ai_synth/docs/superpowers/plans/2026-03-24-llm-scraping.md

LLM-Assisted Scraping — Implementation Plan

For agentic workers: REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (- [ ]) syntax for tracking.

Goal: Add two optional LLM-powered scraping enhancements: LLM link extraction from source pages and LLM article content extraction — controlled by user settings.

Architecture: Two boolean settings control two independent LLM scraping paths. Each has a fallback to existing heuristic-based extraction. ScrapedContent gains a url field for redirect-resolved URLs. New prompt/schema builders for both LLM calls.

Tech Stack: Rust (reqwest, scraper crate, serde_json), existing LLM providers via generate_rewrite_pass

Spec: docs/superpowers/specs/2026-03-24-llm-scraping-design.md

---

Task 1: Migration + backend model (2 bool settings)

Files:

• Create: backend/migrations/20260324000014_add_llm_scraping_settings.sql

• Modify: backend/src/models/settings.rs

• Modify: backend/src/db/settings.rs

• Modify: backend/src/services/prompts.rs (test fixture)

• Modify: CLAUDE.md

• Step 1: Create migration

ALTER TABLE settings ADD COLUMN use_llm_for_source_links BOOLEAN NOT NULL DEFAULT false;
ALTER TABLE settings ADD COLUMN use_llm_for_article_extraction BOOLEAN NOT NULL DEFAULT false;

• Step 2: Add fields to all structs in models/settings.rs

Add pub use_llm_for_source_links: bool and pub use_llm_for_article_extraction: bool to UserSettings, SettingsResponse, UpdateSettingsRequest (after source_diversity_window).

Add to From<UserSettings> for SettingsResponse, Default for UserSettings (both false). No validation needed for bools.

• Step 3: Add to DB queries in db/settings.rs

Add both fields to SettingsRow, TryFrom<SettingsRow>, and both SQL queries (get_or_create_default + upsert). Follow the pattern of the last column added.

• Step 4: Update test fixtures

Add use_llm_for_source_links: false, use_llm_for_article_extraction: false to:

• valid_request() in models/settings.rs tests

• test_settings() in services/prompts.rs tests

• Step 5: Update CLAUDE.md migration count to 14

• Step 6: Run tests + commit

Run: cd backend && cargo test --lib

git add backend/migrations/20260324000014_add_llm_scraping_settings.sql backend/src/models/settings.rs backend/src/db/settings.rs backend/src/services/prompts.rs CLAUDE.md
git commit -m "feat: add use_llm_for_source_links and use_llm_for_article_extraction settings"

---

Task 2: Add url field to ScrapedContent + update scrape_single_article

Files:

• Modify: backend/src/services/scraper.rs

• Modify: backend/src/services/synthesis.rs

• Step 1: Add url to ScrapedContent in scraper.rs

Add pub url: String to the ScrapedContent struct (after is_soft_404).

In scrape_url, populate it from final_url:

Ok(ScrapedContent {
    ok: !is_soft_404,
    status,
    title,
    published_date,
    body_text,
    is_soft_404,
    url: final_url.to_string(),
})

• Step 2: Update scrape_single_article to return (String, String, String)

In synthesis.rs, change scrape_single_article return type from (String, String) to (String, String, String) — (body_text, page_title, final_url):

async fn scrape_single_article(
    http_client: &reqwest::Client,
    url: &str,
    max_age_days: i64,
) -> (String, String, String) {
    match scraper::scrape_url(http_client, url).await {
        Ok(content) => {
            if !content.ok || content.is_soft_404 {
                tracing::warn!(url = url, "Soft 404 or error page detected, skipping content");
                return (String::new(), String::new(), content.url);
            }

            if scraper::is_article_too_old(content.published_date, max_age_days) {
                tracing::warn!(url = url, "Article too old, skipping content");
                return (String::new(), String::new(), content.url);
            }

            let title = content.title.unwrap_or_default();
            (content.body_text, title, content.url)
        }
        Err(e) => {
            tracing::warn!(url = url, error = %e, "Failed to scrape URL, keeping article with empty content");
            (String::new(), String::new(), url.to_string())
        }
    }
}

