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1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 8694261ee2 |
@@ -1,302 +0,0 @@
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"""Self-Modifying Prompt Engine — agent learns from its own failures.
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Analyzes session transcripts, identifies failure patterns, and generates
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prompt patches to prevent future failures.
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The loop: fail → analyze → rewrite → retry → verify improvement.
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Usage:
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from agent.self_modify import PromptLearner
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learner = PromptLearner()
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patches = learner.analyze_session(session_id)
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learner.apply_patches(patches)
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"""
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from __future__ import annotations
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import json
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import logging
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import os
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import re
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import time
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from dataclasses import dataclass, field
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Tuple
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logger = logging.getLogger(__name__)
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HERMES_HOME = Path(os.getenv("HERMES_HOME", Path.home() / ".hermes"))
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PATCHES_DIR = HERMES_HOME / "prompt_patches"
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ROLLBACK_DIR = HERMES_HOME / "prompt_rollback"
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@dataclass
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class FailurePattern:
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"""A detected failure pattern in session transcripts."""
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pattern_type: str # retry_loop, timeout, error_hallucination, context_loss
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description: str
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frequency: int
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example_messages: List[str] = field(default_factory=list)
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suggested_fix: str = ""
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@dataclass
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class PromptPatch:
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"""A modification to the system prompt based on failure analysis."""
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id: str
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failure_type: str
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original_rule: str
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new_rule: str
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confidence: float
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applied_at: Optional[float] = None
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reverted: bool = False
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# Failure detection patterns
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FAILURE_SIGNALS = {
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"retry_loop": {
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"patterns": [
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r"(?i)retry(?:ing)?\s*(?:attempt|again)",
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r"(?i)failed.*retrying",
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r"(?i)error.*again",
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r"(?i)attempt\s+\d+\s*(?:of|/)\s*\d+",
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],
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"description": "Agent stuck in retry loop",
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},
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"timeout": {
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"patterns": [
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r"(?i)timed?\s*out",
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r"(?i)deadline\s+exceeded",
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r"(?i)took\s+(?:too\s+)?long",
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],
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"description": "Operation timed out",
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},
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"hallucination": {
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"patterns": [
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r"(?i)i\s+(?:don't|do\s+not)\s+(?:have|see|find)\s+(?:any|that|this)\s+(?:information|data|file)",
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r"(?i)the\s+file\s+doesn't\s+exist",
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r"(?i)i\s+(?:made|invented|fabricated)\s+(?:that\s+up|this)",
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],
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"description": "Agent hallucinated or fabricated information",
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},
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"context_loss": {
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"patterns": [
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r"(?i)i\s+(?:don't|do\s+not)\s+(?:remember|recall|know)\s+(?:what|where|when|how)",
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r"(?i)could\s+you\s+remind\s+me",
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r"(?i)what\s+were\s+we\s+(?:doing|working|talking)\s+(?:on|about)",
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],
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"description": "Agent lost context from earlier in conversation",
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},
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"tool_failure": {
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"patterns": [
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r"(?i)tool\s+(?:call|execution)\s+failed",
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r"(?i)command\s+not\s+found",
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r"(?i)permission\s+denied",
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r"(?i)no\s+such\s+file",
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],
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"description": "Tool execution failed",
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},
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}
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# Prompt improvement templates
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PROMPT_FIXES = {
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"retry_loop": (
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"If an operation fails more than twice, stop retrying. "
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"Report the failure and ask the user for guidance. "
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"Do not enter retry loops — they waste tokens."
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),
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"timeout": (
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"For operations that may take long, set a timeout and report "
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"progress. If an operation takes more than 30 seconds, report "
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"what you've done so far and ask if you should continue."
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),
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"hallucination": (
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"If you cannot find information, say 'I don't know' or "
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"'I couldn't find that.' Never fabricate information. "
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"If a file doesn't exist, say so — don't guess its contents."
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),
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"context_loss": (
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"When you need context from earlier in the conversation, "
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"use session_search to find it. Don't ask the user to repeat themselves."
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),
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"tool_failure": (
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"If a tool fails, check the error message and try a different approach. "
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"Don't retry the exact same command — diagnose first."
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),
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}
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class PromptLearner:
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"""Analyze session transcripts and generate prompt improvements."""
