feat: add embeddings endpoint and config for OpenAI-compatible text embeddings via gateway

Add POST /openai/v1/embeddings route in openai_gateway router, new config fields for embedding upstream URL/model/key/enabled toggle with defaults pointing to OpenRouter Qwen3 8B, INTERNAL_EMBED_MODEL constant in config.py, documentation in docs_api.py and README.md describing the molodetz~embed model mapping, and embed-call tracking in gateway metrics alongside existing chat/vision counters.
This commit is contained in:
2026-06-14 01:06:18 +00:00
parent 1076696dec
commit c7770ee21a
17 changed files with 662 additions and 62 deletions
@@ -202,3 +202,85 @@ def test_authorize_require_auth_off_is_open(local_db):
assert svc.authorize(_make_request_openai_gateway()) is True
finally:
set_setting("gateway_require_auth", "1")
class FakeEmbedClient_openai_gateway:
def __init__(self, *a, **k):
self.calls = []
def build_request(self, method, url, headers=None, json=None, content=None):
return FakeRequest(method, url, json)
async def send(self, request):
self.calls.append((request.url, request.json_body))
body = request.json_body or {}
return FakeResp_openai_gateway(
payload={
"object": "list",
"model": body.get("model"),
"data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2]}],
"usage": {"prompt_tokens": 5, "total_tokens": 5},
}
)
async def aclose(self):
pass
def test_embeddings_remaps_alias_to_configured_model(local_db, monkeypatch):
monkeypatch.setattr(gwmod.httpx, "AsyncClient", FakeEmbedClient_openai_gateway)
svc = GatewayService()
cfg = svc.effective_config()
cfg["gateway_force_model"] = False
cfg["gateway_embed_enabled"] = True
cfg["gateway_embed_model"] = "qwen/qwen3-embedding-8b"
rt = svc.runtime()
run_async(
rt.handle_embeddings(
{"model": "molodetz~embed", "input": "hello"},
cfg,
("guest", "test"),
"test",
)
)
assert rt._client.calls[-1][1]["model"] == "qwen/qwen3-embedding-8b"
def test_embeddings_disabled_returns_503(local_db, monkeypatch):
monkeypatch.setattr(gwmod.httpx, "AsyncClient", FakeEmbedClient_openai_gateway)
svc = GatewayService()
cfg = svc.effective_config()
cfg["gateway_embed_enabled"] = False
rt = svc.runtime()
resp = run_async(
rt.handle_embeddings(
{"input": "hello"}, cfg, ("guest", "test"), "test"
)
)
assert resp.status_code == 503
def test_compute_cost_embed_branch():
from devplacepy.services.openai_gateway.usage import (
Pricing,
compute_cost,
normalize_usage,
)
pricing = Pricing(
chat_cache_hit_per_m=0.0,
chat_cache_miss_per_m=0.0,
chat_output_per_m=0.0,
vision_input_per_m=0.0,
vision_output_per_m=0.0,
embed_input_per_m=0.01,
)
usage = {"prompt_tokens": 1_000_000, "total_tokens": 1_000_000}
norm = normalize_usage(usage)
total, input_cost, output_cost, native = compute_cost(
usage, norm, pricing, "embed"
)
assert native is False
assert output_cost == 0.0
assert abs(total - 0.01) < 1e-9
assert abs(input_cost - 0.01) < 1e-9