feat: refactor ollama server configuration management

- Add ollama_server_infos attribute to LightRAG class with default initialization
- Move default values to constants.py for centralized configuration
- Refactor OllamaServerInfos class with property accessors and CLI support
- Update OllamaAPI to get configuration through rag object instead of direct import
- Add command line arguments for simulated model name and tag
- Fix type imports to avoid circular dependencies

env.example

@@ -7,7 +7,6 @@ HOST=0.0.0.0
 PORT=9621
 WEBUI_TITLE='My Graph KB'
 WEBUI_DESCRIPTION="Simple and Fast Graph Based RAG System"
-OLLAMA_EMULATING_MODEL_TAG=latest
 # WORKERS=2
 # CORS_ORIGINS=http://localhost:3000,http://localhost:8080
 
@@ -21,6 +20,10 @@ OLLAMA_EMULATING_MODEL_TAG=latest
 # INPUT_DIR=<absolute_path_for_doc_input_dir>
 # WORKING_DIR=<absolute_path_for_working_dir>
 
+### Ollama Emulating Model and Tag
+# OLLAMA_EMULATING_MODEL_NAME=lightrag
+OLLAMA_EMULATING_MODEL_TAG=latest
+
 ### Max nodes return from grap retrieval in webui
 # MAX_GRAPH_NODES=1000
 

lightrag/api/config.py

@@ -26,6 +26,11 @@ from lightrag.constants import (
     DEFAULT_SUMMARY_LANGUAGE,
     DEFAULT_EMBEDDING_FUNC_MAX_ASYNC,
     DEFAULT_EMBEDDING_BATCH_NUM,
+    DEFAULT_OLLAMA_MODEL_NAME,
+    DEFAULT_OLLAMA_MODEL_TAG,
+    DEFAULT_OLLAMA_MODEL_SIZE,
+    DEFAULT_OLLAMA_CREATED_AT,
+    DEFAULT_OLLAMA_DIGEST,
 )
 
 # use the .env that is inside the current folder
@@ -35,13 +40,36 @@ load_dotenv(dotenv_path=".env", override=False)
 
 
 class OllamaServerInfos:
-    # Constants for emulated Ollama model information
-    LIGHTRAG_NAME = "lightrag"
-    LIGHTRAG_TAG = os.getenv("OLLAMA_EMULATING_MODEL_TAG", "latest")
-    LIGHTRAG_MODEL = f"{LIGHTRAG_NAME}:{LIGHTRAG_TAG}"
-    LIGHTRAG_SIZE = 7365960935  # it's a dummy value
-    LIGHTRAG_CREATED_AT = "2024-01-15T00:00:00Z"
-    LIGHTRAG_DIGEST = "sha256:lightrag"
+    def __init__(self, name=None, tag=None):
+        self._lightrag_name = name or os.getenv(
+            "OLLAMA_EMULATING_MODEL_NAME", DEFAULT_OLLAMA_MODEL_NAME
+        )
+        self._lightrag_tag = tag or os.getenv(
+            "OLLAMA_EMULATING_MODEL_TAG", DEFAULT_OLLAMA_MODEL_TAG
+        )
+        self.LIGHTRAG_SIZE = DEFAULT_OLLAMA_MODEL_SIZE
+        self.LIGHTRAG_CREATED_AT = DEFAULT_OLLAMA_CREATED_AT
+        self.LIGHTRAG_DIGEST = DEFAULT_OLLAMA_DIGEST
+
+    @property
+    def LIGHTRAG_NAME(self):
+        return self._lightrag_name
+
+    @LIGHTRAG_NAME.setter
+    def LIGHTRAG_NAME(self, value):
+        self._lightrag_name = value
+
+    @property
+    def LIGHTRAG_TAG(self):
+        return self._lightrag_tag
+
+    @LIGHTRAG_TAG.setter
+    def LIGHTRAG_TAG(self, value):
+        self._lightrag_tag = value
+
+    @property
+    def LIGHTRAG_MODEL(self):
+        return f"{self._lightrag_name}:{self._lightrag_tag}"
 
 
 ollama_server_infos = OllamaServerInfos()
@@ -166,14 +194,19 @@ def parse_args() -> argparse.Namespace:
         help="Path to SSL private key file (required if --ssl is enabled)",
     )
 
-    # Ollama model name
+    # Ollama model configuration
     parser.add_argument(
         "--simulated-model-name",
         type=str,
-        default=get_env_value(
-            "SIMULATED_MODEL_NAME", ollama_server_infos.LIGHTRAG_MODEL
-        ),
-        help="Number of conversation history turns to include (default: from env or 3)",
+        default=get_env_value("OLLAMA_EMULATING_MODEL_NAME", DEFAULT_OLLAMA_MODEL_NAME),
+        help="Name for the simulated Ollama model (default: from env or lightrag)",
+    )
+
+    parser.add_argument(
+        "--simulated-model-tag",
+        type=str,
+        default=get_env_value("OLLAMA_EMULATING_MODEL_TAG", DEFAULT_OLLAMA_MODEL_TAG),
+        help="Tag for the simulated Ollama model (default: from env or latest)",
     )
 