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def __init__(self):
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PATCHES_DIR.mkdir(parents=True, exist_ok=True)
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ROLLBACK_DIR.mkdir(parents=True, exist_ok=True)
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def analyze_session(self, session_data: dict) -> List[FailurePattern]:
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"""Analyze a session for failure patterns.
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Args:
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session_data: Session dict with 'messages' list.
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Returns:
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List of detected failure patterns.
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"""
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messages = session_data.get("messages", [])
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patterns_found: Dict[str, FailurePattern] = {}
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for msg in messages:
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content = str(msg.get("content", ""))
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role = msg.get("role", "")
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# Only analyze assistant messages and tool results
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if role not in ("assistant", "tool"):
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continue
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for failure_type, config in FAILURE_SIGNALS.items():
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for pattern in config["patterns"]:
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if re.search(pattern, content):
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if failure_type not in patterns_found:
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patterns_found[failure_type] = FailurePattern(
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pattern_type=failure_type,
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description=config["description"],
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frequency=0,
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suggested_fix=PROMPT_FIXES.get(failure_type, ""),
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)
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patterns_found[failure_type].frequency += 1
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if len(patterns_found[failure_type].example_messages) < 3:
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patterns_found[failure_type].example_messages.append(
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content[:200]
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)
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break # One match per message per type is enough
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return list(patterns_found.values())
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def generate_patches(self, patterns: List[FailurePattern],
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min_confidence: float = 0.7) -> List[PromptPatch]:
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"""Generate prompt patches from failure patterns.
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Args:
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patterns: Detected failure patterns.
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min_confidence: Minimum confidence to generate a patch.
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Returns:
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List of prompt patches.
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"""
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patches = []
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for pattern in patterns:
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# Confidence based on frequency
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if pattern.frequency >= 3:
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confidence = 0.9
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elif pattern.frequency >= 2:
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confidence = 0.75
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else:
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confidence = 0.5
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if confidence < min_confidence:
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continue
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if not pattern.suggested_fix:
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continue
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patch = PromptPatch(
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id=f"{pattern.pattern_type}-{int(time.time())}",
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failure_type=pattern.pattern_type,
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original_rule="(missing — no existing rule for this pattern)",
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new_rule=pattern.suggested_fix,
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confidence=confidence,
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)
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patches.append(patch)
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return patches
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def apply_patches(self, patches: List[PromptPatch],
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prompt_path: Optional[str] = None) -> int:
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"""Apply patches to the system prompt.
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Args:
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patches: Patches to apply.
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prompt_path: Path to prompt file (default: ~/.hermes/system_prompt.md)
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Returns:
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Number of patches applied.
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"""
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if prompt_path is None:
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prompt_path = str(HERMES_HOME / "system_prompt.md")
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prompt_file = Path(prompt_path)
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# Backup current prompt
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if prompt_file.exists():
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backup = ROLLBACK_DIR / f"{prompt_file.name}.{int(time.time())}.bak"
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backup.write_text(prompt_file.read_text())
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# Read current prompt
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current = prompt_file.read_text() if prompt_file.exists() else ""
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# Apply patches
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applied = 0
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additions = []
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for patch in patches:
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if patch.new_rule not in current:
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additions.append(f"\n## Auto-learned: {patch.failure_type}\n{patch.new_rule}")
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patch.applied_at = time.time()
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applied += 1
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if additions:
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new_content = current + "\n".join(additions)
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prompt_file.write_text(new_content)
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# Log patches
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patches_file = PATCHES_DIR / f"patches-{int(time.time())}.json"
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with open(patches_file, "w") as f:
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json.dump([p.__dict__ for p in patches], f, indent=2, default=str)
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logger.info("Applied %d prompt patches", applied)
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return applied
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def rollback_last(self, prompt_path: Optional[str] = None) -> bool:
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"""Rollback to the most recent backup.
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Args:
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prompt_path: Path to prompt file.
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Returns:
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True if rollback succeeded.
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"""
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if prompt_path is None:
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prompt_path = str(HERMES_HOME / "system_prompt.md")
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backups = sorted(ROLLBACK_DIR.glob("*.bak"), reverse=True)
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if not backups:
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logger.warning("No backups to rollback to")
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return False
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latest = backups[0]
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Path(prompt_path).write_text(latest.read_text())
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logger.info("Rolled back to %s", latest.name)
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return True
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def learn_from_session(self, session_data: dict) -> Dict[str, Any]:
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"""Full learning cycle: analyze → patch → apply.
