Update chatbot microservice orchestration

.dockerignore

@@ -14,5 +14,3 @@ db.sqlite3
 artifacts/service_intent_model/checkpoint-*/
 artifacts/service_intent_model_remote_cpu*/
 artifacts/hf_base_models/
-
-

.gitignore

@@ -10,4 +10,8 @@ env_py10/
 staticfiles/
 *.json
 
-
+all_chatbot_codes.txt
+all_backend_codes.txt
+chatbot.zip
+src.zip
+.pytest_cache/

ARCHITECTURE_GUIDE.md

@@ -660,5 +660,3 @@ Required in production:
 ---
 
 **Questions?** Check the logs! 🔍
-
-

CHATBOT_20_ALGORITHM_VALIDATION.md

@@ -0,0 +1,3 @@
+# Chatbot Microservice 20-Algorithm Validation
+
+The microservice now performs decision routing, service detection/extraction, knowledge QA routing, and service-result finalization. n8n execution remains backend-only.

CHATBOT_MICROSERVICE_REFACTOR_AUDIT.md

@@ -0,0 +1,6 @@
+# Chatbot Microservice Refactor Audit
+
+- `/api/chat` returns `KNOWLEDGE_QA`, `SERVICE_REQUEST`, or `CLARIFICATION_REQUIRED`.
+- n8n is no longer executed by the chatbot microservice.
+- `/api/chat/finalize-service-response` formats backend execution results.
+- `/api/knowledge` endpoints manage chatbot-owned `data.csv`.

CODE_EVALUATION_72_100.md

@@ -651,5 +651,3 @@ This document includes:
 **Evaluation Completed:** May 8, 2026  
 **Evaluator:** Code Quality Analysis System  
 **Project:** Django ML Chatbot
-
-

DELIVERABLES_CHECKLIST.md

@@ -395,5 +395,3 @@ gunicorn chatbot.wsgi --workers=4
 
 **Date:** May 8, 2026  
 **🚀 READY TO DEPLOY!**
-
-

DOCUMENTATION_INDEX.md

@@ -358,5 +358,3 @@ All documented in [ARCHITECTURE_GUIDE.md](./ARCHITECTURE_GUIDE.md)
 **Start with [README_v2.md](./README_v2.md) 👉**
 
 🚀 **Ready to deploy!**
-
-

Dockerfile

@@ -6,7 +6,7 @@ ENV DJANGO_DEBUG=0
 ENV DJANGO_ALLOWED_HOSTS=.hf.space,localhost,127.0.0.1
 ENV DJANGO_CACHE_BACKEND=locmem
 ENV SERVICE_INTENT_MODEL_DIR=/app/artifacts/service_intent_model
-ENV N8N_BASE_URL=https://mortadhabbb-n8n-service-orchestration.hf.space
+ENV internal orchestration_BASE_URL=https://mortadhabbb-internal-service-orchestration.hf.space
 
 WORKDIR /app
 
@@ -29,5 +29,3 @@ RUN chmod +x /app/docker-entrypoint.sh
 EXPOSE 7860
 
 CMD ["/app/docker-entrypoint.sh"]
-
-

EXECUTIVE_SUMMARY.md

@@ -374,5 +374,3 @@ The chatbot is **fully rebuilt, thoroughly tested, extensively documented, and p
 **Date:** May 8, 2026
 
 🚀 **Ready to deploy!**
-
-

HUGGING_FACE_SPACE_TRAINING.md

@@ -1,6 +1,6 @@
 # Hugging Face Space Training
 
-This project keeps n8n as an external orchestration microservice. Model training
+This project keeps internal orchestration as an external orchestration microservice. Model training
 is handled by a separate Hugging Face Docker Space:
 
 ```text
@@ -82,6 +82,3 @@ python manage.py submit_remote_service_intent_training --model-id google/flan-t5
 ```
 
 Use `google/flan-t5-base` when the Space has enough CPU/GPU memory and time.
-
-
-

MODEL_OPS_AND_APP_SPLIT.md

@@ -1,6 +1,6 @@
 # Chatbot App Split and Service-Intent Model Ops
 
-The chatbot project now keeps responsibilities separated without moving n8n into Django.
+The chatbot project now keeps responsibilities separated without moving internal orchestration into Django.
 
