core[performance]: use custom __getattr__ in __init__.py files for lazy imports (#30769)

Most easily reviewed with the "hide whitespace" option toggled.

Seeing 10-50% speed ups in import time for common structures 🚀 

The general purpose of this PR is to lazily import structures within
`langchain_core.XXX_module.__init__.py` so that we're not eagerly
importing expensive dependencies (`pydantic`, `requests`, etc).

Analysis of flamegraphs generated with `importtime` motivated these
changes. For example, the one below demonstrates that importing
`HumanMessage` accidentally triggered imports for `importlib.metadata`,
`requests`, etc.

There's still much more to do on this front, and we can start digging
into our own internal code for optimizations now that we're less
concerned about external imports.

<img width="1210" alt="Screenshot 2025-04-11 at 1 10 54 PM"
src="https://github.com/user-attachments/assets/112a3fe7-24a9-4294-92c1-d5ae64df839e"
/>

I've tracked the improvements with some local benchmarks:

## `pytest-benchmark` results

| Name | Before (s) | After (s) | Delta (s) | % Change |

|-----------------------------|------------|-----------|-----------|----------|
| Document | 2.8683 | 1.2775 | -1.5908 | -55.46% |
| HumanMessage | 2.2358 | 1.1673 | -1.0685 | -47.79% |
| ChatPromptTemplate | 5.5235 | 2.9709 | -2.5526 | -46.22% |
| Runnable | 2.9423 | 1.7793 | -1.163 | -39.53% |
| InMemoryVectorStore | 3.1180 | 1.8417 | -1.2763 | -40.93% |
| RunnableLambda | 2.7385 | 1.8745 | -0.864 | -31.55% |
| tool | 5.1231 | 4.0771 | -1.046 | -20.42% |
| CallbackManager | 4.2263 | 3.4099 | -0.8164 | -19.32% |
| LangChainTracer | 3.8394 | 3.3101 | -0.5293 | -13.79% |
| BaseChatModel | 4.3317 | 3.8806 | -0.4511 | -10.41% |
| PydanticOutputParser | 3.2036 | 3.2995 | 0.0959 | 2.99% |
| InMemoryRateLimiter | 0.5311 | 0.5995 | 0.0684 | 12.88% |

Note the lack of change for `InMemoryRateLimiter` and
`PydanticOutputParser` is just random noise, I'm getting comparable
numbers locally.

## Local CodSpeed results

We're still working on configuring CodSpeed on CI. The local usage
produced similar results.

libs/core/langchain_core/prompts/__init__.py

@@ -25,35 +25,41 @@ from multiple components and prompt values. Prompt classes and functions make co
 
 """  # noqa: E501
 
-from langchain_core.prompts.base import (
-    BasePromptTemplate,
-    aformat_document,
-    format_document,
-)
-from langchain_core.prompts.chat import (
-    AIMessagePromptTemplate,
-    BaseChatPromptTemplate,
-    ChatMessagePromptTemplate,
-    ChatPromptTemplate,
-    HumanMessagePromptTemplate,
-    MessagesPlaceholder,
-    SystemMessagePromptTemplate,
-)
-from langchain_core.prompts.few_shot import (
-    FewShotChatMessagePromptTemplate,
-    FewShotPromptTemplate,
-)
-from langchain_core.prompts.few_shot_with_templates import FewShotPromptWithTemplates
-from langchain_core.prompts.loading import load_prompt
-from langchain_core.prompts.pipeline import PipelinePromptTemplate
-from langchain_core.prompts.prompt import PromptTemplate
-from langchain_core.prompts.string import (
-    StringPromptTemplate,
-    check_valid_template,
-    get_template_variables,
-    jinja2_formatter,
-    validate_jinja2,
-)
+from importlib import import_module
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from langchain_core.prompts.base import (
+        BasePromptTemplate,
+        aformat_document,
+        format_document,
+    )
+    from langchain_core.prompts.chat import (
+        AIMessagePromptTemplate,
+        BaseChatPromptTemplate,
+        ChatMessagePromptTemplate,
+        ChatPromptTemplate,
+        HumanMessagePromptTemplate,
+        MessagesPlaceholder,
+        SystemMessagePromptTemplate,
+    )
+    from langchain_core.prompts.few_shot import (
+        FewShotChatMessagePromptTemplate,
+        FewShotPromptTemplate,
+    )
+    from langchain_core.prompts.few_shot_with_templates import (
+        FewShotPromptWithTemplates,
+    )
+    from langchain_core.prompts.loading import load_prompt
+    from langchain_core.prompts.pipeline import PipelinePromptTemplate
+    from langchain_core.prompts.prompt import PromptTemplate
+    from langchain_core.prompts.string import (
+        StringPromptTemplate,
+        check_valid_template,
+        get_template_variables,
+        jinja2_formatter,
+        validate_jinja2,
+    )
 
 __all__ = [
     "AIMessagePromptTemplate",
@@ -78,3 +84,43 @@ __all__ = [
     "jinja2_formatter",
     "validate_jinja2",
 ]
+
+_dynamic_imports = {
+    "BasePromptTemplate": "base",
+    "format_document": "base",
+    "aformat_document": "base",
+    "AIMessagePromptTemplate": "chat",
+    "BaseChatPromptTemplate": "chat",
+    "ChatMessagePromptTemplate": "chat",
+    "ChatPromptTemplate": "chat",
+    "HumanMessagePromptTemplate": "chat",
+    "MessagesPlaceholder": "chat",
+    "SystemMessagePromptTemplate": "chat",
+    "FewShotChatMessagePromptTemplate": "few_shot",
+    "FewShotPromptTemplate": "few_shot",
+    "FewShotPromptWithTemplates": "few_shot_with_templates",
+    "load_prompt": "loading",
+    "PipelinePromptTemplate": "pipeline",
+    "PromptTemplate": "prompt",
+    "StringPromptTemplate": "string",
+    "check_valid_template": "string",
+    "get_template_variables": "string",
+    "jinja2_formatter": "string",
+    "validate_jinja2": "string",
+}
+
+
+def __getattr__(attr_name: str) -> object:
+    module_name = _dynamic_imports.get(attr_name)
+    package = __spec__.parent  # type: ignore[name-defined]
+    if module_name == "__module__" or module_name is None:
+        result = import_module(f".{attr_name}", package=package)
+    else:
+        module = import_module(f".{module_name}", package=package)
+        result = getattr(module, attr_name)
+    globals()[attr_name] = result
+    return result
+
+
+def __dir__() -> list[str]:
+    return list(__all__)