Kye
1 year ago
parent
4097a9b703
commit
9ef126e8cf
@ -1,67 +0,0 @@
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from swarms.models import Anthropic
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from swarms.structs import Agent
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from swarms.tools.tool import tool
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import asyncio
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llm = Anthropic(
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anthropic_api_key="",
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)
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async def async_load_playwright(url: str) -> str:
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"""Load the specified URLs using Playwright and parse using BeautifulSoup."""
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from bs4 import BeautifulSoup
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from playwright.async_api import async_playwright
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results = ""
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async with async_playwright() as p:
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browser = await p.chromium.launch(headless=True)
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try:
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page = await browser.new_page()
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await page.goto(url)
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page_source = await page.content()
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soup = BeautifulSoup(page_source, "html.parser")
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for script in soup(["script", "style"]):
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script.extract()
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text = soup.get_text()
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lines = (line.strip() for line in text.splitlines())
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chunks = (
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phrase.strip()
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for line in lines
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for phrase in line.split(" ")
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)
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results = "\n".join(chunk for chunk in chunks if chunk)
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except Exception as e:
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results = f"Error: {e}"
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await browser.close()
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return results
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def run_async(coro):
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event_loop = asyncio.get_event_loop()
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return event_loop.run_until_complete(coro)
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@tool
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def browse_web_page(url: str) -> str:
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"""Verbose way to scrape a whole webpage. Likely to cause issues parsing."""
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return run_async(async_load_playwright(url))
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## Initialize the workflow
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agent = Agent(
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llm=llm,
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max_loops=5,
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tools=[browse_web_page],
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dashboard=True,
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)
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out = agent.run(
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"Generate a 10,000 word blog on mental clarity and the benefits"
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" of meditation."
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)
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@ -0,0 +1,19 @@
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from swarms.tools.tool import tool
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from swarms.tools.tool_func_doc_scraper import scrape_tool_func_docs
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@tool
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def search_api(query: str) -> str:
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"""Search API
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Args:
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query (str): _description_
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Returns:
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str: _description_
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"""
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print(f"Searching API for {query}")
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tool_docs = scrape_tool_func_docs(search_api)
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print(tool_docs)
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@ -0,0 +1,40 @@
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import os
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from swarms.models import OpenAIChat
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from swarms.structs import Agent
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from swarms.tools.tool import tool
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from dotenv import load_dotenv
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load_dotenv()
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api_key = os.environ.get("OPENAI_API_KEY")
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llm = OpenAIChat(
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api_key=api_key
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)
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# @tool
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# def search_api(query: str) -> str:
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# """Search API
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# Args:
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# query (str): _description_
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# Returns:
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# str: _description_
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# """
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# print(f"Searching API for {query}")
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## Initialize the workflow
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agent = Agent(
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llm=llm,
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max_loops=5,
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# tools=[search_api],
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dashboard=True,
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)
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out = agent.run(
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"Use the search api to find the best restaurants in New York City."
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)
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print(out)
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@ -0,0 +1,47 @@
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import re
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import json
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def extract_tool_commands(self, text: str):
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"""
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Extract the tool commands from the text
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Example:
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```json
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{
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"tool": "tool_name",
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"params": {
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"tool1": "inputs",
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"param2": "value2"
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}
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}
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```
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"""
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# Regex to find JSON like strings
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pattern = r"```json(.+?)```"
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matches = re.findall(pattern, text, re.DOTALL)
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json_commands = []
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for match in matches:
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try:
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json_commands = json.loads(match)
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json_commands.append(json_commands)
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except Exception as error:
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print(f"Error parsing JSON command: {error}")
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def parse_and_execute_tools(response: str):
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"""Parse and execute the tools"""
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json_commands = extract_tool_commands(response)
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for command in json_commands:
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tool_name = command.get("tool")
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params = command.get("parmas", {})
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execute_tools(tool_name, params)
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def execute_tools(self, tool_name, params):
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"""Execute the tool with the provided params"""
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tool = self.tool_find_by_name(tool_name)
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if tool:
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# Execute the tool with the provided parameters
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tool_result = tool.run(**params)
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print(tool_result)
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