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Switch from urllib to requests to improve reliability (#867)

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* Switch from urllib to requests to improve reliability

* Keep ruff linter-specific

* update

* update

* update
This commit is contained in:
Sebastian Raschka
2025-10-07 15:22:59 -05:00
committed by GitHub
parent 8552565bda
commit 7bd263144e
47 changed files with 592 additions and 436 deletions
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59
ch07/01_main-chapter-code/ch07.ipynb
View File

@@ -169,10 +169,33 @@
"source": [
"import json\n",
"import os\n",
"import urllib\n",
"import requests\n",
"\n",
"\n",
"def download_and_load_file(file_path, url):\n",
" if not os.path.exists(file_path):\n",
" response = requests.get(url, timeout=30)\n",
" response.raise_for_status()\n",
" text_data = response.text\n",
" with open(file_path, \"w\", encoding=\"utf-8\") as file:\n",
" file.write(text_data)\n",
"\n",
" with open(file_path, \"r\", encoding=\"utf-8\") as file:\n",
" data = json.load(file)\n",
"\n",
" return data\n",
"\n",
"\n",
"# The book originally used the following code below\n",
"# However, urllib uses older protocol settings that\n",
"# can cause problems for some readers using a VPN.\n",
"# The `requests` version above is more robust\n",
"# in that regard.\n",
"\n",
"\"\"\"\n",
"import urllib\n",
"\n",
"def download_and_load_file(file_path, url):\n",
"\n",
" if not os.path.exists(file_path):\n",
" with urllib.request.urlopen(url) as response:\n",
@@ -180,15 +203,15 @@
" with open(file_path, \"w\", encoding=\"utf-8\") as file:\n",
" file.write(text_data)\n",
"\n",
" # The book originally contained this unnecessary \"else\" clause:\n",
" #else:\n",
" # with open(file_path, \"r\", encoding=\"utf-8\") as file:\n",
" # text_data = file.read()\n",
" else:\n",
" with open(file_path, \"r\", encoding=\"utf-8\") as file:\n",
" text_data = file.read()\n",
"\n",
" with open(file_path, \"r\", encoding=\"utf-8\") as file:\n",
" data = json.load(file)\n",
"\n",
" return data\n",
"\"\"\"\n",
"\n",
"\n",
"file_path = \"instruction-data.json\"\n",
@@ -2490,7 +2513,8 @@
}
],
"source": [
"import urllib.request\n",
"import requests # noqa: F811\n",
"# import urllib.request\n",
"\n",
"def query_model(\n",
" prompt,\n",
@@ -2512,7 +2536,8 @@
" }\n",
" }\n",
"\n",
"\n",
" \n",
" \"\"\"\n",
" # Convert the dictionary to a JSON formatted string and encode it to bytes\n",
" payload = json.dumps(data).encode(\"utf-8\")\n",
"\n",
@@ -2536,6 +2561,26 @@
" response_data += response_json[\"message\"][\"content\"]\n",
"\n",
" return response_data\n",
" \"\"\"\n",
"\n",
" # The book originally used the commented-out above, which is based\n",
" # on urllib. It works generally fine, but some readers reported\n",
" # issues with using urlib when using a (company) VPN.\n",
" # The code below uses the requests library, which doesn't seem\n",
" # to have these issues.\n",
"\n",
" # Send the POST request\n",
" with requests.post(url, json=data, stream=True, timeout=30) as r:\n",
" r.raise_for_status()\n",
" response_data = \"\"\n",
" for line in r.iter_lines(decode_unicode=True):\n",
" if not line:\n",
" continue\n",
" response_json = json.loads(line)\n",
" if \"message\" in response_json:\n",
" response_data += response_json[\"message\"][\"content\"]\n",
"\n",
" return response_data\n",
"\n",
"\n",
"model = \"llama3\"\n",

