Files
prautoblogger/includes/core/class-image-prompt-builder.php
peptiderepo c8595e05de Fix duplicate image, remove hardcoded model references
Three fixes in one:

1. Duplicate image: prepend_caption_to_post() was embedding the full
   image + caption as a <figure> block, but the theme already displays
   the featured image. Now only the caption text is prepended — no
   second copy of the image.

2. Hardcoded model names: removed all FLUX.1/FLUX.2 references from
   model-agnostic code (pipeline, prompt builder, sideloader, OpenRouter
   provider, interface, admin labels). The Cloudflare provider still
   references FLUX since it specifically wraps that model family.

3. Test alignment: OpenRouterImagePricingTest was asserting against
   removed models (flux-2-pro, seedream). Updated to match current
   COST_PER_IMAGE entries (Gemini Flash, GPT-5 Image).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-18 16:08:36 +07:00

294 lines
10 KiB
PHP

<?php
declare(strict_types=1);
/**
* Builds image prompts from article content or source data.
*
* Uses a cheap LLM (via OpenRouter) to distill article content into concise
* visual scene descriptions optimised for image generation. Falls back to rule-based
* synthesis if the LLM call fails, so image generation never blocks on a
* prompt-rewriting outage.
*
* Triggered by: PRAutoBlogger_Image_Pipeline during content generation run.
* Dependencies: PRAutoBlogger_OpenRouter_Provider (LLM call),
* PRAutoBlogger_Cost_Tracker (logs prompt-rewrite cost),
* PRAutoBlogger_Logger (diagnostics).
*
* @see core/class-image-pipeline.php — Consumes build_article_prompt() and build_source_prompt().
* @see providers/class-open-router-provider.php — LLM provider used for rewriting.
* @see ARCHITECTURE.md — Image generation data flow.
*/
class PRAutoBlogger_Image_Prompt_Builder {
/**
* System prompt that teaches the LLM how to write image-gen prompts.
*
* Why this lives here instead of in wp_options: it's engineering-level
* instruction, not a user-facing setting. Changing it should require a
* code review, not an admin-panel click.
*/
private const REWRITER_SYSTEM_PROMPT = <<<'PROMPT'
You are a comedy writer and single-panel cartoon creator, like Gary Larson (The Far Side) meets science humor.
Given an article title and summary about peptides, supplements, or biohacking, create a SINGLE-PANEL COMIC concept. Output TWO parts separated by a blank line:
SCENE: One sentence describing the visual gag — a funny, absurd, or ironic situation related to the article's topic. Use anthropomorphized molecules, lab-coat-wearing animals, befuddled scientists, gym bros encountering peptide science, supplement bottles with personality, or everyday situations with a peptide twist. Keep it simple — one clear visual joke, 1-3 characters max.
CAPTION: A short, punchy caption or speech bubble line (under 15 words) that delivers the punchline. The humor should be dry, nerdy, and accessible — the reader should chuckle even if they only half-understand the science.
Rules:
- The joke MUST relate to the article's actual subject matter, not generic science humor
- Characters can have simple cartoon faces (round heads, dot eyes, expressive eyebrows)
- Keep the scene physically simple — few objects, clear staging, easy to read at thumbnail size
- The caption should work as a standalone joke even without the image
- No logos, watermarks, or branding
- Output ONLY the scene and caption. No preamble, no explanation.
Example output format:
A muscular gym bro stares in confusion at a tiny vial while a peptide molecule with arms and legs flexes next to him, clearly outperforming him.
"I've been doing this wrong for three years."
PROMPT;
/**
* Max tokens for the rewriter response. Comic concepts need more room
* for the scene description plus the caption punchline.
*/
private const REWRITER_MAX_TOKENS = 180;
/**
* OpenRouter provider for LLM calls. Null until first use.
*
* @var PRAutoBlogger_OpenRouter_Provider|null
*/
private ?PRAutoBlogger_OpenRouter_Provider $llm = null;
/**
* Build a visual prompt from finished article content.
*
* Tries LLM rewriting first; falls back to rule-based synthesis on failure.
* Separates the scene description (for image gen) from the caption text
* (for insertion below the image as HTML). Appends style suffix to the
* scene-only prompt so no text is rendered inside the image.
*
* @param array{
* post_title?: string,
* post_content?: string,
* suggested_title?: string,
* } $article_data Article data with title and HTML content.
*
* @return array{prompt: string, caption: string} Image prompt (scene + style) and caption text.
*/
public function build_article_prompt( array $article_data ): array {
$title = $article_data['post_title'] ?? $article_data['suggested_title'] ?? 'Product';
$content = $article_data['post_content'] ?? '';
$first_para = $this->extract_first_paragraph( $content );
$parsed = $this->rewrite_via_llm( $title, $first_para );
$style_suffix = get_option( 'prautoblogger_image_style_suffix', PRAUTOBLOGGER_DEFAULT_IMAGE_STYLE_SUFFIX );
return [
'prompt' => trim( $parsed['scene'] . ' ' . $style_suffix ),
'caption' => $parsed['caption'],
];
}
/**
* Build a visual prompt from source Reddit thread data.
*
* Tries LLM rewriting first; falls back to rule-based synthesis on failure.
* Appends the style suffix from plugin options.
*
* @param array{
* title?: string,
* selftext?: string,
* comments?: string[],
* } $source_data Reddit source data with title and comments.
*
