377 lines
12 KiB
Python
377 lines
12 KiB
Python
from __future__ import annotations
|
|
|
|
from typing import Any, Mapping
|
|
|
|
import requests
|
|
|
|
from .base import (
|
|
AiCapabilityError,
|
|
AiResponseParseError,
|
|
ImageGenerationResult,
|
|
ResolvedModel,
|
|
TextGenerationResult,
|
|
validate_model_config,
|
|
)
|
|
from .utils import (
|
|
API_CHAT,
|
|
API_GEMINI,
|
|
API_IMAGES,
|
|
API_IMAGES_EDITS,
|
|
extract_image_from_response,
|
|
extract_text_from_response,
|
|
extract_titles_from_response,
|
|
image_bytes_to_data_url,
|
|
normalize_api_url,
|
|
request_timeout,
|
|
resolution_to_size,
|
|
split_data_url,
|
|
)
|
|
|
|
|
|
class BaseHttpProvider:
|
|
def __init__(self, session: requests.Session | None = None):
|
|
self.session = session or requests.Session()
|
|
if hasattr(self.session, "trust_env"):
|
|
self.session.trust_env = False
|
|
|
|
def _headers(self, model: ResolvedModel, *, json: bool = False) -> dict[str, str]:
|
|
headers = {"Authorization": f"Bearer {model.api_key}"}
|
|
if json:
|
|
headers["Content-Type"] = "application/json"
|
|
return headers
|
|
|
|
def _timeout(self, model: ResolvedModel, resolution: str) -> tuple[int, int]:
|
|
return request_timeout(
|
|
model.connect_timeout_seconds,
|
|
model.timeout_seconds,
|
|
resolution,
|
|
)
|
|
|
|
def _read_timeout(self, model: ResolvedModel, resolution: str) -> int:
|
|
return self._timeout(model, resolution)[1]
|
|
|
|
|
|
class ChatCompletionsProvider(BaseHttpProvider):
|
|
def capabilities(self) -> set[str]:
|
|
return {"text", "image", "vision"}
|
|
|
|
def generate_text(
|
|
self,
|
|
prompt: str,
|
|
model: ResolvedModel,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
resolution: str = "1K",
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> TextGenerationResult:
|
|
validate_model_config(model)
|
|
url = normalize_api_url(model.url, API_CHAT)
|
|
payload = build_chat_text_payload(
|
|
model,
|
|
prompt,
|
|
image=image,
|
|
image_mime_type=image_mime_type,
|
|
parameters=parameters,
|
|
)
|
|
response = self.session.post(
|
|
url,
|
|
headers=self._headers(model, json=True),
|
|
json=payload,
|
|
timeout=self._timeout(model, resolution),
|
|
)
|
|
response.raise_for_status()
|
|
raw = response.json()
|
|
titles = extract_titles_from_response(raw)
|
|
text = extract_text_from_response(raw)
|
|
if not text:
|
|
raise AiResponseParseError("AI response did not contain text")
|
|
return TextGenerationResult(text=text, titles=titles, model_used=model.model, raw=raw)
|
|
|
|
def generate_image(
|
|
self,
|
|
prompt: str,
|
|
model: ResolvedModel,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
image_filename: str = "image.png",
|
|
resolution: str = "1K",
|
|
aspect_ratio: str = "1:1",
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> ImageGenerationResult:
|
|
validate_model_config(model)
|
|
url = normalize_api_url(model.url, API_CHAT)
|
|
payload = build_chat_image_payload(
|
|
model,
|
|
prompt,
|
|
image=image,
|
|
image_mime_type=image_mime_type,
|
|
parameters=parameters,
|
|
)
|
|
response = self.session.post(
|
|
url,
|
|
headers=self._headers(model, json=True),
|
|
json=payload,
|
|
timeout=self._timeout(model, resolution),
|
|
)
|
|
response.raise_for_status()
|
|
raw = response.json()
|
|
image_bytes = extract_image_from_response(
|
|
raw,
|
|
session=self.session,
|
|
timeout=self._read_timeout(model, resolution),
|
|
)
|
|
if not image_bytes:
|
|
raise AiResponseParseError("AI response did not contain an image")
|
|
return ImageGenerationResult(image=image_bytes, model_used=model.model, raw=raw)
|
|
|
|