     # Namespace
@@ -333,7 +366,8 @@ def parse_args() -> argparse.Namespace:
         "EMBEDDING_BATCH_NUM", DEFAULT_EMBEDDING_BATCH_NUM, int
     )
 
-    ollama_server_infos.LIGHTRAG_MODEL = args.simulated_model_name
+    ollama_server_infos.LIGHTRAG_NAME = args.simulated_model_name
+    ollama_server_infos.LIGHTRAG_TAG = args.simulated_model_tag
 
     return args
 

lightrag/api/lightrag_server.py

@@ -335,6 +335,13 @@ def create_app(args):
             "Rerank model not configured. Set RERANK_BINDING_API_KEY and RERANK_BINDING_HOST to enable reranking."
         )
 
+    # Create ollama_server_infos from command line arguments
+    from lightrag.api.config import OllamaServerInfos
+
+    ollama_server_infos = OllamaServerInfos(
+        name=args.simulated_model_name, tag=args.simulated_model_tag
+    )
+
     # Initialize RAG
     if args.llm_binding in ["lollms", "ollama", "openai"]:
         rag = LightRAG(
@@ -373,6 +380,7 @@ def create_app(args):
             max_parallel_insert=args.max_parallel_insert,
             max_graph_nodes=args.max_graph_nodes,
             addon_params={"language": args.summary_language},
+            ollama_server_infos=ollama_server_infos,
         )
     else:  # azure_openai
         rag = LightRAG(
@@ -402,6 +410,7 @@ def create_app(args):
             max_parallel_insert=args.max_parallel_insert,
             max_graph_nodes=args.max_graph_nodes,
             addon_params={"language": args.summary_language},
+            ollama_server_infos=ollama_server_infos,
         )
 
     # Add routes

lightrag/api/routers/ollama_api.py

@@ -11,7 +11,7 @@ import asyncio
 from ascii_colors import trace_exception
 from lightrag import LightRAG, QueryParam
 from lightrag.utils import TiktokenTokenizer
-from lightrag.api.utils_api import ollama_server_infos, get_combined_auth_dependency
+from lightrag.api.utils_api import get_combined_auth_dependency
 from fastapi import Depends
 
 
@@ -221,7 +221,7 @@ def parse_query_mode(query: str) -> tuple[str, SearchMode, bool, Optional[str]]:
 class OllamaAPI:
     def __init__(self, rag: LightRAG, top_k: int = 60, api_key: Optional[str] = None):
         self.rag = rag
-        self.ollama_server_infos = ollama_server_infos
+        self.ollama_server_infos = rag.ollama_server_infos
         self.top_k = top_k
         self.api_key = api_key
         self.router = APIRouter(tags=["ollama"])

lightrag/constants.py

@@ -47,3 +47,10 @@ DEFAULT_EMBEDDING_BATCH_NUM = 10  # Default batch size for embedding computation
 DEFAULT_LOG_MAX_BYTES = 10485760  # Default 10MB
 DEFAULT_LOG_BACKUP_COUNT = 5  # Default 5 backups
 DEFAULT_LOG_FILENAME = "lightrag.log"  # Default log filename
+
+# Ollama server configuration defaults
+DEFAULT_OLLAMA_MODEL_NAME = "lightrag"
+DEFAULT_OLLAMA_MODEL_TAG = "latest"
+DEFAULT_OLLAMA_MODEL_SIZE = 7365960935
+DEFAULT_OLLAMA_CREATED_AT = "2024-01-15T00:00:00Z"
+DEFAULT_OLLAMA_DIGEST = "sha256:lightrag"

lightrag/lightrag.py

@@ -41,6 +41,12 @@ from lightrag.kg import (
     verify_storage_implementation,
 )
 
+# Import for type annotation
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from lightrag.api.config import OllamaServerInfos
+
 from lightrag.kg.shared_storage import (
     get_namespace_data,
     get_pipeline_status_lock,
@@ -342,6 +348,9 @@ class LightRAG:
         default=float(os.getenv("COSINE_THRESHOLD", 0.2))
     )
 
+    ollama_server_infos: Optional["OllamaServerInfos"] = field(default=None)
+    """Configuration for Ollama server information."""
+
     _storages_status: StoragesStatus = field(default=StoragesStatus.NOT_CREATED)
 
     def __post_init__(self):
@@ -403,6 +412,12 @@ class LightRAG:
             else:
                 self.tokenizer = TiktokenTokenizer()
 
+        # Initialize ollama_server_infos if not provided
+        if self.ollama_server_infos is None:
+            from lightrag.api.config import OllamaServerInfos
+
+            self.ollama_server_infos = OllamaServerInfos()
+
         # Fix global_config now
         global_config = asdict(self)