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/bookend.py

@@ -0,0 +1,90 @@
+"""Wrapper around Bookend AI embedding models."""
+
+import json
+from typing import Any, List
+
+import requests
+from langchain_core.embeddings import Embeddings
+from langchain_core.pydantic_v1 import BaseModel, Field
+
+API_URL = "https://api.bookend.ai/"
+DEFAULT_TASK = "embeddings"
+PATH = "/models/predict"
+
+
+class BookendEmbeddings(BaseModel, Embeddings):
+    """Bookend AI sentence_transformers embedding models.
+
+    Example:
+        .. code-block:: python
+
+            from langchain_community.embeddings import BookendEmbeddings
+
+            bookend = BookendEmbeddings(
+                domain={domain}
+                api_token={api_token}
+                model_id={model_id}
+            )
+            bookend.embed_documents([
+                "Please put on these earmuffs because I can't you hear.",
+                "Baby wipes are made of chocolate stardust.",
+            ])
+            bookend.embed_query(
+                "She only paints with bold colors; she does not like pastels."
+            )
+    """
+
+    domain: str
+    """Request for a domain at https://bookend.ai/ to use this embeddings module."""
+    api_token: str
+    """Request for an API token at https://bookend.ai/ to use this embeddings module."""
+    model_id: str
+    """Embeddings model ID to use."""
+    auth_header: dict = Field(default_factory=dict)
+
+    def __init__(self, **kwargs: Any):
+        super().__init__(**kwargs)
+        self.auth_header = {"Authorization": "Basic {}".format(self.api_token)}
+
+    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+        """Embed documents using a Bookend deployed embeddings model.
+
+        Args:
+            texts: The list of texts to embed.
+
+        Returns:
+            List of embeddings, one for each text.
+        """
+        result = []
+        headers = self.auth_header
+        headers["Content-Type"] = "application/json; charset=utf-8"
+        params = {
+            "model_id": self.model_id,
+            "task": DEFAULT_TASK,
+        }
+
+        for text in texts:
+            data = json.dumps(
+                {"text": text, "question": None, "context": None, "instruction": None}
+            )
+            r = requests.request(
+                "POST",
+                API_URL + self.domain + PATH,
+                headers=headers,
+                params=params,
+                data=data,
+            )
+            result.append(r.json()[0]["data"])
+
+        return result
+
+    def embed_query(self, text: str) -> List[float]:
+        """Embed a query using a Bookend deployed embeddings model.
+
+        Args:
+            text: The text to embed.
+
+        Returns:
+            Embeddings for the text.
+        """
+        return self.embed_documents([text])[0]