hardcopy-search-service-code

services/search.py

@@ -2,34 +2,35 @@ import asyncio
 import json
 import logging
 import os
-import random
+import secrets
 import time
-from typing import Any, Union
+from typing import Any, Optional
 
 import httpx
 
-from orm.shout import Shout
-from settings import TXTAI_SERVICE_URL
-from utils.logger import root_logger as logger
-
 # Set up proper logging
+logger = logging.getLogger("search")
 logger.setLevel(logging.INFO)  # Change to INFO to see more details
-# Disable noise HTTP cltouchient logging
+# Disable noise HTTP client logging
 logging.getLogger("httpx").setLevel(logging.WARNING)
 logging.getLogger("httpcore").setLevel(logging.WARNING)
 
 # Configuration for search service
 SEARCH_ENABLED = bool(os.environ.get("SEARCH_ENABLED", "true").lower() in ["true", "1", "yes"])
+TXTAI_SERVICE_URL = os.environ.get("TXTAI_SERVICE_URL", "none")
 MAX_BATCH_SIZE = int(os.environ.get("SEARCH_MAX_BATCH_SIZE", "25"))
 
 # Search cache configuration
 SEARCH_CACHE_ENABLED = bool(os.environ.get("SEARCH_CACHE_ENABLED", "true").lower() in ["true", "1", "yes"])
-SEARCH_CACHE_TTL_SECONDS = int(os.environ.get("SEARCH_CACHE_TTL_SECONDS", "300"))  # Default: 5 minutes
+SEARCH_CACHE_TTL_SECONDS = int(os.environ.get("SEARCH_CACHE_TTL_SECONDS", "300"))  # Default: 15 minutes
 SEARCH_PREFETCH_SIZE = int(os.environ.get("SEARCH_PREFETCH_SIZE", "200"))
 SEARCH_USE_REDIS = bool(os.environ.get("SEARCH_USE_REDIS", "true").lower() in ["true", "1", "yes"])
 
 search_offset = 0
 
+# Глобальная коллекция для фоновых задач
+background_tasks = []
+
 # Import Redis client if Redis caching is enabled
 if SEARCH_USE_REDIS:
     try:
@@ -45,8 +46,8 @@ class SearchCache:
     """Cache for search results to enable efficient pagination"""
 
     def __init__(self, ttl_seconds: int = SEARCH_CACHE_TTL_SECONDS, max_items: int = 100) -> None:
-        self.cache: dict[str, list] = {}  # Maps search query to list of results
-        self.last_accessed: dict[str, float] = {}  # Maps search query to last access timestamp
+        self.cache = {}  # Maps search query to list of results
+        self.last_accessed = {}  # Maps search query to last access timestamp
         self.ttl = ttl_seconds
         self.max_items = max_items
         self._redis_prefix = "search_cache:"
@@ -58,7 +59,7 @@ class SearchCache:
         if SEARCH_USE_REDIS:
             try:
                 serialized_results = json.dumps(results)
-                await redis.serialize_and_set(
+                await redis.set(
                     f"{self._redis_prefix}{normalized_query}",
                     serialized_results,
                     ex=self.ttl,
@@ -79,7 +80,7 @@ class SearchCache:
         logger.info(f"Cached {len(results)} search results for query '{query}' in memory")
         return True
 
-    async def get(self, query: str, limit: int = 10, offset: int = 0) -> list[dict] | None:
+    async def get(self, query: str, limit: int = 10, offset: int = 0) -> Optional[list]:
         """Get paginated results for a query"""
         normalized_query = self._normalize_query(query)
         all_results = None
@@ -169,7 +170,7 @@ class SearchCache:
             if key in self.last_accessed:
                 del self.last_accessed[key]
 
-        logger.info("Cleaned up %d expired search cache entries", len(expired_keys))
+        logger.info(f"Cleaned up {len(expired_keys)} expired search cache entries")
 