10
ch07/01_main-chapter-code/exercise_experiments.py
View File

@@ -12,10 +12,10 @@ import math
import os
import re
import time
import urllib
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
import requests
import tiktoken
import torch
from torch.utils.data import Dataset, DataLoader
@@ -234,17 +234,17 @@ def custom_collate_with_masking_fn(
def download_and_load_file(file_path, url):
if not os.path.exists(file_path):
with urllib.request.urlopen(url) as response:
text_data = response.read().decode("utf-8")
response = requests.get(url, timeout=30)
response.raise_for_status()
text_data = response.text
with open(file_path, "w", encoding="utf-8") as file:
file.write(text_data)
else:
with open(file_path, "r", encoding="utf-8") as file:
text_data = file.read()
with open(file_path, "r") as file:
with open(file_path, "r", encoding="utf-8") as file:
data = json.load(file)
return data

76
ch07/01_main-chapter-code/gpt_download.py
View File

@@ -5,11 +5,10 @@
import os
import urllib.request
# import requests
import json
import numpy as np
import requests
import tensorflow as tf
from tqdm import tqdm
@@ -48,44 +47,40 @@ def download_and_load_gpt2(model_size, models_dir):
def download_file(url, destination, backup_url=None):
def _attempt_download(download_url):
with urllib.request.urlopen(download_url) as response:
# Get the total file size from headers, defaulting to 0 if not present
file_size = int(response.headers.get("Content-Length", 0))
response = requests.get(download_url, stream=True, timeout=60)
response.raise_for_status()
# Check if file exists and has the same size
if os.path.exists(destination):
file_size_local = os.path.getsize(destination)
if file_size == file_size_local:
print(f"File already exists and is up-to-date: {destination}")
return True # Indicate success without re-downloading
file_size = int(response.headers.get("Content-Length", 0))
block_size = 1024 # 1 Kilobyte
# Check if file exists and has same size
if os.path.exists(destination):
file_size_local = os.path.getsize(destination)
if file_size and file_size == file_size_local:
print(f"File already exists and is up-to-date: {destination}")
return True
# Initialize the progress bar with total file size
progress_bar_description = os.path.basename(download_url)
with tqdm(total=file_size, unit="iB", unit_scale=True, desc=progress_bar_description) as progress_bar:
with open(destination, "wb") as file:
while True:
chunk = response.read(block_size)
if not chunk:
break
block_size = 1024 # 1 KB
desc = os.path.basename(download_url)
with tqdm(total=file_size, unit="iB", unit_scale=True, desc=desc) as progress_bar:
with open(destination, "wb") as file:
for chunk in response.iter_content(chunk_size=block_size):
if chunk:
file.write(chunk)
progress_bar.update(len(chunk))
return True
return True
try:
if _attempt_download(url):
return
except (urllib.error.HTTPError, urllib.error.URLError):
except requests.exceptions.RequestException:
if backup_url is not None:
print(f"Primary URL ({url}) failed. Attempting backup URL: {backup_url}")
try:
if _attempt_download(backup_url):
return
except urllib.error.HTTPError:
except requests.exceptions.RequestException:
pass
# If we reach here, both attempts have failed
error_message = (
f"Failed to download from both primary URL ({url})"
f"{' and backup URL (' + backup_url + ')' if backup_url else ''}."
@@ -97,37 +92,6 @@ def download_file(url, destination, backup_url=None):
print(f"An unexpected error occurred: {e}")
# Alternative way using `requests`
"""
def download_file(url, destination):
# Send a GET request to download the file in streaming mode
response = requests.get(url, stream=True)
# Get the total file size from headers, defaulting to 0 if not present
file_size = int(response.headers.get("content-length", 0))
# Check if file exists and has the same size
if os.path.exists(destination):
file_size_local = os.path.getsize(destination)
if file_size == file_size_local:
print(f"File already exists and is up-to-date: {destination}")
return
# Define the block size for reading the file
block_size = 1024 # 1 Kilobyte
# Initialize the progress bar with total file size
progress_bar_description = url.split("/")[-1] # Extract filename from URL
with tqdm(total=file_size, unit="iB", unit_scale=True, desc=progress_bar_description) as progress_bar:
# Open the destination file in binary write mode
with open(destination, "wb") as file:
# Iterate over the file data in chunks
for chunk in response.iter_content(block_size):
progress_bar.update(len(chunk)) # Update progress bar
file.write(chunk) # Write the chunk to the file
"""
def load_gpt2_params_from_tf_ckpt(ckpt_path, settings):
# Initialize parameters dictionary with empty blocks for each layer
params = {"blocks": [{} for _ in range(settings["n_layer"])]}

