Compare commits
2 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 10d7cd7d0c | |||
| 28c285a8b6 |
@@ -1,221 +0,0 @@
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"""
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Session Compaction with Fact Extraction — #748
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Before compressing a long conversation, extracts durable facts
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(user preferences, corrections, project details) and saves them
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to the fact store. Then compresses the conversation.
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This ensures key information survives context limits.
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Usage:
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from agent.session_compaction import compact_session
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# In the conversation loop, when context is near limit:
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compact_session(messages, fact_store)
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"""
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import json
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import re
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from typing import Any, Dict, List, Optional, Tuple
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# ---------------------------------------------------------------------------
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# Fact Extraction Patterns
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# ---------------------------------------------------------------------------
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# Patterns that indicate durable facts worth preserving
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_FACT_PATTERNS = [
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# User preferences
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(r"(?:i prefer|i like|i always|my preference is|remember that i)\s+(.+?)(?:\.|$)", "user_pref"),
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(r"(?:call me|my name is|i\'m)\s+([A-Z][a-z]+)", "user_name"),
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(r"(?:don\'t|do not|never)\s+(?:use|do|show|tell)\s+(.+?)(?:\.|$)", "user_constraint"),
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# Corrections
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(r"(?:actually|no,?|correction:?)\s+(.+?)(?:\.|$)", "correction"),
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(r"(?:that\'s wrong|not correct|i meant)\s+(.+?)(?:\.|$)", "correction"),
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# Project facts
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(r"(?:the project|this repo|the codebase)\s+(?:is|has|uses|runs)\s+(.+?)(?:\.|$)", "project_fact"),
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(r"(?:we use|our stack is|deployed on)\s+(.+?)(?:\.|$)", "project_fact"),
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# Technical facts
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(r"(?:the server|the service|the endpoint)\s+(?:is|runs on|listens on)\s+(.+?)(?:\.|$)", "technical"),
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(r"(?:port|url|address|host)\s*(?::|is|=)\s*(.+?)(?:\.|$)", "technical"),
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]
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def extract_facts_from_messages(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""
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Scan conversation messages for durable facts.
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Returns list of fact dicts suitable for fact_store.
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"""
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facts = []
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seen = set() # Deduplicate
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for msg in messages:
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if msg.get("role") != "user":
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continue
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content = msg.get("content", "")
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if not isinstance(content, str) or len(content) < 10:
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continue
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for pattern, category in _FACT_PATTERNS:
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matches = re.findall(pattern, content, re.IGNORECASE)
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for match in matches:
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if isinstance(match, tuple):
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match = match[0] if match else ""
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fact_text = match.strip()
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if len(fact_text) < 5 or len(fact_text) > 200:
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continue
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# Deduplicate
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dedup_key = f"{category}:{fact_text.lower()}"
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if dedup_key in seen:
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continue
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seen.add(dedup_key)
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facts.append({
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"content": fact_text,
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"category": category,
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"source": "session_compaction",
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"trust": 0.7, # Medium trust — extracted, not explicitly stated
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})
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return facts
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def extract_preferences(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""Extract user preferences specifically."""
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prefs = []
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pref_patterns = [
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r"(?:i prefer|i like|i want|use|always)\s+(.+?)(?:\.|$)",
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r"(?:my (?:preferred|favorite|default))\s+(?:is|are)\s+(.+?)(?:\.|$)",
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r"(?:set|configure|make)\s+(?:it to|the default to)\s+(.+?)(?:\.|$)",
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]
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for msg in messages:
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if msg.get("role") != "user":
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continue
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content = msg.get("content", "")
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if not isinstance(content, str):
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continue
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for pattern in pref_patterns:
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matches = re.findall(pattern, content, re.IGNORECASE)
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for match in matches:
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if isinstance(match, str) and len(match) > 5 and len(match) < 200:
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prefs.append({
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"content": match.strip(),
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"category": "user_pref",
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"source": "session_compaction",
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"trust": 0.8,
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})
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return prefs
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def compact_session(
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messages: List[Dict[str, Any]],
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fact_store: Any = None,
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keep_recent: int = 10,
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) -> Tuple[List[Dict[str, Any]], int]:
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"""
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Compact a session by extracting facts and compressing old messages.
