test: Add session model metadata tests (#741)

agent/session_model_metadata.py

@@ -0,0 +1,223 @@
+"""
+Session Model Metadata — Persist model context info per session
+
+When a session switches models mid-conversation, context length and
+token budget need to be updated to prevent silent truncation.
+
+Issue: #741
+"""
+
+import json
+import logging
+from dataclasses import dataclass, asdict
+from pathlib import Path
+from typing import Any, Dict, Optional
+
+logger = logging.getLogger(__name__)
+
+HERMES_HOME = Path.home() / ".hermes"
+
+
+# Common model context lengths (tokens)
+KNOWN_CONTEXT_LENGTHS = {
+    # Anthropic
+    "claude-opus-4-6": 200000,
+    "claude-sonnet-4": 200000,
+    "claude-3.5-sonnet": 200000,
+    "claude-3-haiku": 200000,
+    
+    # OpenAI
+    "gpt-4o": 128000,
+    "gpt-4-turbo": 128000,
+    "gpt-4": 8192,
+    "gpt-3.5-turbo": 16385,
+    
+    # Nous / open models
+    "hermes-3-llama-3.1-405b": 131072,
+    "hermes-3-llama-3.1-70b": 131072,
+    "deepseek-r1": 131072,
+    "deepseek-v3": 131072,
+    
+    # Local
+    "llama-3.1-8b": 131072,
+    "llama-3.1-70b": 131072,
+    "qwen-2.5-72b": 131072,
+    
+    # Xiaomi
+    "mimo-v2-pro": 131072,
+    "mimo-v2-flash": 131072,
+    
+    # Defaults
+    "default": 4096,
+}
+
+# Reserve tokens for system prompt, response, and overhead
+TOKEN_RESERVE = 2000
+
+
+@dataclass
+class ModelMetadata:
+    """Metadata for a model in a session."""
+    model: str
+    provider: str
+    context_length: int
+    available_for_input: int  # context_length - reserve
+    current_tokens_used: int = 0
+    
+    @property
+    def remaining_tokens(self) -> int:
+        """Tokens remaining for new input."""
+        return max(0, self.available_for_input - self.current_tokens_used)
+    
+    @property
+    def utilization_pct(self) -> float:
+        """Percentage of context used."""
+        if self.available_for_input == 0:
+            return 0.0
+        return (self.current_tokens_used / self.available_for_input) * 100
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return asdict(self)
+
+
+def get_context_length(model: str) -> int:
+    """Get context length for a model."""
+    model_lower = model.lower()
+    
+    # Check exact match
+    if model_lower in KNOWN_CONTEXT_LENGTHS:
+        return KNOWN_CONTEXT_LENGTHS[model_lower]
+    
+    # Check partial match
+    for key, length in KNOWN_CONTEXT_LENGTHS.items():
+        if key in model_lower:
+            return length
+    
+    return KNOWN_CONTEXT_LENGTHS["default"]
+
+
+def create_metadata(model: str, provider: str = "", current_tokens: int = 0) -> ModelMetadata:
+    """Create model metadata."""
+    context_length = get_context_length(model)
+    available = max(0, context_length - TOKEN_RESERVE)
+    
+    return ModelMetadata(
+        model=model,
+        provider=provider,
+        context_length=context_length,
+        available_for_input=available,
+        current_tokens_used=current_tokens
+    )
+
+
+def check_model_switch(
+    old_model: str,
+    new_model: str,
+    current_tokens: int
+) -> Dict[str, Any]:
+    """
+    Check impact of switching models mid-session.
+    
+    Returns:
+        Dict with switch analysis including warnings
+    """
+    old_ctx = get_context_length(old_model)
+    new_ctx = get_context_length(new_model)
+    
+    old_available = old_ctx - TOKEN_RESERVE
+    new_available = new_ctx - TOKEN_RESERVE
+    
+    result = {
+        "old_model": old_model,
+        "new_model": new_model,
+        "old_context": old_ctx,
+        "new_context": new_ctx,
+        "current_tokens": current_tokens,
+        "fits_in_new": current_tokens <= new_available,
+        "truncation_needed": max(0, current_tokens - new_available),
+        "warning": None,
+    }
+    
+    if not result["fits_in_new"]:
+        result["warning"] = (
+            f"Switching to {new_model} ({new_ctx:,} ctx) with {current_tokens:,} tokens "
+            f"will truncate {result['truncation_needed']:,} tokens of history. "
+            f"Consider starting a new session."
+        )
+    
+    if new_ctx < old_ctx:
+        reduction = old_ctx - new_ctx
+        result["warning"] = (
+            f"New model has {reduction:,} fewer tokens of context. "
+            f"({old_ctx:,} -> {new_ctx:,})"
+        )
+    
+    return result
+
+
+class SessionModelTracker:
+    """Track model metadata for a session."""
+    
+    def __init__(self, session_id: str):
+        self.session_id = session_id
+        self.metadata: Optional[ModelMetadata] = None
+        self.history: list = []  # Model switch history
+    
+    def set_model(self, model: str, provider: str = "", tokens_used: int = 0):
+        """Set the current model for the session."""
+        old_model = self.metadata.model if self.metadata else None
+        
+        self.metadata = create_metadata(model, provider, tokens_used)
+        
+        # Record switch in history
+        if old_model and old_model != model:
+            self.history.append({
+                "from": old_model,
+                "to": model,
+                "tokens_at_switch": tokens_used,
+                "context_length": self.metadata.context_length
+            })
+        
+        logger.info(
+            "Session %s: model=%s context=%d available=%d",
+            self.session_id[:12], model,
+            self.metadata.context_length,
+            self.metadata.available_for_input
+        )
+    
+    def update_tokens(self, tokens: int):
+        """Update current token usage."""
+        if self.metadata:
+            self.metadata.current_tokens_used = tokens
+    
+    def get_remaining(self) -> int:
+        """Get remaining tokens."""
+        if not self.metadata:
+            return 0
+        return self.metadata.remaining_tokens
+    
+    def can_fit(self, additional_tokens: int) -> bool:
+        """Check if additional tokens fit in context."""
+        if not self.metadata:
+            return False
+        return self.metadata.remaining_tokens >= additional_tokens
+    
+    def get_warning(self) -> Optional[str]:
+        """Get warning if context is running low."""
+        if not self.metadata:
+            return None
+        
+        util = self.metadata.utilization_pct
+        if util > 90:
+            return f"Context {util:.0f}% full. Consider compression or new session."
+        if util > 75:
+            return f"Context {util:.0f}% full."
+        return None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Export state."""
+        return {
+            "session_id": self.session_id,
+            "metadata": self.metadata.to_dict() if self.metadata else None,
+            "history": self.history
+        }

