feat: cli tool

packages/leann-core/pyproject.toml

@@ -15,5 +15,8 @@ dependencies = [
     "tqdm>=4.60.0"
 ]
 
+[project.scripts]
+leann = "leann.cli:main"
+
 [tool.setuptools.packages.find]
 where = ["src"]

packages/leann-core/src/leann/cli.py

@@ -0,0 +1,257 @@
+#!/usr/bin/env python3
+import argparse
+import asyncio
+import sys
+from pathlib import Path
+from typing import Optional
+import os
+
+from llama_index.core import SimpleDirectoryReader
+from llama_index.core.node_parser import SentenceSplitter
+
+from .api import LeannBuilder, LeannSearcher, LeannChat
+
+
+class LeannCLI:
+    def __init__(self):
+        self.indexes_dir = Path.home() / ".leann" / "indexes"
+        self.indexes_dir.mkdir(parents=True, exist_ok=True)
+        
+        self.node_parser = SentenceSplitter(
+            chunk_size=256, chunk_overlap=128, separator=" ", paragraph_separator="\n\n"
+        )
+    
+    def get_index_path(self, index_name: str) -> str:
+        index_dir = self.indexes_dir / index_name
+        return str(index_dir / "documents.leann")
+    
+    def index_exists(self, index_name: str) -> bool:
+        index_dir = self.indexes_dir / index_name
+        meta_file = index_dir / "documents.leann.meta.json"
+        return meta_file.exists()
+    
+    def create_parser(self) -> argparse.ArgumentParser:
+        parser = argparse.ArgumentParser(
+            prog="leann",
+            description="LEANN - Local Enhanced AI Navigation",
+            formatter_class=argparse.RawDescriptionHelpFormatter,
+            epilog="""
+Examples:
+  leann build my-docs --docs ./documents    # Build index named my-docs
+  leann search my-docs "query"             # Search in my-docs index
+  leann ask my-docs "question"             # Ask my-docs index
+  leann list                              # List all stored indexes
+            """
+        )
+        
+        subparsers = parser.add_subparsers(dest="command", help="Available commands")
+        
+        # Build command
+        build_parser = subparsers.add_parser("build", help="Build document index")
+        build_parser.add_argument("index_name", help="Index name")
+        build_parser.add_argument("--docs", type=str, required=True, help="Documents directory")
+        build_parser.add_argument("--backend", type=str, default="hnsw", choices=["hnsw", "diskann"])
+        build_parser.add_argument("--embedding-model", type=str, default="facebook/contriever")
+        build_parser.add_argument("--force", "-f", action="store_true", help="Force rebuild")
+        
+        # Search command
+        search_parser = subparsers.add_parser("search", help="Search documents")
+        search_parser.add_argument("index_name", help="Index name")
+        search_parser.add_argument("query", help="Search query")
+        search_parser.add_argument("--top-k", type=int, default=5)
+        
+        # Ask command
+        ask_parser = subparsers.add_parser("ask", help="Ask questions")
+        ask_parser.add_argument("index_name", help="Index name")
+        ask_parser.add_argument("--llm", type=str, default="ollama", choices=["simulated", "ollama", "hf", "openai"])
+        ask_parser.add_argument("--model", type=str, default="qwen3:8b")
+        ask_parser.add_argument("--host", type=str, default="http://localhost:11434")
+        ask_parser.add_argument("--interactive", "-i", action="store_true")
+        
+        # List command
+        list_parser = subparsers.add_parser("list", help="List all indexes")
+        
+        return parser
+    
+    def list_indexes(self):
+        print("Stored LEANN indexes:")
+        
+        if not self.indexes_dir.exists():
+            print("No indexes found. Use 'leann build <name> --docs <dir>' to create one.")
+            return
+        
+        index_dirs = [d for d in self.indexes_dir.iterdir() if d.is_dir()]
+        
+        if not index_dirs:
+            print("No indexes found. Use 'leann build <name> --docs <dir>' to create one.")
+            return
+        
+        print(f"Found {len(index_dirs)} indexes:")
+        for i, index_dir in enumerate(index_dirs, 1):
+            index_name = index_dir.name
+            status = "✓" if self.index_exists(index_name) else "✗"
+            
+            print(f"  {i}. {index_name} [{status}]")
+            if self.index_exists(index_name):
+                meta_file = index_dir / "documents.leann.meta.json"
+                size_mb = sum(f.stat().st_size for f in index_dir.iterdir() if f.is_file()) / (1024 * 1024)
+                print(f"     Size: {size_mb:.1f} MB")
+        
+        if index_dirs:
+            example_name = index_dirs[0].name
+            print(f"\nUsage:")
+            print(f"  leann search {example_name} \"your query\"")
+            print(f"  leann ask {example_name} --interactive")
+    
+    def load_documents(self, docs_dir: str):
+        print(f"Loading documents from {docs_dir}...")
+        
+        documents = SimpleDirectoryReader(
+            docs_dir,
+            recursive=True,
+            encoding="utf-8",
+            required_exts=[".pdf", ".txt", ".md", ".docx"],
+        ).load_data(show_progress=True)
+        
+        all_texts = []
+        for doc in documents:
+            nodes = self.node_parser.get_nodes_from_documents([doc])
+            for node in nodes:
+                all_texts.append(node.get_content())
+        
+        print(f"Loaded {len(documents)} documents, {len(all_texts)} chunks")
+        return all_texts
+    
+    async def build_index(self, args):
+        docs_dir = args.docs
+        index_name = args.index_name
+        index_dir = self.indexes_dir / index_name
+        index_path = self.get_index_path(index_name)
+        
+        if index_dir.exists() and not args.force:
+            print(f"Index '{index_name}' already exists. Use --force to rebuild.")
+            return
+        
+        all_texts = self.load_documents(docs_dir)
+        if not all_texts:
+            print("No documents found")
+            return
+        
+        index_dir.mkdir(parents=True, exist_ok=True)
+        
+        print(f"Building index '{index_name}' with {args.backend} backend...")
+        
+        builder = LeannBuilder(
+            backend_name=args.backend,
+            embedding_model=args.embedding_model,
+            graph_degree=32,
+            complexity=64,
+            is_compact=True,
+            is_recompute=True,
+            num_threads=1,
+        )
+        
+        for chunk_text in all_texts:
+            builder.add_text(chunk_text)
+        
+        builder.build_index(index_path)
+        print(f"Index built at {index_path}")
+    
+    async def search_documents(self, args):
+        index_name = args.index_name
+        query = args.query
+        index_path = self.get_index_path(index_name)
+        
+        if not self.index_exists(index_name):
+            print(f"Index '{index_name}' not found. Use 'leann build {index_name} --docs <dir>' to create it.")
+            return
+        
+        searcher = LeannSearcher(index_path=index_path)
+        results = searcher.search(query, top_k=args.top_k)
+        
+        print(f"Search results for '{query}' (top {len(results)}):")
+        for i, result in enumerate(results, 1):
+            print(f"{i}. Score: {result.score:.3f}")
+            print(f"   {result.text[:200]}...")
+            print()
+    
+    async def ask_questions(self, args):
+        index_name = args.index_name
+        index_path = self.get_index_path(index_name)
+        
+        if not self.index_exists(index_name):
+            print(f"Index '{index_name}' not found. Use 'leann build {index_name} --docs <dir>' to create it.")
+            return
+        
+        print(f"Starting chat with index '{index_name}'...")
+        print(f"Using {args.model} ({args.llm})")
+        
+        llm_config = {"type": args.llm, "model": args.model}
+        if args.llm == "ollama":
+            llm_config["host"] = args.host
+        
+        chat = LeannChat(index_path=index_path, llm_config=llm_config)
+        
+        if args.interactive:
+            print("LEANN Assistant ready! Type 'quit' to exit")
+            print("=" * 40)
+            
+            while True:
+                user_input = input("\nYou: ").strip()
+                if user_input.lower() in ['quit', 'exit', 'q']:
+                    print("Goodbye!")
+                    break
+                
+                if not user_input:
+                    continue
+                
+                response = chat.ask(
+                    user_input, 
+                    top_k=20, 
+                    recompute_beighbor_embeddings=True, 
+                    complexity=32
+                )
+                print(f"LEANN: {response}")
+        else:
+            query = input("Enter your question: ").strip()
+            if query:
+                response = chat.ask(
+                    query, 
+                    top_k=20, 
+                    recompute_beighbor_embeddings=True, 
+                    complexity=32
+                )
+                print(f"LEANN: {response}")
+    
+    async def run(self, args=None):
+        parser = self.create_parser()
+        
+        if args is None:
+            args = parser.parse_args()
+        
+        if not args.command:
+            parser.print_help()
+            return
+        
+        if args.command == "list":
+            self.list_indexes()
+        elif args.command == "build":
+            await self.build_index(args)
+        elif args.command == "search":
+            await self.search_documents(args)
+        elif args.command == "ask":
+            await self.ask_questions(args)
+        else:
+            parser.print_help()
+
+
+def main():
+    import dotenv
+    dotenv.load_dotenv()
+    
+    cli = LeannCLI()
+    asyncio.run(cli.run())
+
+
+if __name__ == "__main__":
+    main()

