From 3444cf785d0e73ab28649abb8fc8a45256973ade Mon Sep 17 00:00:00 2001
From: terminaldweller <devi@terminaldweller.com>
Date: Thu, 27 Apr 2023 14:28:44 +0330
Subject: magni can now get a user agent from an env var, fixed the readme for
 http_proxy

---
 README.md | 19 +++++++++++++------
 magni.py  | 16 ++++++----------
 2 files changed, 19 insertions(+), 16 deletions(-)

diff --git a/README.md b/README.md
index 9f8a723..64307ac 100644
--- a/README.md
+++ b/README.md
@@ -31,17 +31,24 @@ HTTPS_PROXY=socks5h://127.0.0.1:9094 poetry run ./magni.py --url https://chapman
 ## Env Vars
 magni recognizes three environment variables:</br>
 
-### HTTPS_PROXY
-You must specify a socks5 proxy here since magni uses `pysocks` to make the connections.</br>
-If the env var is not defined magni will not use any proxy.</br>
+### HTTP_PROXY/HTTPS_PROXY
+You can also specify a socks5 proxy here since magni uses `pysocks` to make the connections.</br>
+If the env vars are not defined or are empty magni will not use any proxy.</br>
 
 ### MAGNI_MODEL_PATH
-Path to the directory where magni will store the model.</br>
-If the env var is not defined, magni will use `./models` as a default value.</br>
+Path to the directory where magni will store the models.</br>
+If the env var is not defined or is empty, magni will use `./models` as a default value.</br>
 
 ### MAGNI_IMAGE_PATH
 Path to the directory where magni will store the upscaled images.</br>
-If the env var is not defined or empty magni will use `./images` as a default value.</br>
+If the env var is not defined or is empty magni will use `./images` as a default value.</br>
+
+### MAGNI_USER_AGENT
+The user agent magni will use the download the images.</br>
+If the env var is not defined or is empty, magni will use a default user agent you can see below:</br>
+```
+Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36
+```
 
 ## TODO
 * currently the models we are using are not as effective. I should either fine ones that are specifically trained on greyscale images or just train some myself.</br>
diff --git a/magni.py b/magni.py
index 146a758..0ca77e3 100755
--- a/magni.py
+++ b/magni.py
@@ -120,17 +120,13 @@ def fsrcnn_superscaler(img):
 # flake8: noqa: E501
 def get_user_agent() -> str:
     """Returns a random user agent."""
-    # user_agents = [
-    #     "Mozilla/5.0 (Windows NT 10.0; rv:91.0) Gecko/20100101 Firefox/91.0",
-    #     "Mozilla/5.0 (Windows NT 10.0; rv:78.0) Gecko/20100101 Firefox/78.0",
-    #     "Mozilla/5.0 (X11; Linux x86_64; rv:95.0) Gecko/20100101 Firefox/95.0",
-    #     "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36",
-    # ]
-    user_agents = [
-        "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36",
-    ]
+    user_agent: str = ""
+    if "MAGNI_USER_AGENT" in os.environ and os.environ["MAGNI_USER_AGENT"]:
+        user_agent = os.environ["MAGNI_USER_AGENT"]
+    else:
+        user_agent = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36"
 
-    return user_agents[secrets.randbelow(len(user_agents))]
+    return user_agent
 
 
 def get_proxies() -> typing.Dict:
-- 
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