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/cloudflare_workersai.py

@@ -0,0 +1,94 @@
+from typing import Any, Dict, List
+
+import requests
+from langchain_core.embeddings import Embeddings
+from langchain_core.pydantic_v1 import BaseModel, Extra
+
+DEFAULT_MODEL_NAME = "@cf/baai/bge-base-en-v1.5"
+
+
+class CloudflareWorkersAIEmbeddings(BaseModel, Embeddings):
+    """Cloudflare Workers AI embedding model.
+
+    To use, you need to provide an API token and
+    account ID to access Cloudflare Workers AI.
+
+    Example:
+        .. code-block:: python
+
+            from langchain_community.embeddings import CloudflareWorkersAIEmbeddings
+
+            account_id = "my_account_id"
+            api_token = "my_secret_api_token"
+            model_name =  "@cf/baai/bge-small-en-v1.5"
+
+            cf = CloudflareWorkersAIEmbeddings(
+                account_id=account_id,
+                api_token=api_token,
+                model_name=model_name
+            )
+    """
+
+    api_base_url: str = "https://api.cloudflare.com/client/v4/accounts"
+    account_id: str
+    api_token: str
+    model_name: str = DEFAULT_MODEL_NAME
+    batch_size: int = 50
+    strip_new_lines: bool = True
+    headers: Dict[str, str] = {"Authorization": "Bearer "}
+
+    def __init__(self, **kwargs: Any):
+        """Initialize the Cloudflare Workers AI client."""
+        super().__init__(**kwargs)
+
+        self.headers = {"Authorization": f"Bearer {self.api_token}"}
+
+    class Config:
+        """Configuration for this pydantic object."""
+
+        extra = Extra.forbid
+
+    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+        """Compute doc embeddings using Cloudflare Workers AI.
+
+        Args:
+            texts: The list of texts to embed.
+
+        Returns:
+            List of embeddings, one for each text.
+        """
+        if self.strip_new_lines:
+            texts = [text.replace("\n", " ") for text in texts]
+
+        batches = [
+            texts[i : i + self.batch_size]
+            for i in range(0, len(texts), self.batch_size)
+        ]
+        embeddings = []
+
+        for batch in batches:
+            response = requests.post(
+                f"{self.api_base_url}/{self.account_id}/ai/run/{self.model_name}",
+                headers=self.headers,
+                json={"text": batch},
+            )
+            embeddings.extend(response.json()["result"]["data"])
+
+        return embeddings
+
+    def embed_query(self, text: str) -> List[float]:
+        """Compute query embeddings using Cloudflare Workers AI.
+
+        Args:
+            text: The text to embed.
+
+        Returns:
+            Embeddings for the text.
+        """
+        text = text.replace("\n", " ") if self.strip_new_lines else text
+        response = requests.post(
+            f"{self.api_base_url}/{self.account_id}/ai/run/{self.model_name}",
+            headers=self.headers,
+            json={"text": [text]},
+        )
+        return response.json()["result"]["data"][0]