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Browse files
app.py
CHANGED
@@ -55,17 +55,16 @@ def create_tools(cfg):
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query_tool = tools_factory.create_rag_tool(
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tool_name = "justice_harvard_query",
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tool_description = """
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-
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It can answer questions about the justice, morality, politics and related topics,
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based on transcripts of recordings from the Justice Harvard class that includes a lot of content on these topics.
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When using the tool it's best to ask simple short questions. You can break complex questions into sub-queries.
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""",
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tool_args_schema = JusticeHarvardArgs,
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tool_filter_template = '',
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reranker = "multilingual_reranker_v1", rerank_k = 100,
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n_sentences_before = 2, n_sentences_after = 2, lambda_val = 0.
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summary_num_results = 10,
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vectara_summarizer = 'vectara-summary-ext-24-05-med-omni',
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)
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return (tools_factory.get_tools(
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@@ -79,15 +78,15 @@ def create_tools(cfg):
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)
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def initialize_agent(_cfg):
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date = datetime.datetime.now().strftime("%Y-%m-%d")
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bot_instructions = f"""
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- You are a helpful teacher assistant, with expertise in education in various teaching styles.
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-
-
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- Response in a concise and clear manner, and provide the most relevant information to the student.
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-
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- Always use the rephrase tool at the end in order to ensure it fits the student's age of {_cfg.student_age},
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the {_cfg.style} teaching style and the {_cfg.language} language
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- Always use any guardrails tools to ensure your responses are polite and do not discuss politices.
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"""
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def update_func(status_type: AgentStatusType, msg: str):
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@@ -96,12 +95,15 @@ def initialize_agent(_cfg):
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agent = Agent(
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tools=create_tools(_cfg),
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topic="
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custom_instructions=bot_instructions,
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update_func=update_func
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)
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return agent
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def launch_bot():
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def reset():
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cfg = st.session_state.cfg
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@@ -109,6 +111,7 @@ def launch_bot():
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st.session_state.thinking_message = "Agent at work..."
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st.session_state.agent = initialize_agent(cfg)
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st.session_state.log_messages = []
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st.session_state.show_logs = False
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st.set_page_config(page_title="Justice Harvard Teaching Assistant", layout="wide")
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@@ -150,7 +153,7 @@ def launch_bot():
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st.markdown("\n")
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cfg.student_age = st.number_input(
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'Student age:', min_value=13, value=cfg.student_age,
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step=1, format='%i'
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)
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if st.session_state.student_age != cfg.student_age:
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@@ -158,13 +161,10 @@ def launch_bot():
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reset()
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st.markdown("\n\n")
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bc1,
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with bc1:
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if st.button('Start Over'):
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reset()
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with bc2:
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if st.button('Show Logs'):
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st.session_state.show_logs = not st.session_state.show_logs
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st.markdown("---")
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st.markdown(
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@@ -177,7 +177,7 @@ def launch_bot():
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if "messages" not in st.session_state.keys():
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reset()
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-
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# Display chat messages
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for message in st.session_state.messages:
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with st.chat_message(message["role"], avatar=message["avatar"]):
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@@ -186,27 +186,33 @@ def launch_bot():
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# User-provided prompt
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if prompt := st.chat_input():
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st.session_state.messages.append({"role": "user", "content": prompt, "avatar": 'π§βπ»'})
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with st.chat_message("user", avatar='π§βπ»'):
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print(f"Starting new question: {prompt}\n")
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st.write(prompt)
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if
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with st.chat_message("assistant", avatar='π€'):
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with st.spinner(st.session_state.thinking_message):
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res = st.session_state.agent.chat(prompt)
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message = {"role": "assistant", "content":
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st.session_state.messages.append(message)
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st.
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-
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-
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for msg in st.session_state.log_messages:
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st.write(msg)
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-
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-
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st.
