mirror of
https://github.com/HKUDS/nanobot.git
synced 2026-05-19 16:12:30 +00:00
bb788cdb7d
Adds GeminiImageGenerationClient covering both Imagen 4 (:predict) and Gemini Flash (:generateContent), wires the gemini ProviderConfig through the SDK, API server, and gateway entry points, and updates the image-generation docs and skill. Errors from the Gemini endpoints are logged and surface with the HTTP status and parsed message instead of an empty string. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
340 lines
12 KiB
Python
340 lines
12 KiB
Python
from __future__ import annotations
|
|
|
|
from pathlib import Path
|
|
from typing import Any
|
|
|
|
import httpx
|
|
import pytest
|
|
|
|
from nanobot.providers.image_generation import (
|
|
AIHubMixImageGenerationClient,
|
|
GeminiImageGenerationClient,
|
|
GeneratedImageResponse,
|
|
ImageGenerationError,
|
|
OpenRouterImageGenerationClient,
|
|
)
|
|
|
|
PNG_BYTES = (
|
|
b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01"
|
|
b"\x00\x00\x00\x01\x08\x04\x00\x00\x00\xb5\x1c\x0c\x02"
|
|
b"\x00\x00\x00\x0bIDATx\xdacd\xfc\xff\x1f\x00\x03\x03"
|
|
b"\x02\x00\xef\xbf\xa7\xdb\x00\x00\x00\x00IEND\xaeB`\x82"
|
|
)
|
|
PNG_DATA_URL = (
|
|
"data:image/png;base64,"
|
|
"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mP8/x8AAwMCAO+/p9sAAAAASUVORK5CYII="
|
|
)
|
|
|
|
|
|
class FakeResponse:
|
|
def __init__(
|
|
self,
|
|
payload: dict[str, Any],
|
|
status_code: int = 200,
|
|
content: bytes = b"",
|
|
) -> None:
|
|
self._payload = payload
|
|
self.status_code = status_code
|
|
self.text = str(payload)
|
|
self.content = content
|
|
self.request = httpx.Request("POST", "https://openrouter.ai/api/v1/chat/completions")
|
|
|
|
def json(self) -> dict[str, Any]:
|
|
return self._payload
|
|
|
|
def raise_for_status(self) -> None:
|
|
if self.status_code >= 400:
|
|
response = httpx.Response(self.status_code, request=self.request, text=self.text)
|
|
raise httpx.HTTPStatusError("failed", request=self.request, response=response)
|
|
|
|
|
|
class FakeClient:
|
|
def __init__(self, response: FakeResponse) -> None:
|
|
self.response = response
|
|
self.get_response = response
|
|
self.calls: list[dict[str, Any]] = []
|
|
self.get_calls: list[dict[str, Any]] = []
|
|
|
|
async def post(self, url: str, **kwargs: Any) -> FakeResponse:
|
|
self.calls.append({"url": url, **kwargs})
|
|
return self.response
|
|
|
|
async def get(self, url: str, **kwargs: Any) -> FakeResponse:
|
|
self.get_calls.append({"url": url, **kwargs})
|
|
return self.get_response
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_openrouter_image_generation_payload_and_response(tmp_path: Path) -> None:
|
|
ref = tmp_path / "ref.png"
|
|
ref.write_bytes(PNG_BYTES)
|
|
fake = FakeClient(
|
|
FakeResponse(
|
|
{
|
|
"choices": [
|
|
{
|
|
"message": {
|
|
"content": "done",
|
|
"images": [{"image_url": {"url": PNG_DATA_URL}}],
|
|
}
|
|
}
|
|
]
|
|
}
|
|
)
|
|
)
|
|
client = OpenRouterImageGenerationClient(
|
|
api_key="sk-or-test",
|
|
api_base="https://openrouter.ai/api/v1/",
|
|
extra_headers={"X-Test": "1"},
|
|
client=fake, # type: ignore[arg-type]
|
|
)
|
|
|
|
response = await client.generate(
|
|
prompt="make this blue",
|
|
model="openai/gpt-5.4-image-2",
|
|
reference_images=[str(ref)],
|
|
aspect_ratio="16:9",
|
|
image_size="2K",
|
|
)
|
|
|
|
assert isinstance(response, GeneratedImageResponse)
|
|
assert response.images == [PNG_DATA_URL]
|
|
assert response.content == "done"
|
|
|
|
call = fake.calls[0]
|
|
assert call["url"] == "https://openrouter.ai/api/v1/chat/completions"
|
|
assert call["headers"]["Authorization"] == "Bearer sk-or-test"
|
|
assert call["headers"]["X-Test"] == "1"
|
|
body = call["json"]
|
|
assert body["modalities"] == ["image", "text"]
|
|
assert body["image_config"] == {"aspect_ratio": "16:9", "image_size": "2K"}
|
|
assert body["messages"][0]["content"][0] == {"type": "text", "text": "make this blue"}
