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| # ---------- Dependencies ---------- | |
| import os | |
| import asyncio | |
| import faiss | |
| from typing import Any, Optional, List | |
| from contextlib import contextmanager | |
| from pydantic import BaseModel, Field | |
| from langchain import LLMChain, OpenAI, PromptTemplate | |
| from langchain.chains.base import Chain | |
| from langchain.experimental import BabyAGI | |
| from langchain.embeddings import OpenAIEmbeddings | |
| from langchain.vectorstores.base import VectorStore | |
| from langchain.vectorstores import FAISS | |
| from langchain.docstore import InMemoryDocstore | |
| from langchain.chains.qa_with_sources.loading import load_qa_with_sources_chain | |
| from langchain.agents import ZeroShotAgent, Tool, AgentExecutor | |
| from langchain.text_splitter import RecursiveCharacterTextSplitter | |
| from langchain.tools import BaseTool, DuckDuckGoSearchRun | |
| from langchain.tools.file_management.read import ReadFileTool | |
| from langchain.tools.file_management.write import WriteFileTool | |
| from langchain.tools.human.tool import HumanInputRun | |
| from swarms.tools import Terminal, CodeWriter, CodeEditor, process_csv, WebpageQATool | |
| from langchain.experimental.autonomous_agents.autogpt.agent import AutoGPT | |
| from langchain.chat_models import ChatOpenAI | |
| from langchain.tools import tool | |
| # ---------- Constants ---------- | |
| ROOT_DIR = "./data/" | |
| # ---------- Tools ---------- | |
| openai_api_key = os.environ["OPENAI_API_KEY"] | |
| llm = ChatOpenAI(model_name="gpt-4", temperature=1.0, openai_api_key=openai_api_key) | |
| worker_tools = [ | |
| DuckDuckGoSearchRun(), | |
| WriteFileTool(root_dir=ROOT_DIR), | |
| ReadFileTool(root_dir=ROOT_DIR), | |
| process_csv, | |
| WebpageQATool(qa_chain=load_qa_with_sources_chain(llm)), | |
| # Tool(name='terminal', func=Terminal.execute, description='Operates a terminal'), | |
| # Tool(name='code_writer', func=CodeWriter(), description='Writes code'), | |
| # Tool(name='code_editor', func=CodeEditor(), description='Edits code'),# | |
| ] | |
| # ---------- Vector Store ---------- | |
| embeddings_model = OpenAIEmbeddings() | |
| embedding_size = 1536 | |
| index = faiss.IndexFlatL2(embedding_size) | |
| vectorstore = FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {}) |