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feat(workflow): daily monitor of Databricks Foundation Model Serving pricing
Adds a GitHub Action (daily 02:00 UTC + manual dispatch) that: - Scrapes the official DBU rates for DeepSeek V4 Flash (0731) / V4 Pro (0813) from https://www.databricks.com/product/pricing/foundation-model-serving - Derives per-token USD at $0.07/DBU and updates both model_prices_and_context_window.json and the packaged backup - Opens a PR (base litellm_internal_staging) only when a rate actually changed Runs on the leecoder fork (no repo guard) so the fork stays current and can feed an upstream PR on demand.
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.github/workflows/monitor_databricks_pricing.py
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.github/workflows/monitor_databricks_pricing.py
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#!/usr/bin/env python3
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"""Monitor Databricks Foundation Model Serving pricing pages and update LiteLLM's
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model_prices_and_context_window.json + packaged backup when rates change.
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Triggered daily by .github/workflows/monitor_databricks_pricing.yml.
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Behavior:
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- Fetches the two official Databricks pricing pages (HTML, JS-rendered price
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table). Parses the embedded price data rows via regex extraction of the
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DBU table (works with the current page markup; fails loudly otherwise).
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- Applies the LiteLLM convention: USD = DBU * 0.07 per token.
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- Updates entries for the monitored model set (see MONITORED below).
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- If any monitored rate changed, writes BOTH files, prints a diff summary and
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exits 0 (so the workflow can create the PR). If nothing changed, exits 0
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with "NO_CHANGE" marker so the workflow skips PR creation.
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"""
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import json
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import re
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import sys
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import urllib.request
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from pathlib import Path
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REPO_ROOT = Path(__file__).resolve().parents[2]
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MAIN_MAP = REPO_ROOT / "model_prices_and_context_window.json"
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BACKUP_MAP = REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json"
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DBU_TO_USD = 0.07
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# Databricks Foundation Model Serving page (open models, incl. DeepSeek V4)
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FMS_PAGE = "https://www.databricks.com/product/pricing/foundation-model-serving"
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# Proprietary page (GPT/Claude/Gemini) — fetched but not used for the monitored
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# monitorset; kept for future expansion.
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PROPRIETARY_PAGE = "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving"
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# model_map key -> (name pattern in the DBU table row, )
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# name pattern is the model label as it appears on the pricing page table.
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MONITORED = {
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"databricks/databricks-deepseek-v4-flash-0731": "Deepseek V4 Flash (0731)",
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"databricks/databricks-deepseek-v4-pro-0813": "Deepseek V4 Pro (0813)",
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}
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# Context windows / output caps from Databricks Foundation Model APIs limits doc
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# (kept in sync with what we know; only rates are refreshed by this script).
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MODEL_FIXTURE = {
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"databricks/databricks-deepseek-v4-flash-0731": {
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"max_input_tokens": 200000,
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"max_output_tokens": 10000,
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},
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"databricks/databricks-deepseek-v4-pro-0813": {
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"max_input_tokens": 200000,
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"max_output_tokens": 4000,
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},
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}
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def fetch(url: str, max_bytes: int = 5_000_000) -> str:
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"""Fetch page HTML; returns text. Raises on non-200."""
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req = urllib.request.Request(url, headers={"User-Agent": "litellm-price-monitor/1.0"})
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with urllib.request.urlopen(req, timeout=60) as resp:
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if resp.status != 200:
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raise RuntimeError(f"HTTP {resp.status} fetching {url}")
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return resp.read(max_bytes + 1).decode("utf-8", errors="replace")
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def parse_dbu_table(html: str) -> dict[str, tuple[float, float]]:
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rows: dict[str, tuple[float, float]] = {}
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for tr in re.findall(r"<tr>(.*?)</tr>", html, flags=re.S):
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cells = re.findall(r"<t[hd][^>]*>(.*?)</t[hd]>", tr, flags=re.S)
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if not cells:
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continue
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label = re.sub(r"<[^>]+>", "", cells[0]).strip()
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nums = []
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for c in cells[1:]:
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txt = re.sub(r"<[^>]+>", "", c).strip()
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if re.fullmatch(r"\d+(?:\.\d+)?", txt):
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nums.append(float(txt))
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if label and len(nums) >= 2:
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rows[label] = (nums[0], nums[1])
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results: dict[str, tuple[float, float]] = {}
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for label in MONITORED.values():
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if label not in rows:
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raise RuntimeError(f"Could not locate pricing row for '{label}' on {FMS_PAGE}")
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results[label] = rows[label]
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return results
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def build_entry(model_key: str, input_dbu: float, output_dbu: float) -> dict:
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fx = MODEL_FIXTURE[model_key]
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return {
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"input_cost_per_token": input_dbu / 1_000_000 * DBU_TO_USD,
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"input_dbu_cost_per_token": input_dbu,
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"litellm_provider": "databricks",
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"max_input_tokens": fx["max_input_tokens"],
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"max_output_tokens": fx["max_output_tokens"],
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"max_tokens": fx["max_output_tokens"],
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"metadata": {
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"notes": (
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f"Pricing derived from Databricks Foundation Model Serving DBU rates "
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f"({input_dbu:g} in / {output_dbu:g} out DBU per 1M tokens × ${DBU_TO_USD:.2f}/DBU "
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f"= ${input_dbu*DBU_TO_USD:.2f}/${output_dbu*DBU_TO_USD:.2f} per 1M). "
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f"Auto-refreshed daily by monitor_databricks_pricing workflow."
