Fix RAG inference

rag_inference_bot.py

@@ -2,7 +2,6 @@ import logging
 import chromadb
 from chromadb.utils import embedding_functions
 from inference_bot import InferenceBot # Correctly inherit from the ABC
-from FlagEmbedding import FlagReranker
 import argparse
 import os
 import importlib
@@ -12,12 +11,12 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 
 # --- RAG Configuration ---
 # Must match the settings in create_index.py
-EMBEDDING_MODEL_NAME = """C:\Models\embeddings\Qwen3-Embedding-0.6B"""
-CHROMA_DB_PATH = "C:\Models\embeddings\embedding_result\chroma_db"
+EMBEDDING_MODEL_NAME = os.environ.get("EMBEDDING_MODEL_PATH") 
+CHROMA_DB_PATH = os.environ.get("CHROMA_DB_PATH")
 CHROMA_COLLECTION_NAME = "github_repo"
 
 # Using a powerful open-source reranker model
-RERANKER_MODEL_NAME = """C:\Models\embeddings\Qwen3-Reranker-0.6B"""
+RERANKER_MODEL_NAME = os.environ.get("RERANKER_MODEL_PATH") 
 
 # Number of initial results to fetch from the database before reranking
 N_RESULTS_TO_RETRIEVE = 25
@@ -36,9 +35,9 @@ class RAGInferenceBot(InferenceBot):
         self._processing_status = {}
         try:
             # --- Embedding and Vector DB Initialization ---
-            self.chroma_client = chromadb.PersistentClient(path=CHROMA_DB_PATH)
+            self.chroma_client = chromadb.PersistentClient(path=CHROMA_DB_PATH, settings=chromadb.Settings(anonymized_telemetry=False))
             self.embedding_function = embedding_functions.SentenceTransformerEmbeddingFunction(
-                model_name=EMBEDDING_MODEL_NAME
+                model_name=EMBEDDING_MODEL_NAME, device="cuda"
             )
             self.collection = self.chroma_client.get_collection(
                 name=CHROMA_COLLECTION_NAME,