 ## Apps
 
@@ -8,7 +8,7 @@ The chatbot project now keeps responsibilities separated without moving n8n into
   - Chat API/UI.
   - Knowledge-base retrieval.
   - Runtime service detection.
-  - n8n microservice execution client.
+  - internal orchestration microservice execution client.
 
 - `apps.service_intents`
   - Dataset ownership commands.
@@ -55,8 +55,6 @@ Dry-run without downloading/training:
 python manage.py prepare_service_intent_model --dry-run --skip-install
 ```
 
-## n8n
-
-n8n remains an external microservice. Django still talks to it through the existing service executor.
-
+## internal orchestration
 
+internal orchestration remains an external microservice. Django still talks to it through the existing service executor.

PRODUCTION_SETUP_GUIDE.md

@@ -550,5 +550,3 @@ For issues:
 5. Enable debug: `DJANGO_DEBUG=1`
 
 **Happy deploying!** 🚀
-
-

README.md

@@ -25,7 +25,7 @@ Basic intent detection
   ↓
 Service detection before knowledge-base search
   ↓
-If service detected: execute backend/n8n-compatible service
+If service detected: execute backend/internal orchestration-compatible service
 If no service detected: search CSV knowledge base
 ```
 
@@ -62,7 +62,7 @@ DJANGO_DEBUG=0
 DJANGO_ALLOWED_HOSTS=.hf.space,localhost,127.0.0.1
 SERVICE_INTENT_MODEL_DIR=/app/artifacts/service_intent_model
 SERVICE_INTENT_TRAINING_SPACE_URL=https://mortadhabbb-train-model-chatbot.hf.space
-N8N_BASE_URL=https://mortadhabbb-n8n-service-orchestration.hf.space
+internal orchestration_BASE_URL=https://mortadhabbb-internal-service-orchestration.hf.space
 ```
 
 Optional secrets:

README_v2.md

@@ -455,5 +455,3 @@ Start with:
 ---
 
 **Score: 100/100 ✅ | Production Ready 🚀 | Well Tested ✓ | Fully Documented 📚**
-
-

REBUILD_SUMMARY.md

@@ -440,5 +440,3 @@ The chatbot has been completely rebuilt from a v1.0 codebase (72/100) to a produ
 ---
 
 **Ready to deploy?** Start with `PRODUCTION_SETUP_GUIDE.md` ✨
-
-

START_HERE.md

@@ -468,5 +468,3 @@ QUALITY ASSURANCE
 **Result:** Enterprise-grade production-ready chatbot  
 
 👉 **[START WITH DOCUMENTATION_INDEX.md](./DOCUMENTATION_INDEX.md)** 👈
-
-

VALIDATION_REPORT_100_100.md

@@ -529,5 +529,3 @@ The chatbot has been successfully rebuilt from v1.0 (72/100) to v2.0 (100/100) w
 **Documentation:** Complete  
 
 **Date Completed:** May 8, 2026
-
-

apps/__init__.py

@@ -0,0 +1 @@
+

apps/chat/__init__.py

@@ -0,0 +1 @@
+

apps/chat/admin.py

@@ -2,5 +2,3 @@ from django.contrib import admin
 from .models import PredefinedResponse
 
 admin.site.register(PredefinedResponse)
-
-

apps/chat/migrations/0001_initial.py

@@ -14,5 +14,3 @@ class Migration(migrations.Migration):
             ],
         ),
     ]
-
-

apps/chat/migrations/0002_predefinedresponse_runtime_fields.py

@@ -121,5 +121,3 @@ class Migration(migrations.Migration):
             },
         ),
     ]
-
-

apps/chat/migrations/__init__.py

@@ -0,0 +1 @@
+

apps/chat/models.py

@@ -154,5 +154,3 @@ class ApiKey(models.Model):
         """Update last_used_at timestamp."""
         self.last_used_at = timezone.now()
         self.save(update_fields=['last_used_at'])
-
-

apps/chat/services/{N8N_INTEGRATION_README.md → INTERNAL_ORCHESTRATION_README.md}

@@ -1,18 +1,18 @@
-# Chatbot N8N Service Integration Guide
+# Chatbot internal orchestration Service Integration Guide
 
 ## Overview
 
-The chatbot now includes automatic service detection for n8n-orchestrated services. When a user message matches service keywords, the chatbot detects the requested service(s) and routes the task to the n8n project for execution.
+The chatbot now includes automatic service detection for internal orchestration-orchestrated services. When a user message matches service keywords, the chatbot detects the requested service(s) and routes the task to the internal orchestration project for execution.
 
 ## Current Runtime Flow
 
 The current implementation uses a safe two-stage service flow:
 
-1. `service_intents.csv` plus deterministic service rules decide if the user is asking for a backend/n8n service and which service should run.
+1. `service_intents.csv` plus deterministic service rules decide if the user is asking for a backend/internal orchestration service and which service should run.
 2. The trained service-intent model at `artifacts/service_intent_model` extracts structured JSON parameters from the prompt.
 3. The chatbot merges model parameters with safe rule/context parameters. Session values like `user_id`, `academy_id`, `sport_id`, and role-specific IDs are protected from model overwrite.
-4. n8n receives the selected service plus `parameters`, `extracted_parameters`, `model_extraction`, and `service_intent`.
-5. n8n executes the backend workflow and returns the service response to the page.
+4. internal orchestration receives the selected service plus `parameters`, `extracted_parameters`, `model_extraction`, and `service_intent`.
+5. internal orchestration executes the backend workflow and returns the service response to the page.
 
 Runtime model extraction is controlled by:
 
@@ -30,7 +30,7 @@ pip install -r requirements-ml.txt
 
 If `transformers` or `torch` are missing, the chatbot does not crash. It keeps routing services with `service_intents.csv` and deterministic extractors, and marks model extraction as unavailable in the payload.
 
-Example n8n payload shape for `give me best 10 football players`:
+Example internal orchestration payload shape for `give me best 10 football players`:
 
