feat: ✨ AI Read File Tool, Configurable system prompts and loading lots of llms

src/embedding.py

@@ -1,12 +1,16 @@
 import requests
 from langchain_core.embeddings import Embeddings
+from config_loader import load_config
 
+CFG = load_config()
+API_BASE = CFG["api"]["base_url"]
+API_VERSION = CFG["api"]["api_version"]
 
 class LocalLMEmbeddings(Embeddings):
     def __init__(
-        self, model: str, base_url: str = "http://192.168.0.49:1234", batch_size: int = 32
+        self, model: str, base_url: str = API_BASE, batch_size: int = 32
     ):
-        self.url = f"{base_url}/v1/embeddings"
+        self.url = f"{base_url}/{API_VERSION}/embeddings"
         self.model = model
         self.batch_size = batch_size
 
@@ -27,7 +31,7 @@ class LocalLMEmbeddings(Embeddings):
             return [[] for _ in input_texts]
 
     def embed_documents(self, texts: list[str]) -> list[list[float]]:
-        """Splits 500+ chunks into batches of 32 and processes them."""
+        """Splits chunks into batches of 32 and processes them."""
         all_embeddings = []
 
         for i in range(0, len(texts), self.batch_size):