         # If still above max size, remove oldest entries
         if len(self.cache) >= self.max_items:
@@ -182,12 +183,12 @@ class SearchCache:
                     del self.cache[key]
                 if key in self.last_accessed:
                     del self.last_accessed[key]
-            logger.info("Removed %d oldest search cache entries", remove_count)
+            logger.info(f"Removed {remove_count} oldest search cache entries")
 
 
 class SearchService:
     def __init__(self) -> None:
-        logger.info("Initializing search service with URL: %s", TXTAI_SERVICE_URL)
+        logger.info(f"Initializing search service with URL: {TXTAI_SERVICE_URL}")
         self.available = SEARCH_ENABLED
         # Use different timeout settings for indexing and search requests
         self.client = httpx.AsyncClient(timeout=30.0, base_url=TXTAI_SERVICE_URL)
@@ -202,69 +203,81 @@ class SearchService:
             cache_location = "Redis" if SEARCH_USE_REDIS else "Memory"
             logger.info(f"Search caching enabled using {cache_location} cache with TTL={SEARCH_CACHE_TTL_SECONDS}s")
 
-    async def info(self) -> dict[str, Any]:
-        """Check search service info"""
-        if not SEARCH_ENABLED:
-            return {"status": "disabled", "message": "Search is disabled"}
-
+    async def info(self) -> dict:
+        """Return information about search service"""
+        if not self.available:
+            return {"status": "disabled"}
         try:
-            async with httpx.AsyncClient() as client:
-                response = await client.get(f"{TXTAI_SERVICE_URL}/info")
+            response = await self.client.get("/info")
             response.raise_for_status()
             result = response.json()
             logger.info(f"Search service info: {result}")
             return result
-        except (httpx.ConnectError, httpx.ConnectTimeout) as e:
-            # Используем debug уровень для ошибок подключения
-            logger.debug("Search service connection failed: %s", str(e))
-            return {"status": "error", "message": str(e)}
-        except Exception as e:
-            # Другие ошибки логируем как debug
-            logger.debug("Failed to get search info: %s", str(e))
-            return {"status": "error", "message": str(e)}
+        except Exception:
+            logger.exception("Failed to get search info")
+            return {"status": "error", "message": "Failed to get search info"}
 
     def is_ready(self) -> bool:
         """Check if service is available"""
         return self.available
 
-    async def verify_docs(self, doc_ids: list[int]) -> dict[str, Any]:
+    async def verify_docs(self, doc_ids: list) -> dict:
         """Verify which documents exist in the search index across all content types"""
         if not self.available:
-            return {"status": "error", "message": "Search service not available"}
+            return {"status": "disabled"}
 
         try:
-            # Check documents across all content types
-            results = {}
-            for content_type in ["shouts", "authors", "topics"]:
-                endpoint = f"{TXTAI_SERVICE_URL}/exists/{content_type}"
-                async with httpx.AsyncClient() as client:
-                    response = await client.post(endpoint, json={"ids": doc_ids})
+            logger.info(f"Verifying {len(doc_ids)} documents in search index")
+            response = await self.client.post(
+                "/verify-docs",
+                json={"doc_ids": doc_ids},
+                timeout=60.0,  # Longer timeout for potentially large ID lists
+            )
             response.raise_for_status()
-                results[content_type] = response.json()
+            result = response.json()
 
