feat(llm): add progress bar when ollama is pulling models (#2031)

* fix: add ollama progress bar when pulling models

* feat: add ollama queue

* fix: mypy

private_gpt/utils/ollama.py

@@ -1,4 +1,9 @@
 import logging
+from collections import deque
+from collections.abc import Iterator, Mapping
+from typing import Any
+
+from tqdm import tqdm  # type: ignore
 
 try:
     from ollama import Client  # type: ignore
@@ -19,12 +24,55 @@ def check_connection(client: Client) -> bool:
         return False
 
 
+def process_streaming(generator: Iterator[Mapping[str, Any]]) -> None:
+    progress_bars = {}
+    queue = deque()  # type: ignore
+
+    def create_progress_bar(dgt: str, total: int) -> Any:
+        return tqdm(
+            total=total, desc=f"Pulling model {dgt[7:17]}...", unit="B", unit_scale=True
+        )
+
+    current_digest = None
+
+    for chunk in generator:
+        digest = chunk.get("digest")
+        completed_size = chunk.get("completed", 0)
+        total_size = chunk.get("total")
+
+        if digest and total_size is not None:
+            if digest not in progress_bars and completed_size > 0:
+                progress_bars[digest] = create_progress_bar(digest, total=total_size)
+                if current_digest is None:
+                    current_digest = digest
+                else:
+                    queue.append(digest)
+
+            if digest in progress_bars:
+                progress_bar = progress_bars[digest]
+                progress = completed_size - progress_bar.n
+                if completed_size > 0 and total_size >= progress != progress_bar.n:
+                    if digest == current_digest:
+                        progress_bar.update(progress)
+                        if progress_bar.n >= total_size:
+                            progress_bar.close()
+                            current_digest = queue.popleft() if queue else None
+                    else:
+                        # Store progress for later update
+                        progress_bars[digest].total = total_size
+                        progress_bars[digest].n = completed_size
+
+    # Close any remaining progress bars at the end
+    for progress_bar in progress_bars.values():
+        progress_bar.close()
+
+
 def pull_model(client: Client, model_name: str, raise_error: bool = True) -> None:
     try:
         installed_models = [model["name"] for model in client.list().get("models", {})]
         if model_name not in installed_models:
             logger.info(f"Pulling model {model_name}. Please wait...")
-            client.pull(model_name)
+            process_streaming(client.pull(model_name, stream=True))
             logger.info(f"Model {model_name} pulled successfully")
     except Exception as e:
         logger.error(f"Failed to pull model {model_name}: {e!s}")