import gradio as gr from BMTools.bmtools.agent.tools_controller import MTQuestionAnswerer, load_valid_tools from BMTools.bmtools.agent.singletool import STQuestionAnswerer from langchain.schema import AgentFinish import os import requests 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/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/bing_map/", # "baidu_map": "http://127.0.0.1:8079/tools/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/baidu-translation/", # "nllb-translation": "http://127.0.0.1:8079/tools/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/", } valid_tools_info = [] all_tools_list = [] gr.close_all() MAX_TURNS = 30 MAX_BOXES = MAX_TURNS * 2 return_msg = [] chat_history = "" MAX_SLEEP_TIME = 60 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 = "",): 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 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: not_observation = inter[0].log 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("

BMTools

") with gr.Column(scale=1): gr.Markdown('') 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") 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.", ) 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, ], 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)