+            # Process the more detailed response format
+            bodies_missing = set(result.get("bodies", {}).get("missing", []))
+            titles_missing = set(result.get("titles", {}).get("missing", []))
+
+            # Combine missing IDs from both bodies and titles
+            # A document is considered missing if it's missing from either index
+            all_missing = list(bodies_missing.union(titles_missing))
+
+            # Log summary of verification results
+            bodies_missing_count = len(bodies_missing)
+            titles_missing_count = len(titles_missing)
+            total_missing_count = len(all_missing)
+
+            logger.info(
+                f"Document verification complete: {bodies_missing_count} bodies missing, {titles_missing_count} titles missing"
+            )
+            logger.info(f"Total unique missing documents: {total_missing_count} out of {len(doc_ids)} total")
+
+            # Return in a backwards-compatible format plus the detailed breakdown
             return {
-                "status": "success",
-                "verified": results,
-                "total_docs": len(doc_ids),
+                "missing": all_missing,
+                "details": {
+                    "bodies_missing": list(bodies_missing),
+                    "titles_missing": list(titles_missing),
+                    "bodies_missing_count": bodies_missing_count,
+                    "titles_missing_count": titles_missing_count,
+                },
             }
-        except Exception as e:
+        except Exception:
             logger.exception("Document verification error")
-            return {"status": "error", "message": str(e)}
+            return {"status": "error", "message": "Document verification error"}
 
-    def index(self, shout: Shout) -> None:
+    def index(self, shout: Any) -> None:
         """Index a single document"""
         if not self.available:
             return
-
         logger.info(f"Indexing post {shout.id}")
-        # Start in background to not block
-        task = asyncio.create_task(self.perform_index(shout))
-        # Store task reference to prevent garbage collection
-        self._background_tasks: set[asyncio.Task[None]] = getattr(self, "_background_tasks", set())
-        self._background_tasks.add(task)
-        task.add_done_callback(self._background_tasks.discard)
+        # Start in background to not block - store reference in a background collection
+        # to prevent garbage collection while keeping the method non-blocking
+        background_tasks.append(asyncio.create_task(self.perform_index(shout)))
 
-    async def perform_index(self, shout: Shout) -> None:
+    async def perform_index(self, shout: Any) -> None:
         """Index a single document across multiple endpoints"""
         if not self.available:
             return
@@ -298,10 +311,8 @@ class SearchService:
                                 body_text_parts.append(media_json["body"])
                     except json.JSONDecodeError:
                         body_text_parts.append(media)
-                elif isinstance(media, dict):
-                    if "title" in media:
+                elif isinstance(media, dict) and (media.get("title") or media.get("body")):
                     body_text_parts.append(media["title"])
-                    if "body" in media:
                     body_text_parts.append(media["body"])
 
             if body_text_parts:
@@ -346,36 +357,32 @@ class SearchService:
                 # Check for errors in responses
                 for i, response in enumerate(responses):
                     if isinstance(response, Exception):
-                        logger.error("Error in indexing task %d: %s", i, response)
+                        logger.error(f"Error in indexing task {i}: {response}")
                     elif hasattr(response, "status_code") and response.status_code >= 400:
-                        error_text = ""
-                        if hasattr(response, "text") and callable(response.text):
-                            try:
-                                error_text = await response.text()
-                            except (Exception, httpx.HTTPError):
-                                error_text = str(response)
-                        logger.error("Error response in indexing task %d: %d, %s", i, response.status_code, error_text)
+                        logger.error(
+                            f"Error response in indexing task {i}: {response.status_code}, {await response.text()}"
+                        )
 
-                logger.info("Document %s indexed across %d endpoints", shout.id, len(indexing_tasks))
+                logger.info(f"Document {shout.id} indexed across {len(indexing_tasks)} endpoints")
             else:
-                logger.warning("No content to index for shout %s", shout.id)
+                logger.warning(f"No content to index for shout {shout.id}")
 
         except Exception:
-            logger.exception("Indexing error for shout %s", shout.id)
+            logger.exception(f"Indexing error for shout {shout.id}")
 
-    async def bulk_index(self, shouts: list[Shout]) -> None:
+    async def bulk_index(self, shouts: list) -> None:
         """Index multiple documents across three separate endpoints"""
         if not self.available or not shouts:
             logger.warning(
-                "Bulk indexing skipped: available=%s, shouts_count=%d", self.available, len(shouts) if shouts else 0
+                f"Bulk indexing skipped: available={self.available}, shouts_count={len(shouts) if shouts else 0}"
             )
             return
 
         start_time = time.time()
-        logger.info("Starting multi-endpoint bulk indexing of %d documents", len(shouts))
+        logger.info(f"Starting multi-endpoint bulk indexing of {len(shouts)} documents")
 
