backup current work

This commit is contained in:
Erikas 2024-08-07 21:22:31 +03:00
parent 00775d3514
commit 4b586b3860
5 changed files with 263 additions and 0 deletions

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@ -366,6 +366,8 @@ func getBenchmark(c *gin.Context) {
return
}
getAISummary(benchmarkDatas, benchmark.Title, benchmark.Description, "", "")
c.HTML(http.StatusOK, "benchmark.tmpl", gin.H{
"activePage": "benchmark",
"username": session.Get("Username"),

View File

@ -15,6 +15,8 @@ type Config struct {
DiscordClientSecret string
DiscordRedirectURL string
SessionSecret string
OpenAIApiKey string
OpenAIModel string
Version bool
}
@ -27,6 +29,8 @@ func NewConfig() (*Config, error) {
discordClientSecret := flag.String("discord-client-secret", "", "Discord OAuth2 client secret (see https://discord.com/developers/applications)")
discordRedirectURL := flag.String("discord-redirect-url", "", "Discord OAuth2 redirect URL (<scheme>://<domain>/login/callback)")
sessionSecret := flag.String("session-secret", "", "Session secret")
openaiApiKey := flag.String("openai-api-key", "", "OpenAI API Key (optional, leave empty to disable OpenAI integration)")
openaiModel := flag.String("openai-model", "", "OpenAI model ID (optional, leave empty to use the default model)")
flagVersion := flag.Bool("version", false, "prints version of the application")
envflag.Parse(envflag.WithPrefix("FS_"))
@ -39,6 +43,8 @@ func NewConfig() (*Config, error) {
DiscordClientSecret: *discordClientSecret,
DiscordRedirectURL: *discordRedirectURL,
SessionSecret: *sessionSecret,
OpenAIApiKey: *openaiApiKey,
OpenAIModel: *openaiModel,
Version: *flagVersion,
}
@ -62,6 +68,9 @@ func NewConfig() (*Config, error) {
if config.SessionSecret == "" {
return nil, errors.New("missing session-secret argument")
}
if (config.OpenAIApiKey == "" && config.OpenAIModel != "") || (config.OpenAIApiKey != "" && config.OpenAIModel == "") {
return nil, errors.New("openai-api-key and openai-model must be both empty or both non-empty")
}
return config, nil
}

1
go.mod
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@ -40,6 +40,7 @@ require (
github.com/pelletier/go-toml/v2 v2.2.2 // indirect
github.com/ravener/discord-oauth2 v0.0.0-20230514095040-ae65713199b3
github.com/remyoudompheng/bigfft v0.0.0-20230129092748-24d4a6f8daec // indirect
github.com/sashabaranov/go-openai v1.28.0
github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
github.com/ugorji/go/codec v1.2.12 // indirect
golang.org/x/arch v0.8.0 // indirect

2
go.sum
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@ -171,6 +171,8 @@ github.com/rogpeppe/go-internal v1.3.0/go.mod h1:M8bDsm7K2OlrFYOpmOWEs/qY81heoFR
github.com/rs/xid v1.2.1/go.mod h1:+uKXf+4Djp6Md1KODXJxgGQPKngRmWyn10oCKFzNHOQ=
github.com/rs/zerolog v1.13.0/go.mod h1:YbFCdg8HfsridGWAh22vktObvhZbQsZXe4/zB0OKkWU=
github.com/rs/zerolog v1.15.0/go.mod h1:xYTKnLHcpfU2225ny5qZjxnj9NvkumZYjJHlAThCjNc=
github.com/sashabaranov/go-openai v1.28.0 h1:WS9F9BriSvtHvknPQy2Oi3b+8zkmJdEXcycrWqrSicQ=
github.com/sashabaranov/go-openai v1.28.0/go.mod h1:lj5b/K+zjTSFxVLijLSTDZuP7adOgerWeFyZLUhAKRg=
github.com/satori/go.uuid v1.2.0/go.mod h1:dA0hQrYB0VpLJoorglMZABFdXlWrHn1NEOzdhQKdks0=
github.com/shopspring/decimal v0.0.0-20180709203117-cd690d0c9e24/go.mod h1:M+9NzErvs504Cn4c5DxATwIqPbtswREoFCre64PpcG4=
github.com/shopspring/decimal v1.2.0/go.mod h1:DKyhrW/HYNuLGql+MJL6WCR6knT2jwCFRcu2hWCYk4o=

