Refactored math_utils (#7961)

`math_utils.py` is in the root code folder. This creates the
`langchain.math_utils: Math Utils` group on the API Reference navigation
ToC, on the same level with `Chains` and `Agents` which is not correct.

Refactoring:
- created the `utils/` folder
- moved `math_utils.py` to `utils/math.py`
- moved `utils.py` to `utils/utils.py`
- split `utils.py` into `utils.py, env.py, strings.py`
- added module description

@baskaryan

langchain/document_transformers/embeddings_redundant_filter.py

@@ -5,8 +5,8 @@ import numpy as np
 from pydantic import BaseModel, Field
 
 from langchain.embeddings.base import Embeddings
-from langchain.math_utils import cosine_similarity
 from langchain.schema import BaseDocumentTransformer, Document
+from langchain.utils.math import cosine_similarity
 
 
 class _DocumentWithState(Document):

langchain/evaluation/embedding_distance/base.py

@@ -14,8 +14,8 @@ from langchain.chains.base import Chain
 from langchain.embeddings.base import Embeddings
 from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain.evaluation.schema import PairwiseStringEvaluator, StringEvaluator
-from langchain.math_utils import cosine_similarity
 from langchain.schema import RUN_KEY
+from langchain.utils.math import cosine_similarity
 
 
 class EmbeddingDistance(str, Enum):

langchain/retrievers/document_compressors/embeddings_filter.py

@@ -9,11 +9,11 @@ from langchain.document_transformers.embeddings_redundant_filter import (
     get_stateful_documents,
 )
 from langchain.embeddings.base import Embeddings
-from langchain.math_utils import cosine_similarity
 from langchain.retrievers.document_compressors.base import (
     BaseDocumentCompressor,
 )
 from langchain.schema import Document
+from langchain.utils.math import cosine_similarity
 
 
 class EmbeddingsFilter(BaseDocumentCompressor):

langchain/sql_database.py

@@ -10,7 +10,7 @@ from sqlalchemy.engine import Engine
 from sqlalchemy.exc import ProgrammingError, SQLAlchemyError
 from sqlalchemy.schema import CreateTable
 
-from langchain import utils
+from langchain.utils import get_from_env
 
 
 def _format_index(index: sqlalchemy.engine.interfaces.ReflectedIndex) -> str:
@@ -192,13 +192,11 @@ class SQLDatabase:
 
         default_host = context.browserHostName if context else None
         if host is None:
-            host = utils.get_from_env("host", "DATABRICKS_HOST", default_host)
+            host = get_from_env("host", "DATABRICKS_HOST", default_host)
 
         default_api_token = context.apiToken if context else None
         if api_token is None:
-            api_token = utils.get_from_env(
-                "api_token", "DATABRICKS_TOKEN", default_api_token
-            )
+            api_token = get_from_env("api_token", "DATABRICKS_TOKEN", default_api_token)
 
         if warehouse_id is None and cluster_id is None:
             if context:

langchain/utils/__init__.py

@@ -0,0 +1,33 @@
+"""
+Utility functions for langchain.
+
+These functions do not depend on any other langchain modules.
+"""
+
+from langchain.utils.env import get_from_dict_or_env, get_from_env
+from langchain.utils.math import cosine_similarity, cosine_similarity_top_k
+from langchain.utils.strings import comma_list, stringify_dict, stringify_value
+from langchain.utils.utils import (
+    check_package_version,
+    get_pydantic_field_names,
+    guard_import,
+    mock_now,
+    raise_for_status_with_text,
+    xor_args,
+)
+
+__all__ = [
+    "check_package_version",
+    "comma_list",
+    "cosine_similarity",
+    "cosine_similarity_top_k",
+    "get_from_dict_or_env",
+    "get_from_env",
+    "get_pydantic_field_names",
+    "guard_import",
+    "mock_now",
+    "raise_for_status_with_text",
+    "stringify_dict",
+    "stringify_value",
+    "xor_args",
+]

langchain/utils/env.py

@@ -0,0 +1,26 @@
+import os
+from typing import Any, Dict, Optional
+
+
+def get_from_dict_or_env(
+    data: Dict[str, Any], key: str, env_key: str, default: Optional[str] = None
+) -> str:
+    """Get a value from a dictionary or an environment variable."""
+    if key in data and data[key]:
+        return data[key]
+    else:
+        return get_from_env(key, env_key, default=default)
+
+
+def get_from_env(key: str, env_key: str, default: Optional[str] = None) -> str:
+    """Get a value from a dictionary or an environment variable."""
+    if env_key in os.environ and os.environ[env_key]:
+        return os.environ[env_key]
+    elif default is not None:
+        return default
+    else:
+        raise ValueError(
+            f"Did not find {key}, please add an environment variable"
+            f" `{env_key}` which contains it, or pass"
+            f"  `{key}` as a named parameter."
+        )

