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swarms
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clean up

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Kye 2 years ago
parent f091cc462e
commit 760a74792c
1 changed files with 39 additions and 105 deletions
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swarms/swarms.py
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@ -1,106 +1,61 @@
# ---------- Dependencies ----------
import os
import asyncio
import faiss
from typing import Optional
from contextlib import contextmanager
from collections import deque
from typing import Dict, List, Optional, Any
from langchain import LLMChain, OpenAI, PromptTemplate
from langchain.embeddings import OpenAIEmbeddings
from langchain.llms import BaseLLM
from langchain.vectorstores.base import VectorStore
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 import OpenAI, SerpAPIWrapper, LLMChain
import faiss
#-------------------------------------------------------------------------- WORKER NODE
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
import os
from contextlib import contextmanager
from typing import Optional
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
ROOT_DIR = "./data/"
from langchain.tools import BaseTool, DuckDuckGoSearchRun
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.chains.qa_with_sources.loading import load_qa_with_sources_chain, BaseCombineDocumentsChain
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
# ---------- 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)
query_website_tool = WebpageQATool(qa_chain=load_qa_with_sources_chain(llm))
# !pip install duckduckgo_search
web_search = DuckDuckGoSearchRun()
tools = [
Tool(name='web_search', func=web_search, description='Runs a web search'),
Tool(name='write_file_tool', func=WriteFileTool(root_dir="./data"), description='Writes a file'),
Tool(name='read_file_tool', func=ReadFileTool(root_dir="./data"), description='Reads a file'),
Tool(name='web_search', func=DuckDuckGoSearchRun(), description='Runs a web search'),
Tool(name='write_file_tool', func=WriteFileTool(root_dir=ROOT_DIR), description='Writes a file'),
Tool(name='read_file_tool', func=ReadFileTool(root_dir=ROOT_DIR), description='Reads a file'),
Tool(name='process_csv', func=process_csv, description='Processes a CSV file'),
Tool(name='query_website_tool', func=query_website_tool, description='Queries a website'),
Tool(name='query_website_tool', func=WebpageQATool(qa_chain=load_qa_with_sources_chain(llm)), description='Queries a website'),
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'),
# Add any additional tools here...
Tool(name='code_writer', func=CodeWriter(), description='Writes code'),
Tool(name='code_editor', func=CodeEditor(), description='Edits code'),
]
############## Vectorstore
# ---------- Vector Store ----------
embeddings_model = OpenAIEmbeddings()
embedding_size = 1536
index = faiss.IndexFlatL2(embedding_size)
vectorstore = FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
####################################################################### => Worker Node
# worker_agent = 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, # Set to True if you want to add feedback at each step.
# )
# worker_agent.chain.verbose = True
# ---------- Worker Node ----------
class WorkerNode:
def __init__(self, llm, tools, vectorstore):
self.llm = llm
self.tools = tools
self.vectorstore = vectorstore
def create_agent(self, ai_name, ai_role, human_in_the_loop, search_kwargs):
# Instantiate the agent
self.agent = AutoGPT.from_llm_and_tools(
ai_name=ai_name,
ai_role=ai_role,
@ -111,22 +66,19 @@ class WorkerNode:
)
self.agent.chain.verbose = True
def run_agent```python
def run_agent(self, prompt):
# Run the agent with the given prompt
tree_of_thoughts_prompt = """
Imagine three different experts are answering this question. All experts will write down each chain of thought of each step of their thinking, then share it with the group. Then all experts will go on to the next step, etc. If any expert realises they're wrong at any point then they leave. The question is...
"""
self.agent.run([f"{tree_of_thoughts_prompt} {prompt}"])
# #inti worker node with llm
worker_node = WorkerNode(llm=llm, tools=tools, vectorstore=vectorstore)
# ---------- Boss Node ----------
class BossNode:
def __init__(self, openai_api_key, llm, vectorstore, task_execution_chain, verbose, max_iterations):
def __init__(self, llm, vectorstore, task_execution_chain, verbose, max_iterations):
self.llm = llm
self.openai_api_key = openai_api_key
self.vectorstore = vectorstore
self.task_execution_chain = task_execution_chain
self.verbose = verbose
@ -144,19 +96,13 @@ class BossNode:
def execute_task(self, task):
self.baby_agi(task)
########### ===============> inputs to boss None
# ---------- Inputs to Boss Node ----------
todo_prompt = PromptTemplate.from_template(
"You are a planner who is an expert at coming up with a todo list for a given objective. Come up with a todo list for this objective: {objective}"""
)
todo_chain = LLMChain(llm=OpenAI(temperature=0), prompt=todo_prompt)
# search = SerpAPIWrapper()
tools = [
# Tool(
# name="Search",
# func=search.run,
# description="useful for when you need to answer questions about current events",
# ),
tools += [
Tool(
name="TODO",
func=todo_chain.run,
@ -169,14 +115,11 @@ tools = [
)
]
suffix = """Question: {task}
{agent_scratchpad}"""
prefix = """You are an Boss in a swarm who performs one task based on the following objective: {objective}. Take into account these previously completed tasks: {context}.
"""
prompt = ZeroShotAgent.create_prompt(
tools,
prefix=prefix,
@ -189,9 +132,7 @@ llm_chain = LLMChain(llm=llm, prompt=prompt)
tool_names = [tool.name for tool in tools]
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names)
agent_executor = AgentExecutor.from_agent_and_tools(
agent=agent, tools=tools, verbose=True
)
agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
# boss_node = BossNode(llm=llm, vectorstore=vectorstore, task_execution_chain=agent_executor, verbose=True, max_iterations=5)
@ -209,22 +150,15 @@ class Swarms:
def initialize_tools(self, llm):
web_search = DuckDuckGoSearchRun()
# tools = [web_search, WriteFileTool(root_dir="./data"), ReadFileTool(root_dir="./data"), process_csv,
# # multimodal_agent_tool,
# WebpageQATool(qa_chain=load_qa_with_sources_chain(llm)),
# Terminal, CodeWriter, CodeEditor,
# # math_tool
# ]
tools = [
Tool(name='web_search', func=web_search, description='Runs a web search'),
Tool(name='write_file_tool', func=WriteFileTool(root_dir="./data"), description='Writes a file'),
Tool(name='read_file_tool', func=ReadFileTool(root_dir="./data"), description='Reads a file'),
Tool(name='web_search', func=DuckDuckGoSearchRun(), description='Runs a web search'),
Tool(name='write_file_tool', func=WriteFileTool(root_dir=ROOT_DIR), description='Writes a file'),
Tool(name='read_file_tool', func=ReadFileTool(root_dir=ROOT_DIR), description='Reads a file'),
Tool(name='process_csv', func=process_csv, description='Processes a CSV file'),
Tool(name='query_website_tool', func=query_website_tool, description='Queries a website'),
Tool(name='query_website_tool', func=WebpageQATool(qa_chain=load_qa_with_sources_chain(llm)), description='Queries a website'),
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'),
# Add any additional tools here...
Tool(name='code_writer', func=CodeWriter(), description='Writes code'),
Tool(name='code_editor', func=CodeEditor(), description='Edits code'),
]
return tools

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