style(core): restore high-density professional tables and dense metrics for v1.5.1

litellm_dashboard.py

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