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Args:
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session_data: Session dict.
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Returns:
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Summary of what was learned and applied.
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"""
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patterns = self.analyze_session(session_data)
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patches = self.generate_patches(patterns)
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applied = self.apply_patches(patches)
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return {
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"patterns_detected": len(patterns),
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"patches_generated": len(patches),
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"patches_applied": applied,
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"patterns": [
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{"type": p.pattern_type, "frequency": p.frequency, "description": p.description}
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for p in patterns
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],
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}
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4
cli.py
4
cli.py
@@ -3611,7 +3611,7 @@ class HermesCLI:
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available, unavailable = check_tool_availability()
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# Filter to only those missing API keys (not system deps)
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api_key_missing = [u for u in unavailable if u["missing_vars"]]
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api_key_missing = [u for u in unavailable if u.get("env_vars")]
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if api_key_missing:
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self.console.print()
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@@ -3620,7 +3620,7 @@ class HermesCLI:
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tools_str = ", ".join(item["tools"][:2]) # Show first 2 tools
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if len(item["tools"]) > 2:
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tools_str += f", +{len(item['tools'])-2} more"
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self.console.print(f" [dim]• {item['name']}[/] [dim italic]({', '.join(item['missing_vars'])})[/]")
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self.console.print(f" [dim]• {item['name']}[/] [dim italic]({', '.join(item['env_vars'])})[/]")
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self.console.print("[dim] Run 'hermes setup' to configure[/]")
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except Exception:
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pass # Don't crash on import errors
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@@ -1,265 +0,0 @@
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#!/usr/bin/env python3
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"""Hermes MCP Server — expose hermes-agent tools to fleet peers.
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Runs as a standalone MCP server that other agents can connect to
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and invoke hermes tools remotely.
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Safe tools exposed:
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- terminal (safe commands only)
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- file_read, file_search
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- web_search, web_extract
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- session_search
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NOT exposed (internal tools):
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- approval, delegate, memory, config
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Usage:
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python -m tools.mcp_server --port 8081
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hermes mcp-server --port 8081
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python scripts/mcp_server.py --port 8081 --auth-key SECRET
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"""
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from __future__ import annotations
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import argparse
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import asyncio
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import json
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import logging
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import os
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import sys
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import time
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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logger = logging.getLogger(__name__)
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# Tools safe to expose to other agents
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SAFE_TOOLS = {
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"terminal": {
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"name": "terminal",
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"description": "Execute safe shell commands. Dangerous commands are blocked.",
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"parameters": {
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"type": "object",
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"properties": {
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"command": {"type": "string", "description": "Shell command to execute"},
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},
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"required": ["command"],
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},
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},
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"file_read": {
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"name": "file_read",
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"description": "Read the contents of a file.",
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"parameters": {
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "File path to read"},
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"offset": {"type": "integer", "description": "Start line", "default": 1},
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"limit": {"type": "integer", "description": "Max lines", "default": 200},
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},
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"required": ["path"],
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},
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},
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"file_search": {
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"name": "file_search",
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"description": "Search file contents using regex.",
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"parameters": {
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"type": "object",
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"properties": {
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"pattern": {"type": "string", "description": "Regex pattern"},
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"path": {"type": "string", "description": "Directory to search", "default": "."},
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},
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"required": ["pattern"],
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},
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},
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"web_search": {
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"name": "web_search",
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"description": "Search the web for information.",
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"parameters": {
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"type": "object",
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"properties": {
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"query": {"type": "string", "description": "Search query"},
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},
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"required": ["query"],
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},
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},
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"session_search": {
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"name": "session_search",
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"description": "Search past conversation sessions.",
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"parameters": {
|
||||
"type": "object",
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||||
"properties": {
|
||||
"query": {"type": "string", "description": "Search query"},
|
||||
"limit": {"type": "integer", "description": "Max results", "default": 3},
|
||||
},
|
||||
"required": ["query"],
|
||||
},
|
||||
},
|
||||
}
|
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# Tools explicitly blocked
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BLOCKED_TOOLS = {
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"approval", "delegate", "memory", "config", "skill_install",
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"mcp_tool", "cronjob", "tts", "send_message",
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}
|
||||
|
||||
|
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class MCPServer:
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"""Simple MCP-compatible server for exposing hermes tools."""
