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swarms/swarms/agents/workers/auto_agent.py

96 lines
2.8 KiB

# General
import os
import pandas as pd
from langchain.experimental.autonomous_agents.autogpt.agent import AutoGPT
from langchain.chat_models import ChatOpenAI
from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent
from langchain.docstore.document import Document
import asyncio
import nest_asyncio
# Tools
from contextlib import contextmanager
from typing import Optional
from langchain.agents import tool
from langchain.tools.file_management.read import ReadFileTool
from langchain.tools.file_management.write import WriteFileTool
from langchain.tools import BaseTool, DuckDuckGoSearchRun
from langchain.text_splitter import RecursiveCharacterTextSplitter
from pydantic import Field
from langchain.chains.qa_with_sources.loading import load_qa_with_sources_chain, BaseCombineDocumentsChain
# Memory
import faiss
from langchain.vectorstores import FAISS
from langchain.docstore import InMemoryDocstore
from langchain.embeddings import OpenAIEmbeddings
from langchain.tools.human.tool import HumanInputRun
# from swarms.agents.workers.auto_agent import
from swarms.agents.workers.visual_agent import multimodal_agent_tool
from swarms.tools.main import Terminal, CodeWriter, CodeEditor, process_csv, WebpageQATool
class WorkerAgent:
def __init__(self, objective: str, api_key: str):
self.objective = objective
self.api_key = api_key
self.worker = self.create_agent_worker()
def create_agent_worker(self):
os.environ['OPENAI_API_KEY'] = self.api_key
llm = ChatOpenAI(model_name="gpt-4", temperature=1.0)
embeddings_model = OpenAIEmbeddings()
embedding_size = 1536
index = faiss.IndexFlatL2(embedding_size)
vectorstore = FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
query_website_tool = WebpageQATool(qa_chain=load_qa_with_sources_chain(llm))
web_search = DuckDuckGoSearchRun()
tools = [
web_search,
WriteFileTool(root_dir="./data"),
ReadFileTool(root_dir="./data"),
multimodal_agent_tool,
process_csv,
query_website_tool,
Terminal,
CodeWriter,
CodeEditor
]
agent_worker = AutoGPT.from_llm_and_tools(
ai_name="WorkerX",
ai_role="Assistant",
tools=tools,
llm=llm,
memory=vectorstore.as_retriever(search_kwargs={"k": 8}),
human_in_the_loop=True,
)
agent_worker.chain.verbose = True
return agent_worker
# objective = "Your objective here"
# api_key = "Your OpenAI API key here"
# worker_agent = WorkerAgent(objective, api_key)
# objective = "Your objective here"
# worker_agent = WorkerAgent(objective)