fix: update files for pydantic_v2

src/codeinterpreterapi/brain/params.py

@@ -3,11 +3,11 @@
 
 from codeboxapi import CodeBox  # type: ignore
 from gui_agent_loop_core.schema.agent.schema import AgentDefinition
-from langchain.base_language import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 from langchain.callbacks.base import Callbacks
-from langchain.tools import BaseTool
+from langchain_core.tools import BaseTool
 from langchain_core.language_models.chat_models import BaseChatModel
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel
 from langchain_core.runnables import Runnable, RunnableConfig
 from langchain_core.tools import tool
 

src/codeinterpreterapi/callbacks/markdown/callbacks.py

@@ -4,7 +4,13 @@
 from uuid import UUID
 
 from langchain.callbacks import FileCallbackHandler
-from langchain.schema import AgentAction, AgentFinish, LLMResult
+
+
+from langchain_core.agents import AgentFinish
+
+from langchain_core.agents import AgentAction
+
+from langchain_core.outputs import LLMResult
 
 
 class MarkdownFileCallbackHandler(FileCallbackHandler):

src/codeinterpreterapi/callbacks/stdout/callbacks.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 from uuid import UUID
 
-from langchain.callbacks import StdOutCallbackHandler
+from langchain_core.callbacks import StdOutCallbackHandler
 from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.messages import BaseMessage
 

src/codeinterpreterapi/config.py

@@ -1,8 +1,8 @@
 from typing import Optional
 
 from langchain_core.messages import SystemMessage
-from langchain_core.pydantic_v1 import BaseSettings, SecretStr
-
+from pydantic import SecretStr
+from pydantic_settings import BaseSettings
 from codeinterpreterapi.prompts import code_interpreter_system_message, code_interpreter_system_message_ja
 
 

src/codeinterpreterapi/graphs/agent_wrapper_tool.py

@@ -1,6 +1,6 @@
 from typing import Any, Optional, Type
 
-from langchain.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 from langchain_core.messages import AIMessage, HumanMessage
 from langchain_core.tools import BaseTool
 

src/codeinterpreterapi/graphs/tool_node/tool_node.py

@@ -1,9 +1,11 @@
 from typing import Sequence
 
 from langchain.agents import AgentExecutor
-from langchain.chat_models.base import BaseChatModel
+from langchain_core.language_models import BaseChatModel
 from langchain_core.messages import AIMessage
-from langchain_core.tools import BaseTool, tool
+from langchain_core.tools import tool
+from pydantic import BaseTool
+
 from langgraph.graph import MessageGraph, StateGraph
 from langgraph.prebuilt import ToolNode, tools_condition
 

src/codeinterpreterapi/llm/llm.py

@@ -6,7 +6,7 @@
 from google.generativeai.types.content_types import FunctionDeclarationType  # type: ignore[import]
 from google.generativeai.types.content_types import ToolDict  # type: ignore[import]
 from google.generativeai.types.safety_types import HarmBlockThreshold, HarmCategory
-from langchain.chat_models.base import BaseChatModel
+from langchain_core.language_models import BaseChatModel
 from langchain_core.messages import BaseMessage
 from langchain_core.runnables import Runnable, RunnableConfig
 from langchain_google_genai import ChatGoogleGenerativeAI  # type: ignore

src/codeinterpreterapi/planners/planners.py

@@ -2,7 +2,11 @@
 
 from langchain.agents import AgentExecutor
 from langchain.agents.agent import RunnableAgent
-from langchain.schema import AIMessage, Generation
+
+
+from langchain_core.messages import AIMessage
+
+from langchain_core.outputs import Generation
 from langchain_core.output_parsers import PydanticOutputParser
 from langchain_core.runnables import Runnable
 from pydantic import BaseModel, Field

src/codeinterpreterapi/schema.py

@@ -3,7 +3,7 @@
 
 from codeboxapi.schema import CodeBoxStatus
 from langchain_core.messages import AIMessage, HumanMessage
-from langchain_core.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 from langchain_core.tools import BaseTool
 
 ToolsRenderer = Callable[[List[BaseTool]], str]

src/codeinterpreterapi/session.py

@@ -7,7 +7,9 @@
 from codeboxapi import CodeBox  # type: ignore
 from codeboxapi.schema import CodeBoxStatus  # type: ignore
 from gui_agent_loop_core.schema.message.schema import BaseMessageContent
-from langchain.callbacks.base import BaseCallbackHandler, Callbacks
+from langchain.callbacks.base import Callbacks
+
+from langchain_core.callbacks import BaseCallbackHandler
 from langchain_community.chat_message_histories.in_memory import ChatMessageHistory
 from langchain_community.chat_message_histories.postgres import PostgresChatMessageHistory
 from langchain_community.chat_message_histories.redis import RedisChatMessageHistory

src/codeinterpreterapi/supervisors/supervisors.py

@@ -4,9 +4,10 @@
 from typing import Any, Dict
 
 from langchain.agents import AgentExecutor
-from langchain_core.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 from langchain_core.runnables import Runnable
 from langchain_core.runnables.utils import Input
+from langchain_core.prompts import PromptTemplate
 
 from codeinterpreterapi.agents.agents import CodeInterpreterAgent
 from codeinterpreterapi.brain.params import CodeInterpreterParams
@@ -18,11 +19,13 @@
 from codeinterpreterapi.test_prompts.test_prompt import TestPrompt
 from codeinterpreterapi.utils.multi_converter import MultiConverter
 
