Add verbose debug option to control detailed debug output level

• Added VERBOSE env var & CLI flag
• Implemented verbose_debug() function
• Added verbose option to splash screen
• Reduced default debug output length
• Modified LLM debug logging behavior

.env.example

@@ -18,6 +18,7 @@
 
 ### Logging level
 LOG_LEVEL=INFO
+VERBOSE=False
 
 ### Optional Timeout
 TIMEOUT=300

lightrag/api/lightrag_server.py

@@ -130,8 +130,8 @@ def get_env_value(env_key: str, default: Any, value_type: type = str) -> Any:
     if value is None:
         return default
 
-    if isinstance(value_type, bool):
+    if value_type is bool:
-        return value.lower() in ("true", "1", "yes")
+        return value.lower() in ("true", "1", "yes", "t", "on")
     try:
         return value_type(value)
     except ValueError:
@@ -233,6 +233,8 @@ def display_splash_screen(args: argparse.Namespace) -> None:
     ASCIIColors.yellow(f"{ollama_server_infos.LIGHTRAG_MODEL}")
     ASCIIColors.white("    ├─ Log Level: ", end="")
     ASCIIColors.yellow(f"{args.log_level}")
+    ASCIIColors.white("    ├─ Verbose Debug: ", end="")
+    ASCIIColors.yellow(f"{args.verbose}")
     ASCIIColors.white("    └─ Timeout: ", end="")
     ASCIIColors.yellow(f"{args.timeout if args.timeout else 'None (infinite)'}")
 
@@ -564,6 +566,13 @@ def parse_args() -> argparse.Namespace:
         help="Prefix of the namespace",
     )
 
+    parser.add_argument(
+        "--verbose",
+        type=bool,
+        default=get_env_value("VERBOSE", False, bool),
+        help="Verbose debug output(default: from env or false)",
+    )
+
     args = parser.parse_args()
 
     # conver relative path to absolute path
@@ -685,6 +694,11 @@ global_top_k = 60  # default value
 
 
 def create_app(args):
+    # Initialize verbose debug setting
+    from lightrag.utils import set_verbose_debug
+
+    set_verbose_debug(args.verbose)
+
     global global_top_k
     global_top_k = args.top_k  # save top_k from args
 

lightrag/llm/openai.py

@@ -40,7 +40,7 @@ __version__ = "1.0.0"
 __author__ = "lightrag Team"
 __status__ = "Production"
 
-
+from ..utils import verbose_debug
 import sys
 import os
 
@@ -129,8 +129,8 @@ async def openai_complete_if_cache(
     logger.debug("===== Query Input to LLM =====")
     logger.debug(f"Model: {model}   Base URL: {base_url}")
     logger.debug(f"Additional kwargs: {kwargs}")
-    logger.debug(f"Query: {prompt}")
+    verbose_debug(f"Query: {prompt}")
-    logger.debug(f"System prompt: {system_prompt}")
+    verbose_debug(f"System prompt: {system_prompt}")
     # logger.debug(f"Messages: {messages}")
 
     try:

lightrag/llm/zhipu.py

@@ -43,6 +43,7 @@ __status__ = "Production"
 import sys
 import re
 import json
+from ..utils import verbose_debug
 
 if sys.version_info < (3, 9):
     pass
@@ -119,7 +120,7 @@ async def zhipu_complete_if_cache(
     # Add debug logging
     logger.debug("===== Query Input to LLM =====")
     logger.debug(f"Query: {prompt}")
-    logger.debug(f"System prompt: {system_prompt}")
+    verbose_debug(f"System prompt: {system_prompt}")
 
     # Remove unsupported kwargs
     kwargs = {

lightrag/operate.py

@@ -24,6 +24,7 @@ from .utils import (
     CacheData,
     statistic_data,
     get_conversation_turns,
+    verbose_debug,
 )
 from .base import (
     BaseGraphStorage,
@@ -688,7 +689,7 @@ async def kg_query(
         return sys_prompt
 
     len_of_prompts = len(encode_string_by_tiktoken(query + sys_prompt))
-    logger.debug(f"[kg_query]Prompt Tokens: {len_of_prompts}")
+    verbose_debug(f"[kg_query]Prompt Tokens: {len_of_prompts}")
 
     response = await use_model_func(
         query,
@@ -977,7 +978,7 @@ async def mix_kg_vector_query(
         return sys_prompt
 
     len_of_prompts = len(encode_string_by_tiktoken(query + sys_prompt))
-    logger.debug(f"[mix_kg_vector_query]Prompt Tokens: {len_of_prompts}")
+    verbose_debug(f"[mix_kg_vector_query]Prompt Tokens: {len_of_prompts}")
 
     # 6. Generate response
     response = await use_model_func(
@@ -1807,7 +1808,7 @@ async def kg_query_with_keywords(
         return sys_prompt
 
     len_of_prompts = len(encode_string_by_tiktoken(query + sys_prompt))
-    logger.debug(f"[kg_query_with_keywords]Prompt Tokens: {len_of_prompts}")
+    verbose_debug(f"[kg_query_with_keywords]Prompt Tokens: {len_of_prompts}")
 
     response = await use_model_func(
         query,

lightrag/utils.py

@@ -20,6 +20,23 @@ import tiktoken
 
 from lightrag.prompt import PROMPTS
 
+VERBOSE_DEBUG = False
+
+
+def verbose_debug(msg: str, *args, **kwargs):
+    """Function for outputting detailed debug information.
+    When VERBOSE_DEBUG=True, outputs the complete message.
+    When VERBOSE_DEBUG=False, outputs only the first 30 characters.
+    """
+    if VERBOSE_DEBUG:
+        logger.debug(msg, *args, **kwargs)
+
+
+def set_verbose_debug(enabled: bool):
+    """Enable or disable verbose debug output"""
+    global VERBOSE_DEBUG
+    VERBOSE_DEBUG = enabled
+
 
 class UnlimitedSemaphore:
     """A context manager that allows unlimited access."""