         # Prepare documents for different endpoints
-        title_docs: list[dict[str, Any]] = []
+        title_docs = []
         body_docs = []
         author_docs = {}  # Use dict to prevent duplicate authors
 
@@ -407,10 +414,8 @@ class SearchService:
                                     body_text_parts.append(media_json["body"])
                         except json.JSONDecodeError:
                             body_text_parts.append(media)
-                    elif isinstance(media, dict):
-                        if "title" in media:
+                    elif isinstance(media, dict) and (media.get("title") or media.get("body")):
                         body_text_parts.append(media["title"])
-                        if "body" in media:
                         body_text_parts.append(media["body"])
 
                 # Only add body document if we have body text
@@ -457,7 +462,7 @@ class SearchService:
                         }
 
             except Exception:
-                logger.exception("Error processing shout %s for indexing", getattr(shout, "id", "unknown"))
+                logger.exception(f"Error processing shout {getattr(shout, 'id', 'unknown')} for indexing")
                 total_skipped += 1
 
         # Convert author dict to list
@@ -477,21 +482,18 @@ class SearchService:
 
         elapsed = time.time() - start_time
         logger.info(
-            "Multi-endpoint indexing completed in %.2fs: %d titles, %d bodies, %d authors, %d shouts skipped",
-            elapsed,
-            len(title_docs),
-            len(body_docs),
-            len(author_docs_list),
-            total_skipped,
+            f"Multi-endpoint indexing completed in {elapsed:.2f}s: "
+            f"{len(title_docs)} titles, {len(body_docs)} bodies, {len(author_docs_list)} authors, "
+            f"{total_skipped} shouts skipped"
         )
 
-    async def _index_endpoint(self, documents: list[dict], endpoint: str, doc_type: str) -> None:
+    async def _index_endpoint(self, documents: list, endpoint: str, doc_type: str) -> None:
         """Process and index documents to a specific endpoint"""
         if not documents:
-            logger.info("No %s documents to index", doc_type)
+            logger.info(f"No {doc_type} documents to index")
             return
 
-        logger.info("Indexing %d %s documents", len(documents), doc_type)
+        logger.info(f"Indexing {len(documents)} {doc_type} documents")
 
         # Categorize documents by size
         small_docs, medium_docs, large_docs = self._categorize_by_size(documents, doc_type)
@@ -512,7 +514,7 @@ class SearchService:
                 batch_size = batch_sizes[category]
                 await self._process_batches(docs, batch_size, endpoint, f"{doc_type}-{category}")
 
-    def _categorize_by_size(self, documents: list[dict], doc_type: str) -> tuple[list[dict], list[dict], list[dict]]:
+    def _categorize_by_size(self, documents: list, doc_type: str) -> tuple[list, list, list]:
         """Categorize documents by size for optimized batch processing"""
         small_docs = []
         medium_docs = []
@@ -538,15 +540,11 @@ class SearchService:
                 small_docs.append(doc)
 
         logger.info(
-            "%s documents categorized: %d small, %d medium, %d large",
-            doc_type.capitalize(),
-            len(small_docs),
-            len(medium_docs),
-            len(large_docs),
+            f"{doc_type.capitalize()} documents categorized: {len(small_docs)} small, {len(medium_docs)} medium, {len(large_docs)} large"
         )
         return small_docs, medium_docs, large_docs
 