10
ch07/01_main-chapter-code/gpt_instruction_finetuning.py
View File

@@ -11,9 +11,9 @@ import json
import os
import re
import time
import urllib
import matplotlib.pyplot as plt
import requests
import tiktoken
import torch
from torch.utils.data import Dataset, DataLoader
@@ -97,14 +97,14 @@ def custom_collate_fn(
def download_and_load_file(file_path, url):
if not os.path.exists(file_path):
with urllib.request.urlopen(url) as response:
text_data = response.read().decode("utf-8")
response = requests.get(url, timeout=30)
response.raise_for_status()
text_data = response.text
with open(file_path, "w", encoding="utf-8") as file:
file.write(text_data)
with open(file_path, "r") as file:
with open(file_path, "r", encoding="utf-8") as file:
data = json.load(file)
return data

25
ch07/01_main-chapter-code/ollama_evaluate.py
View File

@@ -8,7 +8,7 @@
import json
import psutil
from tqdm import tqdm
import urllib.request
import requests
def query_model(prompt, model="llama3", url="http://localhost:11434/api/chat"):
@@ -25,23 +25,16 @@ def query_model(prompt, model="llama3", url="http://localhost:11434/api/chat"):
}
}
# Convert the dictionary to a JSON formatted string and encode it to bytes
payload = json.dumps(data).encode("utf-8")
# Create a request object, setting the method to POST and adding necessary headers
request = urllib.request.Request(url, data=payload, method="POST")
request.add_header("Content-Type", "application/json")
# Send the request and capture the response
response_data = ""
with urllib.request.urlopen(request) as response:
# Read and decode the response
while True:
line = response.readline().decode("utf-8")
# Send the POST request
with requests.post(url, json=data, stream=True, timeout=30) as r:
r.raise_for_status()
response_data = ""
for line in r.iter_lines(decode_unicode=True):
if not line:
break
continue
response_json = json.loads(line)
response_data += response_json["message"]["content"]
if "message" in response_json:
response_data += response_json["message"]["content"]
return response_data

28
ch07/03_model-evaluation/llm-instruction-eval-ollama.ipynb
View File

@@ -215,8 +215,8 @@
}
],
"source": [
"import urllib.request\n",
"import json\n",
"import requests\n",
"\n",
"\n",
"def query_model(prompt, model=\"llama3\", url=\"http://localhost:11434/api/chat\"):\n",
@@ -236,27 +236,19 @@
" }\n",
" }\n",
"\n",
" # Convert the dictionary to a JSON formatted string and encode it to bytes\n",
" payload = json.dumps(data).encode(\"utf-8\")\n",
"\n",
" # Create a request object, setting the method to POST and adding necessary headers\n",
" request = urllib.request.Request(url, data=payload, method=\"POST\")\n",
" request.add_header(\"Content-Type\", \"application/json\")\n",
"\n",
" # Send the request and capture the response\n",
" response_data = \"\"\n",
" with urllib.request.urlopen(request) as response:\n",
" # Read and decode the response\n",
" while True:\n",
" line = response.readline().decode(\"utf-8\")\n",
" # Send the POST request\n",
" with requests.post(url, json=data, stream=True, timeout=30) as r:\n",
" r.raise_for_status()\n",
" response_data = \"\"\n",
" for line in r.iter_lines(decode_unicode=True):\n",
" if not line:\n",
" break\n",
" continue\n",
" response_json = json.loads(line)\n",
" response_data += response_json[\"message\"][\"content\"]\n",
" if \"message\" in response_json:\n",
" response_data += response_json[\"message\"][\"content\"]\n",
"\n",
" return response_data\n",
"\n",
"\n",
"result = query_model(\"What do Llamas eat?\")\n",
"print(result)"
]
@@ -640,7 +632,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.16"
}
},
"nbformat": 4,

27
ch07/04_preference-tuning-with-dpo/create-preference-data-ollama.ipynb
View File

