Zack
1 year ago
parent
f6baddecd3
commit
ffd2643095
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import gradio as gr
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from swarms.tools.tools_controller import MTQuestionAnswerer, load_valid_tools
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from swarms.tools.singletool import STQuestionAnswerer
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from langchain.schema import AgentFinish
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import os
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import requests
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from tool_server import run_tool_server
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from threading import Thread
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from multiprocessing import Process
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import time
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tool_server_flag = False
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def start_tool_server():
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# server = Thread(target=run_tool_server)
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server = Process(target=run_tool_server)
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server.start()
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global tool_server_flag
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tool_server_flag = True
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available_models = ["ChatGPT", "GPT-3.5"]
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DEFAULTMODEL = "ChatGPT" # "GPT-3.5"
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tools_mappings = {
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"klarna": "https://www.klarna.com/",
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"weather": "http://127.0.0.1:8079/tools/weather/",
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# "database": "http://127.0.0.1:8079/tools/database/",
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# "db_diag": "http://127.0.0.1:8079/tools/db_diag/",
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"chemical-prop": "http://127.0.0.1:8079/tools/chemical-prop/",
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"douban-film": "http://127.0.0.1:8079/tools/douban-film/",
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"wikipedia": "http://127.0.0.1:8079/tools/wikipedia/",
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# "wikidata": "http://127.0.0.1:8079/tools/kg/wikidata/",
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"wolframalpha": "http://127.0.0.1:8079/tools/wolframalpha/",
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"bing_search": "http://127.0.0.1:8079/tools/bing_search/",
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"office-ppt": "http://127.0.0.1:8079/tools/office-ppt/",
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"stock": "http://127.0.0.1:8079/tools/stock/",
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"bing_map": "http://127.0.0.1:8079/tools/map.bing_map/",
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# "baidu_map": "http://127.0.0.1:8079/tools/map/baidu_map/",
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"zillow": "http://127.0.0.1:8079/tools/zillow/",
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"airbnb": "http://127.0.0.1:8079/tools/airbnb/",
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"job_search": "http://127.0.0.1:8079/tools/job_search/",
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# "baidu-translation": "http://127.0.0.1:8079/tools/translation/baidu-translation/",
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# "nllb-translation": "http://127.0.0.1:8079/tools/translation/nllb-translation/",
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"tutorial": "http://127.0.0.1:8079/tools/tutorial/",
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"file_operation": "http://127.0.0.1:8079/tools/file_operation/",
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"meta_analysis": "http://127.0.0.1:8079/tools/meta_analysis/",
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"code_interpreter": "http://127.0.0.1:8079/tools/code_interpreter/",
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"arxiv": "http://127.0.0.1:8079/tools/arxiv/",
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"google_places": "http://127.0.0.1:8079/tools/google_places/",
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"google_serper": "http://127.0.0.1:8079/tools/google_serper/",
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"google_scholar": "http://127.0.0.1:8079/tools/google_scholar/",
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"python": "http://127.0.0.1:8079/tools/python/",
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"sceneXplain": "http://127.0.0.1:8079/tools/sceneXplain/",
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"shell": "http://127.0.0.1:8079/tools/shell/",
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"image_generation": "http://127.0.0.1:8079/tools/image_generation/",
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"hugging_tools": "http://127.0.0.1:8079/tools/hugging_tools/",
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"gradio_tools": "http://127.0.0.1:8079/tools/gradio_tools/",
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"travel": "http://127.0.0.1:8079/tools/travel",
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"walmart": "http://127.0.0.1:8079/tools/walmart",
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}
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valid_tools_info = []
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all_tools_list = []
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gr.close_all()
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MAX_TURNS = 30
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MAX_BOXES = MAX_TURNS * 2
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return_msg = []
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chat_history = ""
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MAX_SLEEP_TIME = 40
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def load_tools():
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global valid_tools_info
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global all_tools_list
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try:
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valid_tools_info = load_valid_tools(tools_mappings)
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except BaseException as e:
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print(repr(e))
