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Refactor LLM code for performance optimization and logging

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This commit is contained in:
bobo.yang 2024-06-04 08:30:04 +08:00
parent a05caa9f31
commit 4eea931db1
1 changed files with 13 additions and 0 deletions
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13
src/contributes/codecomplete/llm.ts
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@ -193,6 +193,8 @@ export async function * devchatComplete(prompt: string) : AsyncGenerator<CodeCom
model = "ollama/starcoder2:15b";
}
const startTimeLLM = process.hrtime();
const headers = {
'Content-Type': 'application/json'
};
@ -217,6 +219,11 @@ export async function * devchatComplete(prompt: string) : AsyncGenerator<CodeCom
const stream = response.body as any;
const decoder = new TextDecoder("utf-8");
const endTimeLLM = process.hrtime(startTimeLLM);
const durationLLM = endTimeLLM[0] + endTimeLLM[1] / 1e9;
logger.channel()?.debug(`LLM first chunk took ${durationLLM} seconds`);
let hasFirstLine = false;
for await (const chunk of stream) {
const chunkDataText = decoder.decode(chunk).trim();
// split chunkText by "data: ", for example:
@ -245,6 +252,12 @@ export async function * devchatComplete(prompt: string) : AsyncGenerator<CodeCom
try {
const data = JSON.parse(chunkText.substring(5).trim());
if (!hasFirstLine && data.choices[0].text.indexOf("\n") !== -1) {
hasFirstLine = true;
const endTimeLine = process.hrtime(startTimeLLM);
const durationLine = endTimeLine[0] + endTimeLine[1] / 1e9;
logger.channel()?.debug(`LLM first line took ${durationLine} seconds`);
}
yield {
text: data.choices[0].text,
id: data.id