|
||||
|
||||
def __init__(self, host: str = "127.0.0.1", port: int = 8081,
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auth_key: Optional[str] = None):
|
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self._host = host
|
||||
self._port = port
|
||||
self._auth_key = auth_key or os.getenv("MCP_AUTH_KEY", "")
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||||
|
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async def handle_tools_list(self, request: dict) -> dict:
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"""Return available tools."""
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||||
tools = list(SAFE_TOOLS.values())
|
||||
return {"tools": tools}
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||||
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||||
async def handle_tools_call(self, request: dict) -> dict:
|
||||
"""Execute a tool call."""
|
||||
tool_name = request.get("name", "")
|
||||
arguments = request.get("arguments", {})
|
||||
|
||||
if tool_name in BLOCKED_TOOLS:
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||||
return {"error": f"Tool '{tool_name}' is not exposed via MCP"}
|
||||
if tool_name not in SAFE_TOOLS:
|
||||
return {"error": f"Unknown tool: {tool_name}"}
|
||||
|
||||
try:
|
||||
result = await self._execute_tool(tool_name, arguments)
|
||||
return {"content": [{"type": "text", "text": str(result)}]}
|
||||
except Exception as e:
|
||||
return {"error": str(e)}
|
||||
|
||||
async def _execute_tool(self, tool_name: str, arguments: dict) -> str:
|
||||
"""Execute a tool and return result."""
|
||||
if tool_name == "terminal":
|
||||
import subprocess
|
||||
cmd = arguments.get("command", "")
|
||||
# Block dangerous commands
|
||||
from tools.approval import detect_dangerous_command
|
||||
is_dangerous, _, desc = detect_dangerous_command(cmd)
|
||||
if is_dangerous:
|
||||
return f"BLOCKED: Dangerous command detected ({desc}). This tool only executes safe commands."
|
||||
result = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=30)
|
||||
return result.stdout or result.stderr or "(no output)"
|
||||
|
||||
elif tool_name == "file_read":
|
||||
path = arguments.get("path", "")
|
||||
offset = arguments.get("offset", 1)
|
||||
limit = arguments.get("limit", 200)
|
||||
with open(path) as f:
|
||||
lines = f.readlines()
|
||||
return "".join(lines[offset-1:offset-1+limit])
|
||||
|
||||
elif tool_name == "file_search":
|
||||
import re
|
||||
pattern = arguments.get("pattern", "")
|
||||
path = arguments.get("path", ".")
|
||||
results = []
|
||||
for p in Path(path).rglob("*.py"):
|
||||
try:
|
||||
content = p.read_text()
|
||||
for i, line in enumerate(content.split("\n"), 1):
|
||||
if re.search(pattern, line, re.IGNORECASE):
|
||||
results.append(f"{p}:{i}: {line.strip()}")
|
||||
if len(results) >= 20:
|
||||
break
|
||||
except Exception:
|
||||
continue
|
||||
if len(results) >= 20:
|
||||
break
|
||||
return "\n".join(results) or "No matches found"
|
||||
|
||||
elif tool_name == "web_search":
|
||||
try:
|
||||
from tools.web_tools import web_search
|
||||
return web_search(arguments.get("query", ""))
|
||||
except ImportError:
|
||||
return "Web search not available"
|
||||
|
||||
elif tool_name == "session_search":
|
||||
try:
|
||||
from tools.session_search_tool import session_search
|
||||
return session_search(
|
||||
query=arguments.get("query", ""),
|
||||
limit=arguments.get("limit", 3),
|
||||
)
|
||||
except ImportError:
|
||||
return "Session search not available"
|
||||
|
||||
return f"Tool {tool_name} not implemented"
|
||||
|
||||
async def start_http(self):
|
||||
"""Start HTTP server for MCP endpoints."""