* @return array{prompt: string, caption: string} Image prompt (scene + style) and caption text.
*/
public function build_source_prompt( array $source_data ): array {
$title = $source_data['title'] ?? 'Reddit Discussion';
$comments = $source_data['comments'] ?? [];
$context = is_array( $comments ) && ! empty( $comments ) ? $comments[0] : '';
$parsed = $this->rewrite_via_llm( $title, $context );
$style_suffix = get_option( 'prautoblogger_image_style_suffix', PRAUTOBLOGGER_DEFAULT_IMAGE_STYLE_SUFFIX );
return [
'prompt' => trim( $parsed['scene'] . ' ' . $style_suffix ),
'caption' => $parsed['caption'],
];
}
/**
* Use a cheap LLM to distill title + context into a visual scene + caption.
*
* The LLM response contains a SCENE line and a CAPTION line separated by a
* blank line. This method parses them apart so the scene drives image gen
* (no text baked in) and the caption is inserted as HTML below the image.
*
* Falls back to rule-based synthesis if the LLM call fails for any
* reason (network, auth, timeout, unexpected response shape).
*
* Side effects: one OpenRouter API call; one cost-tracker log entry.
*
* @param string $title Article or thread title.
* @param string $context First paragraph or top comment.
* @return array{scene: string, caption: string} Scene for image gen, caption for HTML.
*/
private function rewrite_via_llm( string $title, string $context ): array {
$title = trim( sanitize_text_field( $title ) );
$context = trim( sanitize_text_field( $context ) );
// Truncate context to keep prompt tokens low.
if ( strlen( $context ) > 300 ) {
$context = substr( $context, 0, 300 ) . '...';
}
$user_message = "Article title: {$title}";
if ( '' !== $context ) {
$user_message .= "\n\nSummary: {$context}";
}
try {
$llm = $this->get_llm_provider();
$model = get_option( 'prautoblogger_analysis_model', PRAUTOBLOGGER_DEFAULT_ANALYSIS_MODEL );
$result = $llm->send_chat_completion(
[
[ 'role' => 'system', 'content' => self::REWRITER_SYSTEM_PROMPT ],
[ 'role' => 'user', 'content' => $user_message ],
],
$model,
[
'temperature' => 0.7,
'max_tokens' => self::REWRITER_MAX_TOKENS,
]
);
$raw = trim( $result['content'] ?? '' );
// Log the rewrite cost so it shows in the analytics dashboard.
( new PRAutoBlogger_Cost_Tracker() )->log_api_call(
null,
'image_prompt_rewrite',
'openrouter',
$model,
$result['prompt_tokens'] ?? 0,
$result['completion_tokens'] ?? 0
);
$cost = $llm->estimate_cost(
$model,
$result['prompt_tokens'] ?? 0,
$result['completion_tokens'] ?? 0
);
PRAutoBlogger_Logger::instance()->debug(
sprintf( 'Image prompt rewritten (%d→%d chars, $%.6f): %s', strlen( $user_message ), strlen( $raw ), $cost, substr( $raw, 0, 120 ) ),
'image_prompt_builder'
);
if ( '' !== $raw ) {
return $this->parse_scene_and_caption( $raw );
}
} catch ( \Throwable $e ) {
// LLM failure is not fatal — fall back to rule-based synthesis.
PRAutoBlogger_Logger::instance()->warning(
sprintf( 'Image prompt LLM rewrite %s, using fallback: %s', get_class( $e ), $e->getMessage() ),
'image_prompt_builder'
);
}
return $this->synthesize_visual_concepts_fallback( $title, $context );
}
/**
* Parse the LLM response into separate scene and caption parts.
*
* Expected format from the LLM:
* Scene description text here.
*
* "Caption punchline here."
*
* Falls back gracefully: if no blank-line separator is found, the entire
* response becomes the scene with an empty caption.
*
* @param string $raw Raw LLM response text.
* @return array{scene: string, caption: string}
*/
private function parse_scene_and_caption( string $raw ): array {
// Split on blank line (the format the system prompt requests).
$parts = preg_split( '/\n\s*\n/', $raw, 2 );
if ( count( $parts ) >= 2 ) {
$scene = trim( $parts[0] );
$caption = trim( $parts[1] );
// Strip surrounding quotes from caption — the LLM wraps it in quotes.
$caption = trim( $caption, '"\'' );
return [ 'scene' => $scene, 'caption' => $caption ];
}
// No blank-line separator found — treat entire response as scene.
return [ 'scene' => trim( $raw ), 'caption' => '' ];
}
/**
* Extract the first paragraph from HTML content.
*
* Removes all tags and captures the text up to the first double-newline
* or 200 characters, whichever comes first.
*
* @param string $html HTML content.
* @return string Plain text of the first paragraph.
*/
private function extract_first_paragraph( string $html ): string {
$text = wp_strip_all_tags( $html );
$paras = preg_split( '/\n\n+/', $text );
$para = isset( $paras[0] ) ? trim( $paras[0] ) : '';
if ( strlen( $para ) > 200 ) {
$para = substr( $para, 0, 200 ) . '...';
}
return $para;
}
/**
* Rule-based fallback when LLM rewriting is unavailable.
*
* Kept deliberately simple — this only runs if OpenRouter is down.
*
* @param string $title Main heading / topic.
* @param string $supporting_text Additional context.
* @return array{scene: string, caption: string} Scene for image gen, caption for HTML.
*/
private function synthesize_visual_concepts_fallback( string $title, string $supporting_text ): array {
// Fallback produces a simple comic concept when the LLM is unavailable.
$scene = sprintf(
'A cartoon scientist in a lab coat looking bewildered while examining something related to: %s.',
$title
);
return [
'scene' => trim( $scene ),
'caption' => 'Science is full of surprises.',
];
}
/**
* Lazy-load the OpenRouter provider.
*
* @return PRAutoBlogger_OpenRouter_Provider
*/
private function get_llm_provider(): PRAutoBlogger_OpenRouter_Provider {
if ( null === $this->llm ) {
$this->llm = new PRAutoBlogger_OpenRouter_Provider();
}
return $this->llm;
}
}