Initial commit: 25 scripts Python sauvegardés

Date: 2026-08-28 11:43:34 EDT

skills/devops/jarvis/templates/pipecat-bot-minimal.py

@@ -0,0 +1,83 @@
+#!/usr/bin/env python3
+"""
+Pipecat Bot Template — OpenAILLMService avec API Hermes
+========================================================
+Template minimal pour un bot texte via WebSocket.
+Adapté de ~/workspace/jarvis-pipecat/bot.py
+
+Prérequis: pipecat-ai[websocket]>=1.4.0, openai, uvicorn, websockets
+"""
+
+import json, os, subprocess, sys
+from fastapi import FastAPI, WebSocket
+from fastapi.responses import HTMLResponse
+import uvicorn
+
+# ⚠️ Pipecat 1.4.0 : utiliser `import module as m` (from-import cassé)
+import pipecat.frames.frames as pframes
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.frame_processor import FrameProcessor, FrameDirection
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams, FastAPIWebsocketTransport
+
+# ─── Config ──────────────────────────────────────────────────
+PORT = int(os.environ.get("BOT_PORT", "7081"))
+HERMES_URL = os.environ.get("HERMES_API_URL", "http://localhost:8642/v1")
+HERMES_KEY = os.environ.get("HERMES_API_KEY", "")
+SYSTEM_PROMPT = "Tu es un assistant vocal concis. Parle en français, 3 phrases max."
+
+
+# ─── Processeur custom : texte → LLMMessagesFrame ────────────
+class TextToLLMProcessor(FrameProcessor):
+    """Remplace le context aggregator (buggé en 1.4.0)."""
+
+    def __init__(self, system_prompt: str):
+        super().__init__()
+        self._messages = [{"role": "system", "content": system_prompt}]
+
+    async def process_frame(self, frame, direction):
+        await self.push_frame(frame, direction)
+        if isinstance(frame, pframes.InputTransportMessageFrame):
+            text = frame.message
+            if isinstance(text, str) and text.strip():
+                self._messages.append({"role": "user", "content": text})
+                if len(self._messages) > 21:
+                    self._messages = [self._messages[0]] + self._messages[-20:]
+                await self.push_frame(pframes.LLMMessagesFrame(messages=list(self._messages)))
+        elif isinstance(frame, pframes.LLMFullResponseStartFrame):
+            self._response_text = ""
+        elif isinstance(frame, pframes.TextFrame):
+            if hasattr(self, '_response_text'):
+                self._response_text += frame.text
+        elif isinstance(frame, pframes.LLMFullResponseEndFrame):
+            if hasattr(self, '_response_text') and self._response_text.strip():
+                self._messages.append({"role": "assistant", "content": self._response_text.strip()})
+                del self._response_text
+
+
+# ─── App ─────────────────────────────────────────────────────
+app = FastAPI()
+
+
+@app.websocket("/ws")
+async def ws_endpoint(websocket: WebSocket):
+    transport = FastAPIWebsocketTransport(
+        websocket=websocket,
+        params=FastAPIWebsocketParams(add_wav_header=False, session_timeout=None),
+    )
+    llm = OpenAILLMService(
+        api_key=HERMES_KEY,
+        base_url=HERMES_URL,
+        settings=OpenAILLMService.Settings(model="Hermes Agent", temperature=0.8, max_tokens=300, system_instruction=SYSTEM_PROMPT),
+    )
+    proc = TextToLLMProcessor(SYSTEM_PROMPT)
+    pipeline = Pipeline(processors=[transport.input(), proc, llm, transport.output()])
+    task = PipelineTask(pipeline)
+    runner = PipelineRunner()
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=PORT)

skills/devops/skill-integrity/references/corruption-scanner.py

@@ -0,0 +1,88 @@
+#!/usr/bin/env python3
+"""Scan ~/.hermes/skills/ for corrupted .py scripts.
+
+Usage: python corruption-scanner.py [--fix-dir /path/to/output]
+Output: JSON summary of clean vs corrupted files.
+"""
+import json, os, sys
+from pathlib import Path
+
+def scan_skills(base_dir):
+    results = {"clean": [], "corrupted": [], "skipped": []}
+    
+    for root, dirs, files in os.walk(base_dir):
+        if '__pycache__' in root or 'venv' in root:
+            continue
+        
+        for fname in files:
+            if not fname.endswith('.py'):
+                continue
+            
+            fpath = os.path.join(root, fname)
+            size = os.path.getsize(fpath)
+            
+            # Skip empty __init__.py (normal)
+            if fname == '__init__.py' and size <= 50:
+                results["skipped"].append({"path": fpath, "reason": "empty __init__.py"})
+                continue
+            
+            try:
+                with open(fpath, 'r') as f:
+                    content = f.read(1000)
+                
+                first_line = content.strip().split('\n')[0].lower()
+                
+                if '% partial rewrite' in first_line[:200] or 'latex' in first_line[:200]:
+                    results["corrupted"].append({
+                        "path": fpath,
+                        "size": size,
+                        "type": "latex_contamination"
+                    })
+                elif first_line.startswith('%pdf') or '%PDF' in first_line[:20]:
+                    results["corrupted"].append({
+                        "path": fpath,
+                        "size": size,
+                        "type": "pdf_binary"
+                    })
+                elif len(content) > 200000:
+                    results["corrupted"].append({
+                        "path": fpath,
+                        "size": size,
+                        "type": "oversized"
+                    })
+                else:
+                    results["clean"].append({"path": fpath, "size": size})
+                    
+            except UnicodeDecodeError:
+                results["skipped"].append({"path": fpath, "reason": "binary file"})
+            except Exception as e:
+                results["skipped"].append({"path": fpath, "reason": str(e)})
+    
+    return results
+
+if __name__ == '__main__':
+    base = os.environ.get('HERMES_HOME', str(Path.home() / '.hermes'))
+    skills_dir = os.path.join(base, 'skills')
+    
+    fix_dir = None
+    args = sys.argv[1:]
+    if '--fix-dir' in args:
+        idx = args.index('--fix-dir')
+        if idx + 1 < len(args):
+            fix_dir = args[idx + 1]
+    
+    results = scan_skills(skills_dir)
+    
+    print(json.dumps(results, indent=2, ensure_ascii=False))
+    
+    # Summary
+    print(f"\n{'='*60}")
+    print(f"Scan complete:")
+    print(f"  Clean: {len(results['clean'])}")
+    print(f"  Corrupted: {len(results['corrupted'])}")
+    print(f"  Skipped: {len(results['skipped'])}")
+    
+    if results['corrupted']:
+        print(f"\nCorrupted files:")
+        for f in results['corrupted']:
+            print(f"  ❌ {f['path']} ({f['size']:,} bytes) - {f['type']}")