• Step 3: Update callers of scrape_single_article

In scrape_articles and scrape_flat_urls, update destructuring from (scraped_content, page_title) to (scraped_content, page_title, final_url). Use final_url to set ScrapedNewsItem.url instead of the input URL:

In scrape_articles (inside the join_set.spawn):

let scraped = scrape_single_article(&client, &url, mad).await;
(cat_key, item, scraped)

And in the result handler:

if let Ok((cat_key, item, (scraped_content, page_title, final_url))) = join_result {
    let scraped_item = ScrapedNewsItem {
        title: item.title,
        url: final_url, // Use redirect-resolved URL instead of item.url
        summary: item.summary,
        original_title: page_title,
        scraped_content,
    };

Same pattern in scrape_flat_urls:

if let Ok((url, scraped_content, page_title, final_url)) = join_result {
    results.push(ScrapedNewsItem {
        title: page_title.clone(),
        url: final_url, // Use redirect-resolved URL
        summary: String::new(),
        original_title: page_title,
        scraped_content,
    });

Note: the join_set.spawn closure must also capture and return final_url. Update the spawn to return 4-tuple: (url, scraped_content, page_title, final_url).

• Step 4: Run tests + commit

Run: cd backend && cargo test --lib

git add backend/src/services/scraper.rs backend/src/services/synthesis.rs
git commit -m "feat: add url field to ScrapedContent, use redirect-resolved URLs"

---

Task 3: LLM prompts and schemas for both extraction types

Files:

• Modify: backend/src/services/prompts.rs

• Modify: backend/src/services/llm/schema.rs

• Step 1: Add build_link_extraction_prompt to prompts.rs

/// Build a prompt for LLM-assisted link extraction from a source page.
///
/// # Arguments
/// * `head_html` — the <head> section of the page
/// * `body_html` — first 8000 chars of the <body> section
pub fn build_link_extraction_prompt(head_html: &str, body_html: &str) -> (String, String) {
    let system_prompt =
        "Tu es un assistant qui analyse des pages web. \
         Tu dois identifier les liens vers des articles d'actualite. \
         Reponds uniquement au format JSON demande."
            .to_string();

    let user_prompt = format!(
        "Voici le contenu HTML d'une page de blog ou de site d'actualites.\n\n\
         <head>\n{head}\n</head>\n\n\
         <body (extrait)>\n{body}\n</body>\n\n\
         Extrais UNIQUEMENT les URLs qui pointent vers des articles \
         (pas les liens de navigation, tags, categories, login, pages statiques, etc.).\n\
         Retourne les URLs completes dans le format JSON demande.",
        head = head_html,
        body = body_html,
    );

    (system_prompt, user_prompt)
}

• Step 2: Add build_article_extraction_prompt to prompts.rs

/// Build a prompt for LLM-assisted article content extraction.
///
/// # Arguments
/// * `head_html` — the <head> section (contains meta tags, og:*, canonical)
/// * `body_text` — cleaned body text from existing HTML stripping
pub fn build_article_extraction_prompt(head_html: &str, body_text: &str) -> (String, String) {
    let system_prompt =
        "Tu es un assistant qui analyse des articles web. \
         Tu dois extraire les informations structurees de l'article. \
         Reponds uniquement au format JSON demande."
            .to_string();

    let user_prompt = format!(
        "Voici le contenu d'une page web.\n\n\
         <head>\n{head}\n</head>\n\n\
         Contenu textuel de la page :\n{body}\n\n\
         Extrais les informations suivantes :\n\
         - title : le titre de l'article\n\
         - published_date : la date de publication au format ISO 8601 (YYYY-MM-DDTHH:MM:SSZ), \
         ou une chaine vide si introuvable\n\
         - body_text : le contenu principal de l'article (pas la navigation, pas les pubs)\n\
         - is_error_page : true si c'est une page d'erreur/404, false sinon",
        head = head_html,
        body = body_text,
    );

    (system_prompt, user_prompt)
}

• Step 3: Add schemas to schema.rs

/// Build a JSON Schema for LLM link extraction response.
pub fn build_link_extraction_schema() -> Value {
    serde_json::json!({
        "type": "object",
        "properties": {
            "urls": {
                "type": "array",
                "items": { "type": "string" }
            }
        },
        "required": ["urls"],
        "additionalProperties": false
    })
}