|
|
class GeminiProvider(ChatCompletionsProvider):
|
|
def generate_text(
|
|
self,
|
|
prompt: str,
|
|
model: ResolvedModel,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
resolution: str = "1K",
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> TextGenerationResult:
|
|
validate_model_config(model)
|
|
url = normalize_api_url(model.url, API_GEMINI).replace("{model}", model.model)
|
|
payload = build_gemini_payload(
|
|
model,
|
|
prompt,
|
|
image=image,
|
|
image_mime_type=image_mime_type,
|
|
response_modalities=["TEXT"],
|
|
parameters=parameters,
|
|
)
|
|
response = self.session.post(
|
|
url,
|
|
headers=self._headers(model, json=True),
|
|
json=payload,
|
|
timeout=self._timeout(model, resolution),
|
|
)
|
|
response.raise_for_status()
|
|
raw = response.json()
|
|
titles = extract_titles_from_response(raw)
|
|
text = extract_text_from_response(raw)
|
|
if not text:
|
|
raise AiResponseParseError("AI response did not contain text")
|
|
return TextGenerationResult(text=text, titles=titles, model_used=model.model, raw=raw)
|
|
|
|
def generate_image(
|
|
self,
|
|
prompt: str,
|
|
model: ResolvedModel,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
image_filename: str = "image.png",
|
|
resolution: str = "1K",
|
|
aspect_ratio: str = "1:1",
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> ImageGenerationResult:
|
|
validate_model_config(model)
|
|
url = normalize_api_url(model.url, API_GEMINI).replace("{model}", model.model)
|
|
payload = build_gemini_payload(
|
|
model,
|
|
prompt,
|
|
image=image,
|
|
image_mime_type=image_mime_type,
|
|
response_modalities=["TEXT", "IMAGE"],
|
|
parameters=parameters,
|
|
)
|
|
response = self.session.post(
|
|
url,
|
|
headers=self._headers(model, json=True),
|
|
json=payload,
|
|
timeout=self._timeout(model, resolution),
|
|
)
|
|
response.raise_for_status()
|
|
raw = response.json()
|
|
image_bytes = extract_image_from_response(
|
|
raw,
|
|
session=self.session,
|
|
timeout=self._read_timeout(model, resolution),
|
|
)
|
|
if not image_bytes:
|
|
raise AiResponseParseError("AI response did not contain an image")
|
|
return ImageGenerationResult(image=image_bytes, model_used=model.model, raw=raw)
|
|
|
|
|
|
class ImagesGenerationProvider(BaseHttpProvider):
|
|
def capabilities(self) -> set[str]:
|
|
return {"image"}
|
|
|
|
def generate_text(self, *args: Any, **kwargs: Any) -> TextGenerationResult:
|
|
raise AiCapabilityError("images generation provider cannot generate text")
|
|
|
|
def generate_image(
|
|
self,
|
|
prompt: str,
|
|
model: ResolvedModel,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
image_filename: str = "image.png",
|
|
resolution: str = "1K",
|
|
aspect_ratio: str = "1:1",
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> ImageGenerationResult:
|
|
validate_model_config(model)
|
|
url = normalize_api_url(model.url, API_IMAGES)
|
|
payload: dict[str, Any] = {
|
|
"model": model.model,
|
|
"prompt": prompt,
|
|
"aspect_ratio": aspect_ratio,
|
|
"resolution": resolution,
|
|
"n": 1,
|
|
}
|
|
if image is not None:
|
|
payload["image_urls"] = [image_bytes_to_data_url(image, image_mime_type)]
|
|
apply_extra_body(payload, model, parameters)
|
|
response = self.session.post(
|
|
url,
|
|
headers=self._headers(model, json=True),
|
|
json=payload,
|
|
timeout=self._timeout(model, resolution),
|
|
)
|
|
response.raise_for_status()
|
|
raw = response.json()
|
|
image_bytes = extract_image_from_response(
|
|
raw,
|
|
session=self.session,
|
|
timeout=self._read_timeout(model, resolution),
|
|
)
|
|
if not image_bytes:
|
|
