Pivy does request and complete but doesn't hint or fill

[Marthaarman]

Tell us what you need help with.

I'm running pivy locally on docker and it works. Sending prompts gives me results.
But, for the inline editor neither the autocomplete nor manual mode give hints (suggestions) in the editor.

the model that i use:
deepseek-coder:1.3b-base

The output:

Any thoughts? What else can I provide you with?

[Marthaarman]

Is it true that the larger code prompts might cause pivy to stop working?

[srikanth235]

From the attached image, it looks like the request was being sent to Ollama instance, but it didn't receive any response. When this happens, I usually restart my Ollama instance and the problem gets resolved. As long as code prompts fit in the context window (16k for deepseek-coder per my knowledge), there shouldn't be any problem with Privy.

[Marthaarman]

From the attached image, it looks like the request was being sent to Ollama instance, but it didn't receive any response. When this happens, I usually restart my Ollama instance and the problem gets resolved. As long as code prompts fit in the context window (16k for deepseek-coder per my knowledge), there shouldn't be any problem with Privy.

That's odd. When posting a small file like:

<?php

function add($a, $b) {
 <pivy do your magic here>
}

?>

Works like a charm...
But opening a larger file, 244 lines, 6 kB. No longer a response and I need to restart pivy.

[srikanth235]

One way of checking whether Ollama is causing trouble or not is by copy-pasting the prompt from the VSCode logs and trying it on Ollama CLI.

[Marthaarman]

One way of checking whether Ollama is causing trouble or not is by copy-pasting the prompt from the VSCode logs and trying it on Ollama CLI.

will do tomorrow, I'll let you know

[Marthaarman]

I created a txt file: prompt.txt
I pasted the prompt which is also shown in the output in vs code and saved it

file_content=$(<prompt.txt)

Than I ran:

curl http://localhost:11434/api/generate -d '{
  "model": "deepseek-coder:1.3b-base",
  "prompt": "$file_content"
}'

I got back a whole stream:

{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.166394846Z","response":" =","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.197782262Z","response":" '","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.236616542Z","response":"\n","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.26618142Z","response":"   ","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.295955301Z","response":" const","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.325796298Z","response":" config","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.355276855Z","response":" =","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.385206786Z","response":" {","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.417631977Z","response":"\n","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.460066369Z","response":"       ","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.4903207Z","response":" api","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.519440794Z","response":":","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.548275457Z","response":" \"","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.590703679Z","response":"'.","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.62059622Z","response":"$","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.66392041Z","response":"api","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.693767657Z","response":".'","done":false}
{"model":"deepseek-coder:1.3b-base","created_at":"2024-03-20T10:19:56.723409658Z","response":"\",","done":false}
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[srikanth235]

Apologies for the delayed response. I tested it with large-size files from my end too. The inline suggestions are not displayed when the inference times are longer (~5 seconds or longer). My guess is probably some sort of timeout logic from the VSCode editor end. In the output attached above too, I see the total inference duration is around ~8 seconds. Probably, that's why you are not seeing the editor suggestions too. I haven't yet completely tracked this down due to time constraints. Once I made some progress, will update here.

[Marthaarman]

Apologies for the delayed response. I tested it with large-size files from my end too. The inline suggestions are not displayed when the inference times are longer (~5 seconds or longer). My guess is probably some sort of timeout logic from the VSCode editor end. In the output attached above too, I see the total inference duration is around ~8 seconds. Probably, that's why you are not seeing the editor suggestions too. I haven't yet completely tracked this down due to time constraints. Once I made some progress, will update here.

Good debugging!
So maybe, since I'm just running ollama in a docker container (see setup below) on my dell xps13 laptop without nvidia graphics card this is too slow?

version: '3.8'
services:
  ollama:
    image: ollama/ollama:latest
    ports:
      - 11434:11434
    volumes:
      - .:/code
      - ./ollama/ollama:/root/.ollama
    container_name: ollama
    pull_policy: always
    tty: true
    restart: unless-stopped

[srikanth235]

Quite possible. The key point per my understanding, is for the files you want to run Privy on, the inference time from your Ollama host shouldn't take more than a few seconds. If you can speed up your local Ollama instance, please give it a try.