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bc55efe
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Parent(s):
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app.py
CHANGED
@@ -7,8 +7,12 @@ import os
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CSS ="""
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.contain { display: flex; flex-direction: column; }
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.gradio-container { height: 100vh !important; }
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#chatbot { flex-grow: 1; overflow: auto;}
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footer {visibility: hidden}
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"""
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openAIToken = os.environ['openAIToken']
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@@ -63,30 +67,51 @@ def create_suggestions_list(suggestions):
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update_hide = [gr.update(visible=False, value="") for _ in range(6-len(suggestions))]
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return update_show + update_hide
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def process_text_chunk(text,
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print(text, end="", flush=True)
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local_message = None
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if "[" in text:
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is_loading_suggestions = True
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if is_loading_suggestions != True:
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-
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else:
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is_loading_suggestions = False
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list_of_suggestions, local_message = transform_suggestions_into_list(string_of_suggestions)
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string_of_suggestions = ""
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elif "]" in string_of_suggestions and "]#" not in string_of_suggestions and not string_of_suggestions.endswith("]"):
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is_loading_suggestions = False
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local_message = string_of_suggestions
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string_of_suggestions = ""
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return local_message, list_of_suggestions, string_of_suggestions, is_loading_suggestions
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def handle_events(threadId, chat_history, storage):
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try:
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with client.beta.threads.runs.stream(
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thread_id=threadId,
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@@ -95,10 +120,10 @@ def handle_events(threadId, chat_history, storage):
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for event in stream:
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if event.event == "thread.message.delta" and event.data.delta.content:
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text = event.data.delta.content[0].text.value
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local_message,
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if local_message is not None:
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chat_history[-1][1] += local_message
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yield [ chat_history, storage]
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if event.event == 'thread.run.requires_action':
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result = handle_requires_action(event.data)
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tool_outputs = [x["tool_output"] for x in result]
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@@ -108,19 +133,18 @@ def handle_events(threadId, chat_history, storage):
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tool_outputs=tool_outputs,
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) as action_stream:
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for text in action_stream.text_deltas:
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local_message,
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if local_message is not None:
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chat_history[-1][1] += local_message
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yield [chat_history, storage]
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action_stream.close()
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stream.until_done()
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print("")
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storage["
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return [chat_history, storage]
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except Exception as e:
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print(e)
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chat_history[-1][1] = "Error occured during processing your message. Please try again"
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yield [chat_history, storage]
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def initiate_chatting(chat_history, storage):
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threadId = storage["threadId"]
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@@ -140,8 +164,12 @@ def respond_on_user_msg(chat_history, storage):
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def create_application():
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with gr.Blocks(css=CSS, fill_height=True) as demo:
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storage = gr.State({})
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btn_list = []
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with gr.Row():
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for i in range(6):
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@@ -169,7 +197,7 @@ def create_application():
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return message_box
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add_user_message_flow = [user, [msg,chatbot], [msg,chatbot]]
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chat_response_flow = [respond_on_user_msg, [chatbot, storage], [chatbot, storage]]
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update_suggestions_flow = [update_suggestions, storage, btn_list]
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hide_suggestions_flow = [hide_suggestions, None, btn_list]
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disable_msg_flow = [disable_msg, None, msg]
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@@ -191,7 +219,7 @@ def create_application():
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).then(*enable_msg_flow)
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demo.load(create_thread_openai, inputs=storage, outputs=storage
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).then(initiate_chatting, inputs=[chatbot, storage], outputs=[chatbot, storage]
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).then(*update_suggestions_flow
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).then(*enable_msg_flow)
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return demo
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CSS ="""
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.contain { display: flex; flex-direction: column; }
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.gradio-container { height: 100vh !important; }
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.svelte-vt1mxs div:first-child { flex-grow: 1; overflow: auto;}
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#chatbot { flex-grow: 1; overflow: auto;}
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footer {visibility: hidden}
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.app.svelte-182fdeq.svelte-182fdeq {
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max-width: 100vw !important;
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}
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"""
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openAIToken = os.environ['openAIToken']
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update_hide = [gr.update(visible=False, value="") for _ in range(6-len(suggestions))]
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return update_show + update_hide
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def process_text_chunk(text, storage):
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print(text, end="", flush=True)
