chore: import upstream snapshot with attribution

tests/test_llmtxt.py

@@ -0,0 +1,52 @@
+from crawl4ai.llmtxt import AsyncLLMTextManager  # Changed to AsyncLLMTextManager
+from crawl4ai.async_logger import AsyncLogger
+from pathlib import Path
+import asyncio
+
+
+async def main():
+    current_file = Path(__file__).resolve()
+    # base_dir = current_file.parent.parent / "local/_docs/llm.txt/test_docs"
+    base_dir = current_file.parent.parent / "local/_docs/llm.txt"
+    docs_dir = base_dir
+
+    # Create directory if it doesn't exist
+    docs_dir.mkdir(parents=True, exist_ok=True)
+
+    # Initialize logger
+    logger = AsyncLogger()
+    # Updated initialization with default batching params
+    # manager = AsyncLLMTextManager(docs_dir, logger, max_concurrent_calls=3, batch_size=2)
+    manager = AsyncLLMTextManager(docs_dir, logger, batch_size=2)
+
+    # Let's first check what files we have
+    print("\nAvailable files:")
+    for f in docs_dir.glob("*.md"):
+        print(f"- {f.name}")
+
+    # Generate index files
+    print("\nGenerating index files...")
+    await manager.generate_index_files(
+        force_generate_facts=False, clear_bm25_cache=False
+    )
+
+    # Test some relevant queries about Crawl4AI
+    test_queries = [
+        "How is using the `arun_many` method?",
+    ]
+
+    print("\nTesting search functionality:")
+    for query in test_queries:
+        print(f"\nQuery: {query}")
+        results = manager.search(query, top_k=2)
+        print(f"Results length: {len(results)} characters")
+        if results:
+            print(
+                "First 200 chars of results:", results[:200].replace("\n", " "), "..."
+            )
+        else:
+            print("No results found")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())