-    async def _process_batches(self, documents: list[dict], batch_size: int, endpoint: str, batch_prefix: str) -> None:
+    async def _process_batches(self, documents: list, batch_size: int, endpoint: str, batch_prefix: str) -> None:
         """Process document batches with retry logic"""
         for i in range(0, len(documents), batch_size):
             batch = documents[i : i + batch_size]
@@ -563,9 +561,7 @@ class SearchService:
                     if response.status_code == 422:
                         error_detail = response.json()
                         logger.error(
-                            "Validation error from search service for batch %s: %s",
-                            batch_id,
-                            self._truncate_error_detail(error_detail),
+                            f"Validation error from search service for batch {batch_id}: {self._truncate_error_detail(error_detail)}"
                         )
                         break
 
@@ -591,14 +587,14 @@ class SearchService:
                             )
                         else:
                             logger.exception(
-                                "Failed to index single document in batch %s after %d attempts", batch_id, max_retries
+                                f"Failed to index single document in batch {batch_id} after {max_retries} attempts"
                             )
                         break
 
-                    wait_time = (2**retry_count) + (random.SystemRandom().random() * 0.5)
+                    wait_time = (2**retry_count) + (secrets.random() * 0.5)
                     await asyncio.sleep(wait_time)
 
-    def _truncate_error_detail(self, error_detail: Union[dict, str, int]) -> Union[dict, str, int]:
+    def _truncate_error_detail(self, error_detail: Any) -> Any:
         """Truncate error details for logging"""
         truncated_detail = error_detail.copy() if isinstance(error_detail, dict) else error_detail
 
@@ -632,174 +628,115 @@ class SearchService:
 
         return truncated_detail
 
-    async def search(self, text: str, limit: int, offset: int) -> list[dict]:
+    async def search(self, text: str, limit: int, offset: int) -> list:
         """Search documents"""
         if not self.available:
-            logger.warning("Search service not available")
             return []
 
-        if not text or not text.strip():
-            logger.warning("Empty search query provided")
-            return []
+        # Check if we can serve from cache
+        if SEARCH_CACHE_ENABLED:
+            has_cache = await self.cache.has_query(text)
+            if has_cache:
+                cached_results = await self.cache.get(text, limit, offset)
+                if cached_results is not None:
+                    return cached_results
 
-        # Устанавливаем общий размер выборки поиска
+        # Not in cache or cache disabled, perform new search
+        try:
+            # Decide whether to prefetch and cache or just get what we need
             search_limit = SEARCH_PREFETCH_SIZE if SEARCH_CACHE_ENABLED else limit
 
-        logger.info("Searching for: '%s' (limit=%d, offset=%d, search_limit=%d)", text, limit, offset, search_limit)
+            logger.info(f"Searching for: '{text}' (limit={limit}, offset={offset}, search_limit={search_limit})")
 
-        try:
             response = await self.client.post(
                 "/search-combined",
                 json={"text": text, "limit": search_limit},
             )
+            response.raise_for_status()
+            result = response.json()
+            formatted_results = result.get("results", [])
 
-            logger.debug(f"Search service response status: {response.status_code}")
+            # filter out non‑numeric IDs
+            valid_results = [r for r in formatted_results if r.get("id", "").isdigit()]
+            if len(valid_results) != len(formatted_results):
+                formatted_results = valid_results
 
-            if response.status_code != 200:
-                logger.error(f"Search service returned status {response.status_code}: {response.text}")
-                return []
+            if len(valid_results) != len(formatted_results):
+                formatted_results = valid_results
 
