Add Qdrant and ChromaDB support to the project

- Added Qdrant service to both docker-compose files for production and development.
- Updated environment variables in .env.example and settings.py to include Qdrant configuration.
- Included necessary dependencies for Qdrant and ChromaDB in requirements.txt.
- Updated .gitignore to exclude ChromaDB data files.

rag/config.py

@@ -0,0 +1,93 @@
+"""
+بارگذاری تنظیمات RAG از rag_config.yaml
+"""
+import os
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+
+@dataclass
+class EmbeddingConfig:
+    provider: str
+    model: str
+    batch_size: int = 32
+    api_key_env: str | None = None
+    base_url: str | None = None
+
+
+@dataclass
+class QdrantConfig:
+    host: str = "localhost"
+    port: int = 6333
+    collection_name: str = "croplogic_kb"
+    vector_size: int = 384
+
+
+@dataclass
+class ChunkingConfig:
+    max_chunk_tokens: int = 500
+    overlap_tokens: int = 50
+
+
+@dataclass
+class RAGConfig:
+    embedding: EmbeddingConfig
+    qdrant: QdrantConfig
+    chunking: ChunkingConfig
+    tone_file: str = "config/tone.txt"
+    knowledge_base_path: str = "config/knowledge_base"
+    user_info_path: str = "config/user_info"
+    chromadb: dict[str, Any] = field(default_factory=dict)
+
+
+def load_rag_config(config_path: str | Path | None = None) -> RAGConfig:
+    """
+    بارگذاری تنظیمات از YAML و env.
+    QDRANT_HOST و QDRANT_PORT از متغیرهای محیطی override می‌شوند.
+    """
+    if config_path is None:
+        base = Path(__file__).resolve().parent.parent
+        config_path = base / "config" / "rag_config.yaml"
+
+    path = Path(config_path)
+    if not path.exists():
+        raise FileNotFoundError(f"RAG config not found: {path}")
+
+    with open(path, encoding="utf-8") as f:
+        data = yaml.safe_load(f) or {}
+
+    emb = data.get("embedding", {})
+    embedding = EmbeddingConfig(
+        provider=emb.get("provider", "sentence_transformers"),
+        model=emb.get("model", "text-embedding-3-small"),
+        batch_size=emb.get("batch_size", 32),
+        api_key_env=emb.get("api_key_env"),
+        base_url=emb.get("base_url"),
+    )
+
+    qd = data.get("qdrant", {})
+    qdrant = QdrantConfig(
+        host=os.environ.get("QDRANT_HOST", qd.get("host", "localhost")),
+        port=int(os.environ.get("QDRANT_PORT", qd.get("port", 6333))),
+        collection_name=qd.get("collection_name", "croplogic_kb"),
+        vector_size=qd.get("vector_size", 1536),
+    )
+
+    ch = data.get("chunking", {})
+    chunking = ChunkingConfig(
+        max_chunk_tokens=ch.get("max_chunk_tokens", 500),
+        overlap_tokens=ch.get("overlap_tokens", 50),
+    )
+
+    return RAGConfig(
+        embedding=embedding,
+        qdrant=qdrant,
+        chunking=chunking,
+        tone_file=data.get("tone_file", "config/tone.txt"),
+        knowledge_base_path=data.get("knowledge_base_path", "config/knowledge_base"),
+        user_info_path=data.get("user_info_path", "config/user_info"),
+        chromadb=data.get("chromadb", {}),
+    )