feat: Add percentage progress to downloading status in UI and extension
Browse files- firefox-extension/content.js +18 -7
- flowread-extension.zip +0 -0
- main.py +28 -1
- static/index.html +4 -2
- test_stderr.py +21 -0
- test_tqdm.py +21 -0
firefox-extension/content.js
CHANGED
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@@ -56,8 +56,10 @@ browser.runtime.onMessage.addListener(async (request, sender, sendResponse) => {
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const statusRes = await fetch(`${apiUrl}/status`);
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if (statusRes.ok) {
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const statusData = await statusRes.json();
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-
if (statusData[modelVersion]
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-
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}
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}
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} catch (e) {
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@@ -188,8 +190,10 @@ async function processEntirePage() {
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const statusRes = await fetch(`${apiUrl}/status`);
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if (statusRes.ok) {
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const statusData = await statusRes.json();
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-
if (statusData[modelVersion]
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-
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}
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}
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} catch (e) {}
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@@ -203,8 +207,13 @@ async function processEntirePage() {
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// Only show analyzing text if not downloading
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const statusResTemp = await fetch(`${apiUrl}/status`).catch(() => null);
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if (!statusResTemp || !statusResTemp.ok
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showToast(`FlowRead analyzing page (${processedCount}/${nodesToProcess.length} blocks)...`, 0);
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}
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await Promise.all(batch.map(async (node) => {
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@@ -287,8 +296,10 @@ async function updateExisting(newSettings) {
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const statusRes = await fetch(`${apiUrl}/status`);
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if (statusRes.ok) {
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const statusData = await statusRes.json();
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-
if (statusData[modelVersion]
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-
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}
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}
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} catch (e) {}
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const statusRes = await fetch(`${apiUrl}/status`);
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if (statusRes.ok) {
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const statusData = await statusRes.json();
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if (statusData[modelVersion] && statusData[modelVersion].startsWith("downloading")) {
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const parts = statusData[modelVersion].split(": ");
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const progress = parts.length > 1 ? parts[1] : "...";
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showToast(`Downloading Gemma 4 (${modelVersion}) ${progress}... this may take a few minutes.`, 0);
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}
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}
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} catch (e) {
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const statusRes = await fetch(`${apiUrl}/status`);
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if (statusRes.ok) {
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const statusData = await statusRes.json();
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if (statusData[modelVersion] && statusData[modelVersion].startsWith("downloading")) {
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const parts = statusData[modelVersion].split(": ");
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const progress = parts.length > 1 ? parts[1] : "...";
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showToast(`Downloading Gemma 4 (${modelVersion}) ${progress}... this may take a few minutes.`, 0);
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}
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}
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} catch (e) {}
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// Only show analyzing text if not downloading
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const statusResTemp = await fetch(`${apiUrl}/status`).catch(() => null);
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if (!statusResTemp || !statusResTemp.ok) {
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showToast(`FlowRead analyzing page (${processedCount}/${nodesToProcess.length} blocks)...`, 0);
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} else {
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const statusJson = await statusResTemp.json();
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if (!statusJson[modelVersion] || !statusJson[modelVersion].startsWith("downloading")) {
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showToast(`FlowRead analyzing page (${processedCount}/${nodesToProcess.length} blocks)...`, 0);
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}
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}
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await Promise.all(batch.map(async (node) => {
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const statusRes = await fetch(`${apiUrl}/status`);
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if (statusRes.ok) {
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const statusData = await statusRes.json();
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if (statusData[modelVersion] && statusData[modelVersion].startsWith("downloading")) {
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const parts = statusData[modelVersion].split(": ");
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const progress = parts.length > 1 ? parts[1] : "...";
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showToast(`Downloading Gemma 4 (${modelVersion}) ${progress}... this may take a few minutes.`, 0);
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}
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}
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} catch (e) {}
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flowread-extension.zip
CHANGED
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Binary files a/flowread-extension.zip and b/flowread-extension.zip differ
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main.py
CHANGED
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@@ -233,6 +233,30 @@ def get_study_stats():
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"preferences": preferences
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}
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# --- Saliency API (Existing) ---
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models = {}
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tokenizers = {}
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@@ -249,7 +273,8 @@ def load_model(model_name: str):
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return models[model_name], tokenizers[model_name]
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print(f"Loading {model_name} on {device}...")
