style(core): restore high-density professional tables and dense metrics for v1.5.1
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6add0680ac
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1 file changed
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-48
+53
-48
@@ -2,10 +2,10 @@
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title: LiteLLM Dashboard
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author: Kagamine Rin & VAI
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author_url: https://rin.captcouch.xyz
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description: Consolidated Hardcore LiteLLM observability — status, usage, and history.
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description: Professional LiteLLM observability — High-density health, cost breakdown, and request history.
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required_open_webui_version: 0.4.0
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requirements: requests
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version: 1.5.0
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version: 1.5.1
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licence: MIT
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"""
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@@ -26,7 +26,7 @@ class Tools:
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"""LiteLLM proxy connection settings."""
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litellm_url: str = Field(
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default="http://localhost:4000",
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description="LiteLLM proxy base URL",
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description="LiteLLM proxy base URL (e.g. http://localhost:4000)",
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)
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litellm_master_key: str = Field(
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default="",
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@@ -55,7 +55,6 @@ class Tools:
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return self.valves.litellm_url.rstrip("/")
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def _fetch_live_prices(self):
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"""Sync internal price cache with LiteLLM's live model registry."""
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if not self.valves.enable_dynamic_pricing or self._price_cache:
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return
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try:
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@@ -95,7 +94,6 @@ class Tools:
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return date_str
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def _audit_cost(self, model: str, prompt: int, cached: int, completion: int, reported_cost: float, reasoning: int = 0) -> str:
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"""Audit reported cost with dynamic pricing."""
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self._fetch_live_prices()
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pricing = self._price_cache.get(model)
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if not pricing: return ""
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@@ -114,40 +112,38 @@ class Tools:
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Comprehensive system check: Proxy readiness, DB connectivity, and Model health.
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Use this to verify the infrastructure is up and which models are available.
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"""
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lines = [f"LiteLLM Infrastructure Status — {self._base_url()}", "=" * 50]
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lines = [f"LiteLLM Infrastructure Status — {self._base_url()}"]
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lines.append("=" * 60)
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# 1. Readiness
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try:
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r = requests.get(f"{self._base_url()}/health/readiness", timeout=5)
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if r.status_code == 200:
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d = r.json()
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lines.append(f"Proxy: ✅ {d.get('status')} | DB: {d.get('db')} | v{d.get('litellm_version')}")
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else: lines.append(f"Proxy Readiness: ⚠️ Status {r.status_code}")
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except Exception: lines.append("Proxy Readiness: ❌ Connection Error")
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lines.append(f"✅ Proxy: {d.get('status')} | DB: {d.get('db')} | v{d.get('litellm_version')}")
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else: lines.append(f"⚠️ Proxy Readiness: Status {r.status_code}")
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except Exception: lines.append("❌ Proxy Readiness: Connection Error")
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# 2. Model Health
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try:
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h = requests.get(f"{self._base_url()}/health", headers=self._headers(), timeout=10)
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if h.status_code == 200:
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hd = h.json()
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healthy = hd.get("healthy_endpoints", [])
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unhealthy = hd.get("unhealthy_endpoints", [])
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lines.append(f"Models: {len(healthy)} healthy, {len(unhealthy)} unhealthy")
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for ep in healthy[:15]: # Cap display to save tokens
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lines.append(f"\nHealthy Models: {len(healthy)} | Unhealthy: {len(unhealthy)}")
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lines.append("-" * 60)
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for ep in healthy:
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m = ep.get("model", "unknown")
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lines.append(f" ✅ {m:25s} | rpm: {ep.get('rpm','?'):>3}")
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if len(healthy) > 15: lines.append(f" ... and {len(healthy)-15} more healthy models.")
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display = m.replace("gemini/", "").replace("openai/", "")
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lines.append(f" ✅ {display:30s} — rpm: {ep.get('rpm','?'):>3}, timeout: {ep.get('timeout','?')}s")
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for ep in unhealthy:
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lines.append(f" ❌ {ep.get('model', 'unknown')}")
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except Exception: lines.append("Model Health: ❌ Failed to fetch")
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except Exception as e: lines.append(f"\n❌ Health Check Failed: {str(e)}")
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return "\n".join(lines)
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def litellm_usage(self, start_date: str = "today", end_date: str = "today", detail_level: Literal["summary", "full"] = "summary") -> str:
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"""
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Get fiscal usage and spend data.
