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import gradio as gr
from agents import run_first_aider, run_introspect, run_journaling_pipeline
from journal_utils import (
log_entry, log_chat_interaction, export_to_pdf, export_to_md,
generate_emotion_map, get_weekly_summary, get_counselor_view
)
chat_history = []
with gr.Blocks() as demo:
gr.Markdown("## 🤖 MoodJournal Bot")
with gr.Tab("🗣️ Empathetic Chat"):
mood = gr.Radio(["😊", "😐", "😢", "😠", "😰"], label="Your Mood")
user_input = gr.Textbox(label="Talk to me", lines=2)
chat_output = gr.Chatbot(label="AI Listener")
chat_btn = gr.Button("Send")
introspect_btn = gr.Button("🪞 Introspect with AI")
def handle_chat(msg, mood):
ai = run_first_aider(msg, mood)
chat_history.append((msg, ai))
log_chat_interaction(msg, ai, mood)
return chat_history
chat_btn.click(handle_chat, [user_input, mood], chat_output)
def start_introspect(msg, mood):
reply = run_introspect(msg, mood)
chat_history.append(("Introspect", reply))
return chat_history
introspect_btn.click(start_introspect, [user_input, mood], chat_output)
with gr.Tab("📔 Journal"):
mode = gr.Radio(["Adult (Personal Growth)", "Workplace (EAP-Focused)"])
mood_j = gr.Radio(["😊", "😐", "😢", "😠", "😰"], label="Mood")
entry = gr.Textbox(lines=6, label="Write your thoughts")
outbox = gr.Textbox(label="AI Response")
btn = gr.Button("Submit")
def journal_entry_flow(mood, entry, mode):
result = run_journaling_pipeline(mood, entry, mode)
log_entry(result)
return result["response"]
btn.click(journal_entry_flow, [mood_j, entry, mode], outbox)
gr.Button("Export to PDF").click(export_to_pdf, [entry, mood_j, mode])
gr.Button("Export to Markdown").click(export_to_md, [entry, mood_j, mode])
with gr.Tab("📊 Counselor View"):
gr.Button("Generate Weekly Mood Chart").click(generate_emotion_map, outputs=gr.Image())
gr.Button("Get Weekly Summary").click(get_weekly_summary, outputs=gr.JSON())
gr.Button("Get Counselor Insights").click(get_counselor_view, outputs=gr.Textbox())
demo.launch(share=True)
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