feat: add ShrewdAgent implementation for AI-assisted tool integration

ShrewdAgent.py

@@ -0,0 +1,91 @@
+import os
+from typing import TypedDict, Annotated, Optional, Any, Callable, Sequence, Union
+
+from langchain_core.messages import AnyMessage, SystemMessage, HumanMessage
+from langchain_core.tools import BaseTool
+from langchain_openai import ChatOpenAI
+from langgraph.constants import START
+from langgraph.errors import GraphRecursionError
+from langgraph.graph import add_messages, StateGraph
+from langgraph.prebuilt import ToolNode, tools_condition
+from langgraph.pregel import PregelProtocol
+from loguru import logger
+from pydantic import SecretStr
+
+
+class AgentState(TypedDict):
+    messages: Annotated[list[AnyMessage], add_messages]
+
+
+class ShrewdAgent:
+    message_system = """You are a general AI assistant equipped with a suite of external tools. Your task is to
+                        answer the following question as accurately and helpfully as possible by using the tools
+                        provided. Do not write or execute code yourself. For any operation requiring computation,
+                        data retrieval, or external access, explicitly invoke the appropriate tool.
+        
+                        Follow these guidelines:"
+                        - Clearly explain your reasoning step by step.
+                        - Justify your choice of tool(s) at each step.
+                        - If multiple interpretations are possible, outline them and explain your reasoning for selecting one.
+                        - If the answer requires external data or inference, retrieve or deduce it via the available tools.
+        
+                        Important: Your final output must be only a number or a short phrase, with no additional text or explanation."""
+
+    def __init__(self):
+        self.tools = []
+        self.llm = ChatOpenAI(
+            model="gpt-4o-mini",
+            temperature=0,
+            api_key=SecretStr(os.environ['OPENAI_API_KEY'])
+        ).bind_tools(self.tools)
+
+        def assistant_node(state: AgentState):
+            return {
+                "messages": [self.llm.invoke(state["messages"])],
+            }
+
+        self.agent = _build_state_graph(AgentState, assistant_node, self.tools)
+        logger.info("ShrewdAgent initialized.")
+
+    def __call__(self, question: str) -> str:
+        logger.info(f"Agent received question: {question}")
+        accumulated_response = []
+        try:
+            for chunk in self.agent.stream(
+                    {"messages": [
+                        SystemMessage(self.message_system),
+                        HumanMessage(question, )
+                    ]},
+                    {"recursion_limit": 12},
+            ):
+                assistant = chunk.get("assistant")
+                if assistant:
+                    logger.debug(f"{assistant.get('messages')[0].pretty_repr()}")
+                tools = chunk.get("tools")
+                if tools:
+                    logger.debug(f"{tools.get('messages')[0].pretty_repr()}")
+                accumulated_response.append(chunk)
+
+        except GraphRecursionError as e:
+            logger.error(f"GraphRecursionError: {e}")
+
+        final_answer = "I couldn't find the answer"
+        if accumulated_response[-1].get("assistant"):
+            final_answer = accumulated_response[-1]["assistant"]['messages'][-1].content
+        logger.info(f"Agent returning answer: {final_answer}")
+        return final_answer
+
+
+def _build_state_graph(
+        state_schema: Optional[type[Any]],
+        assistant: Callable,
+        tools: Sequence[Union[BaseTool, Callable]]) -> PregelProtocol:  # CompiledStateGraph:
+
+    return (StateGraph(state_schema)
+            .add_node("assistant", assistant)
+            .add_node("tools", ToolNode(tools))
+            .add_edge(START, "assistant")
+            .add_conditional_edges("assistant", tools_condition)
+            .add_edge("tools", "assistant")
+            .compile()
+            )

requirements.txt

@@ -1,2 +1,8 @@
-gradio
-requests
+gradio~=5.29.1
+requests~=2.32.3
+pandas~=2.2.3
+langchain-core~=0.3.60
+langchain-openai~=0.3.17
+langgraph~=0.4.5
+loguru~=0.7.3
+pydantic~=2.11.4