feat: complete production-quality Model Router AI traffic control platform

2026-08-31 17:33:38 +05:30
commit 4e6f742272
66 changed files with 8969 additions and 0 deletions
@@ -0,0 +1,67 @@
+import json
+import re
+from typing import Optional
+from app.models.schemas import RequestAnalysis, TaskType, PriorityLevel
+from app.analyzer.heuristics import analyze_request_heuristics, estimate_tokens
+from app.providers.registry import provider_registry
+from app.config.settings import get_settings
+
+settings = get_settings()
+
+CLASSIFIER_PROMPT = """You are a real-time request classifier for an intelligent LLM model router.
+Analyze the user prompt and return ONLY a JSON object matching this schema:
+{
+  "task_type": "GENERAL_QA" | "CODING" | "DEBUGGING" | "REASONING" | "SUMMARIZATION" | "EXTRACTION" | "WRITING" | "TRANSLATION" | "ANALYSIS" | "MATH" | "LONG_CONTEXT" | "CREATIVE",
+  "complexity": 0.0 to 1.0,
+  "reasoning_required": true/false,
+  "coding_required": true/false,
+  "vision_required": true/false,
+  "latency_priority": "LOW" | "MEDIUM" | "HIGH",
+  "cost_sensitivity": "LOW" | "MEDIUM" | "HIGH",
+  "quality_requirement": "LOW" | "MEDIUM" | "HIGH"
+}
+Output valid JSON only with no markdown wrapping or additional text.
+"""
+
+
+async def analyze_request(prompt: str, analyzer_mode: Optional[str] = None) -> RequestAnalysis:
+    mode = (analyzer_mode or settings.ROUTER_ANALYZER).lower()
+
+    if mode == "llm":
+        try:
+            # Attempt to use local or configured provider for classification
+            provider = provider_registry.get_provider("ollama")
+            if provider:
+                health = await provider.check_health()
+                if health.get("status") == "CONNECTED":
+                    resp = await provider.generate(
+                        prompt=f"Classify this request:\n\n{prompt[:1000]}",
+                        model_id="qwen2.5-coder",
+                        system_prompt=CLASSIFIER_PROMPT,
+                        temperature=0.1,
+                    )
+                    clean_json = re.search(r"\{.*\}", resp.content, re.DOTALL)
+                    if clean_json:
+                        data = json.loads(clean_json.group(0))
+                        comp = float(data.get("complexity", 0.5))
+                        comp_label = PriorityLevel.HIGH if comp >= 0.75 else (PriorityLevel.MEDIUM if comp >= 0.45 else PriorityLevel.LOW)
+                        return RequestAnalysis(
+                            task_type=TaskType(data.get("task_type", "GENERAL_QA")),
+                            complexity=comp,
+                            complexity_label=comp_label,
+                            reasoning_required=bool(data.get("reasoning_required", False)),
+                            coding_required=bool(data.get("coding_required", False)),
+                            vision_required=bool(data.get("vision_required", False)),
+                            context_size=estimate_tokens(prompt),
+                            latency_priority=PriorityLevel(data.get("latency_priority", "MEDIUM")),
+                            cost_sensitivity=PriorityLevel(data.get("cost_sensitivity", "MEDIUM")),
+                            quality_requirement=PriorityLevel(data.get("quality_requirement", "MEDIUM")),
+                            keywords_detected=["llm_classified"],
+                            analyzer_used="llm",
+                        )
+        except Exception:
+            # Graceful fallback to heuristics if LLM classifier is unavailable or times out
+            pass
+
+    # Default to fast, deterministic heuristics
+    return analyze_request_heuristics(prompt)