update recommender and news_fetcher

backend/main.py

@@ -1,7 +1,7 @@
 from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 from .news_fetcher import fetch_all_news, save_raw_news, save_processed_news
-from .recommender import recommend_similar, process_articles_for_vector_db
+from .recommender import recommend_similar, process_articles_for_vector_db, news_recommender
 from .recommender import analyze_article_with_groq
 from .recommender import get_personalized_recommendations, vector_db
 from .vector_store import VectorDB
@@ -41,7 +41,7 @@ async def root():
 
 @app.get("/fetch-news")
 async def fetch_news():
-    """Fetch news from RSS feeds"""
+    """Fetch news from RSS feeds with duplicate detection"""
     try:
         articles = fetch_all_news()
 
@@ -74,7 +74,7 @@ async def fetch_news():
 
 @app.get("/recommend-news")
 async def recommend_news(article_id: str):
-    """Retrieve similar news based on the selected article"""
+    """Retrieve similar news based on the selected article (backward compatibility)"""
     try:
         recommendations = recommend_similar(article_id)
 
@@ -91,6 +91,25 @@ async def recommend_news(article_id: str):
         raise HTTPException(status_code=500, detail=f"Error getting recommendations: {str(e)}")
 
 
+@app.get("/recommend-by-text")
+async def recommend_by_text(text_description: str, top_n: int = 3):
+    """Recommend articles based on text description"""
+    try:
+        recommendations = news_recommender.recommend_by_text(text_description, top_n)
+
+        if not recommendations:
+            raise HTTPException(status_code=404, detail="No recommendations found")
+
+        return {
+            "text_description": text_description,
+            "recommendations": recommendations,
+            "count": len(recommendations)
+        }
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Error getting recommendations: {str(e)}")
+
+
 @app.get("/analyze-article")
 async def analyze_article(article_id: str):
     """Analyze article using Groq LLM"""
@@ -134,6 +153,7 @@ async def health_check():
     """Health check endpoint"""
     return {"status": "healthy", "database_articles": len(vector_db.articles)}
 
+
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+    uvicorn.run(app, host="0.0.0.0", port=8000)