# thinkrank/2.10.0/includes/ai/class-openai-client.php ThinkRank AI SEO – AI SEO Plugin for WordPress: Schema, XML Sitemaps, Meta Tags, Search Console & Local SEO, version 2.10.0. 1,257 lines. - Page: https://pluginprobe.com/plugins/thinkrank/2.10.0/code/includes/ai/class-openai-client.php - Raw: https://pluginprobe.com/plugins/thinkrank/2.10.0/raw/includes/ai/class-openai-client.php - Modified: 2026-09-27T11:16:58+00:00 Line numbers below start at 1. Link to a line or a range by appending a fragment to the page URL, for example `https://pluginprobe.com/plugins/thinkrank/2.10.0/code/includes/ai/class-openai-client.php#L10-L20`. ```php api_key = $api_key; $this->model = $model; $this->timeout = $timeout; $base_url = rtrim(trim($base_url), '/'); $this->base_url = '' !== $base_url ? $base_url : self::API_BASE_URL; } /** * Turn on response_format: json_object for calls that want a JSON object. * * ThinkRank otherwise enforces JSON through the prompt alone, and a small * local model then writes an unescaped quote inside a string (DeepSeek-R1 * 7B quoting a phrase in the brief's HTML body) and the whole brief fails * to parse. Ollama, vLLM and llama.cpp turn this field into a grammar, so * the reply cannot be malformed JSON. Only calls passing the `json_object` * option get it: a plain-text caller would be forced into JSON too. * * @since 2.8.0 * * @param bool $enabled Whether the endpoint accepts response_format json_object. * @return void */ public function set_json_mode(bool $enabled): void { $this->json_mode = $enabled; } /** * Get the base URL this client talks to. * * @since 2.8.0 * * @return string Base URL without a trailing slash. */ public function get_base_url(): string { return $this->base_url; } /** * Is this client pointed at a server other than OpenAI's? * * Used for error copy: naming "OpenAI" in a failure from someone's local * Ollama box sends them to the wrong place to debug it. * * @since 2.8.0 * * @return bool */ private function is_custom_endpoint(): bool { return self::API_BASE_URL !== $this->base_url; } /** * Name to use for this endpoint in user-facing messages. * * @since 2.8.0 * * @return string */ private function get_endpoint_label(): string { if (!$this->is_custom_endpoint()) { return 'OpenAI'; } $host = wp_parse_url($this->base_url, PHP_URL_HOST); return is_string($host) && '' !== $host ? $host : __('the AI endpoint', 'thinkrank'); } /** * Get Prompt Builder instance * * @since 1.0.0 * * @return Prompt_Builder Prompt Builder instance */ private function get_prompt_builder(): Prompt_Builder { if (!$this->prompt_builder) { // Ensure Prompt Builder is loaded if (!class_exists('ThinkRank\\AI\\Prompt_Builder')) { require_once THINKRANK_PLUGIN_DIR . 'includes/ai/class-prompt-builder.php'; } $this->prompt_builder = new Prompt_Builder(); } return $this->prompt_builder; } /** * Generate completion using OpenAI * * @param string $prompt The prompt to send * @param array $options Additional options * @return array Response data * @throws \Exception If API request fails */ public function generate_completion(string $prompt, array $options = []): array { $default_options = [ 'model' => $this->model, 'max_tokens' => 1000, 'temperature' => 0.7, 'top_p' => 1, 'frequency_penalty' => 0, 'presence_penalty' => 0, ]; $options = array_merge($default_options, $options); $body = $this->build_chat_completion_body($prompt, $options); return $this->make_request('chat/completions', $body); } /** * Build the chat/completions request body for the given (merged) options. * * Extracted so the per-model-family parameter handling is unit-testable: * reasoning models take max_completion_tokens (and only the GPT-5 family * accepts reasoning_effort — o1/o3 reject it), while standard models take * temperature/top_p/penalties/max_tokens. Keeping this in one place stops a * future refactor from silently regressing the GPT-5-only guard (issue #286). * * @param string $prompt User prompt. * @param array $options Merged options (must include model, max_tokens, and * the sampling defaults; reasoning_effort and * json_object optional). * @return array Request body for the chat/completions endpoint. */ private function build_chat_completion_body(string $prompt, array $options): array { $body = [ 'model' => $options['model'], 'messages' => [ [ 'role' => 'user', 'content' => $prompt, ] ], ]; // Get safe token limit for this model $safe_tokens = $this->get_safe_token_limit($options['model'], $options['max_tokens']); // Add parameters based on model type if ($this->is_reasoning_model($options['model'])) { // Reasoning models (o1/o3) have fixed parameters and restricted support // temperature, top_p, frequency_penalty, presence_penalty are not supported $body['max_completion_tokens'] = $safe_tokens; // GPT-5 models accept reasoning_effort ('minimal'…'high'). Callers // wanting a quick answer pass a low level so hidden reasoning // can't consume the whole completion budget and return empty // text. Only the GPT-5 // family gets it: o1 rejects the parameter