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fix readme

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yichuan-w
2025-10-08 21:38:55 +00:00
parent 3ec5e8d035
commit 5be0c144ad
72 changed files with 16608 additions and 4175 deletions
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133
packages/leann-core/src/leann/cli.py
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@@ -8,7 +8,9 @@ from llama_index.core.node_parser import SentenceSplitter
from tqdm import tqdm
from .api import LeannBuilder, LeannChat, LeannSearcher
from .interactive_utils import create_cli_session
from .registry import register_project_directory
from .settings import resolve_ollama_host, resolve_openai_api_key, resolve_openai_base_url
def extract_pdf_text_with_pymupdf(file_path: str) -> str:
@@ -123,6 +125,24 @@ Examples:
choices=["sentence-transformers", "openai", "mlx", "ollama"],
help="Embedding backend mode (default: sentence-transformers)",
)
build_parser.add_argument(
"--embedding-host",
type=str,
default=None,
help="Override Ollama-compatible embedding host",
)
build_parser.add_argument(
"--embedding-api-base",
type=str,
default=None,
help="Base URL for OpenAI-compatible embedding services",
)
build_parser.add_argument(
"--embedding-api-key",
type=str,
default=None,
help="API key for embedding service (defaults to OPENAI_API_KEY)",
)
build_parser.add_argument(
"--force", "-f", action="store_true", help="Force rebuild existing index"
)
@@ -238,6 +258,11 @@ Examples:
# Ask command
ask_parser = subparsers.add_parser("ask", help="Ask questions")
ask_parser.add_argument("index_name", help="Index name")
ask_parser.add_argument(
"query",
nargs="?",
help="Question to ask (omit for prompt or when using --interactive)",
)
ask_parser.add_argument(
"--llm",
type=str,
@@ -248,7 +273,12 @@ Examples:
ask_parser.add_argument(
"--model", type=str, default="qwen3:8b", help="Model name (default: qwen3:8b)"
)
ask_parser.add_argument("--host", type=str, default="http://localhost:11434")
ask_parser.add_argument(
"--host",
type=str,
default=None,
help="Override Ollama-compatible host (defaults to LEANN_OLLAMA_HOST/OLLAMA_HOST)",
)
ask_parser.add_argument(
"--interactive", "-i", action="store_true", help="Interactive chat mode"
)
@@ -277,6 +307,18 @@ Examples:
default=None,
help="Thinking budget for reasoning models (low/medium/high). Supported by GPT-Oss:20b and other reasoning models.",
)
ask_parser.add_argument(
"--api-base",
type=str,
default=None,
help="Base URL for OpenAI-compatible APIs (e.g., http://localhost:10000/v1)",
)
ask_parser.add_argument(
"--api-key",
type=str,
default=None,
help="API key for OpenAI-compatible APIs (defaults to OPENAI_API_KEY)",
)
# List command
subparsers.add_parser("list", help="List all indexes")
@@ -1325,10 +1367,20 @@ Examples:
print(f"Building index '{index_name}' with {args.backend} backend...")
embedding_options: dict[str, Any] = {}
if args.embedding_mode == "ollama":
embedding_options["host"] = resolve_ollama_host(args.embedding_host)
elif args.embedding_mode == "openai":
embedding_options["base_url"] = resolve_openai_base_url(args.embedding_api_base)
resolved_embedding_key = resolve_openai_api_key(args.embedding_api_key)
if resolved_embedding_key:
embedding_options["api_key"] = resolved_embedding_key
builder = LeannBuilder(
backend_name=args.backend,
embedding_model=args.embedding_model,
embedding_mode=args.embedding_mode,
embedding_options=embedding_options or None,
graph_degree=args.graph_degree,
complexity=args.complexity,
is_compact=args.compact,
@@ -1476,58 +1528,49 @@ Examples:
llm_config = {"type": args.llm, "model": args.model}
if args.llm == "ollama":
llm_config["host"] = args.host
llm_config["host"] = resolve_ollama_host(args.host)
elif args.llm == "openai":
llm_config["base_url"] = resolve_openai_base_url(args.api_base)
resolved_api_key = resolve_openai_api_key(args.api_key)
if resolved_api_key:
llm_config["api_key"] = resolved_api_key
chat = LeannChat(index_path=index_path, llm_config=llm_config)
llm_kwargs: dict[str, Any] = {}
if args.thinking_budget:
llm_kwargs["thinking_budget"] = args.thinking_budget
def _ask_once(prompt: str) -> None:
response = chat.ask(
prompt,
top_k=args.top_k,
complexity=args.complexity,
beam_width=args.beam_width,
prune_ratio=args.prune_ratio,
recompute_embeddings=args.recompute_embeddings,
pruning_strategy=args.pruning_strategy,
llm_kwargs=llm_kwargs,
)
print(f"LEANN: {response}")
initial_query = (args.query or "").strip()
if args.interactive:
print("LEANN Assistant ready! Type 'quit' to exit")
print("=" * 40)
# Create interactive session
session = create_cli_session(index_name)
while True:
user_input = input("\nYou: ").strip()
if user_input.lower() in ["quit", "exit", "q"]:
print("Goodbye!")
break
if initial_query:
_ask_once(initial_query)
if not user_input:
continue
# Prepare LLM kwargs with thinking budget if specified
llm_kwargs = {}
if args.thinking_budget:
llm_kwargs["thinking_budget"] = args.thinking_budget
response = chat.ask(
user_input,
top_k=args.top_k,
complexity=args.complexity,
beam_width=args.beam_width,
prune_ratio=args.prune_ratio,
recompute_embeddings=args.recompute_embeddings,
pruning_strategy=args.pruning_strategy,
llm_kwargs=llm_kwargs,
)
print(f"LEANN: {response}")
session.run_interactive_loop(_ask_once)
else:
query = input("Enter your question: ").strip()
if query:
# Prepare LLM kwargs with thinking budget if specified
llm_kwargs = {}
if args.thinking_budget:
llm_kwargs["thinking_budget"] = args.thinking_budget
query = initial_query or input("Enter your question: ").strip()
if not query:
print("No question provided. Exiting.")
return
response = chat.ask(
query,
top_k=args.top_k,
complexity=args.complexity,
beam_width=args.beam_width,
prune_ratio=args.prune_ratio,
recompute_embeddings=args.recompute_embeddings,
pruning_strategy=args.pruning_strategy,
llm_kwargs=llm_kwargs,
)
print(f"LEANN: {response}")
_ask_once(query)
async def run(self, args=None):
parser = self.create_parser()