+from codeinterpreterapi.tools.tools import CodeInterpreterTools
+
 
 class CodeInterpreterSupervisor:
     def __init__(self, planner: Runnable, ci_params: CodeInterpreterParams):
         self.planner = ci_params.planner_agent
-        self.ci_params = ci_params
+        self.ci_params: CodeInterpreterParams = ci_params
         self.supervisor_chain = None
         self.supervisor_chain_no_agent = None
         self.initialize()
@@ -82,8 +85,20 @@ def get_executor(self) -> AgentExecutor:
         # TODO: impl
         return self.supervisor_chain
 
+    def zoltraak_pre_process(self, input: Input) -> str:
+        prompt_template = PromptTemplate(
+            template="zoltraakによる前処理でinputを一般的な汎用言語表現に翻訳してください。: {input}"
+        )
+        tools = CodeInterpreterTools.get_zoltraak_tools(self.ci_params)
+        llm_with_tools = self.ci_params.llm.bind_tools(tools)
+        chain = prompt_template | llm_with_tools
+        pre_processed_input = chain.invoke(input)
+        print("zoltraak_pre_process pre_processed_input=", pre_processed_input)
+        return pre_processed_input
+
     def invoke(self, input: Input) -> CodeInterpreterIntermediateResult:
-        planner_result = self.planner.invoke(input, config=self.ci_params.runnable_config)
+        pre_processed_input = self.zoltraak_pre_process(input)
+        planner_result = self.planner.invoke(pre_processed_input, config=self.ci_params.runnable_config)
         print("supervisor.invoke type(planner_result)=", type(planner_result))
         if isinstance(planner_result, CodeInterpreterPlanList):
             plan_list: CodeInterpreterPlanList = planner_result

src/codeinterpreterapi/thoughts/base.py

@@ -3,10 +3,10 @@
 from textwrap import indent
 from typing import Any, Dict, List, Optional, Type
 
-from langchain.base_language import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 from langchain_core.callbacks.manager import AsyncCallbackManagerForChainRun, CallbackManagerForChainRun
 from langchain_core.runnables import Runnable
-from langchain_experimental.pydantic_v1 import Extra
+from langchain_experimental.pydantic_v2 import Extra
 from langchain_experimental.tot.base import ToTChain
 from langchain_experimental.tot.checker import ToTChecker
 from langchain_experimental.tot.controller import ToTController
@@ -21,13 +21,10 @@ class MyToTChain(ToTChain):
     """
 
     llm: Runnable
-    """
-    Language model to use. It must be set to produce different variations for
-    the same prompt.
-    """
+    """Language model to use. It must be set to produce different variations for the same prompt."""
     checker: ToTChecker
     """ToT Checker to use."""
-    output_key: str = "response"  #: :meta private:
+    output_key: str = "response"
     k: int = 10
     """The maximum number of conversation rounds"""
     c: int = 3
@@ -36,7 +33,7 @@ class MyToTChain(ToTChain):
     tot_controller: ToTController = ToTController()
     tot_strategy_class: Type[BaseThoughtGenerationStrategy] = ProposePromptStrategy
     verbose_llm: bool = False
-    thought_generator: BaseThoughtGenerationStrategy = None
+    thought_generator: Optional[BaseThoughtGenerationStrategy] = None
 
     class Config:
         """Configuration for this pydantic object."""
@@ -50,7 +47,7 @@ def initialize_thought_generator(self):
         print("initialize_thought_generator prompt.input_variables=", input_variables)
 
     @classmethod
-    def from_llm(cls, llm: BaseLanguageModel, **kwargs: Any) -> ToTChain:
+    def from_llm(cls, llm: BaseLanguageModel, **kwargs: Any) -> MyToTChain:
         """
         Create a ToTChain from a language model.
 