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Args:
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messages: Full conversation history
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fact_store: Optional fact_store instance for saving facts
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keep_recent: Number of recent messages to keep uncompressed
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Returns:
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Tuple of (compacted_messages, facts_extracted)
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"""
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if len(messages) <= keep_recent * 2:
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return messages, 0
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# Split into old (to compress) and recent (to keep)
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split_point = len(messages) - keep_recent
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old_messages = messages[:split_point]
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recent_messages = messages[split_point:]
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# Extract facts from old messages
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facts = extract_facts_from_messages(old_messages)
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prefs = extract_preferences(old_messages)
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all_facts = facts + prefs
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# Save facts to store if available
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saved_count = 0
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if fact_store and all_facts:
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for fact in all_facts:
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try:
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if hasattr(fact_store, 'store'):
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fact_store.store(
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content=fact["content"],
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category=fact["category"],
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tags=["session_compaction"],
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)
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saved_count += 1
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elif hasattr(fact_store, 'add'):
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fact_store.add(fact["content"])
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saved_count += 1
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except Exception:
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pass # Don't let fact saving block compaction
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# Create summary of old messages
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summary_parts = []
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if saved_count > 0:
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summary_parts.append(f"[Session compacted: {saved_count} facts extracted and saved]")
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# Count message types
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user_msgs = sum(1 for m in old_messages if m.get("role") == "user")
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asst_msgs = sum(1 for m in old_messages if m.get("role") == "assistant")
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summary_parts.append(f"[Previous conversation: {user_msgs} user messages, {asst_msgs} assistant responses]")
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summary = " ".join(summary_parts)
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# Build compacted messages
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compacted = []
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# Add summary as system message
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if summary:
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compacted.append({
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"role": "system",
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"content": summary,
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"_compacted": True,
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})
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# Add extracted facts as system context
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if all_facts:
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facts_text = "Known facts from previous conversation:\n"
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for fact in all_facts[:20]: # Limit to 20 facts
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facts_text += f"- [{fact['category']}] {fact['content']}\n"
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compacted.append({
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"role": "system",
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"content": facts_text,
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"_extracted_facts": True,
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})
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# Add recent messages
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compacted.extend(recent_messages)
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return compacted, saved_count
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def should_compact(messages: List[Dict[str, Any]], max_tokens: int = 80000) -> bool:
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"""
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Determine if compaction is needed based on message count/length.
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Simple heuristic: compact if we have many messages or very long content.
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"""
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if len(messages) < 50:
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return False
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# Estimate token count (rough: 4 chars per token)
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total_chars = sum(len(str(m.get("content", ""))) for m in messages)
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estimated_tokens = total_chars // 4
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return estimated_tokens > max_tokens * 0.8 # Compact at 80% of limit
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55
tests/test_error_classifier.py
Normal file
55
tests/test_error_classifier.py
Normal file
@@ -0,0 +1,55 @@
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"""
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Tests for error classification (#752).
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"""
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import pytest
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from tools.error_classifier import classify_error, ErrorCategory, ErrorClassification
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class TestErrorClassification:
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def test_timeout_is_retryable(self):
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err = Exception("Connection timed out")
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result = classify_error(err)
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assert result.category == ErrorCategory.RETRYABLE
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assert result.should_retry is True
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def test_429_is_retryable(self):
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err = Exception("Rate limit exceeded")
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result = classify_error(err, response_code=429)
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assert result.category == ErrorCategory.RETRYABLE
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assert result.should_retry is True
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def test_404_is_permanent(self):
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err = Exception("Not found")
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result = classify_error(err, response_code=404)
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assert result.category == ErrorCategory.PERMANENT
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assert result.should_retry is False
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def test_403_is_permanent(self):
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err = Exception("Forbidden")
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result = classify_error(err, response_code=403)
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assert result.category == ErrorCategory.PERMANENT
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assert result.should_retry is False
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def test_500_is_retryable(self):
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err = Exception("Internal server error")
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result = classify_error(err, response_code=500)
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assert result.category == ErrorCategory.RETRYABLE
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assert result.should_retry is True
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def test_schema_error_is_permanent(self):
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err = Exception("Schema validation failed")
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result = classify_error(err)
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assert result.category == ErrorCategory.PERMANENT
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assert result.should_retry is False
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def test_unknown_is_retryable_with_caution(self):
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err = Exception("Some unknown error")
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result = classify_error(err)
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assert result.category == ErrorCategory.UNKNOWN
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assert result.should_retry is True
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assert result.max_retries == 1
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if __name__ == "__main__":
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pytest.main([__file__])
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@@ -1,84 +0,0 @@
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"""Tests for session compaction with fact extraction (#748)."""
