feat(CG4-credits): GET /billing/credits — kreditt-saldo, burn rate og tom-dato
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@ -15,7 +15,7 @@ class BillingAgent:
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self.bq_client = bigquery.Client(project=self.project_id)
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# ── summary ──────────────────────────────────────────────────────────────
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# ── summary ────────────────────────────────────────────────────────────────────
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def get_summary(self):
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query = f"""
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SELECT
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@ -48,7 +48,7 @@ class BillingAgent:
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}
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return {"summary": summary}
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# ── forecast ──────────────────────────────────────────────────────────────
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# ── forecast ──────────────────────────────────────────────────────────────────
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def get_forecast(self):
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q7 = f"""
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SELECT SUM(cost) + SUM(IFNULL(
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@ -84,7 +84,129 @@ class BillingAgent:
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"data_note": "Prognose basert på siste 7 dager. BigQuery kan ha 24-48 timers forsinkelse.",
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}
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# ── anomalier ─────────────────────────────────────────────────────────────
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# ── credits-status (ny) ───────────────────────────────────────────────────────
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def get_credits_status(self, days: int = 90):
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"""
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CG4-credits: Henter faktiske kreditter fra BigQuery billing export.
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Returnerer:
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- credits_used_total: total kreditter brukt hittil (alle typer)
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- credits_by_type: [{type, full_name, amount}] sortert størst først
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- gross_cost_total: bruttokostnad uten kreditter
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- net_cost_total: nettokostnad etter kreditter
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- daily_gross_burn: gjennomsnittlig daglig bruttokostnad (7d)
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- daily_credit_burn: gjennomsnittlig daglig kredittforbruk (7d)
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- credit_runway_days: estimert antall dager til credits er tom
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- credit_exhaustion_date: estimert dato når credits går tom
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- data_as_of: siste dato med data i BQ (24-48t forsinkelse)
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- warning: settes hvis runway < 30 dager
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"""
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# 1. Total kreditter brukt og type-breakdown
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q_credits = f"""
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SELECT
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cr.type AS credit_type,
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cr.full_name AS full_name,
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ROUND(SUM(cr.amount), 4) AS total_amount
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FROM `{self.billing_table}`,
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UNNEST(credits) AS cr
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WHERE _PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL {int(days)} DAY)
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GROUP BY credit_type, full_name
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ORDER BY total_amount ASC
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"""
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# 2. Daglig burn siste 7 dager (brutto og kreditter separat)
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q_burn = f"""
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SELECT
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ROUND(SUM(cost) / 7, 6) AS daily_gross,
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ROUND(SUM(IFNULL(
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(SELECT SUM(c.amount) FROM UNNEST(credits) c), 0)) / 7, 6) AS daily_credit
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FROM `{self.billing_table}`
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WHERE _PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY)
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"""
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# 3. Total brutto + netto hittil
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q_totals = f"""
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SELECT
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ROUND(SUM(cost), 4) AS gross_total,
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ROUND(SUM(cost) + SUM(IFNULL(
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(SELECT SUM(c.amount) FROM UNNEST(credits) c), 0)), 4) AS net_total
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FROM `{self.billing_table}`
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WHERE _PARTITIONTIME >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL {int(days)} DAY)
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"""
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# 4. Siste dato med data
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q_latest = f"""
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SELECT MAX(DATE(usage_start_time)) AS latest_date
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FROM `{self.billing_table}`
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"""
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credits_rows = list(self.bq_client.query(q_credits).result())
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burn_row = list(self.bq_client.query(q_burn).result())[0]
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totals_row = list(self.bq_client.query(q_totals).result())[0]
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latest_row = list(self.bq_client.query(q_latest).result())[0]
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credits_by_type = [
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{
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"type": row.credit_type,
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"full_name": row.full_name,
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"amount": float(row.total_amount),
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}
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for row in credits_rows
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]
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credits_used_total = abs(sum(r["amount"] for r in credits_by_type))
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gross_total = float(totals_row.gross_total or 0)
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net_total = float(totals_row.net_total or 0)
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daily_gross = float(burn_row.daily_gross or 0)
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daily_credit = abs(float(burn_row.daily_credit or 0))
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data_as_of = str(latest_row.latest_date) if latest_row.latest_date else None
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# Runway: Google Vertex AI free tier er typisk $300 USD per prosjekt
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# Vi beregner gjenstående basert på faktisk brukt vs antatt total-kreditt
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# Brukeren må sette GOOGLE_CREDIT_TOTAL_USD i env for nøyaktig beregning
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credit_total_usd = float(os.environ.get("GOOGLE_CREDIT_TOTAL_USD", "0"))
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runway_days = None
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exhaustion_date = None
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credits_remaining = None
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if credit_total_usd > 0 and daily_credit > 0:
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credits_remaining = round(credit_total_usd - credits_used_total, 2)
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runway_days = int(credits_remaining / daily_credit) if credits_remaining > 0 else 0
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exhaustion_date = str(
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datetime.date.today() + datetime.timedelta(days=runway_days)
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) if runway_days > 0 else str(datetime.date.today())
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elif daily_credit > 0:
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# Ingen total satt: gi burn rate men ikke runway
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credits_remaining = None
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runway_days = None
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exhaustion_date = None
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warning = None
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if runway_days is not None and runway_days < 30:
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warning = f"⚠️ Kreditter estimert tom om {runway_days} dager ({exhaustion_date}). Aktiver fakturering!"
