mirror of
https://github.com/MODSetter/SurfSense.git
synced 2026-07-16 23:01:06 +02:00
2ff7ea4cb6
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>
123 lines
4 KiB
Python
123 lines
4 KiB
Python
"""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",
|
|
]
|