test with a simple file

cognee/config.py

@@ -79,6 +79,11 @@ class Config:
     graph_topology:str = DefaultGraphModel
     cognitive_layers_limit: int = 2
 
+    from cognee.shared.data_models import MonitoringTool
+
+    # Monitoring tool
+    monitoring_tool: str = os.getenv("MONITORING_TOOL", MonitoringTool.LANGFUSE)
+
     if (
         os.getenv("ENV") == "prod"
         or os.getenv("ENV") == "dev"

cognee/infrastructure/InfrastructureConfig.py

@@ -33,6 +33,7 @@ class InfrastructureConfig():
     chunk_strategy = config.chunk_strategy
     chunk_engine = None
     graph_topology = config.graph_topology
+    monitoring_tool = config.monitoring_tool
 
     def get_config(self, config_entity: str = None) -> dict:
         if (config_entity is None or config_entity == "database_engine") and self.database_engine is None:

cognee/infrastructure/llm/openai/adapter.py

@@ -2,11 +2,21 @@ import asyncio
 from typing import List, Type
 import openai
 import instructor
-from openai import AsyncOpenAI, OpenAI
 from pydantic import BaseModel
 from tenacity import retry, stop_after_attempt
+
+from cognee.config import Config
 from cognee.infrastructure.llm.llm_interface import LLMInterface
 from cognee.infrastructure.llm.prompts import read_query_prompt
+from cognee.shared.data_models import MonitoringTool
+
+config = Config()
+config.load()
+
+if config.monitoring_tool == MonitoringTool.LANGFUSE:
+    from langfuse.openai import AsyncOpenAI, OpenAI
+else:
+    from openai import AsyncOpenAI, OpenAI
 
 class OpenAIAdapter(LLMInterface):
     """Adapter for OpenAI's GPT-3, GPT=4 API"""

cognee/shared/data_models.py

@@ -252,3 +252,9 @@ class ResponseSummaryModel(BaseModel):
     document_id: str
     response_summary: str
 
+
+class MonitoringTool(str, Enum):
+    """ Monitoring tools """
+    LANGFUSE = "langfuse"
+    LLMLITE = "llmlite"
+

docker-compose.yml

@@ -55,6 +55,18 @@ services:
        - cognee_backend
      ports:
        - "5432:5432"
+  litellm:
+    build:
+      context: .
+      args:
+        target: runtime
+    image: ghcr.io/berriai/litellm:main-latest
+    ports:
+      - "4000:4000" # Map the container port to the host, change the host port if necessary
+    volumes:
+      - ./litellm-config.yaml:/app/config.yaml # Mount the local configuration file
+    # You can change the port or number of workers as per your requirements or pass any new supported CLI augument. Make sure the port passed here matches with the container port defined above in `ports` value
+    command: [ "--config", "/app/config.yaml", "--port", "4000", "--num_workers", "8" ]
 
 networks:
   cognee_backend:

pyproject.toml

@@ -66,6 +66,7 @@ deepeval = "^0.21.36"
 litellm = "^1.37.3"
 groq = "^0.5.0"
 tantivy = "^0.21.0"
+langfuse = "^2.32.0"
 
 
 [tool.poetry.extras]