@@ -274,8 +274,8 @@
}
],
"source": [
"import urllib.request\n",
"import json\n",
"import requests\n",
"\n",
"\n",
"def query_model(prompt, model=\"llama3.1:70b\", url=\"http://localhost:11434/api/chat\"):\n",
@@ -294,23 +294,16 @@
" }\n",
" }\n",
"\n",
" # Convert the dictionary to a JSON formatted string and encode it to bytes\n",
" payload = json.dumps(data).encode(\"utf-8\")\n",
"\n",
" # Create a request object, setting the method to POST and adding necessary headers\n",
" request = urllib.request.Request(url, data=payload, method=\"POST\")\n",
" request.add_header(\"Content-Type\", \"application/json\")\n",
"\n",
" # Send the request and capture the response\n",
" response_data = \"\"\n",
" with urllib.request.urlopen(request) as response:\n",
" # Read and decode the response\n",
" while True:\n",
" line = response.readline().decode(\"utf-8\")\n",
" # Send the POST request\n",
" with requests.post(url, json=data, stream=True, timeout=30) as r:\n",
" r.raise_for_status()\n",
" response_data = \"\"\n",
" for line in r.iter_lines(decode_unicode=True):\n",
" if not line:\n",
" break\n",
" continue\n",
" response_json = json.loads(line)\n",
" response_data += response_json[\"message\"][\"content\"]\n",
" if \"message\" in response_json:\n",
" response_data += response_json[\"message\"][\"content\"]\n",
"\n",
" return response_data\n",
"\n",
@@ -587,7 +580,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.16"
}
},
"nbformat": 4,

12
ch07/04_preference-tuning-with-dpo/dpo-from-scratch.ipynb
View File

@@ -231,23 +231,21 @@
"source": [
"import json\n",
"import os\n",
"import urllib\n",
"import requests\n",
"\n",
"\n",
"def download_and_load_file(file_path, url):\n",
"\n",
" if not os.path.exists(file_path):\n",
" with urllib.request.urlopen(url) as response:\n",
" text_data = response.read().decode(\"utf-8\")\n",
" response = requests.get(url, timeout=30)\n",
" response.raise_for_status()\n",
" text_data = response.text\n",
" with open(file_path, \"w\", encoding=\"utf-8\") as file:\n",
" file.write(text_data)\n",
" else:\n",
" with open(file_path, \"r\", encoding=\"utf-8\") as file:\n",
" text_data = file.read()\n",
"\n",
" with open(file_path, \"r\", encoding=\"utf-8\") as file:\n",
" data = json.load(file)\n",
"\n",
" data = json.loads(text_data)\n",
" return data\n",
"\n",
"\n",

32
ch07/05_dataset-generation/llama3-ollama.ipynb
View File

@@ -194,8 +194,8 @@
"metadata": {},
"outputs": [],
"source": [
"import urllib.request\n",
"import json\n",
"import requests\n",
"\n",
"def query_model(prompt, model=\"llama3\", url=\"http://localhost:11434/api/chat\", role=\"user\"):\n",
" # Create the data payload as a dictionary\n",
@@ -209,25 +209,21 @@
" ]\n",
" }\n",
"\n",
" # Convert the dictionary to a JSON formatted string and encode it to bytes\n",
" payload = json.dumps(data).encode(\"utf-8\")\n",
"\n",
" # Create a request object, setting the method to POST and adding necessary headers\n",
" request = urllib.request.Request(url, data=payload, method=\"POST\")\n",
" request.add_header(\"Content-Type\", \"application/json\")\n",
"\n",
" # Send the request and capture the response\n",
" response_data = \"\"\n",
" with urllib.request.urlopen(request) as response:\n",
" # Read and decode the response\n",
" while True:\n",
" line = response.readline().decode(\"utf-8\")\n",
" # Send the POST request\n",
" with requests.post(url, json=data, stream=True, timeout=30) as r:\n",
" r.raise_for_status()\n",
" response_data = \"\"\n",
" for line in r.iter_lines(decode_unicode=True):\n",
" if not line:\n",
" break\n",
" continue\n",
" response_json = json.loads(line)\n",
" response_data += response_json[\"message\"][\"content\"]\n",
" if \"message\" in response_json:\n",
" response_data += response_json[\"message\"][\"content\"]\n",
"\n",
" return response_data"
" return response_data\n",
"\n",
"result = query_model(\"What do Llamas eat?\")\n",
"print(result)"
]
},
{
@@ -498,7 +494,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
"version": "3.10.16"
}
},
"nbformat": 4,