clean up poetry

cognee/infrastructure/llm/config.py

@@ -3,7 +3,10 @@ from typing import Optional, ClassVar
 from functools import lru_cache
 from pydantic_settings import BaseSettings, SettingsConfigDict
 from pydantic import model_validator
-from baml_py import ClientRegistry
+try:
+    from baml_py import ClientRegistry
+except ImportError:
+    ClientRegistry = None
 
 
 class LLMConfig(BaseSettings):
@@ -63,25 +66,27 @@ class LLMConfig(BaseSettings):
     fallback_endpoint: str = ""
     fallback_model: str = ""
 
-    baml_registry: ClassVar[ClientRegistry] = ClientRegistry()
+    baml_registry: ClassVar = None
 
     model_config = SettingsConfigDict(env_file=".env", extra="allow")
 
     def model_post_init(self, __context) -> None:
         """Initialize the BAML registry after the model is created."""
-        self.baml_registry.add_llm_client(
-            name=self.baml_llm_provider,
-            provider=self.baml_llm_provider,
-            options={
-                "model": self.baml_llm_model,
-                "temperature": self.baml_llm_temperature,
-                "api_key": self.baml_llm_api_key,
-                "base_url": self.baml_llm_endpoint,
-                "api_version": self.baml_llm_api_version,
-            },
-        )
-        # Sets the primary client
-        self.baml_registry.set_primary(self.baml_llm_provider)
+        if ClientRegistry is not None:
+            self.baml_registry = ClientRegistry()
+            self.baml_registry.add_llm_client(
+                name=self.baml_llm_provider,
+                provider=self.baml_llm_provider,
+                options={
+                    "model": self.baml_llm_model,
+                    "temperature": self.baml_llm_temperature,
+                    "api_key": self.baml_llm_api_key,
+                    "base_url": self.baml_llm_endpoint,
+                    "api_version": self.baml_llm_api_version,
+                },
+            )
+            # Sets the primary client
+            self.baml_registry.set_primary(self.baml_llm_provider)
 
     @model_validator(mode="after")
     def ensure_env_vars_for_ollama(self) -> "LLMConfig":

cognee/infrastructure/llm/structured_output_framework/baml/baml_src/extraction/extract_summary.py

@@ -37,6 +37,9 @@ async def extract_summary(content: str, response_model: Type[BaseModel]):
     """
     config = get_llm_config()
 
+    if config.baml_registry is None:
+        raise ImportError("BAML is not available. Please install with 'pip install cognee[baml]' to use BAML extraction features.")
+
     # Use BAML's SummarizeContent function
     summary_result = await b.SummarizeContent(
         content, baml_options={"client_registry": config.baml_registry}
@@ -77,6 +80,9 @@ async def extract_code_summary(content: str):
         try:
             config = get_llm_config()
 
+            if config.baml_registry is None:
+                raise ImportError("BAML is not available. Please install with 'pip install cognee[baml]' to use BAML extraction features.")
+
             result = await b.SummarizeCode(
                 content, baml_options={"client_registry": config.baml_registry}
             )

cognee/infrastructure/llm/structured_output_framework/baml/baml_src/extraction/knowledge_graph/extract_content_graph.py

@@ -16,6 +16,9 @@ async def extract_content_graph(
 
     get_logger(level="INFO")
 
+    if config.baml_registry is None:
+        raise ImportError("BAML is not available. Please install with 'pip install cognee[baml]' to use BAML extraction features.")
+
     # if response_model:
     #     # tb = TypeBuilder()
     #     # country = tb.union \

pyproject.toml

@@ -28,9 +28,7 @@ dependencies = [
     "nltk>=3.9.1,<4.0.0",
     "numpy>=1.26.4, <=4.0.0",
     "pandas>=2.2.2,<3.0.0",
-    # Note: New s3fs and boto3 versions don't work well together
-    # Always use comaptible fixed versions of these two dependencies
-    "s3fs[boto3]==2025.3.2",
+
     "sqlalchemy>=2.0.39,<3.0.0",
     "aiosqlite>=0.20.0,<1.0.0",
     "tiktoken>=0.8.0,<1.0.0",
@@ -53,10 +51,10 @@ dependencies = [
     "fastapi>=0.115.7,<1.0.0",
     "python-multipart>=0.0.20,<1.0.0",
     "fastapi-users[sqlalchemy]>=14.0.1,<15.0.0",
-    "dlt[sqlalchemy]>=1.9.0,<2",
+
     "sentry-sdk[fastapi]>=2.9.0,<3",
     "structlog>=25.2.0,<26",
-    "baml-py (>=0.201.0,<0.202.0)",
+
     "pympler>=1.1,<2.0.0",
     "onnxruntime>=1.0.0,<2.0.0",
     "pylance>=0.22.0,<1.0.0",
@@ -116,14 +114,13 @@ evals = [
     "plotly>=6.0.0,<7",
     "gdown>=5.2.0,<6",
 ]
-gui = [
-    "pyside6>=6.8.3,<7",
-    "qasync>=0.27.1,<0.28",
-]
+
 graphiti = ["graphiti-core>=0.7.0,<0.8"]
 # Note: New s3fs and boto3 versions don't work well together
 # Always use comaptible fixed versions of these two dependencies
 aws = ["s3fs[boto3]==2025.3.2"]
+dlt = ["dlt[sqlalchemy]>=1.9.0,<2"]
+baml = ["baml-py (>=0.201.0,<0.202.0)"]
 dev = [
     "pytest>=7.4.0,<8",
     "pytest-cov>=6.1.1,<7.0.0",