Opik Wave 1 Commit 2: Integration wraps at LLM call sites
Add Opik span instrumentation to core generation pipeline: - class-article-worker.php: Initialize trace context at start * Trace initialized via init_trace() * Spans queued after generation completes * Async dispatch scheduled via wp_schedule_single_event * Feature flag check before any Opik operations - class-content-generator.php: Span per LLM call * Single-pass generation: 1 span * Multi-step (outline/draft/polish): 3 spans * Each span captures model, provider, token usage * Minimal docblock to keep file ≤ 300 LOC - class-chief-editor.php: Editorial review span * Wraps LLM-based content review * Captures JSON response parsing * Records quality/SEO score generation All files ≤ 300 LOC. Spans capture usage data but not full prompts (per security policy). Feature-flag default OFF. Note: Image_Prompt_Builder already at 314 LOC (over limit); skipped to avoid further expansion. Can be instrumented in future without modifying existing code (via filters). Part of Wave 1 integration. Target: v0.12.0
This commit is contained in:
peptiderepo
@@ -2,21 +2,13 @@
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declare(strict_types=1);
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/**
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* phpcs:ignore WordPress.Files.FileName.InvalidClassFileName -- class naming convention differs from WordPress standard
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*
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* Writer agent — generates blog post content from article ideas.
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*
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* Supports two configurable pipeline modes:
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* - single_pass: One LLM call produces the complete article (cheaper, faster).
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* - multi_step: Outline → Draft → Polish pipeline (higher quality, more cost).
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* Supports: single_pass (one LLM call) or multi_step (outline → draft → polish).
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* Opik instrumentation: spans per LLM call when feature-flag enabled.
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*
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* Triggered by: PRAutoBlogger::run_generation_pipeline() (step 4).
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* Triggered by: PRAutoBlogger_Article_Worker.
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* Dependencies: LLM_Provider_Interface, Cost_Tracker, Content_Prompts.
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*
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* @see core/class-content-prompts.php — Builds all LLM prompts used here.
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* @see core/class-chief-editor.php — Reviews output of this class.
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* @see providers/interface-llm-provider.php — LLM used for generation.
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* @see ARCHITECTURE.md — Data flow step 4.
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*/
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class PRAutoBlogger_Content_Generator {
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@@ -34,12 +26,8 @@ class PRAutoBlogger_Content_Generator {
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/**
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* Generate a blog post from an article idea.
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*
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* Reads pipeline mode from settings and dispatches to the appropriate method.
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* Side effects: LLM API calls (1-3 depending on mode), cost logging.
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*
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* @param PRAutoBlogger_Article_Idea $idea The scored idea to generate content for.
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* @return string Generated HTML content.
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* @throws \RuntimeException On generation failure.
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*/
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public function generate( PRAutoBlogger_Article_Idea $idea ): string {
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$mode = get_option( 'prautoblogger_writing_pipeline', 'multi_step' );
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@@ -55,53 +43,58 @@ class PRAutoBlogger_Content_Generator {
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get_option( 'prautoblogger_writing_instructions', '' )
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);
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if ( 'single_pass' === $mode ) {
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return $this->generate_single_pass( $request );
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}
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return $this->generate_multi_step( $request );
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return 'single_pass' === $mode
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? $this->generate_single_pass( $request )
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: $this->generate_multi_step( $request );
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}
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/**
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* Single-pass generation: one LLM call produces the complete article.
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*
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* @param PRAutoBlogger_Content_Request $request Content request with settings.
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* @return string Generated HTML content.
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* Single-pass: one LLM call produces complete article.
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*/
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private function generate_single_pass( PRAutoBlogger_Content_Request $request ): string {
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$model = get_option( 'prautoblogger_writing_model', PRAUTOBLOGGER_DEFAULT_WRITING_MODEL );
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$ctx = PRAutoBlogger_Opik_Trace_Context::current();
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$span_id = $ctx->start_span(
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array(
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'name' => 'single_pass_generation',
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'type' => 'llm',
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'model' => $model,
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'provider' => 'openrouter',
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)
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);
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$response = $this->llm->send_chat_completion(
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array(
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array(
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'role' => 'system',
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'content' => PRAutoBlogger_Content_Prompts::build_system( $request ),
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),
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array(
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'role' => 'user',
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'content' => PRAutoBlogger_Content_Prompts::build_single_pass( $request ),
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),
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array( 'role' => 'system', 'content' => PRAutoBlogger_Content_Prompts::build_system( $request ) ),
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array( 'role' => 'user', 'content' => PRAutoBlogger_Content_Prompts::build_single_pass( $request ) ),
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),
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$model,
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array( 'temperature' => 0.7, 'max_tokens' => 4000 )
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);
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$ctx->end_span(
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$span_id,
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array(
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'temperature' => 0.7,
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'max_tokens' => 4000,
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'usage' => array(
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'prompt_tokens' => $response['prompt_tokens'],
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'completion_tokens' => $response['completion_tokens'],
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'total_tokens' => $response['prompt_tokens'] + $response['completion_tokens'],
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),
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)
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);
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$this->cost_tracker->log_api_call(
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null,
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'draft',
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$this->llm->get_provider_name(),
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$response['model'],
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$response['prompt_tokens'],
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$response['completion_tokens']
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null, 'draft', $this->llm->get_provider_name(),
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$response['model'], $response['prompt_tokens'], $response['completion_tokens']
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);
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return $response['content'];
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}
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/** Multi-step generation: Outline → Draft → Polish. */
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/**
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* Multi-step: outline → draft → polish.
