feat: WorkflowRunner, matching sémantique et replay distant (P0-4, P0-6, P0-7)
P0-4: WorkflowRunner — orchestrateur de replay intelligent - Boucle capture → match FAISS → résolution sémantique → exécution - Mode dry_run, substitution de variables, anti-boucle (max 200 steps) - Découplé de pyautogui via executor_callback P0-6: Unification des répertoires workflows - SemanticMatcher scanne data/workflows/ + data/training/workflows/ - Auto-reload sur changement de répertoire (60s) P0-7: Matching sémantique via Ollama - Pré-filtrage Jaccard + re-ranking LLM (qwen2.5:7b) - Score final : 40% Jaccard + 60% LLM, fallback si Ollama indisponible Agent Chat: exécution distante via streaming server - POST http://localhost:5005/api/v1/traces/stream/replay - Fallback sur exécution locale si serveur indisponible Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Dom
@@ -14,7 +14,7 @@ Composants intégrés:
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Usage:
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python agent_chat/app.py
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Puis ouvrir: http://localhost:5002
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Puis ouvrir: http://localhost:5004
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Auteur: Dom - Janvier 2026
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"""
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@@ -28,6 +28,8 @@ from pathlib import Path
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from datetime import datetime
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from typing import Dict, Any, List, Optional
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import requests as http_requests # Pour les appels au streaming server
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from flask import Flask, render_template, request, jsonify
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from flask_socketio import SocketIO, emit
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@@ -83,6 +85,11 @@ action_executor = None
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execution_loop = None
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screen_capturer = None
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# URL du streaming server (Agent V1) pour l'exécution distante
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STREAMING_SERVER_URL = os.environ.get(
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"RPA_STREAMING_URL", "http://localhost:5005"
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)
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execution_status = {
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"running": False,
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"workflow": None,
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@@ -99,10 +106,22 @@ def init_system():
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global intent_parser, confirmation_loop, response_generator, conversation_manager
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global autonomous_planner
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# 1. SemanticMatcher
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# 1. SemanticMatcher — multi-répertoires (P0-6) + matching LLM (P0-7)
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# Scan data/workflows/ + data/training/workflows/ + data/training/live_sessions/workflows/
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try:
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matcher = SemanticMatcher("data/workflows")
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logger.info(f"✓ SemanticMatcher: {len(matcher.get_all_workflows())} workflows")
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matcher = SemanticMatcher(
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workflows_dir=None, # None = scan tous les répertoires par défaut
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use_llm=True, # Matching sémantique via Ollama (P0-7)
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llm_model="qwen2.5:7b",
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)
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dirs_info = matcher.get_directories()
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dirs_summary = ", ".join(
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f"{d['path']}({d['workflow_count']})" for d in dirs_info if d['exists']
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)
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logger.info(
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f"✓ SemanticMatcher: {len(matcher.get_all_workflows())} workflows "
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f"[{dirs_summary}]"
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)
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except Exception as e:
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logger.error(f"✗ SemanticMatcher: {e}")
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matcher = None
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@@ -267,20 +286,55 @@ def api_status():
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@app.route('/api/workflows')
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def api_workflows():
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"""Liste des workflows."""
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"""Liste des workflows (tous répertoires confondus)."""
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if not matcher:
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return jsonify({"workflows": []})
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return jsonify({"workflows": [], "directories": []})
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workflows = []
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for wf in matcher.get_all_workflows():
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workflows.append({
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"id": wf.workflow_id,
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"name": wf.name,
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"description": wf.description,
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"tags": wf.tags
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"tags": wf.tags,
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"source": wf.source_dir,
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})
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return jsonify({"workflows": workflows})
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return jsonify({
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"workflows": workflows,
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"directories": matcher.get_directories(),
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})
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@app.route('/api/workflows/refresh', methods=['POST'])
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def api_workflows_refresh():
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"""
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Forcer le rechargement des workflows depuis tous les répertoires.
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Utile après qu'un nouveau workflow a été appris par le StreamProcessor.
