[#24213] Docker fixes

src/vulcanai/console/console.py

@@ -16,10 +16,12 @@
 
 import argparse
 import asyncio
+import os
 import sys
 import threading
 
 import pyperclip  # To paste the clipboard into the terminal
+from textual import constants as textual_constants
 from textual import events, work
 from textual.app import App, ComposeResult
 from textual.binding import Binding
@@ -89,6 +91,7 @@ class VulcanConsole(App):
         border: tall #333333;
         scrollbar-size-vertical: 0;
         scrollbar-size-horizontal: 0;
+        color: #ffffff;
     }
 
     #llm_spinner {
@@ -100,12 +103,14 @@ class VulcanConsole(App):
 
     #cmd {
         dock: bottom;
+        color: #ffffff;
     }
 
     #history_title {
         content-align: center middle;
         margin: 0;
         padding: 0;
+        color: #ffffff;
     }
 
     #history_scroll {
@@ -118,6 +123,10 @@ class VulcanConsole(App):
     #history {
         width: 100%;
     }
+
+    #variables {
+        color: #ffffff;
+    }
     """
 
     # Bindings for the console
@@ -140,6 +149,13 @@ def __init__(
         user_context: str = "",
         main_node=None,
     ):
+        # Used to set the same textual colors in a docker container
+        os.environ.setdefault("COLORTERM", "truecolor")
+        textual_constants.COLOR_SYSTEM = "truecolor"
+
+        # Keep Hugging Face download progress bars out of redirected Textual stdout/stderr.
+        os.environ.setdefault("HF_HUB_DISABLE_PROGRESS_BARS", "1")
+
         super().__init__()  # Textual lib
 
         # -- Main variables --

src/vulcanai/tools/embedder.py

@@ -12,12 +12,25 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from typing import Optional
+
 import numpy as np
 from sentence_transformers import SentenceTransformer
 
+from vulcanai.console.logger import VulcanAILogger
+
+
+def info_msg_hf_model_loading(model_name: str, logger: Optional[VulcanAILogger] = None) -> None:
+    msg = f"Hugging Face is loading '{model_name}'. If the model is not cached yet, files are being downloaded..."
+    if logger is not None:
+        logger.log_console(msg)
+    else:
+        VulcanAILogger.default().log_console(msg)
+
 
 class SBERTEmbedder:
-    def __init__(self, model_name="all-MiniLM-L6-v2"):
+    def __init__(self, model_name="all-MiniLM-L6-v2", logger: Optional[VulcanAILogger] = None):
+        info_msg_hf_model_loading(model_name, logger)
         self.model = SentenceTransformer(model_name)
 
     def embed(self, text: str) -> np.ndarray:

src/vulcanai/tools/tool_registry.py

@@ -86,7 +86,7 @@ def __init__(self, embedder=None, logger=None):
         # Dictionary of deactivated_tools (name -> tool instance)
         self.deactivated_tools: Dict[str, ITool] = {}
         # Embedding model for tool metadata
-        self.embedder = embedder or SBERTEmbedder()
+        self.embedder = embedder or SBERTEmbedder(logger=self.logger)
         # Simple in-memory index of (name, embedding)
         self._index: list[Tuple[str, np.ndarray]] = []
         # List of modules where tools can be loaded from