Initial working version

bot/recommender.py

@@ -0,0 +1,89 @@
+# bot/recommender.py
+
+import openai
+import os
+from dotenv import load_dotenv
+from typing import List, Dict, Literal
+from library_cache import LibraryCache
+from config import OPENAI_API_KEY, OPENAI_MODEL
+
+load_dotenv()
+
+openai.api_key = OPENAI_API_KEY
+
+MediaType = Literal["movie", "show"]
+
+class Recommender:
+    def __init__(self):
+        self.cache = LibraryCache()
+
+    def recommend(self, watched_titles: List[str], media_type: MediaType = "movie", max_recs: int = 5) -> Dict[str, List[str]]:
+        if not watched_titles:
+            raise ValueError("No watched titles provided.")
+
+        prompt = self.build_prompt(watched_titles, media_type, max_recs)
+        response = self.query_openai(prompt)
+
+        print("🧠 Prompt:", prompt)
+        print("📥 Raw response:", response)
+
+        all_titles = self.parse_titles(response)
+        print("📦 Parsed titles:", all_titles)
+
+        available = [title for title in all_titles if self.cache.search(title, media_type)]
+        requestable = [title for title in all_titles if title not in available]
+
+        return {
+            "available": available,
+            "requestable": requestable
+        }
+
+    def build_prompt(self, watched: List[str], media_type: str, max_recs: int) -> str:
+        type_text = "movies" if media_type == "movie" else "TV shows"
+        
+        # You could optionally summarize genres here
+        genre_summary = self.extract_common_genres(watched, media_type)
+
+        return (
+            f"A user has watched the following {type_text}: {', '.join(watched[:20])}. "
+            f"These shows are mostly {genre_summary}. "
+            f"Recommend {max_recs} similar {type_text} based on theme and tone. "
+            f"Return only a plain comma-separated list of titles — no numbers, no explanations."
+        )
+
+    def extract_common_genres(self, watched: List[str], media_type: str) -> str:
+        genre_counts = {}
+        for item in self.cache.data:
+            if item["title"] in watched and item["type"] == media_type:
+                for genre in item.get("genres", []):
+                    genre_counts[genre] = genre_counts.get(genre, 0) + 1
+        sorted_genres = sorted(genre_counts.items(), key=lambda x: x[1], reverse=True)
+        top_genres = [g for g, _ in sorted_genres[:3]]
+        return ", ".join(top_genres) if top_genres else "varied genres"
+
+
+    def query_openai(self, prompt: str) -> str:
+        try:
+            response = openai.ChatCompletion.create(
+                model=OPENAI_MODEL,
+                messages=[
+                    {"role": "system", "content": "You're a helpful and precise media recommender."},
+                    {"role": "user", "content": prompt}
+                ],
+                temperature=0.4,
+                max_tokens=150
+            )
+            return response.choices[0].message.content
+        except Exception as e:
+            print("⚠️ OpenAI API error:", e)
+            return ""
+
+    def parse_titles(self, response: str) -> List[str]:
+        lines = response.replace("\n", ",").split(",")
+        cleaned = []
+        for item in lines:
+            item = item.strip()
+            item = item.lstrip("-•*0123456789. ").strip()
+            if item:
+                cleaned.append(item)
+        return cleaned