yangdx
commited on
Commit
·
45e3112
1
Parent(s):
5a7b64e
Adjust concurrency limits more LLM friendly settings for new comers
Browse files- Lowered max async LLM processes to 4
- Enabled LLM cache for entity extraction
- Reduced max parallel insert to 2
- README.md +1 -1
- env.example +2 -1
- lightrag/api/README.md +1 -1
- lightrag/api/utils_api.py +1 -1
- lightrag/lightrag.py +2 -2
README.md
CHANGED
@@ -1061,7 +1061,7 @@ Valid modes are:
|
|
1061 |
| **llm\_model\_func** | `callable` | Function for LLM generation | `gpt_4o_mini_complete` |
|
1062 |
| **llm\_model\_name** | `str` | LLM model name for generation | `meta-llama/Llama-3.2-1B-Instruct` |
|
1063 |
| **llm\_model\_max\_token\_size** | `int` | Maximum token size for LLM generation (affects entity relation summaries) | `32768`(default value changed by env var MAX_TOKENS) |
|
1064 |
-
| **llm\_model\_max\_async** | `int` | Maximum number of concurrent asynchronous LLM processes | `
|
1065 |
| **llm\_model\_kwargs** | `dict` | Additional parameters for LLM generation | |
|
1066 |
| **vector\_db\_storage\_cls\_kwargs** | `dict` | Additional parameters for vector database, like setting the threshold for nodes and relations retrieval. | cosine_better_than_threshold: 0.2(default value changed by env var COSINE_THRESHOLD) |
|
1067 |
| **enable\_llm\_cache** | `bool` | If `TRUE`, stores LLM results in cache; repeated prompts return cached responses | `TRUE` |
|
|
|
1061 |
| **llm\_model\_func** | `callable` | Function for LLM generation | `gpt_4o_mini_complete` |
|
1062 |
| **llm\_model\_name** | `str` | LLM model name for generation | `meta-llama/Llama-3.2-1B-Instruct` |
|
1063 |
| **llm\_model\_max\_token\_size** | `int` | Maximum token size for LLM generation (affects entity relation summaries) | `32768`(default value changed by env var MAX_TOKENS) |
|
1064 |
+
| **llm\_model\_max\_async** | `int` | Maximum number of concurrent asynchronous LLM processes | `4`(default value changed by env var MAX_ASYNC) |
|
1065 |
| **llm\_model\_kwargs** | `dict` | Additional parameters for LLM generation | |
|
1066 |
| **vector\_db\_storage\_cls\_kwargs** | `dict` | Additional parameters for vector database, like setting the threshold for nodes and relations retrieval. | cosine_better_than_threshold: 0.2(default value changed by env var COSINE_THRESHOLD) |
|
1067 |
| **enable\_llm\_cache** | `bool` | If `TRUE`, stores LLM results in cache; repeated prompts return cached responses | `TRUE` |
|
env.example
CHANGED
@@ -50,7 +50,8 @@
|
|
50 |
# MAX_TOKEN_SUMMARY=500 # Max tokens for entity or relations summary
|
51 |
# SUMMARY_LANGUAGE=English
|
52 |
# MAX_EMBED_TOKENS=8192
|
53 |
-
# ENABLE_LLM_CACHE_FOR_EXTRACT=
|
|
|
54 |
|
55 |
### LLM Configuration (Use valid host. For local services installed with docker, you can use host.docker.internal)
|
56 |
LLM_BINDING=ollama
|
|
|
50 |
# MAX_TOKEN_SUMMARY=500 # Max tokens for entity or relations summary
|
51 |
# SUMMARY_LANGUAGE=English
|
52 |
# MAX_EMBED_TOKENS=8192
|
53 |
+
# ENABLE_LLM_CACHE_FOR_EXTRACT=true # Enable LLM cache for entity extraction
|
54 |
+
# MAX_PARALLEL_INSERT=2 # Maximum number of parallel processing documents in pipeline
|
55 |
|
56 |
### LLM Configuration (Use valid host. For local services installed with docker, you can use host.docker.internal)
|
57 |
LLM_BINDING=ollama
|
lightrag/api/README.md
CHANGED
@@ -224,7 +224,7 @@ LightRAG supports binding to various LLM/Embedding backends:
|
|
224 |
Use environment variables `LLM_BINDING` or CLI argument `--llm-binding` to select LLM backend type. Use environment variables `EMBEDDING_BINDING` or CLI argument `--embedding-binding` to select LLM backend type.
