remove CVEs (#8092)

This PR aims to move all code with CVEs into `langchain.experimental`.
Note that we are NOT yet removing from the core `langchain` package - we
will give people a week to migrate here.

See MIGRATE.md for how to migrate

Zero changes to functionality

Vulnerabilities this addresses:

PALChain:
- https://security.snyk.io/vuln/SNYK-PYTHON-LANGCHAIN-5752409
- https://security.snyk.io/vuln/SNYK-PYTHON-LANGCHAIN-5759265

SQLDatabaseChain
- https://security.snyk.io/vuln/SNYK-PYTHON-LANGCHAIN-5759268

`load_prompt` (Python files only)
- https://security.snyk.io/vuln/SNYK-PYTHON-LANGCHAIN-5725807

libs/experimental/langchain_experimental/plan_and_execute/planners/base.py

@@ -1,39 +0,0 @@
-from abc import abstractmethod
-from typing import Any, List, Optional
-
-from langchain.callbacks.manager import Callbacks
-from langchain.chains.llm import LLMChain
-from langchain.experimental.plan_and_execute.schema import Plan, PlanOutputParser
-from pydantic import BaseModel
-
-
-class BasePlanner(BaseModel):
-    @abstractmethod
-    def plan(self, inputs: dict, callbacks: Callbacks = None, **kwargs: Any) -> Plan:
-        """Given input, decide what to do."""
-
-    @abstractmethod
-    async def aplan(
-        self, inputs: dict, callbacks: Callbacks = None, **kwargs: Any
-    ) -> Plan:
-        """Given input, decide what to do."""
-
-
-class LLMPlanner(BasePlanner):
-    llm_chain: LLMChain
-    output_parser: PlanOutputParser
-    stop: Optional[List] = None
-
-    def plan(self, inputs: dict, callbacks: Callbacks = None, **kwargs: Any) -> Plan:
-        """Given input, decide what to do."""
-        llm_response = self.llm_chain.run(**inputs, stop=self.stop, callbacks=callbacks)
-        return self.output_parser.parse(llm_response)
-
-    async def aplan(
-        self, inputs: dict, callbacks: Callbacks = None, **kwargs: Any
-    ) -> Plan:
-        """Given input, decide what to do."""
-        llm_response = await self.llm_chain.arun(
-            **inputs, stop=self.stop, callbacks=callbacks
-        )
-        return self.output_parser.parse(llm_response)