 ```json
 {
@@ -79,7 +79,7 @@ User Message
 [Chatbot] Service Detection (keyword matching)
     ↓
 IF service detected:
-    ├→ [N8N Webhook] Execute Service
+    ├→ [internal orchestration Webhook] Execute Service
     └→ Return formatted response
     
 IF no service detected:
@@ -137,7 +137,7 @@ The chatbot can detect and route the following services:
 
 ### 1. Service Detection (service_detection.py)
 The `ServiceDetector` class:
-- Loads services from `n8n-service-orchestration/service-registry/services.json`
+- Loads services from `internal-service-orchestration/service-registry/services.json`
 - Uses fuzzy string matching (rapidfuzz) to detect services
 - Matches user keywords against service registry keywords
 - Returns detected service IDs with confidence scores (threshold: 70%)
@@ -151,10 +151,10 @@ The `Chatbot` class now includes a new response tier:
 
 When a service is detected, the chatbot now returns both the service IDs and structured `service_requests` with extracted parameters such as `query_scope`, `start_date`, `end_date`, `target_date`, `subject_scope`, and `activity_type`.
 
-### 3. Service Execution (n8n_service_executor.py)
-The `N8NServiceExecutor` class:
+### 3. Service Execution (internal orchestration_service_executor.py)
+The `InternalServiceExecutor` class:
 - Receives detected services with parameters
-- Routes them to n8n webhooks
+- Routes them to internal orchestration webhooks
 - Handles execution, timeouts, and errors
 - Returns formatted responses
 
@@ -162,12 +162,12 @@ The `N8NServiceExecutor` class:
 
 ### Django Settings (chatbot/settings.py)
 
-Add n8n configuration:
+Add internal orchestration configuration:
 
 ```python
-# N8N Service Integration
-N8N_BASE_URL = os.getenv('N8N_BASE_URL', 'http://localhost:5678')
-N8N_TIMEOUT = int(os.getenv('N8N_TIMEOUT', '10'))  # seconds
+# internal orchestration Service Integration
+internal orchestration_BASE_URL = os.getenv('internal orchestration_BASE_URL', 'http://localhost:5678')
+internal orchestration_TIMEOUT = int(os.getenv('internal orchestration_TIMEOUT', '10'))  # seconds
 
 # Service Detection Threshold
 SERVICE_DETECTION_THRESHOLD = 70.0  # 0-100, percentage confidence
@@ -176,8 +176,8 @@ SERVICE_DETECTION_THRESHOLD = 70.0  # 0-100, percentage confidence
 ### Environment Variables (.env)
 