-            results = response.json()
-            logger.debug(f"Raw search results: {len(results) if results else 0} items")
-
-            if not results or not isinstance(results, list):
-                logger.warning(f"No search results or invalid format for query '{text}'")
-                return []
-
-            # Обрабатываем каждый результат
-            formatted_results = []
-            for i, item in enumerate(results):
-                if isinstance(item, dict):
-                    formatted_result = self._format_search_result(item)
-                    formatted_results.append(formatted_result)
-                    logger.debug(
-                        f"Formatted result {i}: id={formatted_result.get('id')}, title={formatted_result.get('title', '')[:50]}..."
-                    )
-                else:
-                    logger.warning(f"Invalid search result item {i}: {type(item)}")
-
-            logger.info(f"Successfully formatted {len(formatted_results)} search results for '{text}'")
-
-            # Сохраняем результаты в кеше
-            if SEARCH_CACHE_ENABLED and self.cache:
+            if SEARCH_CACHE_ENABLED:
+                # Store the full prefetch batch, then page it
                 await self.cache.store(text, formatted_results)
-                logger.debug(f"Stored {len(formatted_results)} results in cache for '{text}'")
-
-            # Если включен кеш и есть лишние результаты
-            if SEARCH_CACHE_ENABLED and self.cache and await self.cache.has_query(text):
-                cached_result = await self.cache.get(text, limit, offset)
-                logger.debug(f"Retrieved {len(cached_result) if cached_result else 0} results from cache for '{text}'")
-                return cached_result or []
+                return await self.cache.get(text, limit, offset)
 
             return formatted_results
-
-        except Exception as e:
-            logger.error(f"Search error for '{text}': {e}", exc_info=True)
+        except Exception:
+            logger.exception(f"Search error for '{text}'")
             return []
 
-    async def search_authors(self, text: str, limit: int = 10, offset: int = 0) -> list[dict]:
+    async def search_authors(self, text: str, limit: int = 10, offset: int = 0) -> list:
         """Search only for authors using the specialized endpoint"""
         if not self.available or not text.strip():
             return []
 
-        # Кеш для авторов
         cache_key = f"author:{text}"
-        if SEARCH_CACHE_ENABLED and self.cache and await self.cache.has_query(cache_key):
+
+        # Check if we can serve from cache
+        if SEARCH_CACHE_ENABLED:
+            has_cache = await self.cache.has_query(cache_key)
+            if has_cache:
                 cached_results = await self.cache.get(cache_key, limit, offset)
-            if cached_results:
+                if cached_results is not None:
                     return cached_results
 
+        # Not in cache or cache disabled, perform new search
         try:
-            # Устанавливаем общий размер выборки поиска
             search_limit = SEARCH_PREFETCH_SIZE if SEARCH_CACHE_ENABLED else limit
 
             logger.info(
-                "Searching authors for: '%s' (limit=%d, offset=%d, search_limit=%d)", text, limit, offset, search_limit
+                f"Searching authors for: '{text}' (limit={limit}, offset={offset}, search_limit={search_limit})"
             )
             response = await self.client.post("/search-author", json={"text": text, "limit": search_limit})
+            response.raise_for_status()
 
-            results = await response.json()
-            if not results or not isinstance(results, list):
-                return []
+            result = response.json()
+            author_results = result.get("results", [])
 
-            # Форматируем результаты поиска авторов
-            author_results = []
-            for item in results:
-                if isinstance(item, dict):
-                    formatted_author = self._format_author_result(item)
-                    author_results.append(formatted_author)
+            # Filter out any invalid results if necessary
+            valid_results = [r for r in author_results if r.get("id", "").isdigit()]
+            if len(valid_results) != len(author_results):
+                author_results = valid_results
 
-            # Сохраняем результаты в кеше
-            if SEARCH_CACHE_ENABLED and self.cache:
+            if SEARCH_CACHE_ENABLED:
+                # Store the full prefetch batch, then page it
                 await self.cache.store(cache_key, author_results)
+                return await self.cache.get(cache_key, limit, offset)
 
-            # Возвращаем нужную порцию результатов
             return author_results[offset : offset + limit]
 
         except Exception:
-            logger.exception("Error searching authors for '%s'", text)
+            logger.exception(f"Error searching authors for '{text}'")
             return []
 
     async def check_index_status(self) -> dict:
         """Get detailed statistics about the search index health"""
         if not self.available:
-            return {"status": "unavailable", "message": "Search service not available"}
+            return {"status": "disabled"}
 
         try:
-            response = await self.client.post("/check-index")
-            result = await response.json()
+            response = await self.client.get("/index-status")
+            response.raise_for_status()
+            result = response.json()
 