tests/test_session_model_metadata.py

@@ -0,0 +1,105 @@
+"""
+Tests for session model metadata
+
+Issue: #741
+"""
+
+import unittest
+from agent.session_model_metadata import (
+    get_context_length,
+    create_metadata,
+    check_model_switch,
+    SessionModelTracker,
+)
+
+
+class TestContextLength(unittest.TestCase):
+    
+    def test_known_model(self):
+        ctx = get_context_length("claude-opus-4-6")
+        self.assertEqual(ctx, 200000)
+    
+    def test_partial_match(self):
+        ctx = get_context_length("anthropic/claude-sonnet-4")
+        self.assertEqual(ctx, 200000)
+    
+    def test_unknown_model(self):
+        ctx = get_context_length("unknown-model-xyz")
+        self.assertEqual(ctx, 4096)
+
+
+class TestModelMetadata(unittest.TestCase):
+    
+    def test_create(self):
+        meta = create_metadata("gpt-4o", "openai", 1000)
+        self.assertEqual(meta.context_length, 128000)
+        self.assertEqual(meta.current_tokens_used, 1000)
+        self.assertGreater(meta.remaining_tokens, 0)
+    
+    def test_utilization(self):
+        meta = create_metadata("gpt-4o", "openai", 64000)
+        self.assertAlmostEqual(meta.utilization_pct, 50.0, delta=1)
+
+
+class TestModelSwitch(unittest.TestCase):
+    
+    def test_safe_switch(self):
+        result = check_model_switch("gpt-3.5-turbo", "gpt-4o", 5000)
+        self.assertTrue(result["fits_in_new"])
+        self.assertIsNone(result["warning"])
+    
+    def test_truncation_warning(self):
+        result = check_model_switch("gpt-4o", "gpt-3.5-turbo", 20000)
+        self.assertFalse(result["fits_in_new"])
+        self.assertIsNotNone(result["warning"])
+        self.assertIn("truncate", result["warning"].lower())
+    
+    def test_downgrade_warning(self):
+        result = check_model_switch("claude-opus-4-6", "gpt-4", 5000)
+        self.assertIsNotNone(result["warning"])
+
+
+class TestSessionModelTracker(unittest.TestCase):
+    
+    def test_set_model(self):
+        tracker = SessionModelTracker("test")
+        tracker.set_model("gpt-4o", "openai")
+        self.assertEqual(tracker.metadata.model, "gpt-4o")
+    
+    def test_update_tokens(self):
+        tracker = SessionModelTracker("test")
+        tracker.set_model("gpt-4o")
+        tracker.update_tokens(5000)
+        self.assertEqual(tracker.metadata.current_tokens_used, 5000)
+    
+    def test_remaining(self):
+        tracker = SessionModelTracker("test")
+        tracker.set_model("gpt-4o")
+        tracker.update_tokens(10000)
+        self.assertGreater(tracker.get_remaining(), 0)
+    
+    def test_can_fit(self):
+        tracker = SessionModelTracker("test")
+        tracker.set_model("gpt-4o")
+        tracker.update_tokens(10000)
+        self.assertTrue(tracker.can_fit(5000))
+        self.assertFalse(tracker.can_fit(200000))
+    
+    def test_warning_low_context(self):
+        tracker = SessionModelTracker("test")
+        tracker.set_model("gpt-4o")
+        tracker.update_tokens(115000)  # ~90% used
+        warning = tracker.get_warning()
+        self.assertIsNotNone(warning)
+    
+    def test_model_switch_history(self):
+        tracker = SessionModelTracker("test")
+        tracker.set_model("gpt-4o", "openai")
+        tracker.update_tokens(5000)
+        tracker.set_model("claude-opus-4-6", "anthropic")
+        self.assertEqual(len(tracker.history), 1)
+        self.assertEqual(tracker.history[0]["from"], "gpt-4o")
+
+
+if __name__ == "__main__":
+    unittest.main()