/// Build a JSON Schema for LLM article content extraction response.
pub fn build_article_extraction_schema() -> Value {
    serde_json::json!({
        "type": "object",
        "properties": {
            "title": { "type": "string", "description": "Article title" },
            "published_date": { "type": "string", "description": "ISO 8601 date or empty string if not found" },
            "body_text": { "type": "string", "description": "Main article content" },
            "is_error_page": { "type": "boolean", "description": "True if this is an error/404 page" }
        },
        "required": ["title", "published_date", "body_text", "is_error_page"],
        "additionalProperties": false
    })
}

• Step 4: Add tests

In prompts.rs tests:

    #[test]
    fn link_extraction_prompt_includes_html() {
        let (_, user) = build_link_extraction_prompt("<title>Blog</title>", "<a href='/post'>P</a>");
        assert!(user.contains("<title>Blog</title>"));
        assert!(user.contains("articles"));
    }

    #[test]
    fn article_extraction_prompt_includes_content() {
        let (_, user) = build_article_extraction_prompt("<meta name='date' content='2026'>", "Article body text here");
        assert!(user.contains("Article body text here"));
        assert!(user.contains("published_date"));
    }

In schema.rs tests:

    #[test]
    fn link_extraction_schema_has_urls_array() {
        let schema = build_link_extraction_schema();
        assert_eq!(schema["properties"]["urls"]["type"], "array");
        assert_eq!(schema["additionalProperties"], false);
    }

    #[test]
    fn article_extraction_schema_has_all_fields() {
        let schema = build_article_extraction_schema();
        let props = schema["properties"].as_object().unwrap();
        assert!(props.contains_key("title"));
        assert!(props.contains_key("published_date"));
        assert!(props.contains_key("body_text"));
        assert!(props.contains_key("is_error_page"));
        assert_eq!(schema["additionalProperties"], false);
    }

• Step 5: Run tests + commit

Run: cd backend && cargo test --lib

git add backend/src/services/prompts.rs backend/src/services/llm/schema.rs
git commit -m "feat: add LLM prompts and schemas for link and article extraction"

---

Task 4: LLM-assisted source link extraction in source_scraper.rs

Files:

• Modify: backend/src/services/source_scraper.rs

• Step 1: Update extract_article_links to accept optional LLM provider

Add a new public function extract_article_links_with_llm that accepts LLM parameters. The existing extract_article_links stays unchanged for non-LLM path.

use crate::services::llm::LlmProvider;
use crate::services::llm::schema::build_link_extraction_schema;
use crate::services::prompts::build_link_extraction_prompt;

/// Extract article links using LLM analysis of the page HTML.
///
/// Falls back to heuristic extraction if the LLM call fails or returns empty results.
pub async fn extract_article_links_with_llm(
    http_client: &reqwest::Client,
    source_url: &str,
    max_links: usize,
    provider: &dyn LlmProvider,
    model: &str,
) -> Result<Vec<String>, AppError> {
    let base_url = Url::parse(source_url)
        .map_err(|e| AppError::BadRequest(format!("Invalid source URL: {}", e)))?;
    let base_domain = base_url.host_str().unwrap_or("").to_lowercase();

    // Fetch the page
    let response = http_client.get(source_url).send().await.map_err(|e| {
        tracing::warn!(url = source_url, error = %e, "Failed to fetch source page");
        AppError::Internal(anyhow::anyhow!("Failed to fetch source page"))
    })?;

    if !response.status().is_success() {
        tracing::warn!(url = source_url, status = %response.status(), "Source page returned non-200");
        return Ok(Vec::new());
    }

    let html_text = response.text().await.map_err(|e| {
        AppError::Internal(anyhow::anyhow!("Failed to read source page body: {}", e))
    })?;

