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/chat_models/promptlayer_openai.py

@@ -0,0 +1,140 @@
+"""PromptLayer wrapper."""
+import datetime
+from typing import Any, Dict, List, Optional
+
+from langchain_core.callbacks import (
+    AsyncCallbackManagerForLLMRun,
+    CallbackManagerForLLMRun,
+)
+from langchain_core.messages import BaseMessage
+from langchain_core.outputs import ChatResult
+
+from langchain_community.chat_models import ChatOpenAI
+
+
+class PromptLayerChatOpenAI(ChatOpenAI):
+    """`PromptLayer` and `OpenAI` Chat large language models API.
+
+    To use, you should have the ``openai`` and ``promptlayer`` python
+    package installed, and the environment variable ``OPENAI_API_KEY``
+    and ``PROMPTLAYER_API_KEY`` set with your openAI API key and
+    promptlayer key respectively.
+
+    All parameters that can be passed to the OpenAI LLM can also
+    be passed here. The PromptLayerChatOpenAI adds to optional
+
+    parameters:
+        ``pl_tags``: List of strings to tag the request with.
+        ``return_pl_id``: If True, the PromptLayer request ID will be
+            returned in the ``generation_info`` field of the
+            ``Generation`` object.
+
+    Example:
+        .. code-block:: python
+
+            from langchain_community.chat_models import PromptLayerChatOpenAI
+            openai = PromptLayerChatOpenAI(model_name="gpt-3.5-turbo")
+    """
+
+    pl_tags: Optional[List[str]]
+    return_pl_id: Optional[bool] = False
+
+    @classmethod
+    def is_lc_serializable(cls) -> bool:
+        return False
+
+    def _generate(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        stream: Optional[bool] = None,
+        **kwargs: Any,
+    ) -> ChatResult:
+        """Call ChatOpenAI generate and then call PromptLayer API to log the request."""
+        from promptlayer.utils import get_api_key, promptlayer_api_request
+
+        request_start_time = datetime.datetime.now().timestamp()
+        generated_responses = super()._generate(
+            messages, stop, run_manager, stream=stream, **kwargs
+        )
+        request_end_time = datetime.datetime.now().timestamp()
+        message_dicts, params = super()._create_message_dicts(messages, stop)
+        for i, generation in enumerate(generated_responses.generations):
+            response_dict, params = super()._create_message_dicts(
+                [generation.message], stop
+            )
+            params = {**params, **kwargs}
+            pl_request_id = promptlayer_api_request(
+                "langchain.PromptLayerChatOpenAI",
+                "langchain",
+                message_dicts,
+                params,
+                self.pl_tags,
+                response_dict,
+                request_start_time,
+                request_end_time,
+                get_api_key(),
+                return_pl_id=self.return_pl_id,
+            )
+            if self.return_pl_id:
+                if generation.generation_info is None or not isinstance(
+                    generation.generation_info, dict
+                ):
+                    generation.generation_info = {}
+                generation.generation_info["pl_request_id"] = pl_request_id
+        return generated_responses
+
+    async def _agenerate(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        stream: Optional[bool] = None,
+        **kwargs: Any,
+    ) -> ChatResult:
+        """Call ChatOpenAI agenerate and then call PromptLayer to log."""
+        from promptlayer.utils import get_api_key, promptlayer_api_request_async
+
+        request_start_time = datetime.datetime.now().timestamp()
+        generated_responses = await super()._agenerate(
+            messages, stop, run_manager, stream=stream, **kwargs
+        )
+        request_end_time = datetime.datetime.now().timestamp()
+        message_dicts, params = super()._create_message_dicts(messages, stop)
+        for i, generation in enumerate(generated_responses.generations):
+            response_dict, params = super()._create_message_dicts(
+                [generation.message], stop
+            )
+            params = {**params, **kwargs}
+            pl_request_id = await promptlayer_api_request_async(
+                "langchain.PromptLayerChatOpenAI.async",
+                "langchain",
+                message_dicts,
+                params,
+                self.pl_tags,
+                response_dict,
+                request_start_time,
+                request_end_time,
+                get_api_key(),
+                return_pl_id=self.return_pl_id,
+            )
+            if self.return_pl_id:
+                if generation.generation_info is None or not isinstance(
+                    generation.generation_info, dict
+                ):
+                    generation.generation_info = {}
+                generation.generation_info["pl_request_id"] = pl_request_id
+        return generated_responses
+
+    @property
+    def _llm_type(self) -> str:
+        return "promptlayer-openai-chat"
+
+    @property
+    def _identifying_params(self) -> Dict[str, Any]:
+        return {
+            **super()._identifying_params,
+            "pl_tags": self.pl_tags,
+            "return_pl_id": self.return_pl_id,
+        }