feat: Add Alateya, Clan, Eonarch agents + fix gateway-router connection

## Agents Added
- Alateya: R&D, biotech, innovations
- Clan (Spirit): Community spirit agent
- Eonarch: Consciousness evolution agent

## Changes
- docker-compose.node1.yml: Added tokens for all 3 new agents
- gateway-bot/http_api.py: Added configs and webhook endpoints
- gateway-bot/clan_prompt.txt: New prompt file
- gateway-bot/eonarch_prompt.txt: New prompt file

## Fixes
- Fixed ROUTER_URL from :9102 to :8000 (internal container port)
- All 9 Telegram agents now working

## Documentation
- Created PROJECT-MASTER-INDEX.md - single entry point
- Added various status documents and scripts

Tokens configured:
- Helion, NUTRA, Agromatrix (existing)
- Alateya, Clan, Eonarch (new)
- Druid, GreenFood, DAARWIZZ (configured)

services/rag-service/app/embedding.py

@@ -4,49 +4,45 @@ Uses SentenceTransformers via Haystack
 """
 
 import logging
-from typing import Optional
+from typing import Optional, List, Dict, Any
 
-from haystack.components.embedders import SentenceTransformersTextEmbedder
+from sentence_transformers import SentenceTransformer
 
 from app.core.config import settings
 
 logger = logging.getLogger(__name__)
 
+
+class SimpleEmbedder:
+    def __init__(self, model_name: str, device: str) -> None:
+        self.model = SentenceTransformer(model_name, device=device)
+
+    def run(self, texts: Optional[List[str]] = None, text: Optional[str] = None) -> Dict[str, Any]:
+        if texts is not None:
+            embeddings = self.model.encode(texts, convert_to_numpy=True).tolist()
+            return {"embeddings": embeddings}
+        if text is not None:
+            embedding = self.model.encode([text], convert_to_numpy=True).tolist()
+            return {"embedding": embedding}
+        return {"embeddings": []}
+
+
 # Global embedder instance
-_text_embedder: Optional[SentenceTransformersTextEmbedder] = None
+_text_embedder: Optional[SimpleEmbedder] = None
 
 
-def get_text_embedder() -> SentenceTransformersTextEmbedder:
-    """
-    Get or create SentenceTransformersTextEmbedder instance
-    
-    Returns:
-        SentenceTransformersTextEmbedder configured with embedding model
-    """
+def get_text_embedder() -> SimpleEmbedder:
     global _text_embedder
-    
     if _text_embedder is not None:
         return _text_embedder
-    
     logger.info(f"Loading embedding model: {settings.EMBED_MODEL_NAME}")
     logger.info(f"Device: {settings.EMBED_DEVICE}")
-    
-    try:
-        _text_embedder = SentenceTransformersTextEmbedder(
-            model=settings.EMBED_MODEL_NAME,
-            device=settings.EMBED_DEVICE,
-        )
-        
-        logger.info("Text embedder initialized successfully")
-        return _text_embedder
-        
-    except Exception as e:
-        logger.error(f"Failed to initialize TextEmbedder: {e}", exc_info=True)
-        raise RuntimeError(f"TextEmbedder initialization failed: {e}") from e
+    _text_embedder = SimpleEmbedder(settings.EMBED_MODEL_NAME, settings.EMBED_DEVICE)
+    logger.info("Text embedder initialized successfully")
+    return _text_embedder
 
 
 def reset_embedder():
-    """Reset global embedder instance (for testing)"""
     global _text_embedder
     _text_embedder = None