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import os
from langchain import hub
from langchain.agents import initialize_agent, AgentType, Tool
from langchain.llms import HuggingFaceHub
from langchain_community.tools import DuckDuckGoSearchResults
from langchain_experimental.tools import PythonREPLTool
from langchain.agents.agent_toolkits import create_python_agent
from langchain.agents import load_tools
# Lade dein Hugging Face Token (falls benötigt)
from huggingface_hub import login
# login(token="your-huggingface-token-here") # Optional, falls dein Space das braucht
# LLM: Mistral-7B-Instruct über Hugging Face Inference API
llm = HuggingFaceHub(
repo_id="mistralai/Mistral-7B-Instruct-v0.2",
model_kwargs={"temperature": 0.2, "max_new_tokens": 512}
)
# Tools definieren
search_tool = DuckDuckGoSearchResults()
python_tool = PythonREPLTool()
tools = [
Tool(
name="Search",
func=search_tool.run,
description="Useful for when you need to answer questions about current events or look up information online."
),
Tool(
name="Python_REPL",
func=python_tool.run,
description="Useful for math, calculations, or running simple python code."
),
]
# Agent initialisieren
agent_executor = initialize_agent(
tools,
llm,
agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
verbose=True,
handle_parsing_errors=True,
)
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