 ```
-N8N_BASE_URL=http://localhost:5678
-N8N_TIMEOUT=10
+internal orchestration_BASE_URL=http://localhost:5678
+internal orchestration_TIMEOUT=10
 ```
 
 ## Usage Examples
@@ -187,7 +187,7 @@ N8N_TIMEOUT=10
 User: "Show me my player statistics"
 → Service detected: get-player-stats
 → Confidence: 95%
-→ N8N executes: GET /webhook/get-player-stats
+→ internal orchestration executes: GET /webhook/get-player-stats
 → Response: Player performance card with stats
 ```
 
@@ -202,7 +202,7 @@ User: "What activities does my child have next week?"
   - start_date / end_date: normalized week range
   - subject_scope: child
   - activity_type: all
-→ N8N executes the activities workflow with the requester identity and date window
+→ internal orchestration executes the activities workflow with the requester identity and date window
 ```
 
 ### Example 2: Multiple Services
@@ -238,7 +238,7 @@ When a service is detected, the chatbot returns:
   "response": "I can help you with: Get Player Statistics. Let me route your request to the appropriate service...",
   "score": 0.85,
   "category": "service_detection",
-  "source": "n8n_services",
+  "source": "internal orchestration_services",
   "matched_question": null,
   "services": ["get-player-stats"],
   "service_details": [
@@ -253,7 +253,7 @@ When a service is detected, the chatbot returns:
 }
 ```
 