|
225 |
|
226 |
### Entity Extraction Configuration
|
227 |
-
* ENABLE_LLM_CACHE_FOR_EXTRACT: Enable LLM cache for entity extraction (default:
|
228 |
|
229 |
It's very common to set `ENABLE_LLM_CACHE_FOR_EXTRACT` to true for test environment to reduce the cost of LLM calls.
|
230 |
|
|
|
224 |
Use environment variables `LLM_BINDING` or CLI argument `--llm-binding` to select LLM backend type. Use environment variables `EMBEDDING_BINDING` or CLI argument `--embedding-binding` to select LLM backend type.
|
225 |
|
226 |
### Entity Extraction Configuration
|
227 |
+
* ENABLE_LLM_CACHE_FOR_EXTRACT: Enable LLM cache for entity extraction (default: true)
|
228 |
|
229 |
It's very common to set `ENABLE_LLM_CACHE_FOR_EXTRACT` to true for test environment to reduce the cost of LLM calls.
|
230 |
|
lightrag/api/utils_api.py
CHANGED
@@ -364,7 +364,7 @@ def parse_args(is_uvicorn_mode: bool = False) -> argparse.Namespace:
|
|
364 |
|
365 |
# Inject LLM cache configuration
|
366 |
args.enable_llm_cache_for_extract = get_env_value(
|
367 |
-
"ENABLE_LLM_CACHE_FOR_EXTRACT",
|
368 |
)
|
369 |
|
370 |
# Select Document loading tool (DOCLING, DEFAULT)
|
|
|
364 |
|
365 |
# Inject LLM cache configuration
|
366 |
args.enable_llm_cache_for_extract = get_env_value(
|
367 |
+
"ENABLE_LLM_CACHE_FOR_EXTRACT", True, bool
|
368 |
)
|
369 |
|
370 |
# Select Document loading tool (DOCLING, DEFAULT)
|
lightrag/lightrag.py
CHANGED
@@ -214,7 +214,7 @@ class LightRAG:
|
|
214 |
llm_model_max_token_size: int = field(default=int(os.getenv("MAX_TOKENS", 32768)))
|
215 |
"""Maximum number of tokens allowed per LLM response."""
|
216 |
|
217 |
-
llm_model_max_async: int = field(default=int(os.getenv("MAX_ASYNC",
|
218 |
"""Maximum number of concurrent LLM calls."""
|
219 |
|
220 |
llm_model_kwargs: dict[str, Any] = field(default_factory=dict)
|
@@ -238,7 +238,7 @@ class LightRAG:
|
|
238 |
# Extensions
|
239 |
# ---
|
240 |
|
241 |
-
max_parallel_insert: int = field(default=int(os.getenv("MAX_PARALLEL_INSERT",
|
242 |
"""Maximum number of parallel insert operations."""
|
243 |
|
244 |
addon_params: dict[str, Any] = field(
|
|
|
214 |
llm_model_max_token_size: int = field(default=int(os.getenv("MAX_TOKENS", 32768)))
|
215 |
"""Maximum number of tokens allowed per LLM response."""
|
216 |
|
217 |
+
llm_model_max_async: int = field(default=int(os.getenv("MAX_ASYNC", 4)))
|
218 |
"""Maximum number of concurrent LLM calls."""
|
219 |
|
220 |
llm_model_kwargs: dict[str, Any] = field(default_factory=dict)
|
|
|
238 |
# Extensions
|
239 |
# ---
|
240 |
|
241 |
+
max_parallel_insert: int = field(default=int(os.getenv("MAX_PARALLEL_INSERT", 2)))
|
242 |
"""Maximum number of parallel insert operations."""
|
243 |
|
244 |
addon_params: dict[str, Any] = field(
|