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all_tools_list = sorted(list(valid_tools_info.keys()))
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return gr.update(choices=all_tools_list)
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def set_environ(OPENAI_API_KEY: str,
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WOLFRAMALPH_APP_ID: str = "",
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WEATHER_API_KEYS: str = "",
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BING_SUBSCRIPT_KEY: str = "",
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ALPHA_VANTAGE_KEY: str = "",
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BING_MAP_KEY: str = "",
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BAIDU_TRANSLATE_KEY: str = "",
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RAPIDAPI_KEY: str = "",
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SERPER_API_KEY: str = "",
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GPLACES_API_KEY: str = "",
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SCENEX_API_KEY: str = "",
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STEAMSHIP_API_KEY: str = "",
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HUGGINGFACE_API_KEY: str = "",
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AMADEUS_ID: str = "",
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AMADEUS_KEY: str = "",):
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os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
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os.environ["WOLFRAMALPH_APP_ID"] = WOLFRAMALPH_APP_ID
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os.environ["WEATHER_API_KEYS"] = WEATHER_API_KEYS
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os.environ["BING_SUBSCRIPT_KEY"] = BING_SUBSCRIPT_KEY
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os.environ["ALPHA_VANTAGE_KEY"] = ALPHA_VANTAGE_KEY
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os.environ["BING_MAP_KEY"] = BING_MAP_KEY
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os.environ["BAIDU_TRANSLATE_KEY"] = BAIDU_TRANSLATE_KEY
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os.environ["RAPIDAPI_KEY"] = RAPIDAPI_KEY
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os.environ["SERPER_API_KEY"] = SERPER_API_KEY
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os.environ["GPLACES_API_KEY"] = GPLACES_API_KEY
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os.environ["SCENEX_API_KEY"] = SCENEX_API_KEY
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os.environ["STEAMSHIP_API_KEY"] = STEAMSHIP_API_KEY
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os.environ["HUGGINGFACE_API_KEY"] = HUGGINGFACE_API_KEY
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os.environ["AMADEUS_ID"] = AMADEUS_ID
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os.environ["AMADEUS_KEY"] = AMADEUS_KEY
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if not tool_server_flag:
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start_tool_server()
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time.sleep(MAX_SLEEP_TIME)
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return gr.update(value="OK!")
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def show_avatar_imgs(tools_chosen):
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if len(tools_chosen) == 0:
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tools_chosen = list(valid_tools_info.keys())
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img_template = '<a href="{}" style="float: left"> <img style="margin:5px" src="{}.png" width="24" height="24" alt="avatar" /> {} </a>'
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imgs = [valid_tools_info[tool]['avatar'] for tool in tools_chosen if valid_tools_info[tool]['avatar'] != None]
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imgs = ' '.join([img_template.format(img, img, tool) for img, tool in zip(imgs, tools_chosen)])
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return [gr.update(value='<span class="">' + imgs + '</span>', visible=True), gr.update(visible=True)]
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def answer_by_tools(question, tools_chosen, model_chosen):
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global return_msg
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return_msg += [(question, None), (None, '...')]
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yield [gr.update(visible=True, value=return_msg), gr.update(), gr.update()]
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OPENAI_API_KEY = os.environ.get('OPENAI_API_KEY', '')
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if len(tools_chosen) == 0: # if there is no tools chosen, we use all todo (TODO: What if the pool is too large.)
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tools_chosen = list(valid_tools_info.keys())
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if len(tools_chosen) == 1:
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answerer = STQuestionAnswerer(OPENAI_API_KEY.strip(), stream_output=True, llm=model_chosen)
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agent_executor = answerer.load_tools(tools_chosen[0], valid_tools_info[tools_chosen[0]],
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prompt_type="react-with-tool-description", return_intermediate_steps=True)
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else:
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answerer = MTQuestionAnswerer(OPENAI_API_KEY.strip(),
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load_valid_tools({k: tools_mappings[k] for k in tools_chosen}),
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stream_output=True, llm=model_chosen)
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agent_executor = answerer.build_runner()
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global chat_history
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chat_history += "Question: " + question + "\n"
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question = chat_history
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for inter in agent_executor(question):
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if isinstance(inter, AgentFinish): continue
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result_str = []
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return_msg.pop()
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if isinstance(inter, dict):
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result_str.append("<font color=red>Answer:</font> {}".format(inter['output']))
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chat_history += "Answer:" + inter['output'] + "\n"
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result_str.append("...")