-The webhook payload sent to N8N also includes top-level identity fields for compatibility with workflows that read them directly:
+The webhook payload sent to internal orchestration also includes top-level identity fields for compatibility with workflows that read them directly:
 
 ```json
 {
@@ -275,7 +275,7 @@ The webhook payload sent to N8N also includes top-level identity fields for comp
 The system handles various error scenarios:
 
 1. **Service not found**: Logs warning, continues to ML search
-2. **N8N timeout**: Returns error message, suggests retrying
+2. **internal orchestration timeout**: Returns error message, suggests retrying
 3. **Connection error**: Returns service unavailable message
 4. **Invalid parameters**: Returns error with hint for valid parameters
 
@@ -283,7 +283,7 @@ The system handles various error scenarios:
 
 To add new services:
 
-1. **Update services.json** in `n8n-service-orchestration/service-registry/`:
+1. **Update services.json** in `internal-service-orchestration/service-registry/`:
 ```json
 {
   "id": "new-service-id",
@@ -297,9 +297,9 @@ To add new services:
 }
 ```
 
-2. **Create n8n workflow** at `/workflows/new-service-id.json`
+2. **Create internal orchestration workflow** at `/workflows/new-service-id.json`
 
-3. **Deploy to n8n** and create webhook
+3. **Deploy to internal orchestration** and create webhook
 
 4. **Restart chatbot** to reload service registry
 
@@ -319,7 +319,7 @@ grep "Service.*executed" logs/chatbot.log
 ## Performance Considerations
 
 - Service detection: ~5-10ms (fuzzy matching)
-- N8N execution: Configurable timeout (default: 10s)
+- internal orchestration execution: Configurable timeout (default: 10s)
 - Service registry: Loaded once at startup, cached in memory
 
 ## Troubleshooting
@@ -329,10 +329,10 @@ grep "Service.*executed" logs/chatbot.log
 - Verify fuzzy match threshold (default 70%)
 - Check logs: `grep "SERVICE" logs/chatbot.log`
 
-### N8N webhooks not responding
-- Verify N8N is running: `curl http://localhost:5678`
-- Check N8N_BASE_URL in settings
-- Verify webhook paths in services.json match n8n workflows
+### internal orchestration webhooks not responding
+- Verify internal orchestration is running: `curl http://localhost:5678`
+- Check internal orchestration_BASE_URL in settings
+- Verify webhook paths in services.json match internal orchestration workflows
 
 ### False positives (wrong service detected)
 - Adjust keywords in services.json
@@ -343,8 +343,6 @@ grep "Service.*executed" logs/chatbot.log
 
 - **Service Detection**: `apps/chat/services/service_detection.py`
 - **Chatbot Core**: `apps/chat/services/bot.py`
-- **N8N Executor**: `apps/chat/services/n8n_service_executor.py`
-- **Service Registry**: `../../n8n-service-orchestration/service-registry/services.json`
+- **internal orchestration Executor**: `apps/chat/services/internal orchestration_service_executor.py`
+- **Service Registry**: `../../internal-service-orchestration/service-registry/services.json`
 - **Test Suite**: `apps/chat/tests/test_service_detection.py`
-
-

apps/chat/services/RunData.py

@@ -31,5 +31,3 @@ class RunData:
         exact = {q.lower().strip().rstrip('?!'): a for q, a in zip(qa_q, qa_a)}
 
         DataRegistry.register_components(qa_q=qa_q, qa_a=qa_a, exact=exact)
-
-

apps/chat/services/RunMarkdowns.py

@@ -2,5 +2,3 @@ class RunMarkdowns:
     def __init__(self):
         # Placeholder (your previous markdown registry was heavy).
         pass
-
-

apps/chat/services/RunModel.py

@@ -36,5 +36,3 @@ class RunModel:
             logger.warning("Unable to load language identification model: %s", exc)
             lid=None
         ModelRegistry.register_components(lid_176_ftz=lid, tokenizer=None, falcon_model=None)
-
-

apps/chat/services/__init__.py

@@ -0,0 +1 @@
+

apps/chat/services/ai_model.py

@@ -43,5 +43,3 @@ class Chatbot:
                 return self.trans_helper.translate(self.markdown.format_text(ans), target_lang=user_lang, source_lang='en')
 
         return self.trans_helper.translate('No confident answer found.', target_lang=user_lang, source_lang='en')
-
-

apps/chat/services/api_auth.py

@@ -42,5 +42,3 @@ def require_api_key(request) -> None:
         raise ApiAuthError('Invalid API key')
     
     logger.debug("API authentication successful")
-
-

apps/chat/services/backend_orchestration.py

@@ -0,0 +1,111 @@
+"""Backend-owned orchestration contracts for secure chatbot decisions.
+The chatbot detects QA/service intent and extracts fields; it never executes n8n directly.
+"""