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elif runway_days is not None and runway_days < 60:
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warning = f"⚠️ Kreditter estimert tom om {runway_days} dager ({exhaustion_date})."
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return {
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"credits_used_total_usd": round(credits_used_total, 4),
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"credits_remaining_usd": credits_remaining,
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"credit_total_usd": credit_total_usd if credit_total_usd > 0 else None,
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"gross_cost_total_usd": gross_total,
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"net_cost_total_usd": net_total,
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"daily_gross_burn_usd": round(daily_gross, 6),
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"daily_credit_burn_usd": round(daily_credit, 6),
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"credit_runway_days": runway_days,
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"credit_exhaustion_date": exhaustion_date,
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"credits_by_type": credits_by_type,
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"data_as_of": data_as_of,
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"period_days": days,
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"warning": warning,
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"setup_note": None if credit_total_usd > 0 else (
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"Sett GOOGLE_CREDIT_TOTAL_USD i Cloud Run env for nøyaktig runway-beregning. "
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"Eksempel: 300 for $300 Google gratis-kreditter."
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),
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}
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# ── anomalier ──────────────────────────────────────────────────────────────────
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def get_anomalies(self):
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query = f"""
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WITH daily_costs AS (
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@ -126,12 +248,8 @@ class BillingAgent:
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]
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}
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# ── daglig historikk for bar-chart (CG6) ──────────────────────────────────
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# ── daglig historikk for bar-chart (CG6) ───────────────────────────────────
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def get_daily_history(self, days: int = 30):
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"""
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Returnerer [{date: str, mtd: float}] for siste `days` dager, sortert ASC.
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MTD er kumulativ sum fra 1. i måneden til den dato.
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"""
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query = f"""
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SELECT
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DATE(usage_start_time) AS usage_date,
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@ -153,13 +271,8 @@ class BillingAgent:
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history.append({"date": str(row.usage_date), "mtd": round(mtd, 6)})
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return history
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# ── tjenester gruppert per service (CG5+CG6) ─────────────────────────────
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# ── tjenester gruppert per service (CG5+CG6) ─────────────────────────────────
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def get_service_totals(self, days: int = 30):
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"""
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Grupperer kostnader per tjeneste (ikke per SKU).
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Compute Engine vises som én rad med total, med SKU-detaljer som sub-liste.
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Unngår duplikate tjeneste-rader i dashbordet.
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"""
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query = f"""
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SELECT
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service.description AS service,
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@ -174,8 +287,6 @@ class BillingAgent:
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ORDER BY service, sku_cost DESC
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"""
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results = self.bq_client.query(query).result()
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# Grupper SKU-er under tjeneste — én rad per tjeneste i dashbordet
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services: dict = {}
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for row in results:
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svc = row.service
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@ -188,14 +299,14 @@ class BillingAgent:
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"sku": row.sku,
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"sku_cost": round(float(row.sku_cost), 6),
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})
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return sorted(services.values(), key=lambda x: x["total_cost"], reverse=True)
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if __name__ == '__main__':
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agent = BillingAgent()
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print("Summary:", agent.get_summary())
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print("Forecast:", agent.get_forecast())
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print("Anomalies:", agent.get_anomalies())
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print("By-service:", agent.get_service_totals())
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print("History:", agent.get_daily_history())
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print("Summary:", agent.get_summary())
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print("Forecast:", agent.get_forecast())
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print("Credits status:", agent.get_credits_status())
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print("Anomalies:", agent.get_anomalies())
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print("By-service:", agent.get_service_totals())
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print("History:", agent.get_daily_history())
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