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:param start_date: YYYY-MM-DD or shortcut (today, yesterday, 7 days ago)
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:param end_date: YYYY-MM-DD or shortcut
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:param detail_level: 'summary' for quick spend snapshot, 'full' for daily breakdown and sparklines.
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"""
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if not self.valves.litellm_master_key: return "❌ Master key required."
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@@ -160,13 +156,15 @@ class Tools:
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if s.status_code == 200:
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models = sorted(s.json(), key=lambda x: x.get("total_spend", 0), reverse=True)
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total = sum(m.get("total_spend", 0) for m in models)
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lines = [f"LiteLLM Spend Summary (Lifetime)", "=" * 40, f"Total Lifetime Spend: ${total:.2f}"]
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for m in models[:5]:
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lines.append(f" - {m['model']}: ${m['total_spend']:.2f}")
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lines = [f"LiteLLM Spend Snapshot (Lifetime)", "=" * 50, f"Total Lifetime Spend: ${total:.2f}\n"]
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lines.append(f"{'Model':30s} | {'Spend':>10s}")
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lines.append("-" * 45)
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for m in models[:8]:
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display = m['model'].split("/")[-1]
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lines.append(f" {display:28s} | ${m['total_spend']:9.2f}")
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return "\n".join(lines)
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except Exception: pass
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# Full Report
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try:
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url = f"{self._base_url()}/user/daily/activity"
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resp = requests.get(url, headers=self._headers(), params={"start_date": r_start, "end_date": r_end}, timeout=30)
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@@ -186,43 +184,47 @@ class Tools:
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return " [" + "".join(chars[int((v - low) / rng * 7)] for v in vals) + "]"
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meta = data.get("metadata", {})
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lines = [f"LiteLLM Usage Report: {r_start} to {r_end}", "=" * 60]
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lines.append(f"Spend: ${meta.get('total_spend', 0):.2f}{get_spark(spends)}")
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lines.append(f"Requests: {meta.get('total_successful_requests', 0)} ok, {meta.get('total_failed_requests', 0)} fail")
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lines = [f"LiteLLM Usage Report: {r_start} to {r_end}"]
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lines.append("=" * 75)
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lines.append(f"Total Spend: ${meta.get('total_spend', 0):.2f}{get_spark(spends)}")
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lines.append(f"Total Tokens: {meta.get('total_tokens', 0):,} ({meta.get('total_prompt_tokens',0):,} prompt + {meta.get('total_completion_tokens',0):,} completion)")
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lines.append(f"Requests: {meta.get('total_successful_requests', 0)} successful, {meta.get('total_failed_requests', 0)} failed")
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# Aggregated Model Breakdown
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# Model Breakdown
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model_totals = {}
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for day in results:
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models = day.get("breakdown", {}).get("models", {})
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for m_name, m_data in models.items():
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metrics = m_data.get("metrics", {})
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if m_name not in model_totals:
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model_totals[m_name] = {"spend": 0, "reqs": 0}
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model_totals[m_name] = {"spend": 0, "reqs": 0, "tokens": 0}
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model_totals[m_name]["spend"] += metrics.get("spend", 0)
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model_totals[m_name]["reqs"] += metrics.get("successful_requests", 0)
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model_totals[m_name]["tokens"] += metrics.get("total_tokens", 0)
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if model_totals:
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lines.append("\nBy Model (Spend > $0.001):")
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sorted_models = sorted(model_totals.items(), key=lambda x: x[1]["spend"], reverse=True)
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for m_name, m_stats in sorted_models:
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if m_stats["spend"] >= 0.001 or not self.valves.default_hide_zero_spend:
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# Strip common prefixes for readability
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display = m_name.split("/")[-1]
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lines.append(f" {display:25s} | ${m_stats['spend']:7.2f} | {m_stats['reqs']:4d} ok")
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lines.append(f"\n{'Model':30s} | {'Spend':>10s} | {'Requests':>12s} | {'Tokens':>12s}")