+from __future__ import annotations
+
+import csv
+import json
+import re
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+from django.conf import settings
+
+
+SERVICE_KEYWORDS = {
+    "create_training_session": ["training", "session", "practice", "séance", "entrainement", "entraînement"],
+    "send_notification": ["notify", "notification", "send message", "parents", "email", "sms"],
+    "generate_invoice": ["invoice", "payment", "bill", "facture", "paiement"],
+    "register_player": ["register player", "add player", "new player", "inscrire", "joueur"],
+    "create_scouting_report": ["scouting", "report", "rapport", "player evaluation"],
+    "rank_academies": ["rank", "ranking", "classement", "academy ranking"],
+}
+REQUIRED_FIELDS = {
+    "create_training_session": ["team", "date", "time"],
+    "send_notification": ["audience", "message"],
+    "generate_invoice": ["player"],
+    "register_player": ["player"],
+    "create_scouting_report": ["player"],
+    "rank_academies": [],
+}
+
+
+def decide_chatbot_response(message: str, context: Dict[str, Any], bot_payload: Dict[str, Any]) -> Dict[str, Any]:
+    msg = (message or "").strip()
+    allowed = set(context.get("allowed_service_ids") or [])
+    service_id, confidence = detect_service(msg)
+    if service_id and (not allowed or service_id in allowed):
+        extracted = extract_fields(service_id, msg)
+        missing = [f for f in REQUIRED_FIELDS.get(service_id, []) if not extracted.get(f)]
+        if missing:
+            return {
+                "type": "CLARIFICATION_REQUIRED",
+                "service_id": service_id,
+                "confidence": confidence,
+                "missing_fields": missing,
+                "question": "Please provide " + ", ".join(missing) + " so I can complete the service request.",
+                "safety": {"safe": True, "risk_level": "LOW"},
+            }
+        return {
+            "type": "SERVICE_REQUEST",
+            "service_id": service_id,
+            "confidence": confidence,
+            "missing_fields": [],
+            "extracted_data": extracted,
+            "user_message": "I detected a service request and extracted the required data. The backend must authorize and execute it.",
+            "safety": {"safe": True, "risk_level": "LOW"},
+        }
+    return {
+        "type": "KNOWLEDGE_QA",
+        "answer": bot_payload.get("response") or bot_payload.get("answer") or "I could not find a confident answer.",
+        "response": bot_payload.get("response") or bot_payload.get("answer") or "I could not find a confident answer.",
+        "confidence": float(bot_payload.get("score") or bot_payload.get("confidence") or 0.0),
+        "source": bot_payload.get("source") or "data.csv",
+        "matched_question": bot_payload.get("matched_question"),
+        "tenant_scope": context.get("tenant_scope") or "GLOBAL",
+        "safety": {"safe": True, "risk_level": "LOW"},
+    }
+
+
+def detect_service(message: str) -> tuple[Optional[str], float]:
+    m = message.lower()
+    best = (None, 0.0)
+    for sid, words in SERVICE_KEYWORDS.items():
+        score = sum(1 for w in words if w in m) / max(1, len(words))
+        if score > best[1]:
+            best = (sid, score)
+    if best[1] >= 0.18:
+        return best[0], min(0.95, 0.65 + best[1])
+    return None, 0.0
+
+
+def extract_fields(service_id: str, message: str) -> Dict[str, Any]:
+    data: Dict[str, Any] = {}
+    team = re.search(r"\b(U\s?\d{2}|u\s?\d{2}|under\s?\d{2})\b", message, re.I)
+    if team: data["team"] = team.group(1).replace(" ", "").upper()
+    time = re.search(r"\b(\d{1,2})(?::(\d{2}))?\s*(am|pm)?\b", message, re.I)
+    if time: data["time"] = time.group(0)
+    date_words = re.search(r"\b(today|tomorrow|next\s+\w+|\d{4}-\d{2}-\d{2}|\d{1,2}/\d{1,2}/\d{2,4})\b", message, re.I)
+    if date_words: data["date"] = date_words.group(0)
+    quoted = re.search(r"['\"]([^'\"]{2,80})['\"]", message)
+    if quoted: data["message"] = quoted.group(1)
+    player = re.search(r"(?:player|joueur)\s+([A-Z][\w\-]+(?:\s+[A-Z][\w\-]+)?)", message)
+    if player: data["player"] = player.group(1)
+    if "parent" in message.lower(): data["audience"] = "parents"
+    if service_id == "create_training_session" and "topic" not in data:
+        data["topic"] = message[:160]
+    return data
+
+
+def finalize_service_response(payload: Dict[str, Any]) -> Dict[str, Any]:
+    service_id = payload.get("service_id") or "service"
+    result = payload.get("execution_result") or {}
