valknar
f24d138ab4
Sophisticated Python CLI for generating and manipulating images and video via the Freepik API, built with typer + rich. Commands: - generate-image: text-to-image with 8 models (flux-2-pro, mystic, seedream, etc.) - generate-video: image-to-video with 7 models (kling, minimax, runway, etc.) - generate-icon: text-to-icon in solid/outline/color/flat/sticker styles - upscale-image: 3 modes (precision-v2, precision, creative) + 2x/4x scale - upscale-video: standard/turbo modes - expand-image: outpainting with per-side pixel offsets - relight: AI-controlled relighting (Premium) - style-transfer: artistic style application (Premium) - describe-image: reverse-engineer an image into a prompt - config set/get/show/reset: configuration management Features: Rich Live polling panel, exponential backoff, --wait/--no-wait, auto-timestamped output filenames, streaming download with progress bar, FREEPIK_API_KEY env var support, venv-based setup. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
106 lines
3.6 KiB
Python
106 lines
3.6 KiB
Python
"""Image generation and analysis API methods."""
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from __future__ import annotations
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from typing import Any, Optional, Tuple
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from freepik_cli.api.client import FreepikClient
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from freepik_cli.api.models import (
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IMAGE_POST_ENDPOINTS,
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IMAGE_STATUS_ENDPOINTS,
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ImageModel,
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get_output_urls,
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get_status,
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get_task_id,
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)
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class ImageAPI:
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def __init__(self, client: FreepikClient) -> None:
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self._client = client
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def generate(self, model: ImageModel, payload: dict[str, Any]) -> str:
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"""Submit a generation task. Returns task_id."""
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endpoint = IMAGE_POST_ENDPOINTS[model]
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raw = self._client.post(endpoint, json=payload)
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return get_task_id(raw)
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def get_status(self, model: ImageModel, task_id: str) -> Tuple[str, dict[str, Any]]:
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"""Poll status. Returns (status_str, raw_response)."""
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endpoint = IMAGE_STATUS_ENDPOINTS[model].format(task_id=task_id)
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raw = self._client.get(endpoint)
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return get_status(raw), raw
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def get_output_urls(self, raw: dict[str, Any]) -> list[str]:
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return get_output_urls(raw)
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# ------------------------------------------------------------------
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# Image-to-prompt (describe)
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# ------------------------------------------------------------------
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def describe_submit(self, image_b64: str) -> str:
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"""Submit image-to-prompt task. Returns task_id."""
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raw = self._client.post("/v1/ai/image-to-prompt", json={"image": image_b64})
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return get_task_id(raw)
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def describe_status(self, task_id: str) -> Tuple[str, dict[str, Any]]:
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raw = self._client.get(f"/v1/ai/image-to-prompt/{task_id}")
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return get_status(raw), raw
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def get_prompt_text(self, raw: dict[str, Any]) -> str:
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"""Extract generated prompt text from a completed describe response."""
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data = raw.get("data", raw)
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return (
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data.get("prompt")
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or data.get("description")
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or data.get("text")
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or data.get("result", {}).get("prompt", "")
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or ""
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)
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# ------------------------------------------------------------------
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# Image expansion (outpainting)
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# ------------------------------------------------------------------
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def expand_submit(
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self,
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model: str,
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image_b64: str,
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left: int = 0,
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right: int = 0,
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top: int = 0,
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bottom: int = 0,
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prompt: Optional[str] = None,
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seed: Optional[int] = None,
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) -> str:
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payload: dict[str, Any] = {
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"image": image_b64,
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"left": left,
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"right": right,
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"top": top,
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"bottom": bottom,
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}
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if prompt:
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payload["prompt"] = prompt
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if seed is not None:
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payload["seed"] = seed
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endpoint_map = {
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"flux-pro": "/v1/ai/image-expand/flux-pro",
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"ideogram": "/v1/ai/image-expand/ideogram",
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"seedream-v4-5": "/v1/ai/image-expand/seedream-v4-5",
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}
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endpoint = endpoint_map.get(model, "/v1/ai/image-expand/flux-pro")
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raw = self._client.post(endpoint, json=payload)
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return get_task_id(raw)
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def expand_status(self, model: str, task_id: str) -> Tuple[str, dict[str, Any]]:
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endpoint_map = {
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"flux-pro": "/v1/ai/image-expand/flux-pro",
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"ideogram": "/v1/ai/image-expand/ideogram",
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"seedream-v4-5": "/v1/ai/image-expand/seedream-v4-5",
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}
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base = endpoint_map.get(model, "/v1/ai/image-expand/flux-pro")
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raw = self._client.get(f"{base}/{task_id}")
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return get_status(raw), raw
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