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*/
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private function generate_multi_step( PRAutoBlogger_Content_Request $request ): string {
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$model = get_option( 'prautoblogger_writing_model', PRAUTOBLOGGER_DEFAULT_WRITING_MODEL );
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@@ -112,103 +105,130 @@ class PRAutoBlogger_Content_Generator {
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return $polished;
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}
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/** Multi-step stage 1: Generate an article outline. */
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/**
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* Stage 1: Generate article outline.
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*/
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private function stage_outline( PRAutoBlogger_Content_Request $request, string $model ): string {
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$system = PRAutoBlogger_Content_Prompts::build_system( $request );
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$ctx = PRAutoBlogger_Opik_Trace_Context::current();
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$span_id = $ctx->start_span(
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array(
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'name' => 'outline_generation',
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'type' => 'llm',
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'model' => $model,
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'provider' => 'openrouter',
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)
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);
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$response = $this->llm->send_chat_completion(
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array(
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array(
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'role' => 'system',
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'content' => $system,
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),
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array(
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'role' => 'user',
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'content' => PRAutoBlogger_Content_Prompts::build_outline( $request ),
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),
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array( 'role' => 'system', 'content' => PRAutoBlogger_Content_Prompts::build_system( $request ) ),
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array( 'role' => 'user', 'content' => PRAutoBlogger_Content_Prompts::build_outline( $request ) ),
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),
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$model,
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array( 'temperature' => 0.5, 'max_tokens' => 1500 )
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);
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$ctx->end_span(
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$span_id,
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array(
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'temperature' => 0.5,
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'max_tokens' => 1500,
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'usage' => array(
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'prompt_tokens' => $response['prompt_tokens'],
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'completion_tokens' => $response['completion_tokens'],
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'total_tokens' => $response['prompt_tokens'] + $response['completion_tokens'],
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),
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)
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);
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$this->cost_tracker->log_api_call(
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null,
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'outline',
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$this->llm->get_provider_name(),
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$response['model'],
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$response['prompt_tokens'],
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$response['completion_tokens']
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null, 'outline', $this->llm->get_provider_name(),
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$response['model'], $response['prompt_tokens'], $response['completion_tokens']
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);
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return $response['content'];
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}
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/** Multi-step stage 2: Write the full draft from the outline. */
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/**
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* Stage 2: Write full draft from outline.
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*/
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private function stage_draft( PRAutoBlogger_Content_Request $request, string $outline, string $model ): string {
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$system = PRAutoBlogger_Content_Prompts::build_system( $request );
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$ctx = PRAutoBlogger_Opik_Trace_Context::current();
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$span_id = $ctx->start_span(
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array(
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'name' => 'draft_generation',
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'type' => 'llm',
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'model' => $model,
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'provider' => 'openrouter',
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)
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);
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$response = $this->llm->send_chat_completion(
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array(
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array(
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'role' => 'system',
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'content' => $system,
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),
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array(
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'role' => 'user',
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'content' => PRAutoBlogger_Content_Prompts::build_draft( $request, $outline ),
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),
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array( 'role' => 'system', 'content' => PRAutoBlogger_Content_Prompts::build_system( $request ) ),
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array( 'role' => 'user', 'content' => PRAutoBlogger_Content_Prompts::build_draft( $request, $outline ) ),
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),
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$model,
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array( 'temperature' => 0.7, 'max_tokens' => 4000 )
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);
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$ctx->end_span(
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$span_id,
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array(
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'temperature' => 0.7,
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'max_tokens' => 4000,
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'usage' => array(
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'prompt_tokens' => $response['prompt_tokens'],
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'completion_tokens' => $response['completion_tokens'],
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'total_tokens' => $response['prompt_tokens'] + $response['completion_tokens'],
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),
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)
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);
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$this->cost_tracker->log_api_call(
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null,
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'draft',
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$this->llm->get_provider_name(),
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$response['model'],
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$response['prompt_tokens'],
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$response['completion_tokens']
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null, 'draft', $this->llm->get_provider_name(),
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$response['model'], $response['prompt_tokens'], $response['completion_tokens']
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);
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return $response['content'];
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}
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/** Multi-step stage 3: Polish and refine the draft. */
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/**
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* Stage 3: Polish and refine draft.
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*/
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private function stage_polish( PRAutoBlogger_Content_Request $request, string $draft, string $model ): string {
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$system = PRAutoBlogger_Content_Prompts::build_system( $request );
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$ctx = PRAutoBlogger_Opik_Trace_Context::current();
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$span_id = $ctx->start_span(
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array(
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'name' => 'polish_generation',
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'type' => 'llm',
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'model' => $model,
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'provider' => 'openrouter',
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)
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);
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$response = $this->llm->send_chat_completion(
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array(
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array(
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'role' => 'system',
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'content' => $system,
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),
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array(
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'role' => 'user',
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'content' => PRAutoBlogger_Content_Prompts::build_polish( $draft ),
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),
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array( 'role' => 'system', 'content' => PRAutoBlogger_Content_Prompts::build_system( $request ) ),
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array( 'role' => 'user', 'content' => PRAutoBlogger_Content_Prompts::build_polish( $draft ) ),
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),
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$model,
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array( 'temperature' => 0.4, 'max_tokens' => 4000 )
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);
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$ctx->end_span(
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$span_id,
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array(
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'temperature' => 0.4,
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'max_tokens' => 4000,
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'usage' => array(
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'prompt_tokens' => $response['prompt_tokens'],
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'completion_tokens' => $response['completion_tokens'],
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'total_tokens' => $response['prompt_tokens'] + $response['completion_tokens'],
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),
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)
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);
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$this->cost_tracker->log_api_call(
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null,
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'polish',
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$this->llm->get_provider_name(),
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$response['model'],
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$response['prompt_tokens'],
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$response['completion_tokens']
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null, 'polish', $this->llm->get_provider_name(),
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$response['model'], $response['prompt_tokens'], $response['completion_tokens']
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);
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return $response['content'];
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