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)
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},
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"mode": "chat",
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"output_cost_per_token": output_dbu / 1_000_000 * DBU_TO_USD,
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"output_dbu_cost_per_token": output_dbu,
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"source": FMS_PAGE,
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"supports_function_calling": True,
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"supports_reasoning": True,
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"supports_tool_choice": True,
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}
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def main() -> int:
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html = fetch(FMS_PAGE)
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rates = parse_dbu_table(html)
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with MAIN_MAP.open() as f:
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main_data = json.load(f)
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with BACKUP_MAP.open() as f:
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backup_data = json.load(f)
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changed = False
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for model_key, label in MONITORED.items():
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in_dbu, out_dbu = rates[label]
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entry = build_entry(model_key, in_dbu, out_dbu)
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old = main_data.get(model_key)
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if old != entry:
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main_data[model_key] = entry
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backup_data[model_key] = entry
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changed = True
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print(f"CHANGED {model_key}: {old and old.get('input_cost_per_token')} -> {entry['input_cost_per_token']}")
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if not changed:
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print("NO_CHANGE")
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return 0
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with MAIN_MAP.open("w") as f:
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json.dump(main_data, f, indent=4)
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f.write("\n")
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with BACKUP_MAP.open("w") as f:
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json.dump(backup_data, f, indent=4)
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f.write("\n")
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print("WROTE updated model map and backup")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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56
.github/workflows/monitor_databricks_pricing.yml
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.github/workflows/monitor_databricks_pricing.yml
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name: Monitor Databricks Pricing (deepseek/glm/kimi)
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on:
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schedule:
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- cron: "0 2 * * *" # daily 02:00 UTC
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workflow_dispatch:
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permissions:
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contents: write
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pull-requests: write
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jobs:
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monitor-db-pricing:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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with:
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persist-credentials: false
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fetch-depth: 0
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- name: Set up Python
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uses: actions/setup-python@v5
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with:
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python-version: "3.12"
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- name: Run monitor
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id: monitor
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run: |
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python .github/workflows/monitor_databricks_pricing.py | tee /tmp/monitor_out.txt
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if grep -q '^NO_CHANGE' /tmp/monitor_out.txt; then
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echo "changed=false" >> "$GITHUB_OUTPUT"
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else
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echo "changed=true" >> "$GITHUB_OUTPUT"
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fi
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- name: Open PR if changed
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if: steps.monitor.outputs.changed == 'true'
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env:
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GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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run: |
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BRANCH="monitor-dbx-pricing-$(date +'%Y-%m-%d')"
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git config user.name "github-actions[bot]"
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git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
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git checkout -b "$BRANCH"
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git add model_prices_and_context_window.json litellm/model_prices_and_context_window_backup.json
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git commit -m "chore(model_prices): refresh Databricks Foundation Model Serving rates
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Automated daily monitor detected changed DBU rates on
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https://www.databricks.com/product/pricing/foundation-model-serving
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Updated entries: databricks/databricks-deepseek-v4-*"
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git push origin "$BRANCH"
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gh pr create --repo "${{ github.repository }}" \
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--base litellm_internal_staging \
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--head "$BRANCH" \
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--title "chore(model_prices): refresh Databricks Foundation Model Serving rates" \
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--body "Automated daily check of the Databricks Foundation Model Serving pricing page detected rate changes. Updated model_prices_and_context_window.json and packaged backup for monitored models." || true
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