community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)

Moved the following modules to new package langchain-community in a backwards compatible fashion:

```
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
```

Moved the following to core
```
mv langchain/langchain/utils/json_schema.py core/langchain_core/utils
mv langchain/langchain/utils/html.py core/langchain_core/utils
mv langchain/langchain/utils/strings.py core/langchain_core/utils
cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py
rm langchain/langchain/utils/env.py
```

See .scripts/community_split/script_integrations.sh for all changes

libs/community/langchain_community/embeddings/mlflow.py

@@ -0,0 +1,74 @@
+from __future__ import annotations
+
+from typing import Any, Iterator, List
+from urllib.parse import urlparse
+
+from langchain_core.embeddings import Embeddings
+from langchain_core.pydantic_v1 import BaseModel, PrivateAttr
+
+
+def _chunk(texts: List[str], size: int) -> Iterator[List[str]]:
+    for i in range(0, len(texts), size):
+        yield texts[i : i + size]
+
+
+class MlflowEmbeddings(Embeddings, BaseModel):
+    """Wrapper around embeddings LLMs in MLflow.
+
+    To use, you should have the `mlflow[genai]` python package installed.
+    For more information, see https://mlflow.org/docs/latest/llms/deployments/server.html.
+
+    Example:
+        .. code-block:: python
+
+            from langchain_community.embeddings import MlflowEmbeddings
+
+            embeddings = MlflowEmbeddings(
+                target_uri="http://localhost:5000",
+                endpoint="embeddings",
+            )
+    """
+
+    endpoint: str
+    """The endpoint to use."""
+    target_uri: str
+    """The target URI to use."""
+    _client: Any = PrivateAttr()
+
+    def __init__(self, **kwargs: Any):
+        super().__init__(**kwargs)
+        self._validate_uri()
+        try:
+            from mlflow.deployments import get_deploy_client
+
+            self._client = get_deploy_client(self.target_uri)
+        except ImportError as e:
+            raise ImportError(
+                "Failed to create the client. "
+                f"Please run `pip install mlflow{self._mlflow_extras}` to install "
+                "required dependencies."
+            ) from e
+
+    @property
+    def _mlflow_extras(self) -> str:
+        return "[genai]"
+
+    def _validate_uri(self) -> None:
+        if self.target_uri == "databricks":
+            return
+        allowed = ["http", "https", "databricks"]
+        if urlparse(self.target_uri).scheme not in allowed:
+            raise ValueError(
+                f"Invalid target URI: {self.target_uri}. "
+                f"The scheme must be one of {allowed}."
+            )
+
+    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+        embeddings: List[List[float]] = []
+        for txt in _chunk(texts, 20):
+            resp = self._client.predict(endpoint=self.endpoint, inputs={"input": txt})
+            embeddings.extend(r["embedding"] for r in resp["data"])
+        return embeddings
+
+    def embed_query(self, text: str) -> List[float]:
+        return self.embed_documents([text])[0]