    // Extract <head> and first 8000 chars of <body> for the LLM
    let (head_html, body_html) = extract_head_and_body(&html_text);

    let (system, user) = build_link_extraction_prompt(&head_html, &body_html);
    let schema = build_link_extraction_schema();

    match provider.generate_rewrite_pass(model, &system, &user, &schema).await {
        Ok(response) => {
            let urls = response
                .get("urls")
                .and_then(|u| u.as_array())
                .map(|arr| {
                    arr.iter()
                        .filter_map(|v| v.as_str())
                        .filter_map(|href| {
                            // Resolve relative URLs
                            let resolved = base_url.join(href).ok()?;
                            // Filter: http/https only, same domain
                            if resolved.scheme() != "http" && resolved.scheme() != "https" {
                                return None;
                            }
                            let domain = resolved.host_str()?.to_lowercase();
                            if domain != base_domain {
                                return None;
                            }
                            Some(resolved.to_string())
                        })
                        .collect::<Vec<_>>()
                })
                .unwrap_or_default();

            if urls.is_empty() {
                tracing::warn!(url = source_url, "LLM returned no links, falling back to heuristic extraction");
                let fallback = extract_links_from_html(&html_text, &base_url, &base_domain);
                Ok(fallback.into_iter().take(max_links).collect())
            } else {
                // Deduplicate
                let mut seen = std::collections::HashSet::new();
                let deduped: Vec<String> = urls.into_iter().filter(|u| seen.insert(u.clone())).collect();
                Ok(deduped.into_iter().take(max_links).collect())
            }
        }
        Err(e) => {
            tracing::warn!(url = source_url, error = %e, "LLM link extraction failed, falling back to heuristic");
            let fallback = extract_links_from_html(&html_text, &base_url, &base_domain);
            Ok(fallback.into_iter().take(max_links).collect())
        }
    }
}

/// Extract the <head> section and first N chars of <body> from HTML.
fn extract_head_and_body(html: &str) -> (String, String) {
    let head_start = html.find("<head").unwrap_or(0);
    let head_end = html.find("</head>").map(|i| i + 7).unwrap_or(head_start);
    let head = &html[head_start..head_end];

    let body_start = html.find("<body").unwrap_or(head_end);
    let body_end = (body_start + 8000).min(html.len());
    let body = &html[body_start..body_end];

    (head.to_string(), body.to_string())
}

• Step 2: Add tests

    #[test]
    fn extract_head_and_body_splits_correctly() {
        let html = "<html><head><title>T</title></head><body><p>Content</p></body></html>";
        let (head, body) = extract_head_and_body(html);
        assert!(head.contains("<title>T</title>"));
        assert!(body.contains("<p>Content</p>"));
    }

    #[test]
    fn extract_head_and_body_truncates_body() {
        let long_body = "x".repeat(20000);
        let html = format!("<head></head><body>{}</body>", long_body);
        let (_, body) = extract_head_and_body(&html);
        assert!(body.len() <= 8006); // <body> tag + 8000 chars
    }

• Step 3: Run tests + commit

Run: cd backend && cargo test --lib

git add backend/src/services/source_scraper.rs
git commit -m "feat: LLM-assisted source link extraction with heuristic fallback"

---

Task 5: LLM-assisted article extraction in synthesis pipeline

Files:

• Modify: backend/src/services/synthesis.rs

• Step 1: Add scrape_single_article_with_llm function

Add a new async function alongside scrape_single_article:

/// Scrape an article URL using LLM for content extraction.
///
/// Falls back to heuristic extraction if the LLM call fails.
async fn scrape_single_article_with_llm(
    http_client: &reqwest::Client,
    url: &str,
    max_age_days: i64,
    provider: &dyn crate::services::llm::LlmProvider,
    model: &str,
) -> (String, String, String) {
    // First, do the HTTP fetch (same as regular scraping)
    let fetch_result = scraper::scrape_url(http_client, url).await;

    let content = match fetch_result {
        Ok(c) => c,
        Err(e) => {
            tracing::warn!(url = url, error = %e, "Failed to fetch URL for LLM extraction");
            return (String::new(), String::new(), url.to_string());
        }
    };

    let final_url = content.url.clone();

    if !content.ok || content.is_soft_404 {
        return (String::new(), String::new(), final_url);
    }