outright. if (isset($options['reasoning_effort']) && str_starts_with($options['model'], 'gpt-5')) { $body['reasoning_effort'] = (string) $options['reasoning_effort']; } } else { // Standard models support all parameters $body['temperature'] = $options['temperature']; $body['top_p'] = $options['top_p']; $body['frequency_penalty'] = $options['frequency_penalty']; $body['presence_penalty'] = $options['presence_penalty']; $body['max_tokens'] = $safe_tokens; } if ($this->json_mode && $this->is_custom_endpoint() && !empty($options['json_object'])) { $body['response_format'] = ['type' => 'json_object']; } return $body; } /** * Generate SEO metadata * * @param string $content Content to analyze * @param array $options Generation options * @return array Generated metadata * @throws \Exception If generation fails */ public function generate_seo_metadata(string $content, array $options = []): array { $target_keyword = $options['target_keyword'] ?? ''; $content_type = $options['content_type'] ?? 'blog_post'; $tone = $options['tone'] ?? 'professional'; $prompt_builder = $this->get_prompt_builder(); $language = is_string($options['language'] ?? null) ? $options['language'] : ''; $prompt = $prompt_builder->build_seo_prompt($content, $target_keyword, $content_type, $tone, 'openai', $language); $response = $this->generate_completion($prompt, [ 'max_tokens' => $this->get_recommended_tokens('seo_metadata'), 'temperature' => 0.3, // Lower temperature for more consistent SEO output 'json_object' => true, ]); return $this->parse_seo_response($response); } /** * Analyze content for SEO optimization * * @param string $content Content to analyze * @param array $metadata Existing metadata * @return array Analysis results * @throws \Exception If analysis fails */ public function analyze_content(string $content, array $metadata = []): array { $prompt_builder = $this->get_prompt_builder(); $prompt = $prompt_builder->build_analysis_prompt($content, $metadata, 'openai'); $response = $this->generate_completion($prompt, [ 'max_tokens' => $this->get_recommended_tokens('analysis'), 'temperature' => 0.3, // Lower temperature for more consistent analysis 'json_object' => true, ]); return $this->parse_analysis_response($response); } private function is_reasoning_model(string $model): bool { // Models that require max_completion_tokens and restrict parameters (no temperature/top_p) // Includes OpenAI o1/o3 series and GPT-5 family $reasoning_models = [ 'o1-preview', 'o1-mini', 'o3-mini', 'o3-2024-12-17', 'gpt-5', 'gpt-5-mini', 'gpt-5-nano', ]; // Check for exact matches or model prefixes foreach ($reasoning_models as $reasoning_model) { if ($model === $reasoning_model || strpos($model, $reasoning_model) === 0) { return true; } } return false; } /** * Get maximum completion tokens for a model * * @param string $model Model name * @return int Maximum completion tokens */ private function get_max_completion_tokens(string $model): int { // Model-specific token limits (completion tokens, not context) $token_limits = [ // GPT-5 series (optimized for reasoning + content tokens based on usage data) 'gpt-5' => 20480, // 20K tokens for full GPT-5 'gpt-5-mini' => 15360, // 15K tokens for mini variant (increased) 'gpt-5-nano' => 12288, // 12K tokens for nano (increased from 10K for better buffer) // GPT-4o series 'gpt-4o' => 4096, 'gpt-4o-2024-08-06' => 4096, 'gpt-4o-2024-05-13' => 4096, 'gpt-4o-mini' => 16384, 'gpt-4o-mini-2024-07-18' => 16384, // o1/o3 reasoning models (higher limits) 'o1-preview' => 32768, 'o1-mini' => 65536, 'o3-mini' => 65536, 'o3-2024-12-17' => 65536, ]; // Check for exact match first if (isset($token_limits[$model])) { return $token_limits[$model]; } // Check for partial matches (for versioned models) foreach ($token_limits as $known_model => $limit) { if (strpos($model, $known_model) === 0) { return $limit; } } // A model we have never heard of on OpenAI's own API gets a // conservative ceiling. On a user-named server nearly every model is // unknown, and 4096 left a brief ~2.9K tokens after length scaling, // which a reasoning model (DeepSeek-R1, Qwen3) spends half of thinking // before the JSON starts. max_tokens is a cap, not a reservation, so a // higher one costs nothing on a model that finishes early. if ($this->is_custom_endpoint()) { /** * Filters the output-token ceiling for an unrecognised model on an * OpenAI-compatible endpoint. * * Lower it for a server that rejects max_tokens beyond its context * window (vLLM does); raise it for a large-context local model. * * @since 2.8.0 * * @param int $limit Ceiling in tokens. Default 8192. * @param string $model Model id sent to the endpoint. */ $limit = (int) apply_filters('thinkrank_openai_compatible_max_output_tokens', self::COMPATIBLE_DEFAULT_MAX_TOKENS, $model); return $limit > 0 ? $limit : self::COMPATIBLE_DEFAULT_MAX_TOKENS; } // Default fallback for unknown models return 4096; } /** * Get safe token limit for a request * * @param string $model Model name * @param int $requested_tokens Requested token count * @return int Safe token count (capped at model limit) */ public function get_safe_token_limit(string $model, int $requested_tokens): int { $max_tokens = $this->get_max_completion_tokens($model); return min($requested_tokens, $max_tokens); } /** * Get recommended token limit for specific use cases * * @param string $use_case Use case (e.g., 'content_brief', 'seo_metadata', 'analysis') * @return int Recommended token limit */ public function get_recommended_tokens(string $use_case): int { $max_tokens = $this->get_max_completion_tokens($this->model); // For reasoning models (GPT-5, o1, o3), we need much higher token limits // because they use reasoning tokens + content tokens if ($this->is_reasoning_model($this->model)) { $reasoning_recommendations = [ 'content_brief' => 0.95, // 95% of max tokens (reasoning + content) 'seo_metadata' => 0.8, // 80% for reasoning models (safe buffer) 'analysis' => 0.85, // 85% for reasoning models (safe buffer) 'llms_txt' => 0.8, // 80% for reasoning models (safe buffer) 'optimization' => 0.9, // 90% for reasoning models (based on 5.9K usage + 50% buffer) ]; $percentage = $reasoning_recommendations[$use_case] ?? 0.3; } else { // Standard models - original percentages $standard_recommendations = [ 'content_brief' => 0.9, // 90% of max tokens for comprehensive briefs 'seo_metadata' => 0.15, // 15% of max tokens for metadata 'analysis' => 0.25, // 25% of max tokens for analysis 'llms_txt' => 0.5, // 50% of max tokens for llms.txt 'optimization' => 0.15, // 15% of max tokens for optimization ]; $percentage = $standard_recommendations[$use_case] ?? 0.15; } return (int) ($max_tokens * $percentage); } /** * Build request body for chat completions with model-specific parameters * * @param string $user_prompt User prompt * @param string|null $system_prompt System prompt (ignored for reasoning models) * @param int $max_tokens Maximum tokens * @param float $temperature Temperature (ignored for reasoning models) * @return array Request body */ private function build_chat_request(string $user_prompt, ?string $system_prompt = null, int $max_tokens = 600, float $temperature = 0.4): array { $body = [ 'model' => $this->model, ]; // Get safe token limit for this model $safe_tokens = $this->get_safe_token_limit($this->model, $max_tokens); // Build messages based on model type if ($this->is_reasoning_model($this->model)) { // Reasoning/GPT‑5 family: use max_completion_tokens and omit temperature $content = $user_prompt; // Some GPT‑5 responses may expect array content parts; we'll send string $body['messages'] = [ [ 'role' => 'user', 'content' => $content ] ]; $body['max_completion_tokens'] = $safe_tokens; } else { // Standard models support system messages and temperature $messages = []; if ($system_prompt) { $messages[] = [ 'role' => 'system', 'content' => $system_prompt ]; } $messages[] = [ 'role' => 'user', 'content' => $user_prompt ]; $body['messages'] = $messages; $body['temperature'] = $temperature; $body['max_tokens'] = $safe_tokens; } return $body; } /** * Get current model * * @return string Current model name */ public function get_model(): string { return $this->model; } /** * Test API connection * * @return bool True if connection successful */ public function test_connection(): bool { try { $response = $this->make_request('models'); return isset($response['data']) && is_array($response['data']); } catch (\Exception $e) { return false; } } /** * Make API request to OpenAI * * @param string $endpoint API endpoint * @param array $body Request body * @return array Response data * @throws \Exception If request fails */ private function make_request(string $endpoint, array $body = []): array { // The user's daily ceiling and kill switch are enforced here, at the // one place every outbound OpenAI call passes through, so no feature // path can bypass them by forgetting to ask first (#448). Spend_Guard::guard(); Spend_Guard::record(); // Not string concatenation: a base URL may carry a query string (Azure // requires ?api-version=…), and the route has to land before it (#721). $url = Endpoint_URL_Validator::route($this->base_url, $endpoint); $headers = [ 'Content-Type' => 'application/json', 'User-Agent' => 'ThinkRank/' . THINKRANK_VERSION, ]; // A local Ollama or LM Studio server wants no key at all; sending // "Bearer " with nothing after it makes some gateways 401. if ('' !== $this->api_key) { $headers['Authorization'] = 'Bearer ' . $this->api_key; // Azure OpenAI reads the key from its own header and ignores // Authorization. Sending both costs nothing and makes an Azure // deployment URL work without a separate provider. $headers['api-key'] = $this->api_key; } $args = [ 'timeout' => $this->timeout, 'headers' => $headers, // Only for an endpoint we do not control: a ceiling generous enough // for the largest thing we ask for (a content brief as JSON), so a // server that ignores its token limit still cannot spend the // worker's memory. Truncation is reported below, not parsed (#721). 