refactor: unified LLM config - CHAT_URL/VISION_URL/SUMMARY_URL with env var overrides
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@@ -41,10 +41,10 @@ async fn translate_text(
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req.target_language, req.text
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);
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// Call Gemma4 via llama.cpp (port 8082, OpenAI-compatible API)
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// Call LLM via configurable endpoint
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let client = Client::new();
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let llm_url = "http://localhost:8082/v1/chat/completions";
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let model = "google_gemma-4-26B-A4B-it-Q5_K_M.gguf".to_string();
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let llm_url = crate::core::config::llm::CHAT_URL.as_str();
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let model = crate::core::config::llm::CHAT_MODEL.as_str();
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let body = serde_json::json!({
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"model": model,
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@@ -71,20 +71,15 @@ async fn translate_text(
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)
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})?;
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let translated_text = llm_resp
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.get("choices")
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.and_then(|c| c.as_array())
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.and_then(|c| c.first())
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.and_then(|c| c.get("message"))
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.and_then(|m| m.get("content"))
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.and_then(|v| v.as_str())
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.unwrap_or("Translation failed")
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let translated_text = llm_resp["choices"][0]["message"]["content"]
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.as_str()
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.unwrap_or("")
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.to_string();
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Ok(Json(TranslationResponse {
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success: true,
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translated_text,
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source_language_detected: req.source_language.unwrap_or("unknown".to_string()),
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model_used: model,
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source_language_detected: req.source_language.unwrap_or_else(|| "auto".to_string()),
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model_used: model.to_string(),
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}))
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}
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@@ -96,27 +96,11 @@ struct SceneSummaryResult {
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// ── LLM Endpoint ──
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fn llm_base_url() -> String {
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let v = std::env::var("MOMENTRY_LLM_URL");
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if v.is_ok() {
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return v.unwrap();
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}
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let v = std::env::var("MOMENTRY_LLM_SUMMARY_URL");
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if v.is_ok() {
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return v.unwrap();
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}
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"http://localhost:8082/v1/chat/completions".to_string()
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crate::core::config::llm::SUMMARY_URL.clone()
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}
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fn llm_model() -> String {
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let v = std::env::var("MOMENTRY_LLM_MODEL");
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if v.is_ok() {
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return v.unwrap();
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}
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let v = std::env::var("MOMENTRY_LLM_SUMMARY_MODEL");
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if v.is_ok() {
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return v.unwrap();
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}
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"google_gemma-4-26B-A4B-it-Q5_K_M.gguf".to_string()
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crate::core::config::llm::SUMMARY_MODEL.clone()
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}
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// ── Data Fetching ──
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