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/tools/bearly/tool.py

@@ -0,0 +1,162 @@
+import base64
+import itertools
+import json
+import re
+from pathlib import Path
+from typing import Dict, List, Type
+
+import requests
+from langchain_core.pydantic_v1 import BaseModel, Field
+
+from langchain_community.tools import Tool
+
+
+def strip_markdown_code(md_string: str) -> str:
+    """Strip markdown code from a string."""
+    stripped_string = re.sub(r"^`{1,3}.*?\n", "", md_string, flags=re.DOTALL)
+    stripped_string = re.sub(r"`{1,3}$", "", stripped_string)
+    return stripped_string
+
+
+def head_file(path: str, n: int) -> List[str]:
+    """Get the first n lines of a file."""
+    try:
+        with open(path, "r") as f:
+            return [str(line) for line in itertools.islice(f, n)]
+    except Exception:
+        return []
+
+
+def file_to_base64(path: str) -> str:
+    """Convert a file to base64."""
+    with open(path, "rb") as f:
+        return base64.b64encode(f.read()).decode()
+
+
+class BearlyInterpreterToolArguments(BaseModel):
+    """Arguments for the BearlyInterpreterTool."""
+
+    python_code: str = Field(
+        ...,
+        example="print('Hello World')",
+        description=(
+            "The pure python script to be evaluated. "
+            "The contents will be in main.py. "
+            "It should not be in markdown format."
+        ),
+    )
+
+
+base_description = """Evaluates python code in a sandbox environment. \
+The environment resets on every execution. \
+You must send the whole script every time and print your outputs. \
+Script should be pure python code that can be evaluated. \
+It should be in python format NOT markdown. \
+The code should NOT be wrapped in backticks. \
+All python packages including requests, matplotlib, scipy, numpy, pandas, \
+etc are available. \
+If you have any files outputted write them to "output/" relative to the execution \
+path. Output can only be read from the directory, stdout, and stdin. \
+Do not use things like plot.show() as it will \
+not work instead write them out `output/` and a link to the file will be returned. \
+print() any output and results so you can capture the output."""
+
+
+class FileInfo(BaseModel):
+    """Information about a file to be uploaded."""
+
+    source_path: str
+    description: str
+    target_path: str
+
+
+class BearlyInterpreterTool:
+    """Tool for evaluating python code in a sandbox environment."""
+
+    api_key: str
+    endpoint = "https://exec.bearly.ai/v1/interpreter"
+    name = "bearly_interpreter"
+    args_schema: Type[BaseModel] = BearlyInterpreterToolArguments
+    files: Dict[str, FileInfo] = {}
+
+    def __init__(self, api_key: str):
+        self.api_key = api_key
+
+    @property
+    def file_description(self) -> str:
+        if len(self.files) == 0:
+            return ""
+        lines = ["The following files available in the evaluation environment:"]
+        for target_path, file_info in self.files.items():
+            peek_content = head_file(file_info.source_path, 4)
+            lines.append(
+                f"- path: `{target_path}` \n first four lines: {peek_content}"
+                f" \n description: `{file_info.description}`"
+            )
+        return "\n".join(lines)
+
+    @property
+    def description(self) -> str:
+        return (base_description + "\n\n" + self.file_description).strip()
+
+    def make_input_files(self) -> List[dict]:
+        files = []
+        for target_path, file_info in self.files.items():
+            files.append(
+                {
+                    "pathname": target_path,
+                    "contentsBasesixtyfour": file_to_base64(file_info.source_path),
+                }
+            )
+        return files
+
+    def _run(self, python_code: str) -> dict:
+        script = strip_markdown_code(python_code)
+        resp = requests.post(
+            "https://exec.bearly.ai/v1/interpreter",
+            data=json.dumps(
+                {
+                    "fileContents": script,
+                    "inputFiles": self.make_input_files(),
+                    "outputDir": "output/",
+                    "outputAsLinks": True,
+                }
+            ),
+            headers={"Authorization": self.api_key},
+        ).json()
+        return {
+            "stdout": base64.b64decode(resp["stdoutBasesixtyfour"]).decode()
+            if resp["stdoutBasesixtyfour"]
+            else "",
+            "stderr": base64.b64decode(resp["stderrBasesixtyfour"]).decode()
+            if resp["stderrBasesixtyfour"]
+            else "",
+            "fileLinks": resp["fileLinks"],
+            "exitCode": resp["exitCode"],
+        }
+
+    async def _arun(self, query: str) -> str:
+        """Use the tool asynchronously."""
+        raise NotImplementedError("custom_search does not support async")
+
+    def add_file(self, source_path: str, target_path: str, description: str) -> None:
+        if target_path in self.files:
+            raise ValueError("target_path already exists")
+        if not Path(source_path).exists():
+            raise ValueError("source_path does not exist")
+        self.files[target_path] = FileInfo(
+            target_path=target_path, source_path=source_path, description=description
+        )
+
+    def clear_files(self) -> None:
+        self.files = {}
+
+    # TODO: this is because we can't have a dynamic description
+    #  because of the base pydantic class
+    def as_tool(self) -> Tool:
+        return Tool.from_function(
+            func=self._run,
+            name=self.name,
+            description=self.description,
+            args_schema=self.args_schema,
+        )