raise AiResponseParseError("AI response did not contain an image")
|
|
return ImageGenerationResult(image=image_bytes, model_used=model.model, raw=raw)
|
|
|
|
|
|
class ImagesEditsProvider(BaseHttpProvider):
|
|
def capabilities(self) -> set[str]:
|
|
return {"image", "vision"}
|
|
|
|
def generate_text(self, *args: Any, **kwargs: Any) -> TextGenerationResult:
|
|
raise AiCapabilityError("images edits provider cannot generate text")
|
|
|
|
def generate_image(
|
|
self,
|
|
prompt: str,
|
|
model: ResolvedModel,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
image_filename: str = "image.png",
|
|
resolution: str = "1K",
|
|
aspect_ratio: str = "1:1",
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> ImageGenerationResult:
|
|
validate_model_config(model)
|
|
if image is None:
|
|
raise AiCapabilityError("images edits provider requires an input image")
|
|
|
|
url = normalize_api_url(model.url, API_IMAGES_EDITS)
|
|
data: dict[str, Any] = {
|
|
"model": model.model,
|
|
"prompt": prompt,
|
|
"n": "1",
|
|
"size": resolution_to_size(resolution),
|
|
}
|
|
apply_extra_body(data, model, parameters)
|
|
files = {"image": (image_filename, image, image_mime_type)}
|
|
response = self.session.post(
|
|
url,
|
|
headers=self._headers(model),
|
|
data=data,
|
|
files=files,
|
|
timeout=self._timeout(model, resolution),
|
|
)
|
|
response.raise_for_status()
|
|
raw = response.json()
|
|
image_bytes = extract_image_from_response(
|
|
raw,
|
|
session=self.session,
|
|
timeout=self._read_timeout(model, resolution),
|
|
)
|
|
if not image_bytes:
|
|
raise AiResponseParseError("AI response did not contain an image")
|
|
return ImageGenerationResult(image=image_bytes, model_used=model.model, raw=raw)
|
|
|
|
|
|
def build_chat_text_payload(
|
|
model: ResolvedModel,
|
|
prompt: str,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> dict[str, Any]:
|
|
content: list[dict[str, Any]] = [{"type": "text", "text": prompt}]
|
|
if image is not None:
|
|
content.append(
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": image_bytes_to_data_url(image, image_mime_type)},
|
|
}
|
|
)
|
|
payload: dict[str, Any] = {
|
|
"model": model.model,
|
|
"messages": [{"role": "user", "content": content}],
|
|
"stream": False,
|
|
}
|
|
apply_extra_body(payload, model, parameters)
|
|
return payload
|
|
|
|
|
|
def build_chat_image_payload(
|
|
model: ResolvedModel,
|
|
prompt: str,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> dict[str, Any]:
|
|
return build_chat_text_payload(
|
|
model,
|
|
prompt,
|
|
image=image,
|
|
image_mime_type=image_mime_type,
|
|
parameters=parameters,
|
|
)
|
|
|
|
|
|
def build_gemini_payload(
|
|
model: ResolvedModel,
|
|
prompt: str,
|
|
*,
|
|
image: bytes | None = None,
|
|
image_mime_type: str = "image/png",
|
|
response_modalities: list[str],
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> dict[str, Any]:
|
|
parts: list[dict[str, Any]] = [{"text": prompt}]
|
|
if image is not None:
|
|
data_url = image_bytes_to_data_url(image, image_mime_type)
|
|
mime_type, data = split_data_url(data_url)
|
|
parts.append({"inlineData": {"mimeType": mime_type, "data": data}})
|
|
payload: dict[str, Any] = {
|
|
"contents": [{"parts": parts}],
|
|
"generationConfig": {"responseModalities": response_modalities},
|
|
}
|
|
apply_extra_body(payload, model, parameters)
|
|
return payload
|
|
|
|
|
|
def apply_extra_body(
|
|
payload: dict[str, Any],
|
|
model: ResolvedModel,
|
|
parameters: Mapping[str, Any] | None = None,
|
|
) -> None:
|
|
payload.update(model.extra_body)
|
|
if parameters:
|
|
payload.update(dict(parameters))
|