-            if isinstance(result, dict):
-                # Проверяем на NULL эмбеддинги
+            if result.get("consistency", {}).get("status") != "ok":
                 null_count = result.get("consistency", {}).get("null_embeddings_count", 0)
                 if null_count > 0:
-                    logger.warning("Found %d documents with NULL embeddings", null_count)
-        except Exception as e:
-            logger.exception("Failed to check index status")
-            return {"status": "error", "message": str(e)}
-        else:
+                    logger.warning(f"Found {null_count} documents with NULL embeddings")
+
             return result
-
-    def _format_search_result(self, item: dict) -> dict:
-        """Format search result item"""
-        formatted_result = {}
-
-        # Обязательные поля
-        if "id" in item:
-            formatted_result["id"] = item["id"]
-        if "title" in item:
-            formatted_result["title"] = item["title"]
-        if "body" in item:
-            formatted_result["body"] = item["body"]
-
-        # Дополнительные поля
-        for field in ["subtitle", "lead", "author_id", "author_name", "created_at", "stat"]:
-            if field in item:
-                formatted_result[field] = item[field]
-
-        return formatted_result
-
-    def _format_author_result(self, item: dict) -> dict:
-        """Format author search result item"""
-        formatted_result = {}
-
-        # Обязательные поля для автора
-        if "id" in item:
-            formatted_result["id"] = item["id"]
-        if "name" in item:
-            formatted_result["name"] = item["name"]
-        if "username" in item:
-            formatted_result["username"] = item["username"]
-
-        # Дополнительные поля для автора
-        for field in ["slug", "bio", "pic", "created_at", "stat"]:
-            if field in item:
-                formatted_result[field] = item[field]
-
-        return formatted_result
-
-    def close(self) -> None:
-        """Close the search service"""
+        except Exception:
+            logger.exception("Failed to check index status")
+            return {"status": "error", "message": "Failed to check index status"}
 
 
 # Create the search service singleton
@@ -808,14 +745,14 @@ search_service = SearchService()
 # API-compatible function to perform a search
 
 
-async def search_text(text: str, limit: int = 200, offset: int = 0) -> list[dict]:
+async def search_text(text: str, limit: int = 200, offset: int = 0) -> list:
     payload = []
     if search_service.available:
         payload = await search_service.search(text, limit, offset)
     return payload
 
 
-async def search_author_text(text: str, limit: int = 10, offset: int = 0) -> list[dict]:
+async def search_author_text(text: str, limit: int = 10, offset: int = 0) -> list:
     """Search authors API helper function"""
     if search_service.available:
         return await search_service.search_authors(text, limit, offset)
@@ -827,11 +764,11 @@ async def get_search_count(text: str) -> int:
     if not search_service.available:
         return 0
 
-    if SEARCH_CACHE_ENABLED and search_service.cache is not None and await search_service.cache.has_query(text):
+    if SEARCH_CACHE_ENABLED and await search_service.cache.has_query(text):
         return await search_service.cache.get_total_count(text)
 
-    # Return approximate count for active search
-    return 42  # Placeholder implementation
+    # If not found in cache, fetch from endpoint
+    return len(await search_text(text, SEARCH_PREFETCH_SIZE, 0))
 
 
 async def get_author_search_count(text: str) -> int:
@@ -841,31 +778,48 @@ async def get_author_search_count(text: str) -> int:
 
     if SEARCH_CACHE_ENABLED:
         cache_key = f"author:{text}"
-        if search_service.cache is not None and await search_service.cache.has_query(cache_key):
+        if await search_service.cache.has_query(cache_key):
             return await search_service.cache.get_total_count(cache_key)
 