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from agent.session_compaction import (
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extract_facts_from_messages,
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extract_preferences,
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compact_session,
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should_compact,
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)
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def test_extract_preferences():
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msgs = [
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{"role": "user", "content": "I prefer using Python for this"},
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{"role": "assistant", "content": "OK"},
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{"role": "user", "content": "Always use tabs, not spaces"},
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]
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prefs = extract_preferences(msgs)
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assert len(prefs) >= 1
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def test_extract_facts():
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msgs = [
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{"role": "user", "content": "The server runs on port 8080"},
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{"role": "user", "content": "Actually, the port is 8081"},
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{"role": "user", "content": "Hello"}, # Too short, should be skipped
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]
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facts = extract_facts_from_messages(msgs)
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assert len(facts) >= 1
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assert any("technical" in f["category"] for f in facts)
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def test_extract_deduplicates():
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msgs = [
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{"role": "user", "content": "I prefer Python"},
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{"role": "user", "content": "I prefer Python"},
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]
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facts = extract_facts_from_messages(msgs)
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assert len(facts) == 1
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def test_compact_session():
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messages = []
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for i in range(30):
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messages.append({"role": "user", "content": f"Message {i}: I prefer Python for server {i}"})
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messages.append({"role": "assistant", "content": f"Response {i}"})
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compacted, count = compact_session(messages, keep_recent=10)
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assert len(compacted) < len(messages)
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assert count >= 0
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def test_compact_keeps_recent():
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messages = []
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for i in range(30):
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messages.append({"role": "user", "content": f"Message {i}"})
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messages.append({"role": "assistant", "content": f"Response {i}"})
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compacted, _ = compact_session(messages, keep_recent=10)
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# Should have summary + facts + 10 recent
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assert len(compacted) >= 10
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def test_should_compact_short():
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messages = [{"role": "user", "content": "hi"} for _ in range(10)]
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assert not should_compact(messages)
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def test_should_compact_long():
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messages = [{"role": "user", "content": "x" * 1000} for _ in range(100)]
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assert should_compact(messages)
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if __name__ == "__main__":
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tests = [test_extract_preferences, test_extract_facts, test_extract_deduplicates,
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test_compact_session, test_compact_keeps_recent, test_should_compact_short, test_should_compact_long]
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for t in tests:
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print(f"Running {t.__name__}...")
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t()
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print(" PASS")
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print("\nAll tests passed.")
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233
tools/error_classifier.py
Normal file
233
tools/error_classifier.py
Normal file
@@ -0,0 +1,233 @@
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"""
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Tool Error Classification — Retryable vs Permanent.
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Classifies tool errors so the agent retries transient errors
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but gives up on permanent ones immediately.
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"""
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import logging
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import re
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import time
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from dataclasses import dataclass
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from enum import Enum
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from typing import Optional, Dict, Any
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logger = logging.getLogger(__name__)
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class ErrorCategory(Enum):
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"""Error category classification."""
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RETRYABLE = "retryable"
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PERMANENT = "permanent"
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UNKNOWN = "unknown"
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@dataclass
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class ErrorClassification:
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"""Result of error classification."""
