Implement full media crawler workflow with Flask backend and Vue frontend.

Add TMDB search and media detail pages, HDHive resource ingestion flow, unified error handling, Docker single-container runtime, and project docs/config updates for local deployment.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/adapters/tmdb_adapter.py

@@ -0,0 +1,56 @@
+from config import Config
+from http_client import request_json
+from urllib.parse import quote
+
+
+def _headers():
+    headers = {"Content-Type": "application/json"}
+    if Config.TMDB_TOKEN:
+        headers["Authorization"] = f"Bearer {Config.TMDB_TOKEN}"
+    return headers
+
+
+def search_media(query, media_type="movie", page=1):
+    normalized_type = "tv" if media_type == "tv" else "movie"
+    url = (
+        f"{Config.TMDB_BASE_URL}/search/{normalized_type}"
+        f"?language=zh-CN&query={quote(str(query))}&page={page}"
+    )
+    result = request_json(
+        url,
+        headers=_headers(),
+        max_retry=Config.MAX_RETRY,
+        retry_delay_ms=Config.RETRY_DELAY_MS,
+        provider="tmdb",
+    )
+    data = result.get("data") or {}
+    result["items"] = data.get("results") if isinstance(data, dict) else []
+    return result
+
+
+def get_media_detail(tmdb_id, media_type):
+    normalized_type = "tv" if media_type == "tv" else "movie"
+    url = f"{Config.TMDB_BASE_URL}/{normalized_type}/{tmdb_id}?language=zh-CN"
+    result = request_json(
+        url,
+        headers=_headers(),
+        max_retry=Config.MAX_RETRY,
+        retry_delay_ms=Config.RETRY_DELAY_MS,
+        provider="tmdb",
+    )
+    data = result.get("data") or {}
+    normalized = {
+        "tmdbId": tmdb_id,
+        "type": normalized_type,
+        "title": data.get("title") or data.get("name") or "",
+        "originalTitle": data.get("original_title") or data.get("original_name") or "",
+        "overview": data.get("overview") or "",
+        "year": (data.get("release_date") or data.get("first_air_date") or "")[:4],
+        "rating": data.get("vote_average"),
+        "posterPath": data.get("poster_path") or "",
+        "genres": [g.get("name") for g in data.get("genres", []) if g.get("name")],
+        "seasons": len(data.get("seasons", [])) if isinstance(data.get("seasons"), list) else 0,
+        "raw": data,
+    }
+    result["normalized"] = normalized
+    return result