    // Extract <head> from the raw HTML for the LLM
    // We need to re-fetch the raw HTML or extract it from the scraper
    // Since scraper already parsed it, we'll use the existing body_text + title as input
    let head_html = String::new(); // The scraper doesn't preserve <head> — use empty
    let body_text = &content.body_text;

    let (system, user) = crate::services::prompts::build_article_extraction_prompt(
        &head_html,
        body_text,
    );
    let schema = crate::services::llm::schema::build_article_extraction_schema();

    match provider.generate_rewrite_pass(model, &system, &user, &schema).await {
        Ok(response) => {
            let title = response.get("title").and_then(|t| t.as_str()).unwrap_or("").to_string();
            let extracted_body = response.get("body_text").and_then(|b| b.as_str()).unwrap_or("").to_string();
            let is_error = response.get("is_error_page").and_then(|e| e.as_bool()).unwrap_or(false);
            let date_str = response.get("published_date").and_then(|d| d.as_str()).unwrap_or("");

            if is_error || extracted_body.trim().is_empty() {
                return (String::new(), String::new(), final_url);
            }

            // Check date if provided
            if !date_str.is_empty() {
                if let Ok(date) = chrono::DateTime::parse_from_rfc3339(date_str) {
                    if scraper::is_article_too_old(Some(date.with_timezone(&chrono::Utc)), max_age_days) {
                        tracing::warn!(url = url, "LLM-extracted article too old");
                        return (String::new(), String::new(), final_url);
                    }
                }
            }

            (extracted_body, title, final_url)
        }
        Err(e) => {
            tracing::warn!(url = url, error = %e, "LLM article extraction failed, using heuristic fallback");
            // Fall back to existing heuristic data
            if scraper::is_article_too_old(content.published_date, max_age_days) {
                return (String::new(), String::new(), final_url);
            }
            let title = content.title.unwrap_or_default();
            (content.body_text, title, final_url)
        }
    }
}

• Step 2: Update pipeline to use LLM extraction when enabled

In run_generation_inner, the scraping calls need to branch based on settings.use_llm_for_article_extraction. The simplest approach: update scrape_flat_urls and scrape_articles to accept an optional provider+model, and use scrape_single_article_with_llm when provided.

Add a wrapper that the pipeline calls:

/// Scrape a single article, optionally using LLM extraction.
async fn scrape_article_dispatch(
    http_client: &reqwest::Client,
    url: &str,
    max_age_days: i64,
    llm: Option<(&dyn crate::services::llm::LlmProvider, &str)>,
) -> (String, String, String) {
    match llm {
        Some((provider, model)) => {
            scrape_single_article_with_llm(http_client, url, max_age_days, provider, model).await
        }
        None => scrape_single_article(http_client, url, max_age_days).await,
    }
}

Update scrape_flat_urls and scrape_articles to use scrape_article_dispatch. The provider and model are passed from run_generation_inner based on settings.use_llm_for_article_extraction.

Similarly, update the Phase 1 source scraping in run_generation_inner to call extract_article_links_with_llm vs extract_article_links based on settings.use_llm_for_source_links.

• Step 3: Run tests + commit

Run: cd backend && cargo test --lib

git add backend/src/services/synthesis.rs
git commit -m "feat: LLM-assisted article extraction with heuristic fallback"

---

Task 6: Frontend settings

Files:

• Modify: frontend/src/types.ts

• Modify: frontend/src/i18n/fr.ts

• Modify: frontend/src/pages/Settings.tsx

• Step 1: Add fields to types

In frontend/src/types.ts, add to UserSettings:

use_llm_for_source_links: boolean;
use_llm_for_article_extraction: boolean;

Add to DEFAULT_SETTINGS:

use_llm_for_source_links: false,
use_llm_for_article_extraction: false,

• Step 2: Add i18n labels

In frontend/src/i18n/fr.ts:

'settings.advancedExtraction': 'Extraction avancee',
'settings.useLlmForSourceLinks': "Utiliser l'IA pour extraire les liens",
'settings.useLlmForArticleExtraction': "Utiliser l'IA pour extraire le contenu",

• Step 3: Add checkboxes to Settings page

In frontend/src/pages/Settings.tsx, add a new section after the existing generation settings (after the grid with maxAgeDays/maxItemsPerCategory/maxArticlesPerSource/diversityWindow):