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category: ErrorCategory
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reason: str
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should_retry: bool
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max_retries: int
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backoff_seconds: float
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error_code: Optional[int] = None
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error_type: Optional[str] = None
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# Retryable error patterns
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_RETRYABLE_PATTERNS = [
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# HTTP status codes
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(r"\b429\b", "rate limit", 3, 5.0),
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(r"\b500\b", "server error", 3, 2.0),
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(r"\b502\b", "bad gateway", 3, 2.0),
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(r"\b503\b", "service unavailable", 3, 5.0),
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(r"\b504\b", "gateway timeout", 3, 5.0),
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|
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# Timeout patterns
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(r"timeout", "timeout", 3, 2.0),
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(r"timed out", "timeout", 3, 2.0),
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(r"TimeoutExpired", "timeout", 3, 2.0),
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|
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# Connection errors
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(r"connection refused", "connection refused", 2, 5.0),
|
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(r"connection reset", "connection reset", 2, 2.0),
|
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(r"network unreachable", "network unreachable", 2, 10.0),
|
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(r"DNS", "DNS error", 2, 5.0),
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|
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# Transient errors
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(r"temporary", "temporary error", 2, 2.0),
|
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(r"transient", "transient error", 2, 2.0),
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(r"retry", "retryable", 2, 2.0),
|
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]
|
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|
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# Permanent error patterns
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_PERMANENT_PATTERNS = [
|
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# HTTP status codes
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(r"\b400\b", "bad request", "Invalid request parameters"),
|
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(r"\b401\b", "unauthorized", "Authentication failed"),
|
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(r"\b403\b", "forbidden", "Access denied"),
|
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(r"\b404\b", "not found", "Resource not found"),
|
||||
(r"\b405\b", "method not allowed", "HTTP method not supported"),
|
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(r"\b409\b", "conflict", "Resource conflict"),
|
||||
(r"\b422\b", "unprocessable", "Validation error"),
|
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|
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# Schema/validation errors
|
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(r"schema", "schema error", "Invalid data schema"),
|
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(r"validation", "validation error", "Input validation failed"),
|
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(r"invalid.*json", "JSON error", "Invalid JSON"),
|
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(r"JSONDecodeError", "JSON error", "JSON parsing failed"),
|
||||
|
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# Authentication
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(r"api.?key", "API key error", "Invalid or missing API key"),
|
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(r"token.*expir", "token expired", "Authentication token expired"),
|
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(r"permission", "permission error", "Insufficient permissions"),
|
||||
|
||||
# Not found patterns
|
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(r"not found", "not found", "Resource does not exist"),
|
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(r"does not exist", "not found", "Resource does not exist"),
|
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(r"no such file", "file not found", "File does not exist"),
|
||||
|
||||
# Quota/billing
|
||||
(r"quota", "quota exceeded", "Usage quota exceeded"),
|
||||
(r"billing", "billing error", "Billing issue"),
|
||||
(r"insufficient.*funds", "billing error", "Insufficient funds"),
|
||||
]
|
||||
|
||||
|
||||
def classify_error(error: Exception, response_code: Optional[int] = None) -> ErrorClassification:
|
||||
"""
|
||||
Classify an error as retryable or permanent.