'limit_response_size' => $this->is_custom_endpoint() ? self::MAX_RESPONSE_BYTES : null, // The key travels in these headers. A redirect to another host // would hand it to whoever controls that host, so never follow one // (#721) — a moved endpoint is the administrator's URL to fix. 'redirection' => 0, ]; if (null === $args['limit_response_size']) { unset($args['limit_response_size']); } $args['method'] = empty($body) ? 'GET' : 'POST'; if (!empty($body)) { $args['body'] = wp_json_encode($body); } $response = $this->request_with_retry($url, $args); if (is_wp_error($response)) { throw new \Exception('API request failed: ' . esc_html($response->get_error_message())); } $status_code = wp_remote_retrieve_response_code($response); $response_body = wp_remote_retrieve_body($response); // JSON mode is the administrator's claim that this server takes // response_format. A server that does not (LM Studio wants json_schema) // answers 400 and names the field; drop it and ask once more, so a // wrong toggle costs a round trip rather than the feature. The rest of // this request's calls skip the field instead of failing first. if ($this->should_retry_without_response_format($body, (int) $status_code, (string) $response_body)) { $this->json_mode = false; unset($body['response_format']); if (defined('WP_DEBUG') && WP_DEBUG) { // phpcs:ignore WordPress.PHP.DevelopmentFunctions.error_log_error_log -- diagnostic, WP_DEBUG only. error_log('[ThinkRank] ' . $this->get_endpoint_label() . ' rejected response_format; retrying without JSON mode.'); } $args['body'] = wp_json_encode($body); $response = $this->request_with_retry($url, $args); if (is_wp_error($response)) { throw new \Exception('API request failed: ' . esc_html($response->get_error_message())); } $status_code = wp_remote_retrieve_response_code($response); $response_body = wp_remote_retrieve_body($response); } // A body that reached the ceiling was cut mid-JSON. Say so, rather than // letting it fail as "invalid JSON" — the cause and the fix are // different things. if ($this->is_custom_endpoint() && strlen($response_body) >= self::MAX_RESPONSE_BYTES) { throw new \Exception(sprintf( /* translators: %s: endpoint name or host. */ esc_html__('%s sent more than ThinkRank will read (2 MB). The endpoint is misconfigured or is not answering with a chat completion.', 'thinkrank'), esc_html($this->get_endpoint_label()) )); } if ($status_code >= 400) { $error_data = json_decode($response_body, true); $error_message = $error_data['error']['message'] ?? ($error_data['message'] ?? 'Unknown API error'); throw new \Exception(sprintf( /* translators: 1: endpoint name or host, 2: HTTP status code, 3: error message from the server. */ esc_html__('%1$s API error (%2$d): %3$s', 'thinkrank'), esc_html($this->get_endpoint_label()), (int) $status_code, esc_html((string) $error_message) )); } $data = json_decode($response_body, true); if (json_last_error() !== JSON_ERROR_NONE) { throw new \Exception(sprintf( /* translators: %s: endpoint name or host. */ esc_html__('Invalid JSON response from %s', 'thinkrank'), esc_html($this->get_endpoint_label()) )); } // A local reasoning model (deepseek-r1, a qwen3 thinking build) spends // its token budget on hidden reasoning before writing anything, and // Ollama and vLLM bill that against max_tokens — so the budget runs out // mid-thought and the reply comes back 200 with empty content and // finish_reason "length". Every generator then fails with "no valid // JSON", which blames the model for a budget problem. Ask once more // with reasoning turned off, which those servers accept as // reasoning_effort: none (#721). if (is_array($data) && $this->should_retry_without_reasoning($endpoint, $body, $data)) { $retry_body = $body; $retry_body['reasoning_effort'] = 'none'; $retry_args = $args; $retry_args['body'] = wp_json_encode($retry_body); $retry = $this->request_with_retry($url, $retry_args); if (!is_wp_error($retry) && wp_remote_retrieve_response_code($retry) < 400) { $retry_data = json_decode(wp_remote_retrieve_body($retry), true); // Keep the first answer when the retry is no better — a server // that ignores the parameter answers exactly the same way, and // the error below is then the honest one. if (is_array($retry_data) && '' !== trim((string) ($retry_data['choices'][0]['message']['content'] ?? ''))) { return $retry_data; } } throw new \Exception(sprintf( /* translators: %s: endpoint name or host. */ esc_html__('%s answered with no text: the model spent its whole token budget on hidden reasoning. Use a non-reasoning model, or raise the token budget for this endpoint.', 'thinkrank'), esc_html($this->get_endpoint_label()) )); } // A valid-but-scalar body (null/number/string from a proxy/gateway on a // 2xx) would violate this method's : array return type; reject it here so // it surfaces as a catchable \Exception, not an uncatchable TypeError. if (!is_array($data)) { throw new \Exception(sprintf( /* translators: %s: endpoint name or host. */ esc_html__('Unexpected non-array response from %s', 