Wrestling with the configuration for the models in Continue extension in VS Code.
Weird that none of the configurations worked, except when I set autodetect for Ollama in the Continue extension and suddenly the AI model is introducing themselves to me after I asked them everytime I switched models.
14 billion parameter model is very slow to answer.
PS C:\opt\ai-projects\llm_engineering_in_python> ollama pull qwen2.5-coder:14b
pulling manifest
pulling ac9bc7a69dab: 100% ▕████████████████████████████████████████████▏ 9.0 GB
pulling 66b9ea09bd5b: 100% ▕████████████████████████████████████████████▏ 68 B
pulling 1e65450c3067: 100% ▕████████████████████████████████████████████▏ 1.6 KB
pulling 832dd9e00a68: 100% ▕████████████████████████████████████████████▏ 11 KB
pulling 0578f229f23a: 100% ▕████████████████████████████████████████████▏ 488 B
verifying sha256 digest
writing manifest
success
Time to setup our VS Code with these open source or open weight AI models and hopefully, the AI coding assistance capabilities should be just fine. Who knows I don't need to pay for Codex for the next month 😆
Alright did 2 python exercises under that AI Engineering course and already submitted the PR.
So let's check our Ollama pull for that 14 billion paramater model:
PS C:\opt\ai-projects\llm_engineering_in_python> ollama pull qwen2.5-coder:14b
pulling manifest
pulling ac9bc7a69dab: 51% ▕██████████████████████ ▏ 4.6 GB/9.0 GB 7.9 MB/s 9m11s
Going to get some rest and then we do a 10km run.
Also, I have notified my martial arts master that I won't be around again for the training because of the preparation of the technical interviews and technical tests.
First ever work on a forked project. PR Already submitted. Will be working more on the next coding exercises under AI Engineering.
We still at
PS C:\opt\ai-projects\llm_engineering_in_python> ollama pull qwen2.5-coder:14b
pulling manifest
pulling ac9bc7a69dab: 35% ▕███████████████ ▏ 3.1 GB/9.0 GB 9.1 MB/s 10m41s
Just woke up a few minutes already and my pull for that 14 billion parameters AI model was cut off. Connection reset by the server WTH 😅
Restarted that pull again:
PS C:\opt\ai-projects\llm_engineering_in_python> ollama pull qwen2.5-coder:14b
pulling manifest
pulling ac9bc7a69dab: 27% ▕████ ▏ 2.4 GB/9.0 GB 339 KB/s 5h23m
Fork done and did a git clone but then some issues when I opened the project from Cursor as it is not able to find the appropriate kernel.
Turns out I need to do uv self update which took a new version and then do the update sync which creates the .venv and then from there I was able to select the appropriate Python kernel.
[INFO] Downloaded 340,000/361,483 (94%)
[ERROR] Failed to process CVE-2026-6785
org.owasp.dependencycheck.data.nvdcve.DatabaseException: Error updating 'CVE-2026-6785'; Value too long for column "URL CHARACTER VARYING(1000)": "'https://bugzilla.mozilla.org/buglist.cgi?bug_id=1935995%2C1999158%2C2015952%2C2... (1585)"; SQL statement:
INSERT INTO reference (cveid, name, url, source) VALUES (?, ?, ?, ?) [22001-240]
at org.owasp.dependencycheck.data.nvdcve.CveDB.updateVulnerability (CveDB.java:1104)
at org.owasp.dependencycheck.data.update.nvd.api.NvdApiProcessor.updateCveDb (NvdApiProcessor.java:119)
at org.owasp.dependencycheck.data.update.nvd.api.NvdApiProcessor.call (NvdApiProcessor.java:96)
at org.owasp.dependencycheck.data.update.nvd.api.NvdApiProcessor.call (NvdApiProcessor.java:40)
at java.util.concurrent.FutureTask.run (FutureTask.java:264)
at java.util.concurrent.ThreadPoolExecutor.runWorker (ThreadPoolExecutor.java:1136)
at java.util.concurrent.ThreadPoolExecutor$Worker.run (ThreadPoolExecutor.java:635)
at java.lang.Thread.run (Thread.java:842)
[ERROR] Failed to process CVE-2026-6786
org.owasp.dependencycheck.data.nvdcve.DatabaseException: Error updating 'CVE-2026-6786'; Value too long for column "URL CHARACTER VARYING(1000)": "'https://bugzilla.mozilla.org/buglist.cgi?bug_id=2010727%2C2019004%2C2019224%2C2... (1115)"; SQL statement:
INSERT INTO reference (cveid, name, url, source) VALUES (?, ?, ?, ?) [22001-240]
at org.owasp.dependencycheck.data.nvdcve.CveDB.updateVulnerability (CveDB.java:1104)
at org.owasp.dependencycheck.data.update.nvd.api.NvdApiProcessor.updateCveDb (NvdApiProcessor.java:119)
at org.owasp.dependencycheck.data.update.nvd.api.NvdApiProcessor.call (NvdApiProcessor.java:96)
at org.owasp.dependencycheck.data.update.nvd.api.NvdApiProcessor.call (NvdApiProcessor.java:40)
at java.util.concurrent.FutureTask.run (FutureTask.java:264)
at java.util.concurrent.ThreadPoolExecutor.runWorker (ThreadPoolExecutor.java:1136)
at java.util.concurrent.ThreadPoolExecutor$Worker.run (ThreadPoolExecutor.java:635)
at java.lang.Thread.run (Thread.java:842)
Same problem even if I used the recent version of OWASP Dependency Check dependency in Spring Boot.
Waste of time 😒
In my experience working as a software engineer, I've always been using branch-based workflow on pull requests. That means pull requests are for the same branches within the same repo.
Now I realized that the repo used in the AI Engineering course is read only and so I could not submit my exercises unless I fork and do a fork-based workflow pull request.
Doing a fork now.