Fix gui+dataset (#67)

* fix gui import

* fix dataset import

casalioy/gui.py

@@ -1,13 +1,15 @@
 """LLM through a GUI"""
 
 import streamlit as st
-from load_env import get_embedding_model, model_n_ctx, model_path, model_stop, model_temp, n_gpu_layers, persist_directory, use_mlock, print_HTML
+from load_env import get_embedding_model, model_n_ctx, model_path, model_stop, model_temp, n_gpu_layers, persist_directory, use_mlock
 from streamlit_chat import message
 from streamlit_extras.add_vertical_space import add_vertical_space
 from streamlit_extras.colored_header import colored_header
 
 from casalioy import startLLM
 from casalioy.startLLM import QASystem
+from casalioy.utils import print_HTML
+
 title = "CASALIOY"
 
 

casalioy/load_env.py

@@ -6,15 +6,14 @@
 from langchain.embeddings import HuggingFaceEmbeddings, LlamaCppEmbeddings
 from langchain.prompts import PromptTemplate
 
-from casalioy.utils import download_if_repo, print_HTML
+from casalioy.utils import download_if_repo
 
 load_dotenv()
 text_embeddings_model = os.environ.get("TEXT_EMBEDDINGS_MODEL")
 text_embeddings_model_type = os.environ.get("TEXT_EMBEDDINGS_MODEL_TYPE")
 model_n_ctx = int(os.environ.get("MODEL_N_CTX"))
 use_mlock = os.environ.get("USE_MLOCK").lower() == "true"
 
-print_HTML
 # ingest
 persist_directory = os.environ.get("PERSIST_DIRECTORY")
 documents_directory = os.environ.get("DOCUMENTS_DIRECTORY")
@@ -35,6 +34,7 @@
 text_embeddings_model = download_if_repo(text_embeddings_model)
 model_path = download_if_repo(model_path)
 
+
 def get_embedding_model() -> tuple[HuggingFaceEmbeddings | LlamaCppEmbeddings, Callable]:
     """get the text embedding model
     :returns: tuple[the model, its encoding function]"""

casalioy/utils.py

@@ -48,27 +48,29 @@ def download_if_repo(path: str, file: str = None, allow_patterns: str | list[str
     """download model from HF if not local"""
     if allow_patterns is None:
         allow_patterns = ["*.bin", "*.json"]
-    p = Path("models/"+path)
+
+    # check if dataset
+    split = path.split("/")
+    is_dataset = split[0] == "datasets"
+    if is_dataset:
+        split = split[1:]
+        path = "/".join(split)
+
+    p = "models/datasets" / Path(path) if is_dataset else "models" / Path(path)
     if p.is_file() or p.is_dir():
-        print(p, "already installed")
+        print_HTML(f"<r>found local model at {p}</r>")
         return str(p)
-
-    try:
-        split = path.split("/")
-        is_dataset = split[0] == "datasets"
-        if is_dataset:
-            split = split[1:]
-            path = "/".join(split)
 
+    try:
         if path.endswith(".bin"):
             path, file = "/".join(split[: 3 if is_dataset else 2]), split[-1]
         validate_repo_id(path)
-        print_HTML("<r>Downloading {model} from HF</r>", model=path)
+        print_HTML("<r>Downloading {model_type} {model} from HF</r>", model=path, model_type="dataset" if is_dataset else "model")
         new_path = Path(
             snapshot_download(
                 repo_id=path,
                 allow_patterns=file or allow_patterns,
-                local_dir=f"models/{path}",
+                local_dir=str(p),
                 repo_type="dataset" if is_dataset else None,
                 local_dir_use_symlinks=False,
             )