'thinkrank'), esc_html($this->get_endpoint_label()) )); } return $data; } /** * Did the server refuse the request because of response_format? * * Only when we sent the field, the server answered 400 or 422 (vLLM and * FastAPI-based servers use 422 for a schema error), and the error text * names the field or a JSON-mode type. Any other 400 (wrong model id, a * prompt over the context window) is a real error, and resending without * the field would only repeat it. * * @since 2.8.0 * * @param array $body Request body that was sent. * @param int $status_code HTTP status of the answer. * @param string $response_body Raw answer body. * @return bool */ private function should_retry_without_response_format(array $body, int $status_code, string $response_body): bool { if (!isset($body['response_format']) || !in_array($status_code, [400, 422], true)) { return false; } $error = strtolower($response_body); foreach (['response_format', 'json_object', 'json_schema'] as $needle) { if (false !== strpos($error, $needle)) { return true; } } return false; } /** * Did a chat completion come back empty because the model was still thinking? * * Three things have to be true: this is a chat completion against a custom * endpoint (OpenAI's own reasoning models manage their own budget through * max_completion_tokens), the content is empty, and the server stopped on * "length" or reported reasoning it never got to use. * * @since 2.8.0 * * @param string $endpoint Endpoint path that was called. * @param array $body Request body that was sent. * @param array $data Decoded response. * @return bool */ private function should_retry_without_reasoning(string $endpoint, array $body, array $data): bool { if (!$this->is_custom_endpoint() || 'chat/completions' !== ltrim($endpoint, '/')) { return false; } // Already asked without reasoning — a second identical attempt would // only cost the user another slow generation. if (isset($body['reasoning_effort'])) { return false; } $message = is_array($data['choices'][0]['message'] ?? null) ? $data['choices'][0]['message'] : null; if (null === $message || '' !== trim((string) ($message['content'] ?? ''))) { return false; } $finish = (string) ($data['choices'][0]['finish_reason'] ?? ''); $reasoning = trim((string) ($message['reasoning'] ?? ($message['reasoning_content'] ?? ''))); return 'length' === $finish || '' !== $reasoning; } /** * Perform an HTTP request, retrying transient failures (429 / 5xx / network) * per the plugin's retry settings, honoring a Retry-After header when given. * * @param string $url Request URL * @param array $args wp_remote_request arguments * @return array|\WP_Error Final response (or last error after retries) */ private function request_with_retry(string $url, array $args) { $settings = \ThinkRank\Core\Settings::instance(); $retry_enabled = (bool) $settings->get('retry_failed_requests', true); $max_attempts = $retry_enabled ? max(1, (int) $settings->get('retry_attempts', 3)) : 1; $response = null; for ($attempt = 1; $attempt <= $max_attempts; $attempt++) { // Keep PHP alive for the whole blocking call (see method docblock). $this->raise_request_time_limit(); // A custom endpoint is a host the site owner named, not one of // ours: check where it actually resolves, pin the connection there // and cap the body before any of it is buffered (#721). $response = $this->is_custom_endpoint() ? Endpoint_URL_Validator::guarded_request($url, $args) : wp_remote_request($url, $args); $is_transient = false; $retry_after = 0; if (is_wp_error($response)) { // A client-side timeout means the work genuinely needs longer // than the budget we allowed; re-running the identical prompt, // model and budget just times out again and multiplies the // wait (issue #288). Do not retry a timeout. Other WP_Error // results — DNS, connection refused, TLS — stay retryable. $is_transient = !$this->is_timeout_error($response); } else { $status = wp_remote_retrieve_response_code($response); if (429 === $status || $status >= 500) { $is_transient = true; $retry_after = (int) wp_remote_retrieve_header($response, 'retry-after'); } } if (!$is_transient || $attempt === $max_attempts) { break; } // Honor Retry-After, else exponential backoff (1s, 2s, 4s…), capped. $delay = $retry_after > 0 ? min($retry_after, 30) : min(2 ** ($attempt - 1), 8); sleep($delay); } return $response; } /** * Give PHP enough execution time to outlive a blocking AI HTTP request. * * The provider call blocks for up to $this->timeout seconds, but the web * SAPI's default max_execution_time (commonly 30s) is shorter — so PHP * fatally terminates the script mid-request (inside the cURL transport), * which the web server surfaces as a 502 Bad Gateway. Resetting the limit * before each attempt keeps the script alive for the full call; PHP-FPM's * request_terminate_timeout still caps the absolute maximum. No-op when * set_time_limit() is disabled (e.g. via disable_functions or safe mode). * * @return void */ private function raise_request_time_limit(): void { if (function_exists('set_time_limit')) { // Cover