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sys.stdout.flush()
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query_tool = tools_factory.create_rag_tool(
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tool_name = "justice_harvard_query",
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tool_description = """
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Answer questions about the justice, morality, politics and related topics,
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based on transcripts of recordings from the Justice Harvard class that includes a lot of content on these topics.
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When using the tool it's best to ask simple short questions. You can break complex questions into sub-queries.
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""",
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tool_args_schema = JusticeHarvardArgs,
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reranker = "multilingual_reranker_v1", rerank_k = 100,
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n_sentences_before = 2, n_sentences_after = 2, lambda_val = 0.005,
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summary_num_results = 10,
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vectara_summarizer = 'vectara-summary-ext-24-05-med-omni',
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include_citations = True,
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)
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return (tools_factory.get_tools(
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)
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def initialize_agent(_cfg):
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bot_instructions = f"""
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- You are a helpful teacher assistant, with expertise in education in various teaching styles.
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- Obtain information using tools to answer the user's query.
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- If the tool cannot provide information relevant to the user's query, tell the user that you are unable to provide an answer.
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- If the tool can provide relevant information, use the adjust_response_to_student tool
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to rephrase the response to ensure it fits the student's age of {_cfg.student_age},
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the {_cfg.style} teaching style and the {_cfg.language} language.
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- Response in a concise and clear manner, and provide the most relevant information to the student.
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- Never discuss politics, and always respond politely.
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"""
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def update_func(status_type: AgentStatusType, msg: str):
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agent = Agent(
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tools=create_tools(_cfg),
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topic="justice, morality, politics, and philosophy",
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custom_instructions=bot_instructions,
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update_func=update_func
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)
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return agent
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def toggle_logs():
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st.session_state.show_logs = not st.session_state.show_logs
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def launch_bot():
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def reset():
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cfg = st.session_state.cfg
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st.session_state.thinking_message = "Agent at work..."
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st.session_state.agent = initialize_agent(cfg)
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st.session_state.log_messages = []
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st.session_state.prompt = None
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st.session_state.show_logs = False
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st.set_page_config(page_title="Justice Harvard Teaching Assistant", layout="wide")
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st.markdown("\n")
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cfg.student_age = st.number_input(
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'Student age:', min_value=13, max_value=99, value=cfg.student_age,
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step=1, format='%i'
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)
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if st.session_state.student_age != cfg.student_age:
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reset()
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st.markdown("\n\n")
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bc1, _ = st.columns([1, 1])
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with bc1:
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if st.button('Start Over'):
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reset()
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st.markdown("---")
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st.markdown(
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if "messages" not in st.session_state.keys():
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reset()
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+
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# Display chat messages
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for message in st.session_state.messages:
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with st.chat_message(message["role"], avatar=message["avatar"]):
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# User-provided prompt
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if prompt := st.chat_input():
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st.session_state.messages.append({"role": "user", "content": prompt, "avatar": 'π§βπ»'})
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st.session_state.prompt = prompt # Save the prompt in session state
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st.session_state.log_messages = []
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st.session_state.show_logs = False
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with st.chat_message("user", avatar='π§βπ»'):
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print(f"Starting new question: {prompt}\n")
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st.write(prompt)
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# Generate a new response if last message is not from assistant
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if st.session_state.prompt:
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with st.chat_message("assistant", avatar='π€'):
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with st.spinner(st.session_state.thinking_message):
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res = st.session_state.agent.chat(st.session_state.prompt)
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res = res.replace('$', '\\$') # escape dollar sign for markdown
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message = {"role": "assistant", "content": res, "avatar": 'π€'}
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st.session_state.messages.append(message)
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st.markdown(res)
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st.session_state.prompt = None
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log_placeholder = st.empty()
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with log_placeholder.container():
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if st.session_state.show_logs:
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st.button("Hide Logs", on_click=toggle_logs)
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for msg in st.session_state.log_messages:
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st.write(msg)
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else:
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if len(st.session_state.log_messages) > 0:
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st.button("Show Logs", on_click=toggle_logs)
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sys.stdout.flush()
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