@@ -65,18 +62,12 @@ def __init__(self, **kwargs: Any):
 
     @property
     def input_keys(self) -> List[str]:
-        """Will be whatever keys the prompt expects.
-
-        :meta private:
-        """
+        """Will be whatever keys the prompt expects."""
         return ["problem_description"]
 
     @property
     def output_keys(self) -> List[str]:
-        """Will always return text key.
-
-        :meta private:
-        """
+        """Will always return text key."""
         return [self.output_key]
 
     def log_thought(

src/codeinterpreterapi/thoughts/checker.py

@@ -2,7 +2,7 @@
 from typing import Optional, Tuple
 
 import spacy
-from langchain.prompts import PromptTemplate
+from langchain_core.prompts import PromptTemplate
 from langchain_core.output_parsers import JsonOutputParser, StrOutputParser
 from langchain_core.runnables import Runnable
 from langchain_experimental.tot.checker import ToTChecker

src/codeinterpreterapi/thoughts/thought_generation.py

@@ -2,8 +2,8 @@
 # https://github.com/langchain-ai/langchain/blob/master/libs/experimental/langchain_experimental/tot/thought_generation.py
 from typing import Any, Dict, List, Tuple
 
-from langchain.prompts.base import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from langchain_core.prompts import BasePromptTemplate
+from pydantic import Field
 from langchain_experimental.tot.checker import ToTChecker
 from langchain_experimental.tot.thought import ThoughtValidity
 from langchain_experimental.tot.thought_generation import ProposePromptStrategy, SampleCoTStrategy

src/codeinterpreterapi/tools/tools.py

@@ -1,10 +1,13 @@
-from langchain_community.tools.shell.tool import BaseTool, ShellTool
+from langchain_community.tools.shell.tool import ShellTool
+
+from langchain_core.tools import BaseTool
 from langchain_community.tools.tavily_search import TavilySearchResults
 
 from codeinterpreterapi.brain.params import CodeInterpreterParams
 from codeinterpreterapi.tools.bash import BashTools
 from codeinterpreterapi.tools.code_checker import CodeChecker
 from codeinterpreterapi.tools.python import PythonTools
+from codeinterpreterapi.tools.zoltraak import ZoltraakTools
 from typing import List
 
 
@@ -21,6 +24,7 @@ def get_all_tools(self) -> list[BaseTool]:
         self._additional_tools.extend(CodeChecker.get_tools_code_checker(self._ci_params))
         self.add_tools_shell()
         self.add_tools_web_search()
+        self.add_tools_zoltraak()
         return self._additional_tools
 
     def add_tools_shell(self) -> None:
@@ -42,6 +46,15 @@ def add_tools_web_search(self) -> None:
         tools = [TavilySearchResults(max_results=1)]
         self._additional_tools += tools
 
+    def add_tools_zoltraak(self) -> None:
+        tools = ZoltraakTools.get_tools_zoltraak(self._ci_params)
+        self._additional_tools += tools
+
+    @staticmethod
+    def get_zoltraak_tools(ci_params: CodeInterpreterParams) -> None:
+        tools = ZoltraakTools.get_tools_zoltraak(ci_params)
+        return tools
+
     @staticmethod
     def get_agent_tools(agent_tools: str, all_tools: List[BaseTool]) -> None:
         selected_tools = []

src/codeinterpreterapi/tools/zoltraak.py

@@ -63,11 +63,14 @@ async def arun_design(self, prompt: str, name: str) -> str:
         return self._common_run(prompt, name, ZoltraakCompilerEnum.DESIGN.value)
 
     def _common_run(self, prompt: str, name: str, compiler: str):
+        # mdファイルを生成して内容をreturnする
+        inout_md_path = f"requirements/{name}.md"
+
         try:
             # シェルインジェクションを防ぐためにshlexを使用
             args = []
             args.append('/home/jinno/.pyenv/shims/zoltraak')
-            args.append(f"\"requirements/{name}.md\"")
+            args.append(f"\"{inout_md_path}\"")
             args.append('-p')
             args.append(f"\"{prompt}\"")
             args.append('-c')
@@ -77,7 +80,14 @@ def _common_run(self, prompt: str, name: str, compiler: str):
             )
             print("_common_run output_content=", type(output_content))
             print("_common_run output_content=", output_content)
+
+            if os.path.isfile(inout_md_path):
+                with open(inout_md_path, "r") as file:
+                    output_content = file.read()
+                    print("_common_run output_content(zoltraak)=", output_content)
+                    return output_content
             self.command_log.append((args, output_content))
+            print("WARN: no inout_m inout_md_path=", inout_md_path)
             return output_content
 
         except subprocess.CalledProcessError as e:

src/codeinterpreterapi/utils/runnable.py

@@ -1,6 +1,6 @@
 from typing import Any, Dict, List, Union
 
-from langchain.prompts.base import BasePromptTemplate
+from langchain_core.prompts import BasePromptTemplate
 from langchain_core.runnables import RunnableLambda, RunnableSequence
 
 

src/codeinterpreterapi/utils/runnable_history.py

@@ -5,7 +5,7 @@
 from langchain_community.chat_message_histories import FileChatMessageHistory
 from langchain_core.chat_history import BaseChatMessageHistory
 from langchain_core.messages import BaseMessage
-from langchain_core.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 from langchain_core.runnables import Runnable, RunnableConfig
 from langchain_core.runnables.history import RunnableWithMessageHistory