feat: add search and likes commands

- Add 'twitter search' command with --type (Top/Latest/Photos/Videos), --max, --json, --filter
- Add 'twitter likes' command to view tweets liked by a user
- Add SearchTimeline and Likes GraphQL operations with fallback queryIds
- Update README with new command examples (EN + CN)

twitter_cli/client.py

@@ -28,6 +28,8 @@ FALLBACK_QUERY_IDS = {
     "Bookmarks": "VFdMm9iVZxlU6hD86gfW_A",
     "UserByScreenName": "1VOOyvKkiI3FMmkeDNxM9A",
     "UserTweets": "E3opETHurmVJflFsUBVuUQ",
+    "SearchTimeline": "VhUd6vHVmLBcw0uX-6jMLA",
+    "Likes": "lIDpu_NWL7_VhimGGt0o6A",
 }
 
 TWITTER_OPENAPI_URL = (
@@ -312,6 +314,44 @@ class TwitterClient:
             },
         )
 
+    def fetch_user_likes(self, user_id, count=20):
+        # type: (str, int) -> List[Tweet]
+        """Fetch tweets liked by a user."""
+        return self._fetch_timeline(
+            "Likes",
+            count,
+            lambda data: _deep_get(data, "data", "user", "result", "timeline_v2", "timeline", "instructions"),
+            extra_variables={
+                "userId": user_id,
+                "includePromotedContent": False,
+                "withClientEventToken": False,
+                "withBirdwatchNotes": False,
+                "withVoice": True,
+            },
+        )
+
+    def fetch_search(self, query, count=20, product="Top"):
+        # type: (str, int, str) -> List[Tweet]
+        """Search tweets by query.
+
+        Args:
+            query: Search query string.
+            count: Max number of tweets to return.
+            product: Search tab — "Top", "Latest", "People", "Photos", "Videos".
+        """
+        return self._fetch_timeline(
+            "SearchTimeline",
+            count,
+            lambda data: _deep_get(
+                data, "data", "search_by_raw_query", "search_timeline", "timeline", "instructions",
+            ),
+            extra_variables={
+                "rawQuery": query,
+                "querySource": "typed_query",
+                "product": product,
+            },
+        )
+
     def _fetch_timeline(self, operation_name, count, get_instructions, extra_variables=None):
         # type: (str, int, Callable[[Any], Any], Optional[Dict[str, Any]]) -> List[Tweet]
         """Generic timeline fetcher with pagination and deduplication."""