend consumes.
+"""
+
+from __future__ import annotations
+
+from typing import Any
+
+from app.db import ModelSource
+
+MIN_CONTEXT_LENGTH = 100_000
+
+EXCLUDED_PROVIDER_SLUGS: set[str] = {"amazon"}
+EXCLUDED_MODEL_IDS: set[str] = set()
+EXCLUDED_MODEL_SUFFIXES: tuple[str, ...] = ("-deep-research",)
+
+
+def is_image_output_model(model: dict[str, Any]) -> bool:
+    return bool(model.get("supports_image_generation"))
+
+
+def is_text_output_model(model: dict[str, Any]) -> bool:
+    # Requesty entries are chat-completion models (``api == "chat"``). Treat a
+    # model as text output whenever it is not an image-generation model.
+    return not is_image_output_model(model)
+
+
+def supports_image_input(model: dict[str, Any]) -> bool:
+    return bool(model.get("supports_vision"))
+
+
+def supports_tool_calling(model: dict[str, Any]) -> bool:
+    return bool(model.get("supports_tool_calling"))
+
+
+def has_sufficient_context(model: dict[str, Any]) -> bool:
+    return int(model.get("context_window") or 0) >= MIN_CONTEXT_LENGTH
+
+
+def is_compatible_provider(model: dict[str, Any]) -> bool:
+    model_id = str(model.get("id") or "")
+    slug = model_id.split("/", 1)[0] if "/" in model_id else ""
+    return slug not in EXCLUDED_PROVIDER_SLUGS
+
+
+def is_allowed_model(model: dict[str, Any]) -> bool:
+    model_id = str(model.get("id") or "")
+    if model_id in EXCLUDED_MODEL_IDS:
+        return False
+    base_id = model_id.split(":")[0]
+    return not base_id.endswith(EXCLUDED_MODEL_SUFFIXES)
+
+
+def is_requesty_chat_model(model: dict[str, Any]) -> bool:
+    return (
+        "/" in str(model.get("id") or "")
+        and is_text_output_model(model)
+        and supports_tool_calling(model)
+        and has_sufficient_context(model)
+        and is_compatible_provider(model)
+        and is_allowed_model(model)
+    )
+
+
+def is_requesty_image_model(model: dict[str, Any]) -> bool:
+    return (
+        "/" in str(model.get("id") or "")
+        and is_image_output_model(model)
+        and is_compatible_provider(model)
+        and is_allowed_model(model)
+    )
+
+
+def normalize_requesty_models(
+    raw_models: list[dict[str, Any]],
+) -> list[dict[str, Any]]:
+    normalized: list[dict[str, Any]] = []
+    for model in raw_models:
+        if not is_requesty_chat_model(model):
+            continue
+        model_id = str(model.get("id") or "")
+        normalized.append(
+            {
+                "model_id": model_id,
+                "display_name": model.get("name") or model_id,
+                "source": ModelSource.DISCOVERED,
+                "supports_chat": True,
+                "max_input_tokens": model.get("context_window"),
+                "supports_image_input": supports_image_input(model),
+                "supports_tools": supports_tool_calling(model),
+                "supports_image_generation": False,
+                "metadata": model,
+            }
+        )
+    return normalized
+
+
+__all__ = [
+    "MIN_CONTEXT_LENGTH",
+    "has_sufficient_context",
+    "is_allowed_model",
+    "is_compatible_provider",
+    "is_image_output_model",
+    "is_requesty_chat_model",
+    "is_requesty_image_model",
+    "is_text_output_model",
+    "normalize_requesty_models",
+    "supports_image_input",
+    "supports_tool_calling",
+]