langchain/utils/strings.py

@@ -0,0 +1,39 @@
+from typing import Any, List
+
+
+def stringify_value(val: Any) -> str:
+    """Stringify a value.
+
+    Args:
+        val: The value to stringify.
+
+    Returns:
+        str: The stringified value.
+    """
+    if isinstance(val, str):
+        return val
+    elif isinstance(val, dict):
+        return "\n" + stringify_dict(val)
+    elif isinstance(val, list):
+        return "\n".join(stringify_value(v) for v in val)
+    else:
+        return str(val)
+
+
+def stringify_dict(data: dict) -> str:
+    """Stringify a dictionary.
+
+    Args:
+        data: The dictionary to stringify.
+
+    Returns:
+        str: The stringified dictionary.
+    """
+    text = ""
+    for key, value in data.items():
+        text += key + ": " + stringify_value(value) + "\n"
+    return text
+
+
+def comma_list(items: List[Any]) -> str:
+    return ", ".join(str(item) for item in items)

langchain/utils/utils.py

@@ -2,38 +2,13 @@
 import contextlib
 import datetime
 import importlib
-import os
 from importlib.metadata import version
-from typing import Any, Callable, Dict, List, Optional, Set, Tuple
+from typing import Any, Callable, Optional, Set, Tuple
 
 from packaging.version import parse
 from requests import HTTPError, Response
 
 
-def get_from_dict_or_env(
-    data: Dict[str, Any], key: str, env_key: str, default: Optional[str] = None
-) -> str:
-    """Get a value from a dictionary or an environment variable."""
-    if key in data and data[key]:
-        return data[key]
-    else:
-        return get_from_env(key, env_key, default=default)
-
-
-def get_from_env(key: str, env_key: str, default: Optional[str] = None) -> str:
-    """Get a value from a dictionary or an environment variable."""
-    if env_key in os.environ and os.environ[env_key]:
-        return os.environ[env_key]
-    elif default is not None:
-        return default
-    else:
-        raise ValueError(
-            f"Did not find {key}, please add an environment variable"
-            f" `{env_key}` which contains it, or pass"
-            f"  `{key}` as a named parameter."
-        )
-
-
 def xor_args(*arg_groups: Tuple[str, ...]) -> Callable:
     """Validate specified keyword args are mutually exclusive."""
 
@@ -67,44 +42,6 @@ def raise_for_status_with_text(response: Response) -> None:
         raise ValueError(response.text) from e
 
 
-def stringify_value(val: Any) -> str:
-    """Stringify a value.
-
-    Args:
-        val: The value to stringify.
-
-    Returns:
-        str: The stringified value.
-    """
-    if isinstance(val, str):
-        return val
-    elif isinstance(val, dict):
-        return "\n" + stringify_dict(val)
-    elif isinstance(val, list):
-        return "\n".join(stringify_value(v) for v in val)
-    else:
-        return str(val)
-
-
-def stringify_dict(data: dict) -> str:
-    """Stringify a dictionary.
-
-    Args:
-        data: The dictionary to stringify.
-
-    Returns:
-        str: The stringified dictionary.
-    """
-    text = ""
-    for key, value in data.items():
-        text += key + ": " + stringify_value(value) + "\n"
-    return text
-
-
-def comma_list(items: List[Any]) -> str:
-    return ", ".join(str(item) for item in items)
-
-
 @contextlib.contextmanager
 def mock_now(dt_value):  # type: ignore
     """Context manager for mocking out datetime.now() in unit tests.

langchain/vectorstores/utils.py

@@ -5,7 +5,7 @@ from typing import List
 
 import numpy as np
 
-from langchain.math_utils import cosine_similarity
+from langchain.utils.math import cosine_similarity
 
 
 class DistanceStrategy(str, Enum):

tests/unit_tests/test_document_transformers.py

@@ -2,7 +2,7 @@
 from langchain.document_transformers.embeddings_redundant_filter import (
     _filter_similar_embeddings,
 )
-from langchain.math_utils import cosine_similarity
+from langchain.utils.math import cosine_similarity
 
 
 def test__filter_similar_embeddings() -> None:

tests/unit_tests/test_math_utils.py

@@ -4,7 +4,7 @@ from typing import List
 import numpy as np
 import pytest
 
-from langchain.math_utils import cosine_similarity, cosine_similarity_top_k
+from langchain.utils.math import cosine_similarity, cosine_similarity_top_k
 
 
 @pytest.fixture