packages/leann-core/src/leann/registry.py

@@ -7,30 +7,37 @@ import importlib.metadata
 if TYPE_CHECKING:
     from leann.interface import LeannBackendFactoryInterface
 
-BACKEND_REGISTRY: Dict[str, 'LeannBackendFactoryInterface'] = {}
+BACKEND_REGISTRY: Dict[str, "LeannBackendFactoryInterface"] = {}
+
 
 def register_backend(name: str):
     """A decorator to register a new backend class."""
+
     def decorator(cls):
         print(f"INFO: Registering backend '{name}'")
         BACKEND_REGISTRY[name] = cls
         return cls
+
     return decorator
 
+
 def autodiscover_backends():
     """Automatically discovers and imports all 'leann-backend-*' packages."""
-    print("INFO: Starting backend auto-discovery...")
+    # print("INFO: Starting backend auto-discovery...")
     discovered_backends = []
     for dist in importlib.metadata.distributions():
-        dist_name = dist.metadata['name']
-        if dist_name.startswith('leann-backend-'):
-            backend_module_name = dist_name.replace('-', '_')
+        dist_name = dist.metadata["name"]
+        if dist_name.startswith("leann-backend-"):
+            backend_module_name = dist_name.replace("-", "_")
             discovered_backends.append(backend_module_name)
-            
-    for backend_module_name in sorted(discovered_backends): # sort for deterministic loading
+
+    for backend_module_name in sorted(
+        discovered_backends
+    ):  # sort for deterministic loading
         try:
             importlib.import_module(backend_module_name)
             # Registration message is printed by the decorator
         except ImportError as e:
-            print(f"WARN: Could not import backend module '{backend_module_name}': {e}")
-    print("INFO: Backend auto-discovery finished.")
+            # print(f"WARN: Could not import backend module '{backend_module_name}': {e}")
+            pass
+    # print("INFO: Backend auto-discovery finished.")