the request timeout plus a small buffer for connection // setup and response handling. @set_time_limit($this->timeout + 45); // phpcs:ignore WordPress.PHP.NoSilencedErrors.Discouraged -- set_time_limit() warns when disabled by host policy; the guard is intentional. } } /** * Parse SEO response from OpenAI * * @param array $response OpenAI response * @return array Parsed metadata * @throws \Exception If parsing fails */ private function parse_seo_response(array $response): array { if (!isset($response['choices'][0]['message']['content'])) { throw new \Exception('Invalid response format from OpenAI'); } $content = $response['choices'][0]['message']['content']; $ai_text = $content; // Store the raw AI-generated text (Content Brief pattern) // Try to extract JSON from the response $json_start = strpos($content, '{'); $json_end = strrpos($content, '}'); if (false === $json_start || false === $json_end) { throw new \Exception('No valid JSON found in OpenAI response'); } $json_content = substr($content, $json_start, $json_end - $json_start + 1); $metadata = json_decode($json_content, true); if (json_last_error() !== JSON_ERROR_NONE) { throw new \Exception('Failed to parse JSON from OpenAI response'); } // Validate required fields $required_fields = ['title', 'description', 'focus_keyword']; foreach ($required_fields as $field) { if (!isset($metadata[$field])) { throw new \Exception(sprintf('Missing required field: %s', esc_html($field))); } } return [ 'title' => sanitize_text_field($metadata['title']), 'description' => sanitize_text_field($metadata['description']), 'focus_keyword' => sanitize_text_field($metadata['focus_keyword']), 'suggestions' => array_map('sanitize_text_field', $metadata['suggestions'] ?? []), 'generated_at' => current_time('mysql'), 'tokens_used' => $response['usage']['total_tokens'] ?? 0, '_ai_text' => $ai_text, // Store the raw AI-generated text (Content Brief pattern) ]; } /** * Parse analysis response from OpenAI * * @param array $response OpenAI API response * @return array Parsed analysis data * @throws \Exception If parsing fails */ private function parse_analysis_response(array $response): array { if (!isset($response['choices'][0]['message']['content'])) { throw new \Exception('Invalid response format from OpenAI'); } $content = trim($response['choices'][0]['message']['content']); $ai_text = $content; // Store the raw AI-generated text (Content Brief pattern) // Extract JSON from response $json_start = strpos($content, '{'); $json_end = strrpos($content, '}'); if (false === $json_start || false === $json_end) { throw new \Exception('No valid JSON found in response'); } $json_content = substr($content, $json_start, $json_end - $json_start + 1); $analysis = json_decode($json_content, true); if (json_last_error() !== JSON_ERROR_NONE) { throw new \Exception('Failed to parse JSON response: ' . esc_html(json_last_error_msg())); } // Validate and sanitize response return [ 'seo_score' => min(100, max(0, (int) ($analysis['seo_score'] ?? 0))), 'content_analysis' => [ 'word_count' => (int) ($analysis['content_analysis']['word_count'] ?? 0), 'readability' => sanitize_text_field($analysis['content_analysis']['readability'] ?? 'unknown'), 'keyword_density' => sanitize_text_field($analysis['content_analysis']['keyword_density'] ?? 'unknown'), 'structure' => sanitize_text_field($analysis['content_analysis']['structure'] ?? 'unknown'), ], 'suggestions' => array_map('sanitize_text_field', $analysis['suggestions'] ?? []), 'strengths' => array_map('sanitize_text_field', $analysis['strengths'] ?? []), 'weaknesses' => array_map('sanitize_text_field', $analysis['weaknesses'] ?? []), 'analyzed_at' => current_time('mysql'), 'tokens_used' => $response['usage']['total_tokens'] ?? 0, '_ai_text' => $ai_text, // Store the raw AI-generated text (Content Brief pattern) ]; } /** * Optimize site identity using OpenAI * * @since 1.0.0 * * @param array $site_data Site data to optimize * @param array $options Optimization options * @return array Optimization results * @throws \Exception If optimization fails */ public function optimize_site_identity(array $site_data, array $options = []): array { $business_type = $options['business_type'] ?? 'website'; $target_audience = $options['target_audience'] ?? 'general'; $tone = $options['tone'] ?? 