-    return 0  # Placeholder implementation
+    # If not found in cache, fetch from endpoint
+    return len(await search_author_text(text, SEARCH_PREFETCH_SIZE, 0))
 
 
 async def initialize_search_index(shouts_data: list) -> None:
     """Initialize search index with existing data during application startup"""
     if not SEARCH_ENABLED:
-        logger.info("Search is disabled, skipping index initialization")
         return
 
-    if not search_service.available:
-        logger.warning("Search service not available, skipping index initialization")
+    if not shouts_data:
         return
 
+    info = await search_service.info()
+    if info.get("status") in ["error", "unavailable", "disabled"]:
+        return
+
+    index_stats = info.get("index_stats", {})
+    indexed_doc_count = index_stats.get("total_count", 0)
+
+    index_status = await search_service.check_index_status()
+    if index_status.get("status") == "inconsistent":
+        problem_ids = index_status.get("consistency", {}).get("null_embeddings_sample", [])
+
+        if problem_ids:
+            problem_docs = [shout for shout in shouts_data if str(shout.id) in problem_ids]
+            if problem_docs:
+                await search_service.bulk_index(problem_docs)
+
     # Only consider shouts with body content for body verification
-    def has_body_content(shout: dict) -> bool:
+    def has_body_content(shout: Any) -> bool:
         for field in ["subtitle", "lead", "body"]:
-            if hasattr(shout, field) and getattr(shout, field) and getattr(shout, field).strip():
+            if (
+                getattr(shout, field, None)
+                and isinstance(getattr(shout, field, None), str)
+                and getattr(shout, field).strip()
+            ):
                 return True
-
-        # Check media JSON for content
-        if hasattr(shout, "media") and shout.media:
-            media = shout.media
+        media = getattr(shout, "media", None)
+        if media:
             if isinstance(media, str):
                 try:
                     media_json = json.loads(media)
@@ -877,26 +831,36 @@ async def initialize_search_index(shouts_data: list) -> None:
                 return True
         return False
 
-    total_count = len(shouts_data)
-    processed_count = 0
+    shouts_with_body = [shout for shout in shouts_data if has_body_content(shout)]
+    body_ids = [str(shout.id) for shout in shouts_with_body]
 
-    # Collect categories while we're at it for informational purposes
-    categories: set = set()
-
-    try:
-        for shout in shouts_data:
-            # Skip items that lack meaningful text content
-            if not has_body_content(shout):
-                continue
-
-            # Track categories
-            matching_shouts = [s for s in shouts_data if getattr(s, "id", None) == getattr(shout, "id", None)]
-            if matching_shouts and hasattr(matching_shouts[0], "category"):
-                categories.add(getattr(matching_shouts[0], "category", "unknown"))
-    except (AttributeError, TypeError):
+    if abs(indexed_doc_count - len(shouts_data)) > 10:
+        doc_ids = [str(shout.id) for shout in shouts_data]
+        verification = await search_service.verify_docs(doc_ids)
+        if verification.get("status") == "error":
+            return
+        # Only reindex missing docs that actually have body content
+        missing_ids = [mid for mid in verification.get("missing", []) if mid in body_ids]
+        if missing_ids:
+            missing_docs = [shout for shout in shouts_with_body if str(shout.id) in missing_ids]
+            await search_service.bulk_index(missing_docs)
+    else:
         pass
 
-    logger.info("Search index initialization completed: %d/%d items", processed_count, total_count)
+    try:
+        test_query = "test"
+        # Use body search since that's most likely to return results
+        test_results = await search_text(test_query, 5)
+
+        if test_results:
+            categories = set()
+            for result in test_results:
+                result_id = result.get("id")
+                matching_shouts = [s for s in shouts_data if str(s.id) == result_id]
+                if matching_shouts and hasattr(matching_shouts[0], "category"):
+                    categories.add(getattr(matching_shouts[0], "category", "unknown"))
+    except Exception as ex:
+        logger.warning(f"Test search failed during initialization: {ex}")
 
 
 async def check_search_service() -> None: