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app.py

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+# slack_reporter/app.py
+import os
+import time
+import schedule
+import pandas as pd
+import matplotlib.pyplot as plt
+import requests
+from datetime import datetime, timedelta
+from huggingface_hub import HfApi, hf_hub_download
+import gradio as gr
+
+# --- Konfiguration ---
+REPO_ID = "ChargeNodeEurope/logfiles"
+LOG_FILENAME = "logs/conversation_log.txt"
+WEBHOOK_URL = os.environ.get("SLACK_WEBHOOK_URL")
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
+# --- Funktion: Skapa grafer ---
+def generate_graphs(df):
+    now = datetime.now()
+    df['timestamp'] = pd.to_datetime(df['timestamp'])
+
+    # 1. Unika användare per dag (14 dagar)
+    daily_users = df.groupby(df['timestamp'].dt.date)['user_id'].nunique()
+    daily_users = daily_users.last("14D")
+    plt.figure(figsize=(8,4))
+    daily_users.plot(kind='bar', title="Unika användare per dag (14 dagar)")
+    plt.ylabel("Antal användare")
+    plt.tight_layout()
+    user_graph_path = "daily_users.png"
+    plt.savefig(user_graph_path)
+    plt.close()
+
+    # 2. Meddelanden per timme (72h)
+    cutoff = now - timedelta(hours=72)
+    df_recent = df[df['timestamp'] >= cutoff]
+    hourly = df_recent.groupby(df_recent['timestamp'].dt.floor('H')).size()
+    plt.figure(figsize=(10,4))
+    hourly.plot(title="Meddelanden per timme (senaste 72h)")
+    plt.ylabel("Antal meddelanden")
+    plt.xticks(rotation=45)
+    plt.tight_layout()
+    hourly_graph_path = "hourly_msgs.png"
+    plt.savefig(hourly_graph_path)
+    plt.close()
+
+    return user_graph_path, hourly_graph_path
+
+# --- Funktion: Ladda upp grafer till Hugging Face Hub ---
+def upload_graphs_to_hub(user_graph_path, hourly_graph_path):
+    api = HfApi()
+    api.upload_file(
+        path_or_fileobj=user_graph_path,
+        path_in_repo="graphs/daily_users.png",
+        repo_id=REPO_ID,
+        repo_type="dataset",
+        token=HF_TOKEN
+    )
+    api.upload_file(
+        path_or_fileobj=hourly_graph_path,
+        path_in_repo="graphs/hourly_msgs.png",
+        repo_id=REPO_ID,
+        repo_type="dataset",
+        token=HF_TOKEN
+    )
+    return (
+        f"https://huggingface.co/datasets/{REPO_ID}/resolve/main/graphs/daily_users.png",
+        f"https://huggingface.co/datasets/{REPO_ID}/resolve/main/graphs/hourly_msgs.png"
+    )
+
+# --- Funktion: Skicka Slack-meddelande ---
+def send_to_slack(user_url, hourly_url):
+    payload = {
+        "text": "\ud83d\udcca Dagliga grafer",
+        "attachments": [
+            {"title": "Unika användare (14 dagar)", "image_url": user_url},
+            {"title": "Meddelanden per timme (72h)", "image_url": hourly_url}
+        ]
+    }
+    try:
+        requests.post(WEBHOOK_URL, json=payload)
+    except Exception as e:
+        print("Fel vid Slack-post:", e)
+
+# --- Huvudfunktion ---
+def run_report():
+    print("Genererar grafer och skickar till Slack...")
+    log_path = hf_hub_download(
+        repo_id=REPO_ID,
+        filename=LOG_FILENAME,
+        repo_type="dataset",
+        token=HF_TOKEN
+    )
+    df = pd.read_json(log_path, lines=True)
+    user_graph, hourly_graph = generate_graphs(df)
+    user_url, hourly_url = upload_graphs_to_hub(user_graph, hourly_graph)
+    send_to_slack(user_url, hourly_url)
+    return "Slack-meddelande skickat med grafer."
+
+# --- Schemaläggning ---
+schedule.every().day.at("08:20").do(run_report)
+
+def run_schedule():
+    while True:
+        schedule.run_pending()
+        time.sleep(60)
+
+import threading
+threading.Thread(target=run_schedule, daemon=True).start()
+
+# --- Gradio-knapp för manuell körning ---
+with gr.Blocks() as app:
+    gr.Markdown("# Slack Reporter - ChargeNode")
+    gr.Markdown("Tryck på knappen för att generera dagens rapport och posta till Slack.")
+    btn = gr.Button("Skicka nu")
+    output = gr.Textbox()
+    btn.click(fn=run_report, outputs=output)
+
+if __name__ == "__main__":
+    app.launch()

requirements.txt

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+pandas
+matplotlib
+requests
+schedule
+huggingface_hub
+gradio