'professional'; $prompt_builder = $this->get_prompt_builder(); $prompt = $prompt_builder->build_site_identity_prompt($site_data, $business_type, $target_audience, $tone, 'openai'); $body = $this->build_chat_request( $prompt, 'You are an expert SEO consultant specializing in site identity optimization. Provide actionable, specific recommendations in JSON format.', $this->get_recommended_tokens('optimization'), 0.4 ); $response = $this->make_request('chat/completions', $body); return $this->parse_site_identity_response($response); } /** * Parse site identity optimization response * * @param array $response OpenAI API response * @return array Parsed optimization data * @throws \Exception If parsing fails */ private function parse_site_identity_response(array $response): array { if (!isset($response['choices'][0]['message']['content'])) { throw new \Exception('Invalid response format from OpenAI'); } $content = trim($response['choices'][0]['message']['content']); $ai_text = $content; // Store the raw AI-generated text (Content Brief pattern) // Extract JSON from response $json_start = strpos($content, '{'); $json_end = strrpos($content, '}'); if (false === $json_start || false === $json_end) { throw new \Exception('No valid JSON found in response'); } $json_content = substr($content, $json_start, $json_end - $json_start + 1); $optimization = json_decode($json_content, true); if (json_last_error() !== JSON_ERROR_NONE) { throw new \Exception('Failed to parse JSON response: ' . esc_html(json_last_error_msg())); } // Validate and sanitize response return [ 'optimized_data' => [ 'site_name' => sanitize_text_field($optimization['optimized_data']['site_name'] ?? ''), 'site_description' => sanitize_text_field($optimization['optimized_data']['site_description'] ?? ''), 'tagline' => sanitize_text_field($optimization['optimized_data']['tagline'] ?? ''), 'default_meta_description' => sanitize_text_field($optimization['optimized_data']['default_meta_description'] ?? ''), ], 'analysis' => sanitize_textarea_field($optimization['analysis'] ?? ''), 'suggestions' => array_map('sanitize_text_field', $optimization['suggestions'] ?? []), 'score' => min(100, max(0, (int) ($optimization['score'] ?? 0))), 'tokens_used' => $response['usage']['total_tokens'] ?? 0, '_ai_text' => $ai_text, // Store the raw AI-generated text (Content Brief pattern) ]; } /** * Optimize homepage meta content using AI (copying Site Identity pattern exactly) * * @since 1.0.0 * * @param array $content_data Meta content data to optimize * @param array $options Optimization options * @return array Optimization results * @throws \Exception If optimization fails */ public function optimize_homepage_meta(array $content_data, array $options = []): array { $business_type = $options['business_type'] ?? 'website'; $target_audience = $options['target_audience'] ?? 'general'; $tone = $options['tone'] ?? 'professional'; $context = $options['context'] ?? []; $prompt_builder = $this->get_prompt_builder(); $prompt = $prompt_builder->build_homepage_meta_prompt($content_data, $business_type, $target_audience, $tone, $context, 'openai'); $body = $this->build_chat_request( $prompt, 'You are an expert SEO consultant specializing in homepage meta optimization. Provide actionable, specific recommendations in JSON format.', $this->get_recommended_tokens('optimization'), 0.4 ); $response = $this->make_request('chat/completions', $body); return $this->parse_homepage_meta_response($response); } /** * Optimize homepage hero content using AI (copying Site Identity pattern exactly) * * @since 1.0.0 * * @param array $hero_data Hero content data to optimize * @param array $options Optimization options * @return array Optimization results * @throws \Exception If optimization fails */ public function optimize_homepage_hero(array $hero_data, array $options = []): array { $business_type = $options['business_type'] ?? 'website'; $target_audience = $options['target_audience'] ?? 'general'; $tone = $options['tone'] ?? 'professional'; $context = $options['context'] ?? []; $prompt_builder = $this->get_prompt_builder(); $prompt = $prompt_builder->build_homepage_hero_prompt($hero_data, $business_type, $target_audience, $tone, $context, 'openai'); $body = $this->build_chat_request( $prompt, 'You are an expert conversion optimization specialist specializing in homepage hero sections. Provide actionable, specific recommendations in JSON format.', $this->get_recommended_tokens('optimization'), 0.4 ); $response = $this->make_request('chat/completions', $body); return $this->parse_homepage_hero_response($response); } /** * Optimize LLMs.txt content using OpenAI * * @since 1.0.0 * * @param array $website_data Website data to optimize * @param array $options Optimization options * @return array Optimization results * @throws \Exception If optimization fails */ public function optimize_llms_txt(array $website_data, array $options = []): array { // Use shared prompt builder for consistent prompts across all AI providers $prompt_builder = $this->get_prompt_builder(); $prompt = $prompt_builder->build_llms_txt_prompt($website_data, $options, 'openai'); $body = $this->build_chat_request( $prompt, 'You are an expert technical writer specializing in creating llms.txt files for AI assistants. Provide structured, comprehensive content in JSON format.', $this->get_recommended_tokens('llms_txt'), 0.4 ); $response = $this->make_request('chat/completions', $body); return $this->parse_llms_txt_response($response); } /** * Parse LLMs.txt optimization response * * @param array $response OpenAI API response * @return array Parsed optimization data * @throws \Exception If parsing fails */ private function parse_llms_txt_response(array $response): array { if (!isset($response['choices'][0]['message']['content'])) { throw new \Exception('Invalid response format from OpenAI'); } $content = trim($response['choices'][0]['message']['content']); $ai_text = $content; // Store the raw AI-generated text (Content Brief pattern) // Extract JSON from response $json_start = strpos($content, '{'); $json_end = strrpos($content, '}'); if (false === $json_start || false === $json_end) { throw new \Exception('No valid JSON found in response'); } $json_content = substr($content, $json_start, $json_end - $json_start + 1); $optimization = json_decode($json_content, true); if (json_last_error() !