feat: add MockLlmProvider for integration testing

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/src/services/llm/mock.rs

@@ -0,0 +1,134 @@
+//! Mock LLM provider for integration testing.
+
+use std::sync::Arc;
+use async_trait::async_trait;
+use serde_json::{json, Value};
+use crate::errors::AppError;
+use super::LlmProvider;
+
+/// A mock LLM provider that returns deterministic responses.
+pub struct MockLlmProvider {
+    default_category: String,
+    search_urls: Vec<String>,
+    link_urls: Vec<String>,
+}
+
+impl MockLlmProvider {
+    pub fn new() -> Self {
+        Self {
+            default_category: "Autre".to_string(),
+            search_urls: Vec::new(),
+            link_urls: Vec::new(),
+        }
+    }
+
+    pub fn with_default_category(mut self, category: &str) -> Self {
+        self.default_category = category.to_string();
+        self
+    }
+
+    pub fn with_search_urls(mut self, urls: Vec<String>) -> Self {
+        self.search_urls = urls;
+        self
+    }
+
+    pub fn with_link_urls(mut self, urls: Vec<String>) -> Self {
+        self.link_urls = urls;
+        self
+    }
+
+    pub fn into_arc(self) -> Arc<dyn LlmProvider> {
+        Arc::new(self)
+    }
+}
+
+#[async_trait]
+impl LlmProvider for MockLlmProvider {
+    fn provider_id(&self) -> &str {
+        "mock"
+    }
+
+    async fn call_llm(
+        &self,
+        _model: &str,
+        system_prompt: &str,
+        user_prompt: &str,
+        _response_schema: &Value,
+    ) -> Result<Value, AppError> {
+        let sys_lower = system_prompt.to_lowercase();
+
+        // Classify/summarize call
+        if sys_lower.contains("classer") {
+            let title = user_prompt
+                .lines()
+                .find(|l| l.starts_with("Titre : "))
+                .map(|l| l.trim_start_matches("Titre : ").to_string())
+                .unwrap_or_else(|| "Mock Article".to_string());
+
+            return Ok(json!({
+                "title": title,
+                "summary": format!("Mock summary for: {}", title),
+                "category": self.default_category,
+            }));
+        }
+
+        // Link extraction call
+        if sys_lower.contains("liens") {
+            return Ok(json!({ "urls": self.link_urls }));
+        }
+
+        // Search call
+        if sys_lower.contains("precis") {
+            let items: Vec<Value> = self.search_urls.iter().map(|url| {
+                json!({
+                    "title": format!("Search result: {}", url),
+                    "url": url,
+                    "summary": format!("Mock search summary for {}", url),
+                })
+            }).collect();
+            return Ok(json!({ "category_0": items }));
+        }
+
+        Ok(json!({"result": "mock response"}))
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[tokio::test]
+    async fn mock_provider_returns_classify_response() {
+        let provider = MockLlmProvider::new().with_default_category("AI News");
+        let result = provider
+            .call_llm("model", "Tu dois classer l'article", "Titre : GPT-7\n\nContenu...", &json!({}))
+            .await
+            .unwrap();
+        assert_eq!(result["title"], "GPT-7");
+        assert_eq!(result["category"], "AI News");
+    }
+
+    #[tokio::test]
+    async fn mock_provider_returns_search_response() {
+        let provider = MockLlmProvider::new()
+            .with_search_urls(vec!["http://example.com/a".into()]);
+        let result = provider
+            .call_llm("model", "Tu es un assistant IA precis", "Recherche...", &json!({}))
+            .await
+            .unwrap();
+        let items = result["category_0"].as_array().unwrap();
+        assert_eq!(items.len(), 1);
+    }
+
+    #[tokio::test]
+    async fn mock_provider_returns_link_extraction() {
+        let provider = MockLlmProvider::new()
+            .with_link_urls(vec!["http://example.com/post-1".into()]);
+        let result = provider
+            .call_llm("model", "Tu dois identifier les liens", "Links...", &json!({}))
+            .await
+            .unwrap();
+        let urls = result["urls"].as_array().unwrap();
+        assert_eq!(urls.len(), 1);
+    }
+}

backend/src/services/llm/mod.rs

@@ -6,6 +6,7 @@
 pub mod anthropic;
 pub mod factory;
 pub mod gemini;
+pub mod mock;
 pub mod openai;
 pub mod schema;