import os import warnings from swarms.modelui.modules.block_requests import OpenMonkeyPatch, RequestBlocker from swarms.modelui.modules.logging_colors import logger os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False' os.environ['BITSANDBYTES_NOWELCOME'] = '1' warnings.filterwarnings('ignore', category=UserWarning, message='TypedStorage is deprecated') warnings.filterwarnings('ignore', category=UserWarning, message='Using the update method is deprecated') warnings.filterwarnings('ignore', category=UserWarning, message='Field "model_name" has conflict') with RequestBlocker(): import gradio as gr import matplotlib matplotlib.use('Agg') # This fixes LaTeX rendering on some systems import json import os import sys import time from functools import partial from pathlib import Path from threading import Lock import yaml import swarms.modelui.modules.extensions as extensions_module from swarms.modelui.modules import ( chat, shared, training, ui, ui_chat, ui_default, ui_file_saving, ui_model_menu, ui_notebook, ui_parameters, ui_session, utils ) from swarms.modelui.modules.extensions import apply_extensions from swarms.modelui.modules.LoRA import add_lora_to_model from swarms.modelui.modules.models import load_model from swarms.modelui.modules.models_settings import ( get_fallback_settings, get_model_metadata, update_model_parameters ) from swarms.modelui.modules.utils import gradio import warnings from swarms.modelui.modules.block_requests import OpenMonkeyPatch, RequestBlocker from swarms.modelui.modules.logging_colors import logger os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False' os.environ['BITSANDBYTES_NOWELCOME'] = '1' warnings.filterwarnings('ignore', category=UserWarning, message='TypedStorage is deprecated') warnings.filterwarnings('ignore', category=UserWarning, message='Using the update method is deprecated') warnings.filterwarnings('ignore', category=UserWarning, message='Field "model_name" has conflict') with RequestBlocker(): import gradio as gr import matplotlib matplotlib.use('Agg') # This fixes LaTeX rendering on some systems import json import os import sys import time from functools import partial from pathlib import Path from threading import Lock import yaml import swarms.modelui.modules.extensions as extensions_module from swarms.modelui.modules import ( chat, shared, training, ui, ui_chat, ui_default, ui_file_saving, ui_model_menu, ui_notebook, ui_parameters, ui_session, utils ) from swarms.modelui.modules.extensions import apply_extensions from swarms.modelui.modules.LoRA import add_lora_to_model from swarms.modelui.modules.models import load_model from swarms.modelui.modules.models_settings import ( get_fallback_settings, get_model_metadata, update_model_parameters ) from swarms.modelui.modules.utils import gradio import gradio as gr from swarms.tools.tools_controller import MTQuestionAnswerer, load_valid_tools from swarms.tools.singletool import STQuestionAnswerer from langchain.schema import AgentFinish import os import requests from swarms.modelui.server import create_interface from tool_server import run_tool_server from threading import Thread from multiprocessing import Process import time tool_server_flag = False def start_tool_server(): # server = Thread(target=run_tool_server) server = Process(target=run_tool_server) server.start() global tool_server_flag tool_server_flag = True available_models = ["ChatGPT", "GPT-3.5"] DEFAULTMODEL = "ChatGPT" # "GPT-3.5" tools_mappings = { "klarna": "https://www.klarna.com/", "weather": "http://127.0.0.1:8079/tools/weather/", # "database": "http://127.0.0.1:8079/tools/database/", # "db_diag": "http://127.0.0.1:8079/tools/db_diag/", "chemical-prop": "http://127.0.0.1:8079/tools/chemical-prop/", "douban-film": "http://127.0.0.1:8079/tools/douban-film/", "wikipedia": "http://127.0.0.1:8079/tools/wikipedia/", # "wikidata": "http://127.0.0.1:8079/tools/kg/wikidata/", "wolframalpha": "http://127.0.0.1:8079/tools/wolframalpha/", "bing_search": "http://127.0.0.1:8079/tools/bing_search/", "office-ppt": "http://127.0.0.1:8079/tools/office-ppt/", "stock": "http://127.0.0.1:8079/tools/stock/", "bing_map": "http://127.0.0.1:8079/tools/map.bing_map/", # "baidu_map": "http://127.0.0.1:8079/tools/map/baidu_map/", "zillow": "http://127.0.0.1:8079/tools/zillow/", "airbnb": "http://127.0.0.1:8079/tools/airbnb/", "job_search": "http://127.0.0.1:8079/tools/job_search/", # "baidu-translation": "http://127.0.0.1:8079/tools/translation/baidu-translation/", # "nllb-translation": "http://127.0.0.1:8079/tools/translation/nllb-translation/", "tutorial": "http://127.0.0.1:8079/tools/tutorial/", "file_operation": "http://127.0.0.1:8079/tools/file_operation/", "meta_analysis": "http://127.0.0.1:8079/tools/meta_analysis/", "code_interpreter": "http://127.0.0.1:8079/tools/code_interpreter/", "arxiv": "http://127.0.0.1:8079/tools/arxiv/", "google_places": "http://127.0.0.1:8079/tools/google_places/", "google_serper": "http://127.0.0.1:8079/tools/google_serper/", "google_scholar": "http://127.0.0.1:8079/tools/google_scholar/", "python": "http://127.0.0.1:8079/tools/python/", "sceneXplain": "http://127.0.0.1:8079/tools/sceneXplain/", "shell": "http://127.0.0.1:8079/tools/shell/", "image_generation": "http://127.0.0.1:8079/tools/image_generation/", "hugging_tools": "http://127.0.0.1:8079/tools/hugging_tools/", "gradio_tools": "http://127.0.0.1:8079/tools/gradio_tools/", "travel": "http://127.0.0.1:8079/tools/travel", "walmart": "http://127.0.0.1:8079/tools/walmart", } valid_tools_info = [] all_tools_list = [] gr.close_all() MAX_TURNS = 30 MAX_BOXES = MAX_TURNS * 2 return_msg = [] chat_history = "" MAX_SLEEP_TIME = 40 def load_tools(): global valid_tools_info global all_tools_list try: valid_tools_info = load_valid_tools(tools_mappings) except BaseException as e: print(repr(e)) all_tools_list = sorted(list(valid_tools_info.keys())) return gr.update(choices=all_tools_list) def set_environ(OPENAI_API_KEY: str, WOLFRAMALPH_APP_ID: str = "", WEATHER_API_KEYS: str = "", BING_SUBSCRIPT_KEY: str = "", ALPHA_VANTAGE_KEY: str = "", BING_MAP_KEY: str = "", BAIDU_TRANSLATE_KEY: str = "", RAPIDAPI_KEY: str = "", SERPER_API_KEY: str = "", GPLACES_API_KEY: str = "", SCENEX_API_KEY: str = "", STEAMSHIP_API_KEY: str = "", HUGGINGFACE_API_KEY: str = "", AMADEUS_ID: str = "", AMADEUS_KEY: str = "",): os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY os.environ["WOLFRAMALPH_APP_ID"] = WOLFRAMALPH_APP_ID os.environ["WEATHER_API_KEYS"] = WEATHER_API_KEYS os.environ["BING_SUBSCRIPT_KEY"] = BING_SUBSCRIPT_KEY os.environ["ALPHA_VANTAGE_KEY"] = ALPHA_VANTAGE_KEY os.environ["BING_MAP_KEY"] = BING_MAP_KEY os.environ["BAIDU_TRANSLATE_KEY"] = BAIDU_TRANSLATE_KEY os.environ["RAPIDAPI_KEY"] = RAPIDAPI_KEY os.environ["SERPER_API_KEY"] = SERPER_API_KEY os.environ["GPLACES_API_KEY"] = GPLACES_API_KEY os.environ["SCENEX_API_KEY"] = SCENEX_API_KEY os.environ["STEAMSHIP_API_KEY"] = STEAMSHIP_API_KEY os.environ["HUGGINGFACE_API_KEY"] = HUGGINGFACE_API_KEY os.environ["AMADEUS_ID"] = AMADEUS_ID os.environ["AMADEUS_KEY"] = AMADEUS_KEY if not tool_server_flag: start_tool_server() time.sleep(MAX_SLEEP_TIME) return gr.update(value="OK!") def show_avatar_imgs(tools_chosen): if len(tools_chosen) == 0: tools_chosen = list(valid_tools_info.keys()) img_template = ' avatar {} ' imgs = [valid_tools_info[tool]['avatar'] for tool in tools_chosen if valid_tools_info[tool]['avatar'] != None] imgs = ' '.join([img_template.format(img, img, tool) for img, tool in zip(imgs, tools_chosen)]) return [gr.update(value='' + imgs + '', visible=True), gr.update(visible=True)] def answer_by_tools(question, tools_chosen, model_chosen): global return_msg return_msg += [(question, None), (None, '...')] yield [gr.update(visible=True, value=return_msg), gr.update(), gr.update()] OPENAI_API_KEY = os.environ.get('OPENAI_API_KEY', '') if len(tools_chosen) == 0: # if there is no tools chosen, we use all todo (TODO: What if the pool is too large.) tools_chosen = list(valid_tools_info.keys()) if len(tools_chosen) == 1: answerer = STQuestionAnswerer(OPENAI_API_KEY.strip(), stream_output=True, llm=model_chosen) agent_executor = answerer.load_tools(tools_chosen[0], valid_tools_info[tools_chosen[0]], prompt_type="react-with-tool-description", return_intermediate_steps=True) else: answerer = MTQuestionAnswerer(OPENAI_API_KEY.strip(), load_valid_tools({k: tools_mappings[k] for k in tools_chosen}), stream_output=True, llm=model_chosen) agent_executor = answerer.build_runner() global chat_history chat_history += "Question: " + question + "\n" question = chat_history for inter in agent_executor(question): if isinstance(inter, AgentFinish): continue result_str = [] return_msg.pop() if isinstance(inter, dict): result_str.append("Answer: {}".format(inter['output'])) chat_history += "Answer:" + inter['output'] + "\n" result_str.append("...") else: try: not_observation = inter[0].log except: print(inter[0]) not_observation = inter[0] if not not_observation.startswith('Thought:'): not_observation = "Thought: " + not_observation chat_history += not_observation not_observation = not_observation.replace('Thought:', 'Thought: ') not_observation = not_observation.replace('Action:', 'Action: ') not_observation = not_observation.replace('Action Input:', 'Action Input: ') result_str.append("{}".format(not_observation)) result_str.append("Action output:\n{}".format(inter[1])) chat_history += "\nAction output:" + inter[1] + "\n" result_str.append("...") return_msg += [(None, result) for result in result_str] yield [gr.update(visible=True, value=return_msg), gr.update(), gr.update()] return_msg.pop() if return_msg[-1][1].startswith("Answer: "): return_msg[-1] = (return_msg[-1][0], return_msg[-1][1].replace("Answer: ", "Final Answer: ")) yield [gr.update(visible=True, value=return_msg), gr.update(visible=True), gr.update(visible=False)] def retrieve(tools_search): if tools_search == "": return gr.update(choices=all_tools_list) else: url = "http://127.0.0.1:8079/retrieve" param = { "query": tools_search } response = requests.post(url, json=param) result = response.json() retrieved_tools = result["tools"] return gr.update(choices=retrieved_tools) def clear_retrieve(): return [gr.update(value=""), gr.update(choices=all_tools_list)] def clear_history(): global return_msg global chat_history return_msg = [] chat_history = "" yield gr.update(visible=True, value=return_msg) with gr.Blocks() as demo: with gr.Row(): with gr.Column(scale=14): gr.Markdown("

Swarm Tools

") with gr.Column(scale=1): gr.Image(show_label=False, show_download_button=False, value="images/swarmslogobanner.png") with gr.Tab("Key setting"): OPENAI_API_KEY = gr.Textbox(label="OpenAI API KEY:", placeholder="sk-...", type="text") WOLFRAMALPH_APP_ID = gr.Textbox(label="Wolframalpha app id:", placeholder="Key to use wlframalpha", type="text") WEATHER_API_KEYS = gr.Textbox(label="Weather api key:", placeholder="Key to use weather api", type="text") BING_SUBSCRIPT_KEY = gr.Textbox(label="Bing subscript key:", placeholder="Key to use bing search", type="text") ALPHA_VANTAGE_KEY = gr.Textbox(label="Stock api key:", placeholder="Key to use stock api", type="text") BING_MAP_KEY = gr.Textbox(label="Bing map key:", placeholder="Key to use bing map", type="text") BAIDU_TRANSLATE_KEY = gr.Textbox(label="Baidu translation key:", placeholder="Key to use baidu translation", type="text") RAPIDAPI_KEY = gr.Textbox(label="Rapidapi key:", placeholder="Key to use zillow, airbnb and job search", type="text") SERPER_API_KEY = gr.Textbox(label="Serper key:", placeholder="Key to use google serper and google scholar", type="text") GPLACES_API_KEY = gr.Textbox(label="Google places key:", placeholder="Key to use google places", type="text") SCENEX_API_KEY = gr.Textbox(label="Scenex api key:", placeholder="Key to use sceneXplain", type="text") STEAMSHIP_API_KEY = gr.Textbox(label="Steamship api key:", placeholder="Key to use image generation", type="text") HUGGINGFACE_API_KEY = gr.Textbox(label="Huggingface api key:", placeholder="Key to use models in huggingface hub", type="text") AMADEUS_ID = gr.Textbox(label="Amadeus id:", placeholder="Id to use Amadeus", type="text") AMADEUS_KEY = gr.Textbox(label="Amadeus key:", placeholder="Key to use Amadeus", type="text") key_set_btn = gr.Button(value="Set keys!") with gr.Tab("Chat with Tool"): with gr.Row(): with gr.Column(scale=4): with gr.Row(): with gr.Column(scale=0.85): txt = gr.Textbox(show_label=False, placeholder="Question here. Use Shift+Enter to add new line.", lines=1).style(container=False) with gr.Column(scale=0.15, min_width=0): buttonChat = gr.Button("Chat") chatbot = gr.Chatbot(show_label=False, visible=True).style(height=600) buttonClear = gr.Button("Clear History") buttonStop = gr.Button("Stop", visible=False) with gr.Column(scale=1): model_chosen = gr.Dropdown( list(available_models), value=DEFAULTMODEL, multiselect=False, label="Model provided", info="Choose the model to solve your question, Default means ChatGPT." ) with gr.Row(): tools_search = gr.Textbox( lines=1, label="Tools Search", placeholder="Please input some text to search tools.", ) buttonSearch = gr.Button("Reset search condition") tools_chosen = gr.CheckboxGroup( choices=all_tools_list, value=["chemical-prop"], label="Tools provided", info="Choose the tools to solve your question.", ) with gr.Tab("Models"): create_interface() key_set_btn.click(fn=set_environ, inputs=[ OPENAI_API_KEY, WOLFRAMALPH_APP_ID, WEATHER_API_KEYS, BING_SUBSCRIPT_KEY, ALPHA_VANTAGE_KEY, BING_MAP_KEY, BAIDU_TRANSLATE_KEY, RAPIDAPI_KEY, SERPER_API_KEY, GPLACES_API_KEY, SCENEX_API_KEY, STEAMSHIP_API_KEY, HUGGINGFACE_API_KEY, AMADEUS_ID, AMADEUS_KEY, ], outputs=key_set_btn) key_set_btn.click(fn=load_tools, outputs=tools_chosen) tools_search.change(retrieve, tools_search, tools_chosen) buttonSearch.click(clear_retrieve, [], [tools_search, tools_chosen]) txt.submit(lambda: [gr.update(value=''), gr.update(visible=False), gr.update(visible=True)], [], [txt, buttonClear, buttonStop]) inference_event = txt.submit(answer_by_tools, [txt, tools_chosen, model_chosen], [chatbot, buttonClear, buttonStop]) buttonChat.click(answer_by_tools, [txt, tools_chosen, model_chosen], [chatbot, buttonClear, buttonStop]) buttonStop.click(lambda: [gr.update(visible=True), gr.update(visible=False)], [], [buttonClear, buttonStop], cancels=[inference_event]) buttonClear.click(clear_history, [], chatbot) # demo.queue().launch(share=False, inbrowser=True, server_name="127.0.0.1", server_port=7001) demo.queue().launch()