|
||||
try:
|
||||
from aiohttp import web
|
||||
except ImportError:
|
||||
logger.error("aiohttp required: pip install aiohttp")
|
||||
return
|
||||
|
||||
app = web.Application()
|
||||
|
||||
async def handle_tools_list_route(request):
|
||||
if self._auth_key:
|
||||
auth = request.headers.get("Authorization", "")
|
||||
if auth != f"Bearer {self._auth_key}":
|
||||
return web.json_response({"error": "Unauthorized"}, status=401)
|
||||
result = await self.handle_tools_list({})
|
||||
return web.json_response(result)
|
||||
|
||||
async def handle_tools_call_route(request):
|
||||
if self._auth_key:
|
||||
auth = request.headers.get("Authorization", "")
|
||||
if auth != f"Bearer {self._auth_key}":
|
||||
return web.json_response({"error": "Unauthorized"}, status=401)
|
||||
body = await request.json()
|
||||
result = await self.handle_tools_call(body)
|
||||
return web.json_response(result)
|
||||
|
||||
async def handle_health(request):
|
||||
return web.json_response({"status": "ok", "tools": len(SAFE_TOOLS)})
|
||||
|
||||
app.router.add_get("/mcp/tools", handle_tools_list_route)
|
||||
app.router.add_post("/mcp/tools/call", handle_tools_call_route)
|
||||
app.router.add_get("/health", handle_health)
|
||||
|
||||
runner = web.AppRunner(app)
|
||||
await runner.setup()
|
||||
site = web.TCPSite(runner, self._host, self._port)
|
||||
await site.start()
|
||||
logger.info("MCP server on http://%s:%s", self._host, self._port)
|
||||
logger.info("Tools: %s", ", ".join(SAFE_TOOLS.keys()))
|
||||
if self._auth_key:
|
||||
logger.info("Auth: Bearer token required")
|
||||
else:
|
||||
logger.warning("Auth: No MCP_AUTH_KEY set — server is open")
|
||||
|
||||
try:
|
||||
await asyncio.Event().wait()
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
finally:
|
||||
await runner.cleanup()
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description="Hermes MCP Server")
|
||||
parser.add_argument("--host", default="127.0.0.1")
|
||||
parser.add_argument("--port", type=int, default=8081)
|
||||
parser.add_argument("--auth-key", default=None, help="Bearer token for auth")
|
||||
args = parser.parse_args()
|
||||
|
||||
logging.basicConfig(level=logging.INFO,
|
||||
format="%(asctime)s [%(name)s] %(levelname)s: %(message)s")
|
||||
|
||||
server = MCPServer(host=args.host, port=args.port, auth_key=args.auth_key)
|
||||
print(f"Starting MCP server on http://{args.host}:{args.port}")
|
||||
print(f"Exposed tools: {', '.join(SAFE_TOOLS.keys())}")
|
||||
asyncio.run(server.start_http())
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -201,31 +201,8 @@ def _get_command_timeout() -> int:
|
||||
|
||||
|
||||
def _get_vision_model() -> Optional[str]:
|
||||
"""Model for browser_vision (screenshot analysis — multimodal).
|
||||
|
||||
Priority:
|
||||
1. AUXILIARY_VISION_MODEL env var (explicit override)
|
||||
2. Gemma 4 (native multimodal, no model switching)
|
||||
3. Ollama local vision models
|
||||
4. None (fallback to text-only snapshot)
|
||||
"""
|
||||
# Explicit override always wins
|
||||
explicit = os.getenv("AUXILIARY_VISION_MODEL", "").strip()
|
||||
if explicit:
|
||||
return explicit
|
||||
|
||||
# Prefer Gemma 4 (native multimodal — no separate vision model needed)
|
||||
gemma = os.getenv("GEMMA_VISION_MODEL", "").strip()
|
||||
if gemma:
|
||||
return gemma
|
||||
|
||||
# Check for Ollama vision models
|
||||
ollama_vision = os.getenv("OLLAMA_VISION_MODEL", "").strip()
|
||||
if ollama_vision:
|
||||
return ollama_vision
|
||||
|
||||
# Default: None (text-only fallback)
|
||||
return None
|
||||
"""Model for browser_vision (screenshot analysis — multimodal)."""
|
||||
return os.getenv("AUXILIARY_VISION_MODEL", "").strip() or None
|
||||
|
||||
|
||||
def _get_extraction_model() -> Optional[str]:
|
||||
|
||||
Reference in New Issue
Block a user