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851b838 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | import datetime
from langchain.agents import create_openai_tools_agent, AgentExecutor
from langchain.chat_models import init_chat_model
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_openai import ChatOpenAI
from langchain_tavily import TavilySearch
from langchain.schema import HumanMessage, SystemMessage
from langchain_core.prompts import PromptTemplate
from langchain_openai import ChatOpenAI
from langchain_anthropic import ChatAnthropic
from pydantic import BaseModel, Field
from typing import List
from enum import Enum
from langchain_core.output_parsers import PydanticOutputParser
from langchain_core.output_parsers import JsonOutputParser
import os
from dotenv import load_dotenv
load_dotenv()
from config import settings
class Agents:
def __init__(self, temperature: float = 0.3, model: str = "gpt-4.1", model_type: str = "openai",
is_structured: bool = True):
"""
Initializes the UserSummaryGenerator with necessary settings and model configuration.
"""
self.settings = settings
self.model_type = model_type
self.llm_tavily = init_chat_model(model="gpt-4o", model_provider="openai", temperature=0)
self.tavily_search_tool = TavilySearch(max_results=5, topic="general")
self.tavily_prompt = ChatPromptTemplate.from_messages([
("system", self.settings.COUNTY_RISK_ANALYSIS_PROMPT),
MessagesPlaceholder(variable_name="messages"),
MessagesPlaceholder(variable_name="agent_scratchpad"), # Required for tool calls
])
self.tavily_agent = create_openai_tools_agent(
llm=self.llm_tavily,
tools=[self.tavily_search_tool],
prompt=self.tavily_prompt
)
self.agent_executor = AgentExecutor(agent=self.tavily_agent, tools=[self.tavily_search_tool], verbose=False)
def generate_tavily_search(self, user_input: str) -> str:
response = self.agent_executor.invoke({"messages": [HumanMessage(content=user_input)]},)
return response
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