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lines.append("-" * 75)
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sorted_models = sorted(model_totals.items(), key=lambda x: x[1]["spend"], reverse=True)
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hidden = 0
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for m_name, m_stats in sorted_models:
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if m_stats["spend"] < 0.001 and self.valves.default_hide_zero_spend:
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hidden += 1
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continue
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display = m_name.split("/")[-1][:30]
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lines.append(f" {display:28s} | ${m_stats['spend']:9.2f} | {m_stats['reqs']:10d} ok | {m_stats['tokens']:10,d}")
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if hidden: lines.append(f" ... ({hidden} models with sub-$0.001 spend hidden)")
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lines.append("\nBy Endpoint:")
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lines.append(f"\n{'Endpoint':30s} | {'Spend':>10s} | {'Requests':>12s}")
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lines.append("-" * 60)
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ends = results[0].get("breakdown", {}).get("endpoints", {}) if results else {}
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for path, edata in ends.items():
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for path, edata in sorted(ends.items(), key=lambda x: x[1].get("metrics",{}).get("spend",0), reverse=True):
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m = edata.get("metrics", {})
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lines.append(f" {path:20s} | ${m.get('spend',0):.4f} | {m.get('successful_requests',0)} reqs")
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lines.append(f" {path:28s} | ${m.get('spend',0):9.4f} | {m.get('successful_requests',0):10d} ok")
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return "\n".join(lines)
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def litellm_history(self, limit: int = 20, filter_model: Optional[str] = None) -> str:
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"""
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Get recent request logs with audit data and thought detection.
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:param limit: Number of requests (1-50)
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:param filter_model: Optional string to filter by model name (e.g. 'gpt-4')
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"""
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"""Get recent request logs with audit data and thought detection."""
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if not self.valves.litellm_master_key: return "❌ Master key required."
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try:
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resp = requests.get(f"{self._base_url()}/spend/logs", headers=self._headers(), timeout=30)
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@@ -234,11 +236,11 @@ class Tools:
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logs = [l for l in logs if filter_model.lower() in l.get("model", "").lower()]
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recent = logs[:max(1, min(50, limit))]
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lines = [f"LiteLLM History (Most Recent {len(recent)})", "=" * 95]
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lines = [f"LiteLLM History — {self._base_url()}", "=" * 105]
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for i, entry in enumerate(recent, 1):
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ts = entry.get("startTime", "?")[5:16]
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model = entry.get("model", "unknown")[:25]
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model = entry.get("model", "unknown").split("/")[-1][:25]
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spend = entry.get("spend", 0)
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prompt = entry.get("prompt_tokens", 0) or 0
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completion = entry.get("completion_tokens", 0) or 0
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@@ -249,9 +251,12 @@ class Tools:
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cached = entry.get("cache_read_input_tokens", 0) or 0
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cache_str = f" 💾{int(cached/prompt*100)}%" if prompt and cached else ""
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audit_display = self._audit_cost(entry.get("model"), prompt, cached, completion, spend, reasoning=thought)
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status = "❌" if entry.get("metadata", {}).get("exception") else "✅"
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audit = self._audit_cost(entry.get("model"), prompt, cached, completion, spend, reasoning=thought)
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status = "✅" if not entry.get("metadata", {}).get("exception") else "❌"
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lines.append(f"{i:2d}. {ts} {status} | {model:25s} | ${spend:.4f}{audit_display} | {prompt}→{completion}{thought_str}{cache_str}")
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p_s = f"{prompt/1000:.1f}k" if prompt >= 1000 else str(prompt)
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c_s = f"{completion/1000:.1f}k" if completion >= 1000 else str(completion)
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lines.append(f"{i:2d}. {ts} {status} | {model:25s} | ${spend:.4f}{audit:18s} | {p_s:>6s}→{c_s:<6s}{thought_str}{cache_str}")
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return "\n".join(lines)
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