|
|
assert body["messages"][0]["content"][1]["image_url"]["url"].startswith("data:image/png;base64,")
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_openrouter_image_generation_requires_images() -> None:
|
|
fake = FakeClient(FakeResponse({"choices": [{"message": {"content": "text only"}}]}))
|
|
client = OpenRouterImageGenerationClient(api_key="sk-or-test", client=fake) # type: ignore[arg-type]
|
|
|
|
with pytest.raises(ImageGenerationError, match="returned no images"):
|
|
await client.generate(prompt="draw", model="model")
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_openrouter_image_generation_requires_api_key() -> None:
|
|
client = OpenRouterImageGenerationClient(api_key=None)
|
|
|
|
with pytest.raises(ImageGenerationError, match="API key"):
|
|
await client.generate(prompt="draw", model="model")
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_aihubmix_image_generation_payload_and_response() -> None:
|
|
raw_b64 = PNG_DATA_URL.removeprefix("data:image/png;base64,")
|
|
fake = FakeClient(FakeResponse({"output": {"b64_json": [{"bytesBase64": raw_b64}]}}))
|
|
client = AIHubMixImageGenerationClient(
|
|
api_key="sk-ahm-test",
|
|
api_base="https://aihubmix.com/v1/",
|
|
extra_headers={"APP-Code": "nanobot"},
|
|
extra_body={"quality": "low"},
|
|
client=fake, # type: ignore[arg-type]
|
|
)
|
|
|
|
response = await client.generate(
|
|
prompt="draw a logo",
|
|
model="gpt-image-2-free",
|
|
aspect_ratio="16:9",
|
|
image_size="1K",
|
|
)
|
|
|
|
assert response.images == [PNG_DATA_URL]
|
|
call = fake.calls[0]
|
|
assert call["url"] == "https://aihubmix.com/v1/models/openai/gpt-image-2-free/predictions"
|
|
assert call["headers"]["Authorization"] == "Bearer sk-ahm-test"
|
|
assert call["headers"]["APP-Code"] == "nanobot"
|
|
assert call["json"] == {
|
|
"input": {
|
|
"prompt": "draw a logo",
|
|
"n": 1,
|
|
"size": "1536x1024",
|
|
"quality": "low",
|
|
}
|
|
}
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_aihubmix_image_edit_payload_uses_reference_images(tmp_path: Path) -> None:
|
|
raw_b64 = PNG_DATA_URL.removeprefix("data:image/png;base64,")
|
|
fake = FakeClient(FakeResponse({"output": [{"b64_json": raw_b64}]}))
|
|
ref = tmp_path / "ref.png"
|
|
ref.write_bytes(PNG_BYTES)
|
|
client = AIHubMixImageGenerationClient(
|
|
api_key="sk-ahm-test",
|
|
client=fake, # type: ignore[arg-type]
|
|
)
|
|
|
|
response = await client.generate(
|
|
prompt="edit this",
|
|
model="gpt-image-2-free",
|
|
reference_images=[str(ref)],
|
|
aspect_ratio="1:1",
|
|
)
|
|
|
|
assert response.images == [PNG_DATA_URL]
|
|
call = fake.calls[0]
|
|
assert call["url"] == "https://aihubmix.com/v1/models/openai/gpt-image-2-free/predictions"
|
|
assert call["json"]["input"]["prompt"] == "edit this"
|
|
assert call["json"]["input"]["n"] == 1
|
|
assert call["json"]["input"]["size"] == "1024x1024"
|
|
assert call["json"]["input"]["image"].startswith("data:image/png;base64,")
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_aihubmix_image_generation_downloads_url_response() -> None:
|
|
fake = FakeClient(FakeResponse({"data": [{"url": "https://cdn.example/image.png"}]}))
|
|
fake.get_response = FakeResponse({}, content=PNG_BYTES)
|
|
client = AIHubMixImageGenerationClient(
|
|
api_key="sk-ahm-test",
|
|
client=fake, # type: ignore[arg-type]
|
|
)
|
|
|
|
response = await client.generate(prompt="draw", model="gpt-image-2-free")
|
|
|
|
assert response.images[0].startswith("data:image/png;base64,")
|
|
assert fake.get_calls[0]["url"] == "https://cdn.example/image.png"
|
|
|
|
|
|
RAW_B64 = PNG_DATA_URL.removeprefix("data:image/png;base64,")
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_gemini_imagen_payload_and_response() -> None:
|
|
fake = FakeClient(
|
|
FakeResponse({"predictions": [{"bytesBase64Encoded": RAW_B64, "mimeType": "image/png"}]})
|
|
)
|
|
client = GeminiImageGenerationClient(
|
|
api_key="AIza-test",
|
|