== JSON_ERROR_NONE) { throw new \Exception('Invalid JSON in response: ' . esc_html(json_last_error_msg())); } // Validate and sanitize response return [ 'optimized_data' => [ 'site_name' => sanitize_text_field($optimization['optimized_data']['site_name'] ?? ''), 'project_overview' => sanitize_textarea_field($optimization['optimized_data']['project_overview'] ?? ''), 'key_features' => \ThinkRank\SEO\LLMs_Txt_Manager::normalize_ai_key_features($optimization['optimized_data']['key_features'] ?? ''), 'architecture' => sanitize_textarea_field($optimization['optimized_data']['architecture'] ?? ''), 'development_guidelines' => sanitize_textarea_field($optimization['optimized_data']['development_guidelines'] ?? ''), 'ai_context' => sanitize_textarea_field($optimization['optimized_data']['ai_context'] ?? ''), ], 'suggestions' => array_map('sanitize_text_field', $optimization['suggestions'] ?? []), 'tokens_used' => $response['usage']['total_tokens'] ?? 0, '_ai_text' => $ai_text, // Store the raw AI-generated text (Content Brief pattern) ]; } /** * Parse homepage meta optimization response * * @param array $response OpenAI API response * @return array Parsed optimization data * @throws \Exception If parsing fails */ private function parse_homepage_meta_response(array $response): array { if (!isset($response['choices'][0]['message']['content'])) { throw new \Exception('Invalid response format from OpenAI'); } $content = trim($response['choices'][0]['message']['content']); $ai_text = $content; // Store the raw AI-generated text (Content Brief pattern) // Extract JSON from response $json_start = strpos($content, '{'); $json_end = strrpos($content, '}'); if (false === $json_start || false === $json_end) { throw new \Exception('No valid JSON found in response'); } $json_content = substr($content, $json_start, $json_end - $json_start + 1); $optimization = json_decode($json_content, true); if (json_last_error() !== JSON_ERROR_NONE) { throw new \Exception('Failed to parse JSON response: ' . esc_html(json_last_error_msg())); } // Validate and sanitize response return [ 'optimized_data' => [ 'title' => sanitize_text_field($optimization['optimized_data']['title'] ?? ''), 'meta_description' => sanitize_text_field($optimization['optimized_data']['meta_description'] ?? ''), ], 'analysis' => sanitize_textarea_field($optimization['analysis'] ?? ''), 'suggestions' => array_map('sanitize_text_field', $optimization['suggestions'] ?? []), 'score' => min(100, max(0, (int) ($optimization['score'] ?? 0))), 'tokens_used' => $response['usage']['total_tokens'] ?? 0, '_ai_text' => $ai_text, // Store the raw AI-generated text (Content Brief pattern) ]; } /** * Parse homepage hero optimization response * * @param array $response OpenAI API response * @return array Parsed optimization data * @throws \Exception If parsing fails */ private function parse_homepage_hero_response(array $response): array { if (!isset($response['choices'][0]['message']['content'])) { throw new \Exception('Invalid response format from OpenAI'); } $content = trim($response['choices'][0]['message']['content']); $ai_text = $content; // Store the raw AI-generated text (Content Brief pattern) // Extract JSON from response $json_start = strpos($content, '{'); $json_end = strrpos($content, '}'); if (false === $json_start || false === $json_end) { throw new \Exception('No valid JSON found in response'); } $json_content = substr($content, $json_start, $json_end - $json_start + 1); $optimization = json_decode($json_content, true); if (json_last_error() !== JSON_ERROR_NONE) { throw new \Exception('Failed to parse JSON response: ' . esc_html(json_last_error_msg())); } // Validate and sanitize response return [ 'optimized_data' => [ 'hero_title' => sanitize_text_field($optimization['optimized_data']['hero_title'] ?? ''), 'hero_subtitle' => sanitize_text_field($optimization['optimized_data']['hero_subtitle'] ?? ''), 'hero_cta_text' => sanitize_text_field($optimization['optimized_data']['hero_cta_text'] ?? '') ], 'analysis' => sanitize_textarea_field($optimization['analysis'] ?? ''), 'suggestions' => array_map('sanitize_text_field', $optimization['suggestions'] ?? []), 'score' => min(100, max(0, (int) ($optimization['score'] ?? 0))), 'tokens_used' => $response['usage']['total_tokens'] ?? 0, '_ai_text' => $ai_text, // Store the raw AI-generated text (Content Brief pattern) ]; } } ```