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local_message = None
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if "[" in text:
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storage["is_loading_suggestions"] = True
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if "#" in text and storage["is_loading_suggestions"] != True:
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storage["is_loading_markup"] = True
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if storage["is_loading_suggestions"] == True or storage["is_loading_markup"] == True:
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accumulative_string = storage["accumulative_string"] + text
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if storage["is_loading_suggestions"] == True:
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if "#s#" in accumulative_string:
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storage["is_loading_suggestions"] = False
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list_of_suggestions, local_message = transform_suggestions_into_list(accumulative_string)
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storage["list_of_suggestions"] = list_of_suggestions
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accumulative_string = ""
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elif "]" in accumulative_string and "]#" not in accumulative_string and not accumulative_string.endswith("]"):
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storage["is_loading_suggestions"] = False
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local_message = accumulative_string
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accumulative_string = ""
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else:
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if "#p#" in accumulative_string:
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parts = accumulative_string.split("#p#")
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local_message = parts[0]
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accumulative_string = "#p#" + parts[1]
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storage["markup_string"] = accumulative_string[3:]
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elif "#" in accumulative_string and "#p" not in accumulative_string and not accumulative_string.endswith("#"):
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storage["markup_string"] = accumulative_string[4:]
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storage["is_loading_markup"] = False
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local_message = accumulative_string
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accumulative_string = ""
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storage["accumulative_string"] = accumulative_string
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else:
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local_message = text
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return local_message, storage
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def handle_events(threadId, chat_history, storage):
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storage.update({
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"list_of_suggestions" : [],
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"is_loading_suggestions" : False,
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"is_loading_markup" : False,
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"accumulative_string" : "",
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"markup_string": ""
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})
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try:
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with client.beta.threads.runs.stream(
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thread_id=threadId,
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for event in stream:
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if event.event == "thread.message.delta" and event.data.delta.content:
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text = event.data.delta.content[0].text.value
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local_message, storage = process_text_chunk(text, storage)
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if local_message is not None:
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chat_history[-1][1] += local_message
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yield [ chat_history, storage, storage["markup_string"]]
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if event.event == 'thread.run.requires_action':
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result = handle_requires_action(event.data)
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tool_outputs = [x["tool_output"] for x in result]
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tool_outputs=tool_outputs,
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) as action_stream:
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for text in action_stream.text_deltas:
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local_message, storage = process_text_chunk(text, storage)
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if local_message is not None:
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chat_history[-1][1] += local_message
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yield [chat_history, storage, storage["markup_string"]]
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action_stream.close()
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stream.until_done()
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print("")
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return [chat_history, storage, storage["markup_string"]]
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except Exception as e:
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print(e)
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chat_history[-1][1] = "Error occured during processing your message. Please try again"
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yield [chat_history, storage, storage["markup_string"]]
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def initiate_chatting(chat_history, storage):
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threadId = storage["threadId"]
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def create_application():
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with gr.Blocks(css=CSS, fill_height=True) as demo:
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storage = gr.State({"list_of_suggestions": [], "is_loading_suggestions": False, "is_loading_markup": False, "accumulative_string": "", "markup_string": ""})
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with gr.Row():
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with gr.Column(scale=4):
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chatbot = gr.Chatbot(label="Facility managment bot", line_breaks=False, height=300, show_label=False, show_share_button=False, elem_id="chatbot")
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with gr.Column(scale=1):
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markdown = gr.Markdown(label="Bullet-list", value="# Facility information")
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btn_list = []
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with gr.Row():
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for i in range(6):
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return message_box
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add_user_message_flow = [user, [msg,chatbot], [msg,chatbot]]
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chat_response_flow = [respond_on_user_msg, [chatbot, storage], [chatbot, storage, markdown]]
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update_suggestions_flow = [update_suggestions, storage, btn_list]
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hide_suggestions_flow = [hide_suggestions, None, btn_list]
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disable_msg_flow = [disable_msg, None, msg]
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).then(*enable_msg_flow)
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demo.load(create_thread_openai, inputs=storage, outputs=storage
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).then(initiate_chatting, inputs=[chatbot, storage], outputs=[chatbot, storage, markdown]
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).then(*update_suggestions_flow
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).then(*enable_msg_flow)
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return demo
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