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Browse files- .gitignore +3 -0
- README.md +23 -12
- app.py +105 -0
- requirements.txt +3 -0
.gitignore
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__pycache__/
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*.csv
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*.pyc
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README.md
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# 📣 PromoPlaner – Marketing Kampagnen Tool
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Ein einfaches Webtool zur Organisation und Visualisierung von Werbeaktionen mit Gradio und Plotly.
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## Funktionen
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- 🔐 Login-Funktion
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- 💡 KI-basierte Kampagnenvorschläge
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- 📅 Planung mit Start- und Enddatum
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- 📈 Gantt-Visualisierung der Kampagnen
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- 📤 CSV-Export
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## Nutzung
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```bash
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pip install -r requirements.txt
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python app.py
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```
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## Deployment auf Hugging Face
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```bash
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huggingface-cli login
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gradio deploy
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```
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app.py
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import pandas as pd
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from datetime import datetime
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import plotly.express as px
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import plotly.io as pio
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import gradio as gr
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users = {"PM": "Promo123"}
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campaigns = []
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sessions = {}
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def validate_date(date_str):
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try:
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datetime.strptime(date_str, "%Y-%m-%d")
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return True
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except:
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return False
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def login(username, password):
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if users.get(username) == password:
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sessions["user"] = username
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return gr.update(visible=True), f"Willkommen {username}"
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return gr.update(visible=False), "❌ Login fehlgeschlagen"
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def suggest_campaign(product, goal, channel):
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return f"""💡 Idee:
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Produkt: {product}
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Ziel: {goal}
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Kanal: {channel}
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🚀 Vorschlag:
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Eine kreative {channel}-Kampagne für {product}, z. B. mit exklusiven Angeboten oder Rabattaktionen.
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"""
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def add_campaign(name, goal, product, channel, start, end, budget, responsible):
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if not validate_date(start) or not validate_date(end):
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return pd.DataFrame(campaigns), "❌ Bitte Datum im Format YYYY-MM-DD eingeben."
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campaigns.append({
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"Name": name,
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"Ziel": goal,
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"Produkt": product,
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"Kanal": channel,
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"Start": start,
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"Ende": end,
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"Budget (CHF)": budget,
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"Verantwortlich": responsible
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})
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df = pd.DataFrame(campaigns)
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total = df["Budget (CHF)"].sum()
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return df, f"💰 Gesamtbudget: CHF {total:.2f}"
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def export_csv():
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path = "kampagnen.csv"
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pd.DataFrame(campaigns).to_csv(path, index=False)
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return path
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def generate_gantt():
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if not campaigns:
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return "<i>Keine Kampagnen zum Anzeigen</i>"
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df = pd.DataFrame(campaigns)
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df["Start"] = pd.to_datetime(df["Start"])
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df["Ende"] = pd.to_datetime(df["Ende"])
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try:
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fig = px.timeline(df, x_start="Start", x_end="Ende", y="Name", color="Verantwortlich", title="📊 Kampagnenübersicht")
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fig.update_yaxes(autorange="reversed")
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fig.update_layout(height=400, margin=dict(l=20, r=20, t=30, b=20))
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html = pio.to_html(fig, full_html=False, include_plotlyjs='cdn')
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return html
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except Exception as e:
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return f"<b>Fehler:</b> {e}"
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with gr.Blocks() as app:
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gr.Markdown("## 📣 Promo-Planer mit Visualisierung")
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with gr.Row():
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user = gr.Textbox(label="Benutzer")
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pw = gr.Textbox(label="Passwort", type="password")
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login_btn = gr.Button("🔓 Login")
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login_status = gr.Textbox(interactive=False)
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with gr.Column(visible=False) as planner:
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with gr.Row():
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name = gr.Textbox(label="Kampagnenname")
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goal = gr.Dropdown(["Verkaufsförderung","Werbung", "Event"], label="Ziel")
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product = gr.Textbox(label="Produkt")
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with gr.Row():
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channel = gr.Dropdown(["Tisch","Instagram", "E-Mail", "Plakat"], label="Kanal")
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start = gr.Textbox(label="Startdatum (YYYY-MM-DD)")
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end = gr.Textbox(label="Enddatum (YYYY-MM-DD)")
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with gr.Row():
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budget = gr.Number(label="Budget (CHF)")
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responsible = gr.Dropdown(["Markthalle","Marketing", "PM", "PED"], label="Verantwortlich")
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suggest_btn = gr.Button("💡 KI-Vorschlag")
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idea = gr.Textbox(label="Kampagnenidee")
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submit_btn = gr.Button("✅ Speichern")
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output_table = gr.Dataframe()
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budget_total = gr.Textbox(label="Budget Gesamt", interactive=False)
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export_btn = gr.Button("📤 Export CSV")
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gr.Markdown("### 📈 Gantt-Visualisierung")
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gantt_html = gr.HTML()
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update_chart = gr.Button("🔄 Visualisierung aktualisieren")
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gr.Markdown("🚀 **Deployment-Tipp**: Führe `gradio deploy` im Terminal aus, um diese App auf [Hugging Face Spaces](https://huggingface.co/spaces) zu veröffentlichen.")
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login_btn.click(login, [user, pw], [planner, login_status])
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suggest_btn.click(suggest_campaign, [product, goal, channel], idea)
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submit_btn.click(add_campaign, [name, goal, product, channel, start, end, budget, responsible], [output_table, budget_total])
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export_btn.click(export_csv, outputs=None)
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update_chart.click(generate_gantt, outputs=gantt_html)
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app.launch(share=True)
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requirements.txt
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gradio>=4.18
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pandas
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plotly
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