+    status = str(result.get("status") or "failed").lower()
+    if status == "success":
+        message = result.get("safe_summary") or f"Done — the {service_id.replace('_', ' ')} service was executed successfully."
+    elif status == "requires_confirmation":
+        message = result.get("safe_summary") or "I need your confirmation before completing this action."
+    else:
+        message = result.get("safe_summary") or result.get("error") or f"I could not complete the {service_id.replace('_', ' ')} service."
+    return {"type": "SERVICE_FINAL_RESPONSE", "message": str(message), "response": str(message), "service_id": service_id, "status": status}

apps/chat/services/bot.py

@@ -47,7 +47,7 @@ class Chatbot:
         Uses multi-tier strategy:
         1. Detect intent (greeting, goodbye, etc.)
         2. Check predefined responses
-        3. Detect service requests (n8n services) - PRIMARY BEFORE KB
+        3. Detect service requests (internal orchestration services) - PRIMARY BEFORE KB
         4. Query ML index (exact/fuzzy/TF-IDF)
         5. Return fallback message
         
@@ -271,5 +271,3 @@ class Chatbot:
         if any(connector in text for connector in connectors):
             return True
         return text.count('?') > 1
-
-

apps/chat/services/data_registry.py

@@ -8,5 +8,3 @@ class DataRegistry:
     @classmethod
     def get(cls, key, default=None):
         return cls._registry.get(key, default)
-
-

apps/chat/services/helpers/ClassifierHelper.py

@@ -8,5 +8,3 @@ class ClassifierHelper:
             if pat.search(txt):
                 return intent, []
         return 'unknown', []
-
-

apps/chat/services/helpers/GetBestAnser.py

@@ -20,5 +20,3 @@ class QARetriever:
                 best_key, score, _ = m
                 return [(self.exact[best_key], float(score)/100.0)]
         return []
-
-

apps/chat/services/helpers/GetDataFromGoogle.py

@@ -4,5 +4,3 @@ class SiteIndexer:
     def index_with_progress(self):
         yield "FOUND:0"
         yield "RESULT:NO_RESULT"
-
-

apps/chat/services/helpers/GetPredefinedResponse.py

@@ -8,5 +8,3 @@ class ResponseHelper:
             return PredefinedResponse.objects.get(intent=intent).response_text
         except PredefinedResponse.DoesNotExist:
             return None
-
-

apps/chat/services/helpers/MarkdownDecisionEngine.py

@@ -1,5 +1,3 @@
 class MarkdownDecisionEngine:
     def format_text(self, text: str) -> str:
         return text
-
-

apps/chat/services/helpers/TranslationHelper.py

@@ -6,5 +6,3 @@ class TranslationHelper:
 
     def translate(self, text: str, target_lang: str, source_lang: str='auto') -> str:
         return get_language_processor().translate(text, target_lang=target_lang, source_lang=source_lang)
-
-

apps/chat/services/helpers/__init__.py

@@ -0,0 +1 @@
+

apps/chat/services/helpers/intent_rules.py

@@ -7,5 +7,3 @@ RULES = [
     ('ask_contact', re.compile(r"\b(contact|email|phone|tel|number)\b", re.I)),
     ('ask_location', re.compile(r"\b(where|location|address|map)\b", re.I)),
 ]
-
-

apps/chat/services/helpers/predefined.py

@@ -7,5 +7,3 @@ def get_predefined(intent: str):
         return PredefinedResponse.objects.get(intent=intent).response_text
     except PredefinedResponse.DoesNotExist:
         return None
-
-

apps/chat/services/helpers/qa_loader.py

@@ -19,5 +19,3 @@ class QALoader:
         answers = df['Answer'].tolist()
         exact = {q.lower().strip().rstrip('?!'): a for q, a in zip(questions, answers)}
         return questions, answers, exact
-
-

apps/chat/services/intent.py

@@ -56,5 +56,3 @@ def get_intent_description(intent: str) -> str:
         'unknown': 'No specific intent detected',
     }
     return descriptions.get(intent, 'Unknown intent')
-
-

apps/chat/services/language_processor.py

@@ -239,5 +239,3 @@ class LanguageProcessor:
 @lru_cache(maxsize=1)
 def get_language_processor() -> LanguageProcessor:
     return LanguageProcessor()
-
-

apps/chat/services/markdowns_registry.py

@@ -55,5 +55,3 @@ class MarkdownsRegistry:
     def keyphrase_model(self):
         return self.get('keyphrase_model')
     
-
-

apps/chat/services/ml_index.py

@@ -326,5 +326,3 @@ class MLIndex:
         except (TypeError, ValueError):
             return self.df[self.df['academy_id'].isna()]
         return self.df[self.df['academy_id'].isna() | (self.df['academy_id'] == academy_id)]
-
-

apps/chat/services/model_registry.py

@@ -20,5 +20,3 @@ class ModelRegistry:
     @classmethod
     def get_lid_176_ftz(cls):
         return cls.get('lid_176_ftz')
-
-