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else:
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try:
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not_observation = inter[0].log
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except:
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print(inter[0])
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not_observation = inter[0]
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if not not_observation.startswith('Thought:'):
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not_observation = "Thought: " + not_observation
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chat_history += not_observation
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not_observation = not_observation.replace('Thought:', '<font color=green>Thought: </font>')
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not_observation = not_observation.replace('Action:', '<font color=purple>Action: </font>')
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not_observation = not_observation.replace('Action Input:', '<font color=purple>Action Input: </font>')
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result_str.append("{}".format(not_observation))
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result_str.append("<font color=blue>Action output:</font>\n{}".format(inter[1]))
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chat_history += "\nAction output:" + inter[1] + "\n"
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result_str.append("...")
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return_msg += [(None, result) for result in result_str]
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yield [gr.update(visible=True, value=return_msg), gr.update(), gr.update()]
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return_msg.pop()
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if return_msg[-1][1].startswith("<font color=red>Answer:</font> "):
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return_msg[-1] = (return_msg[-1][0], return_msg[-1][1].replace("<font color=red>Answer:</font> ",
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"<font color=green>Final Answer:</font> "))
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yield [gr.update(visible=True, value=return_msg), gr.update(visible=True), gr.update(visible=False)]
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def retrieve(tools_search):
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if tools_search == "":
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return gr.update(choices=all_tools_list)
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else:
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url = "http://127.0.0.1:8079/retrieve"
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param = {
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"query": tools_search
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}
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response = requests.post(url, json=param)
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result = response.json()
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retrieved_tools = result["tools"]
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return gr.update(choices=retrieved_tools)
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def clear_retrieve():
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return [gr.update(value=""), gr.update(choices=all_tools_list)]
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def clear_history():
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global return_msg
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global chat_history
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return_msg = []
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chat_history = ""
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yield gr.update(visible=True, value=return_msg)
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column(scale=14):
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gr.Markdown("<h1 align='left'> Swarm Tools </h1>")
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with gr.Column(scale=1):
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gr.Image(show_label=False, show_download_button=False, value="images/swarmslogobanner.png")
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with gr.Tab("Key setting"):
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OPENAI_API_KEY = gr.Textbox(label="OpenAI API KEY:", placeholder="sk-...", type="text")
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WOLFRAMALPH_APP_ID = gr.Textbox(label="Wolframalpha app id:", placeholder="Key to use wlframalpha", type="text")
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WEATHER_API_KEYS = gr.Textbox(label="Weather api key:", placeholder="Key to use weather api", type="text")
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BING_SUBSCRIPT_KEY = gr.Textbox(label="Bing subscript key:", placeholder="Key to use bing search", type="text")
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ALPHA_VANTAGE_KEY = gr.Textbox(label="Stock api key:", placeholder="Key to use stock api", type="text")
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BING_MAP_KEY = gr.Textbox(label="Bing map key:", placeholder="Key to use bing map", type="text")
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BAIDU_TRANSLATE_KEY = gr.Textbox(label="Baidu translation key:", placeholder="Key to use baidu translation", type="text")
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RAPIDAPI_KEY = gr.Textbox(label="Rapidapi key:", placeholder="Key to use zillow, airbnb and job search", type="text")
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SERPER_API_KEY = gr.Textbox(label="Serper key:", placeholder="Key to use google serper and google scholar", type="text")
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GPLACES_API_KEY = gr.Textbox(label="Google places key:", placeholder="Key to use google places", type="text")
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SCENEX_API_KEY = gr.Textbox(label="Scenex api key:", placeholder="Key to use sceneXplain", type="text")
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STEAMSHIP_API_KEY = gr.Textbox(label="Steamship api key:", placeholder="Key to use image generation", type="text")
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HUGGINGFACE_API_KEY = gr.Textbox(label="Huggingface api key:", placeholder="Key to use models in huggingface hub", type="text")
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AMADEUS_ID = gr.Textbox(label="Amadeus id:", placeholder="Id to use Amadeus", type="text")
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AMADEUS_KEY = gr.Textbox(label="Amadeus key:", placeholder="Key to use Amadeus", type="text")
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key_set_btn = gr.Button(value="Set keys!")
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with gr.Tab("Chat with Tool"):
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with gr.Row():
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with gr.Column(scale=4):
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with gr.Row():
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with gr.Column(scale=0.85):
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txt = gr.Textbox(show_label=False, placeholder="Question here. Use Shift+Enter to add new line.",
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lines=1).style(container=False)
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with gr.Column(scale=0.15, min_width=0):
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buttonChat = gr.Button("Chat")
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chatbot = gr.Chatbot(show_label=False, visible=True).style(height=600)
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buttonClear = gr.Button("Clear History")
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buttonStop = gr.Button("Stop", visible=False)
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with gr.Column(scale=1):
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model_chosen = gr.Dropdown(
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list(available_models), value=DEFAULTMODEL, multiselect=False, label="Model provided",
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info="Choose the model to solve your question, Default means ChatGPT."
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)
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with gr.Row():
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tools_search = gr.Textbox(
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lines=1,
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label="Tools Search",
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placeholder="Please input some text to search tools.",
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)
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buttonSearch = gr.Button("Reset search condition")
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tools_chosen = gr.CheckboxGroup(
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choices=all_tools_list,
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value=["chemical-prop"],
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label="Tools provided",
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info="Choose the tools to solve your question.",
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)
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key_set_btn.click(fn=set_environ, inputs=[
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OPENAI_API_KEY,
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WOLFRAMALPH_APP_ID,
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WEATHER_API_KEYS,
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BING_SUBSCRIPT_KEY,
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ALPHA_VANTAGE_KEY,
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BING_MAP_KEY,
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BAIDU_TRANSLATE_KEY,
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RAPIDAPI_KEY,
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SERPER_API_KEY,
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GPLACES_API_KEY,
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SCENEX_API_KEY,
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STEAMSHIP_API_KEY,
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HUGGINGFACE_API_KEY,
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AMADEUS_ID,
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AMADEUS_KEY,
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], outputs=key_set_btn)
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key_set_btn.click(fn=load_tools, outputs=tools_chosen)
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tools_search.change(retrieve, tools_search, tools_chosen)
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buttonSearch.click(clear_retrieve, [], [tools_search, tools_chosen])
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txt.submit(lambda: [gr.update(value=''), gr.update(visible=False), gr.update(visible=True)], [],
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[txt, buttonClear, buttonStop])
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inference_event = txt.submit(answer_by_tools, [txt, tools_chosen, model_chosen], [chatbot, buttonClear, buttonStop])
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buttonChat.click(answer_by_tools, [txt, tools_chosen, model_chosen], [chatbot, buttonClear, buttonStop])
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buttonStop.click(lambda: [gr.update(visible=True), gr.update(visible=False)], [], [buttonClear, buttonStop],
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cancels=[inference_event])
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buttonClear.click(clear_history, [], chatbot)
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# demo.queue().launch(share=False, inbrowser=True, server_name="127.0.0.1", server_port=7001)
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demo.queue().launch()
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@ -1,185 +0,0 @@
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import gradio as gr
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from swarms.tools.tools_controller import MTQuestionAnswerer, load_valid_tools
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from swarms.tools.singletool import STQuestionAnswerer
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from langchain.schema import AgentFinish
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import os
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import requests
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available_models = ["ChatGPT", "GPT-3.5"]
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DEFAULTMODEL = "ChatGPT" # "GPT-3.5"
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tools_mappings = {
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"klarna": "https://www.klarna.com/",
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"weather": "http://127.0.0.1:8079/tools/weather/",
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# "database": "http://127.0.0.1:8079/tools/database/",
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# "db_diag": "http://127.0.0.1:8079/tools/db_diag/",
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"chemical-prop": "http://127.0.0.1:8079/tools/chemical-prop/",
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"douban-film": "http://127.0.0.1:8079/tools/douban-film/",
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"wikipedia": "http://127.0.0.1:8079/tools/wikipedia/",
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# "wikidata": "http://127.0.0.1:8079/tools/wikidata/",
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"wolframalpha": "http://127.0.0.1:8079/tools/wolframalpha/",
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"bing_search": "http://127.0.0.1:8079/tools/bing_search/",
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"office-ppt": "http://127.0.0.1:8079/tools/office-ppt/",
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"stock": "http://127.0.0.1:8079/tools/stock/",
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"bing_map": "http://127.0.0.1:8079/tools/bing_map/",
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# "baidu_map": "http://127.0.0.1:8079/tools/baidu_map/",
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"zillow": "http://127.0.0.1:8079/tools/zillow/",
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"airbnb": "http://127.0.0.1:8079/tools/airbnb/",
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"job_search": "http://127.0.0.1:8079/tools/job_search/",
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# "baidu-translation": "http://127.0.0.1:8079/tools/baidu-translation/",
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# "nllb-translation": "http://127.0.0.1:8079/tools/nllb-translation/",
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"tutorial": "http://127.0.0.1:8079/tools/tutorial/",
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"file_operation": "http://127.0.0.1:8079/tools/file_operation/",
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"meta_analysis": "http://127.0.0.1:8079/tools/meta_analysis/",
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"code_interpreter": "http://127.0.0.1:8079/tools/code_interpreter/",
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"arxiv": "http://127.0.0.1:8079/tools/arxiv/",
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"google_places": "http://127.0.0.1:8079/tools/google_places/",
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"google_serper": "http://127.0.0.1:8079/tools/google_serper/",
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"google_scholar": "http://127.0.0.1:8079/tools/google_scholar/",
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"python": "http://127.0.0.1:8079/tools/python/",
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"sceneXplain": "http://127.0.0.1:8079/tools/sceneXplain/",
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"shell": "http://127.0.0.1:8079/tools/shell/",
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"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 = load_valid_tools(tools_mappings)
|
||||
print(valid_tools_info)
|
||||
all_tools_list = sorted(list(valid_tools_info.keys()))
|
||||
|
||||
gr.close_all()
|
||||
|
||||
MAX_TURNS = 30
|
||||
MAX_BOXES = MAX_TURNS * 2
|
||||
|
||||
return_msg = []
|
||||
chat_history = ""
|
||||
|
||||
def show_avatar_imgs(tools_chosen):
|
||||
if len(tools_chosen) == 0:
|
||||
tools_chosen = list(valid_tools_info.keys())
|
||||
img_template = '<a href="{}" style="float: left"> <img style="margin:5px" src="{}.png" width="24" height="24" alt="avatar" /> {} </a>'
|
||||
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='<span class="">'+imgs+'</span>', 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"
|
||||
print(chat_history)
|
||||
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("<font color=red>Answer:</font> {}".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:', '<font color=green>Thought: </font>')
|
||||
not_observation = not_observation.replace('Action:', '<font color=purple>Action: </font>')
|
||||
not_observation = not_observation.replace('Action Input:', '<font color=purple>Action Input: </font>')
|
||||
result_str.append("{}".format(not_observation))
|
||||
result_str.append("<font color=blue>Action output:</font>\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("<font color=red>Answer:</font> "):
|
||||
return_msg[-1] = (return_msg[-1][0], return_msg[-1][1].replace("<font color=red>Answer:</font> ", "<font color=green>Final Answer:</font> "))
|
||||
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("<h1 align='left'> Swarm Tools </h1>")
|
||||
with gr.Column(scale=1):
|
||||
gr.Image('images/swarmslogobanner.png', show_download_button=False, show_label=False )
|
||||
# gr.Markdown('<img src="../../images/swarmslogobanner.png" alt="swarms">')
|
||||
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.",
|
||||
)
|
||||
|
||||
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)
|
||||
Loading…
Reference in new issue