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-
model_status[model_name] = "downloading"
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try:
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if model_name == "27b-4a":
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# Use Gemma 4 27B in 4-bit (requires CUDA)
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@@ -285,10 +310,12 @@ def load_model(model_name: str):
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models[model_name] = model
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tokenizers[model_name] = tokenizer
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model_status[model_name] = "loaded"
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return model, tokenizer
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except Exception as e:
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print(f"Error loading model {model_name}: {e}")
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model_status[model_name] = "error"
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raise e
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# Pre-load default 2b
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"preferences": preferences
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}
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import sys
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import re
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class StderrProgressInterceptor:
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def __init__(self, original):
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self.original = original
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self.current_progress = ""
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self.active_model = None
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def write(self, s):
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self.original.write(s)
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match = re.search(r'(\d+)%\|', s)
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if match and self.active_model:
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pct = match.group(1)
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self.current_progress = f"{pct}%"
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# Update the global status explicitly so the API returns it immediately
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model_status[self.active_model] = f"downloading: {self.current_progress}"
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def flush(self):
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self.original.flush()
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stderr_interceptor = StderrProgressInterceptor(sys.stderr)
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sys.stderr = stderr_interceptor
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# --- Saliency API (Existing) ---
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models = {}
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tokenizers = {}
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return models[model_name], tokenizers[model_name]
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print(f"Loading {model_name} on {device}...")
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model_status[model_name] = "downloading: 0%"
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stderr_interceptor.active_model = model_name
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try:
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if model_name == "27b-4a":
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# Use Gemma 4 27B in 4-bit (requires CUDA)
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models[model_name] = model
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tokenizers[model_name] = tokenizer
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model_status[model_name] = "loaded"
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stderr_interceptor.active_model = None
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return model, tokenizer
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except Exception as e:
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print(f"Error loading model {model_name}: {e}")
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model_status[model_name] = "error"
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stderr_interceptor.active_model = None
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raise e
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# Pre-load default 2b
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static/index.html
CHANGED
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@@ -485,8 +485,10 @@
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const statusRes = await fetch('/status');
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if (statusRes.ok) {
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const statusData = await statusRes.json();
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-
if (statusData[modelVersion]
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-
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}
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}
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} catch(e) {}
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const statusRes = await fetch('/status');
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if (statusRes.ok) {
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const statusData = await statusRes.json();
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if (statusData[modelVersion] && statusData[modelVersion].startsWith("downloading")) {
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const parts = statusData[modelVersion].split(": ");
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const progress = parts.length > 1 ? parts[1] : "...";
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loading.textContent = `Downloading Gemma 4 (${modelVersion}) Model ${progress}... this takes a few minutes.`;
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}
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}
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} catch(e) {}
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test_stderr.py
ADDED
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@@ -0,0 +1,21 @@
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import sys
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import re
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class StderrInterceptor:
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def __init__(self, original):
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self.original = original
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def write(self, s):
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self.original.write(s)
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match = re.search(r'(\d+)%\|', s)
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if match:
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self.original.write(f"\nINTERCEPTED: {match.group(1)}%\n")
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self.original.flush()
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def flush(self):
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self.original.flush()
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sys.stderr = StderrInterceptor(sys.stderr)
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from transformers import AutoConfig
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AutoConfig.from_pretrained("gpt2", force_download=True)
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test_tqdm.py
ADDED
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@@ -0,0 +1,21 @@
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import huggingface_hub.utils as hf_utils
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original_tqdm = hf_utils.tqdm
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class MyTqdm(original_tqdm):
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def update(self, n=1):
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super().update(n)
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if hasattr(self, 'total') and self.total:
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print(f"DL_PROGRESS: {self.n / self.total:.2%}", flush=True)
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hf_utils.tqdm = MyTqdm
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hf_utils.tqdm.tqdm = MyTqdm # Also overwrite the module attribute just in case
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import huggingface_hub.file_download
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huggingface_hub.file_download.tqdm = MyTqdm
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try:
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from transformers import AutoConfig
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AutoConfig.from_pretrained("gpt2", force_download=True)
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except Exception as e:
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print(e)
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