feat: implement Phase 6 Agent Integration (Translation API)

src/api/agent_api.rs

@@ -0,0 +1,87 @@
+use axum::{
+    extract::State,
+    http::StatusCode,
+    response::Json,
+    routing::post,
+    Router,
+};
+use reqwest::Client;
+use serde::{Deserialize, Serialize};
+use tracing;
+
+use crate::api::server::AppState;
+
+pub fn agent_routes() -> Router<AppState> {
+    Router::new()
+        .route("/api/v1/agents/translate", post(translate_text))
+}
+
+#[derive(Debug, Deserialize)]
+pub struct TranslationRequest {
+    pub text: String,
+    pub target_language: String,
+    pub source_language: Option<String>, // "auto" if not specified
+}
+
+#[derive(Debug, Serialize)]
+pub struct TranslationResponse {
+    pub success: bool,
+    pub translated_text: String,
+    pub source_language_detected: String,
+    pub model_used: String,
+}
+
+async fn translate_text(
+    State(_state): State<AppState>,
+    Json(req): Json<TranslationRequest>,
+) -> Result<Json<TranslationResponse>, (StatusCode, String)> {
+    
+    let system_prompt = "You are a professional translator for Momentry Core, a digital asset management system specializing in video analysis.
+    
+    ## Guidelines:
+    1. **Accuracy**: Translate the meaning accurately, maintaining the original tone.
+    2. **Style**: 
+       - For subtitles: Keep it concise and natural for reading.
+       - For technical terms (e.g., 5W1H, metadata): Use standard industry translations.
+    3. **Output**: Return ONLY the translated text. Do not include explanations or notes.";
+
+    let prompt = format!(
+        "Translate the following text to {}: \n\n{}",
+        req.target_language, req.text
+    );
+
+    // Call Ollama API
+    let client = Client::new();
+    let ollama_url = "http://localhost:11434/api/generate";
+    
+    // Using qwen3:latest which is available locally
+    let model = "qwen3:latest".to_string();
+
+    let body = serde_json::json!({
+        "model": model,
+        "prompt": prompt,
+        "system": system_prompt,
+        "stream": false
+    });
+
+    let response = client.post(ollama_url)
+        .json(&body)
+        .send()
+        .await
+        .map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, format!("Failed to call LLM: {}", e)))?;
+
+    let ollama_resp: serde_json::Value = response.json().await
+        .map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, format!("Failed to parse LLM response: {}", e)))?;
+
+    let translated_text = ollama_resp.get("response")
+        .and_then(|v| v.as_str())
+        .unwrap_or("Translation failed")
+        .to_string();
+
+    Ok(Json(TranslationResponse {
+        success: true,
+        translated_text,
+        source_language_detected: req.source_language.unwrap_or("unknown".to_string()),
+        model_used: model,
+    }))
+}

src/api/mod.rs

@@ -1,3 +1,4 @@
+pub mod agent_api;
 pub mod face_recognition;
 pub mod identities;
 pub mod identity_api;

src/api/server.rs

@@ -20,6 +20,7 @@ use crate::core::db::{Database, PostgresDb, QdrantDb, RedisClient, VideoRecord,
 use crate::core::text::tokenizer::tokenize_chinese_text;
 use crate::{Embedder, FileManager};
 
+use super::agent_api;
 use super::face_recognition;
 use super::identities;
 use super::identity_binding;
@@ -2482,6 +2483,7 @@ pub async fn start_server(host: &str, port: u16) -> anyhow::Result<()> {
             post(search_visual_chunks_by_combination),
         )
         .merge(identity_api::identity_routes()) // Phase 3 Routes
+        .merge(agent_api::agent_routes()) // Phase 6 Routes
         .merge(protected_routes)
         .layer(cors)
         .with_state(state);