api_base="https://generativelanguage.googleapis.com/v1beta",
|
|
client=fake, # type: ignore[arg-type]
|
|
)
|
|
|
|
response = await client.generate(
|
|
prompt="a sunset",
|
|
model="imagen-4.0-generate-001",
|
|
aspect_ratio="16:9",
|
|
)
|
|
|
|
assert response.images == [PNG_DATA_URL]
|
|
assert response.content == ""
|
|
call = fake.calls[0]
|
|
assert call["url"].endswith(":predict")
|
|
assert call["headers"]["x-goog-api-key"] == "AIza-test"
|
|
assert "params" not in call
|
|
body = call["json"]
|
|
assert body["instances"] == [{"prompt": "a sunset"}]
|
|
assert body["parameters"]["sampleCount"] == 1
|
|
assert body["parameters"]["aspectRatio"] == "16:9"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_gemini_imagen_ignores_unsupported_aspect_ratio() -> None:
|
|
fake = FakeClient(
|
|
FakeResponse({"predictions": [{"bytesBase64Encoded": RAW_B64, "mimeType": "image/png"}]})
|
|
)
|
|
client = GeminiImageGenerationClient(api_key="AIza-test", client=fake) # type: ignore[arg-type]
|
|
|
|
await client.generate(prompt="a sunset", model="imagen-4.0-generate-001", aspect_ratio="2:3")
|
|
|
|
body = fake.calls[0]["json"]
|
|
assert "aspectRatio" not in body["parameters"]
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_gemini_flash_payload_and_response() -> None:
|
|
fake = FakeClient(
|
|
FakeResponse(
|
|
{
|
|
"candidates": [
|
|
{
|
|
"content": {
|
|
"parts": [
|
|
{"text": "here is your image"},
|
|
{"inlineData": {"mimeType": "image/png", "data": RAW_B64}},
|
|
]
|
|
}
|
|
}
|
|
]
|
|
}
|
|
)
|
|
)
|
|
client = GeminiImageGenerationClient(
|
|
api_key="AIza-test",
|
|
api_base="https://generativelanguage.googleapis.com/v1beta",
|
|
client=fake, # type: ignore[arg-type]
|
|
)
|
|
|
|
response = await client.generate(
|
|
prompt="draw a cat",
|
|
model="gemini-2.0-flash-preview-image-generation",
|
|
)
|
|
|
|
assert response.images == [PNG_DATA_URL]
|
|
assert response.content == "here is your image"
|
|
call = fake.calls[0]
|
|
assert call["url"].endswith(":generateContent")
|
|
assert call["headers"]["x-goog-api-key"] == "AIza-test"
|
|
assert "params" not in call
|
|
body = call["json"]
|
|
assert body["generationConfig"]["responseModalities"] == ["TEXT", "IMAGE"]
|
|
assert body["contents"][0]["parts"][-1] == {"text": "draw a cat"}
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_gemini_flash_reference_images(tmp_path: Path) -> None:
|
|
ref = tmp_path / "ref.png"
|
|
ref.write_bytes(PNG_BYTES)
|
|
fake = FakeClient(
|
|
FakeResponse(
|
|
{
|
|
"candidates": [
|
|
{
|
|
"content": {
|
|
"parts": [{"inlineData": {"mimeType": "image/png", "data": RAW_B64}}]
|
|
}
|
|
}
|
|
]
|
|
}
|
|
)
|
|
)
|
|
client = GeminiImageGenerationClient(api_key="AIza-test", client=fake) # type: ignore[arg-type]
|
|
|
|
response = await client.generate(
|
|
prompt="edit this",
|
|
model="gemini-2.0-flash-preview-image-generation",
|
|
reference_images=[str(ref)],
|
|
)
|
|
|
|
assert response.images == [PNG_DATA_URL]
|
|
parts = fake.calls[0]["json"]["contents"][0]["parts"]
|
|
assert parts[0]["inlineData"]["mimeType"] == "image/png"
|
|
assert parts[0]["inlineData"]["data"].startswith("iVBOR")
|
|
assert parts[1] == {"text": "edit this"}
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_gemini_requires_api_key() -> None:
|
|
client = GeminiImageGenerationClient(api_key=None)
|
|
|
|
with pytest.raises(ImageGenerationError, match="API key"):
|
|
await client.generate(prompt="draw", model="imagen-4.0-generate-001")
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_gemini_no_images_raises() -> None:
|
|
fake = FakeClient(FakeResponse({"candidates": [{"content": {"parts": [{"text": "sorry"}]}}]}))
|
|
client = GeminiImageGenerationClient(api_key="AIza-test", client=fake) # type: ignore[arg-type]
|
|
|
|
with pytest.raises(ImageGenerationError, match="returned no images"):
|
|
await client.generate(prompt="draw", model="gemini-2.0-flash-preview-image-generation")
|