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"""
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if not matcher:
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return jsonify({"success": False, "error": "SemanticMatcher non initialisé"})
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try:
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count = matcher.reload_workflows()
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# Re-injecter les workflows dans l'intent_parser (contexte LLM)
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if intent_parser:
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workflows_for_llm = [
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{"name": wf.name, "description": wf.description, "tags": wf.tags}
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for wf in matcher.get_all_workflows()
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]
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intent_parser.set_workflows(workflows_for_llm)
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return jsonify({
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"success": True,
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"workflows_count": count,
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"directories": matcher.get_directories(),
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})
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except Exception as e:
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logger.error(f"Erreur rechargement workflows: {e}")
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return jsonify({"success": False, "error": str(e)})
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@app.route('/api/search', methods=['POST'])
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@@ -893,12 +947,79 @@ def handle_cancel():
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# Exécution de workflow
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# =============================================================================
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def _try_streaming_server_replay(workflow_id: str, params: Dict[str, Any]) -> Optional[Dict[str, Any]]:
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"""
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Tenter d'exécuter un workflow via le streaming server (Agent V1).
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POST http://localhost:5005/api/v1/traces/stream/replay
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avec workflow_id et params.
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Returns:
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Réponse du serveur si succès, None si indisponible ou erreur.
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"""
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try:
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resp = http_requests.post(
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f"{STREAMING_SERVER_URL}/api/v1/traces/stream/replay",
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json={
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"workflow_id": workflow_id,
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"session_id": f"chat_{datetime.now().strftime('%H%M%S')}",
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"params": params or {},
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},
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timeout=5,
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)
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if resp.status_code == 200:
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data = resp.json()
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logger.info(f"Workflow {workflow_id} envoyé au streaming server: {data}")
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return data
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else:
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logger.debug(
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f"Streaming server refus (HTTP {resp.status_code}): "
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f"{resp.text[:200]}"
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)
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except http_requests.ConnectionError:
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logger.debug("Streaming server non disponible (connexion refusée)")
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except http_requests.Timeout:
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logger.debug("Streaming server timeout")
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except Exception as e:
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logger.debug(f"Erreur streaming server: {e}")
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return None
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def execute_workflow(match, params):
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"""Exécuter un workflow avec le vrai système d'exécution."""
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"""
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Exécuter un workflow — tente d'abord le streaming server,
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puis fallback sur l'exécution locale.
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"""
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global execution_status
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import time
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# Tenter l'exécution via le streaming server (Agent V1 distant)
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replay_result = _try_streaming_server_replay(match.workflow_id, params)
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if replay_result:
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# Le streaming server a accepté le replay
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execution_status["running"] = True
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execution_status["workflow"] = match.workflow_name
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execution_status["progress"] = 50
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execution_status["message"] = "Envoyé au streaming server (Agent V1)"
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socketio.emit('execution_progress', {
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"progress": 50,
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"step": "Exécution via streaming server...",
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"current": 1,
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"total": 1,
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})
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finish_execution(
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match.workflow_name, True,
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f"Workflow envoyé au streaming server ({replay_result.get('status', 'ok')})"
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)
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return
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# Fallback : exécution locale
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logger.info("Streaming server indisponible, exécution locale")
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try:
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# Charger le workflow
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with open(match.workflow_path, 'r') as f:
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@@ -1257,10 +1378,10 @@ if __name__ == '__main__':
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╔════════════════════════════════════════════════════════════╗
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║ RPA Vision V3 - Interface de Commande ║
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║ ║
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║ 🌐 http://localhost:5002 ║
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║ 🌐 http://localhost:5004 ║
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║ ║
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║ Ctrl+C pour arrêter ║
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╚════════════════════════════════════════════════════════════╝
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""")
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socketio.run(app, host='127.0.0.1', port=5002, debug=False, allow_unsafe_werkzeug=True)
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socketio.run(app, host='127.0.0.1', port=5004, debug=False, allow_unsafe_werkzeug=True)
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