          {/* Advanced extraction */}
          <div class="mt-6">
            <h3 class="text-lg font-medium text-gray-900 mb-4">
              {t('settings.advancedExtraction')}
            </h3>
            <div class="space-y-4">
              <div class="flex items-center">
                <input
                  type="checkbox"
                  id="useLlmSourceLinks"
                  checked={settings().use_llm_for_source_links}
                  onChange={(e) =>
                    setSettings((prev) => ({
                      ...prev,
                      use_llm_for_source_links: e.currentTarget.checked,
                    }))
                  }
                  class="h-4 w-4 text-indigo-600 focus:ring-indigo-500 border-gray-300 rounded"
                />
                <label for="useLlmSourceLinks" class="ml-2 block text-sm text-gray-700">
                  {t('settings.useLlmForSourceLinks')}
                </label>
              </div>
              <div class="flex items-center">
                <input
                  type="checkbox"
                  id="useLlmArticleExtraction"
                  checked={settings().use_llm_for_article_extraction}
                  onChange={(e) =>
                    setSettings((prev) => ({
                      ...prev,
                      use_llm_for_article_extraction: e.currentTarget.checked,
                    }))
                  }
                  class="h-4 w-4 text-indigo-600 focus:ring-indigo-500 border-gray-300 rounded"
                />
                <label for="useLlmArticleExtraction" class="ml-2 block text-sm text-gray-700">
                  {t('settings.useLlmForArticleExtraction')}
                </label>
              </div>
            </div>
          </div>

• Step 4: Run frontend tests + commit

Run: cd frontend && npx tsc --noEmit && npx vitest run

git add frontend/src/types.ts frontend/src/i18n/fr.ts frontend/src/pages/Settings.tsx
git commit -m "feat: add LLM scraping toggles to Settings page"

---

Task 7: Update E2E test with comprehensive synthesis validation

Files:

• Modify: e2e/tests/generation-live.spec.ts

• Step 1: Update settings payload

Add the new boolean fields to the PUT settings call:

use_llm_for_source_links: false,
use_llm_for_article_extraction: false,

• Step 2: Add comprehensive validation after synthesis fetch

After the existing structure validation, add:

    // Comprehensive synthesis validation
    const allUrls: string[] = [];
    const domainCounts: Record<string, number> = {};

    for (const section of synthesis.sections) {
      for (const item of section.items) {
        // Collect URLs for duplicate check
        allUrls.push(item.url);

        // Count domains for source diversity check
        try {
          const domain = new URL(item.url).hostname;
          domainCounts[domain] = (domainCounts[domain] || 0) + 1;
        } catch {}
      }

      // Category article count check
      if (section.title !== 'Autre') {
        expect(section.items.length).toBeLessThanOrEqual(4); // max_items_per_category
      }
    }

    // No duplicate URLs across all sections
    const uniqueUrls = new Set(allUrls);
    expect(uniqueUrls.size).toBe(allUrls.length);

    // No domain exceeds max_articles_per_source (3)
    for (const [domain, count] of Object.entries(domainCounts)) {
      expect(count).toBeLessThanOrEqual(3);
    }

    // Verify article links actually work (HTTP 200)
    // Test a sample of up to 3 URLs to avoid slowness
    const sampleUrls = allUrls.slice(0, 3);
    for (const articleUrl of sampleUrls) {
      const linkCheck = await page.evaluate(async (url: string) => {
        try {
          const resp = await fetch(url, { method: 'HEAD', redirect: 'follow' });
          return resp.status;
        } catch {
          return 0;
        }
      }, articleUrl);
      expect(linkCheck).toBeGreaterThanOrEqual(200);
      expect(linkCheck).toBeLessThan(400);
    }

• Step 3: Run E2E test

cd e2e && docker compose -f docker-compose.test.yml down
docker compose -f docker-compose.test.yml up --build -d
sleep 25 && npx tsx seed.ts && npx playwright test generation-live --reporter=list

• Step 4: Commit

git add e2e/tests/generation-live.spec.ts
git commit -m "test: comprehensive E2E synthesis validation (duplicates, links, counts)"