Delete agents.py

agents.py

@@ -1,81 +0,0 @@
-from ast import main
-import os
-from typing import TypedDict, List, Dict, Any, Optional
-from langgraph.graph import StateGraph, START, END
-from langchain_core.messages import HumanMessage, AIMessage, SystemMessage
-from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain_core.rate_limiters import InMemoryRateLimiter
-
-
-GAIA_PROMPT = "You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string."
-
-# Initialize our LLM
-
-
-# Data
-class GAIAAgentState(TypedDict):
-    """State of the GAIA agent."""
-
-    task_id: str
-    question: str
-    file_id: Optional[str]
-    answer: Optional[str]
-    thought: Optional[str]
-    # TODO add file binary fields
-
-
-class BasicAgent:
-    def __init__(self):
-        # Set up the rate limiter
-        self.rate_limiter = InMemoryRateLimiter(
-            requests_per_second=0.2  # 12 requests per minute
-        )
-        self.model = ChatGoogleGenerativeAI(
-            model="gemini-2.0-flash",
-            temperature=0,
-            max_tokens=None,
-            timeout=None,
-            max_retries=2,
-            google_api_key=os.environ["GEMINI_API_KEY"],
-            rate_limiter=self.rate_limiter,
-        )
-        print("BasicAgent initialized.")
-
-    def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        messages = [
-            ("system", GAIA_PROMPT),
-            ("human", question),
-        ]
-
-        # Pass the messages to the model
-        ai_msg = self.model.invoke(messages)
-
-        # Extract and return the AI's response
-        print(f"Agent returning response: {ai_msg.content}")
-        return (
-            str(ai_msg.content)
-            if not isinstance(ai_msg.content, str)
-            else ai_msg.content
-        )
-
-
-class GraphManager:
-    def __init__(self):
-        self.graph = StateGraph(GAIAAgentState)
-        print("GraphManager initialized.")
-
-    def read_question_and_define_gaia_state(
-        self, state: GAIAAgentState
-    ) -> GAIAAgentState:
-        pass  # TODO: Implement the logic to read the question and define the GAIA state
-
-    def build_graph(self) -> StateGraph:
-        # Add nodes
-        self.graph.add_node(
-            "read_question_and_define_gaia_state",
-            self.read_question_and_define_gaia_state,
-        )
-        # Add edges
-        self.graph.add_edge(START, "read_question_and_define_gaia_state")
-        return self.graph