|
||||
|
||||
Args:
|
||||
error: The exception that occurred
|
||||
response_code: HTTP response code if available
|
||||
|
||||
Returns:
|
||||
ErrorClassification with retry guidance
|
||||
"""
|
||||
error_str = str(error).lower()
|
||||
error_type = type(error).__name__
|
||||
|
||||
# Check response code first
|
||||
if response_code:
|
||||
if response_code in (429, 500, 502, 503, 504):
|
||||
return ErrorClassification(
|
||||
category=ErrorCategory.RETRYABLE,
|
||||
reason=f"HTTP {response_code} - transient server error",
|
||||
should_retry=True,
|
||||
max_retries=3,
|
||||
backoff_seconds=5.0 if response_code == 429 else 2.0,
|
||||
error_code=response_code,
|
||||
error_type=error_type,
|
||||
)
|
||||
elif response_code in (400, 401, 403, 404, 405, 409, 422):
|
||||
return ErrorClassification(
|
||||
category=ErrorCategory.PERMANENT,
|
||||
reason=f"HTTP {response_code} - client error",
|
||||
should_retry=False,
|
||||
max_retries=0,
|
||||
backoff_seconds=0,
|
||||
error_code=response_code,
|
||||
error_type=error_type,
|
||||
)
|
||||
|
||||
# Check retryable patterns
|
||||
for pattern, reason, max_retries, backoff in _RETRYABLE_PATTERNS:
|
||||
if re.search(pattern, error_str, re.IGNORECASE):
|
||||
return ErrorClassification(
|
||||
category=ErrorCategory.RETRYABLE,
|
||||
reason=reason,
|
||||
should_retry=True,
|
||||
max_retries=max_retries,
|
||||
backoff_seconds=backoff,
|
||||
error_type=error_type,
|
||||
)
|
||||
|
||||
# Check permanent patterns
|
||||
for pattern, error_code, reason in _PERMANENT_PATTERNS:
|
||||
if re.search(pattern, error_str, re.IGNORECASE):
|
||||
return ErrorClassification(
|
||||
category=ErrorCategory.PERMANENT,
|
||||
reason=reason,
|
||||
should_retry=False,
|
||||
max_retries=0,
|
||||
backoff_seconds=0,
|
||||
error_type=error_type,
|
||||
)
|
||||
|
||||
# Default: unknown, treat as retryable with caution
|
||||
return ErrorClassification(
|
||||
category=ErrorCategory.UNKNOWN,
|
||||
reason=f"Unknown error type: {error_type}",
|
||||
should_retry=True,
|
||||
max_retries=1,
|
||||
backoff_seconds=1.0,
|
||||
error_type=error_type,
|
||||
)
|
||||
|
||||
|
||||
def execute_with_retry(
|
||||
func,
|
||||
*args,
|
||||
max_retries: int = 3,
|
||||
backoff_base: float = 1.0,
|
||||
**kwargs,
|
||||
) -> Any:
|
||||
"""
|
||||
Execute a function with automatic retry on retryable errors.
|
||||
|
||||
Args:
|
||||
func: Function to execute
|
||||
*args: Function arguments
|
||||
max_retries: Maximum retry attempts
|
||||
backoff_base: Base backoff time in seconds
|
||||
**kwargs: Function keyword arguments
|
||||
|
||||
Returns:
|
||||
Function result
|
||||
|
||||
Raises:
|
||||
Exception: If permanent error or max retries exceeded
|
||||
"""
|
||||
last_error = None
|
||||
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
return func(*args, **kwargs)
|
||||
except Exception as e:
|
||||
last_error = e
|
||||
|
||||
# Classify the error
|
||||
classification = classify_error(e)
|
||||
|
||||
logger.info(
|
||||
"Attempt %d/%d failed: %s (%s, retryable: %s)",
|
||||
attempt + 1, max_retries + 1,
|
||||
classification.reason,
|
||||
classification.category.value,
|
||||
classification.should_retry,
|
||||
)
|
||||
|
||||
# If permanent error, fail immediately
|
||||
if not classification.should_retry:
|
||||
logger.error("Permanent error: %s", classification.reason)
|
||||
raise
|
||||
|
||||
# If this was the last attempt, raise
|
||||
if attempt >= max_retries:
|
||||
logger.error("Max retries (%d) exceeded", max_retries)
|
||||
raise
|
||||
|
||||
# Calculate backoff with exponential increase
|
||||
backoff = backoff_base * (2 ** attempt)
|
||||
logger.info("Retrying in %.1fs...", backoff)
|
||||
time.sleep(backoff)
|
||||
|
||||
# Should not reach here, but just in case
|
||||
raise last_error
|
||||
|
||||
|
||||
def format_error_report(classification: ErrorClassification) -> str:
|
||||
"""Format error classification as a report string."""
|
||||
icon = "🔄" if classification.should_retry else "❌"
|
||||
return f"{icon} {classification.category.value}: {classification.reason}"
|
||||
Reference in New Issue
Block a user