249
openai.go Normal file
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@ -0,0 +1,249 @@
package flightlesssomething
import (
"context"
"fmt"
"math"
"sort"
"strconv"
"strings"
openai "github.com/sashabaranov/go-openai"
)
const systemMessage = `
You are given a summary of PC benchmark data. Your task is to provide conclusion and overview of the given data:
0. Your summary must consist of max 3 segments - "Highest and Smoothest FPS", "Anomalies" and "Summary".
1. Provide which run has the highest (average) fps and which has the smoothest fps (based on fps/frametime std.dev. and variance). Do not hesitate to mention multiple runs if they are incredibly similar. Also provide overall the best run. Try to understand which one has the best sweet "average" in terms of being smoothest and highest FPS.
2. Anomalies in the data (if any). For example, if all benchmarks uses the same hardware/software? Or of certain run has lower/higher FPS that correlates to higher/lower VRAM usage, core clock, mem clock, etc. Try to figure out why is it so, by looking ONLY at the provided data. Do NOT mention anything if it's not an anomaly.
3. If certain run had much worse FPS/Frametime than others, then exclude it from consideration in point 1. In point 2, try to figure out why it is so (first consider GPU VRAM, core clock, mem clock, then RAM/SWAP and other factors, while lastly CPU and GPU usage). If you can't figure out why, then just say so.
4. Point 3 must be your TOP priority. Do NOT provide any other information than requested.
5. You can mention labels in a natural way. E.g. you can call "lavd-defaults" just "LAVD" (if this makes sense).
6. Use bullet points for point 1 and 2. Use paragraph for point 3.
7. NEVER provide actual number or "higher/lower than". Instead, ALWAYS provide exact/approximate percentage in comparison to others.
8. NEVER guess the issue outside of the provided data. If you can't figure out why, then just say so.
9. ALWAYS mention in "anomalies" if certain run has correlation of higher/lower FPS with certain metrics (e.g. VRAM usage, core clock, mem clock, ram, swap, cpu, gpu). Only mention if there is significant correlation, at least 5 percent.
10. Provide an extended summary overview of all runs, but avoid repeating yourself of what you mentioned in point 1 and 2.
Do not provide numbers or visualize anything - user can already see charts.
`
func getAISummary(bds []*BenchmarkData, bdTitle, bdDescription, openaiApiKey, openaiModel string) (string, error) {
userPrompt := writeAIPrompt(bds, bdTitle, bdDescription)
fmt.Println(userPrompt)
return "", nil
client := openai.NewClient(openaiApiKey)
resp, err := client.CreateChatCompletion(
context.Background(),
openai.ChatCompletionRequest{
Model: openaiModel,
Messages: []openai.ChatCompletionMessage{
{Role: openai.ChatMessageRoleSystem, Content: systemMessage},
{Role: openai.ChatMessageRoleUser, Content: userPrompt},
},
},
)
if err != nil {
return "", err
}
return resp.Choices[0].Message.Content, nil
}
func writeAIPrompt(bds []*BenchmarkData, bdTitle, bdDescription string) string {
sb := strings.Builder{}
sb.WriteString("Benchmark title: ")
sb.WriteString(bdTitle)
sb.WriteString("\n")
sb.WriteString("Benchmark description: \n")
sb.WriteString(bdDescription)
sb.WriteString("\n\n")
sb.WriteString("Benchmark contains ")
sb.WriteString(strconv.Itoa(len(bds)))
sb.WriteString(" runs:\n")
for _, benchmarkRun := range bds {
sb.WriteString("\nLabel: ")
sb.WriteString(benchmarkRun.Label)
sb.WriteString("\n")
sb.WriteString("OS: ")
sb.WriteString(benchmarkRun.SpecOS)
sb.WriteString("\n")
sb.WriteString("GPU: ")
sb.WriteString(benchmarkRun.SpecGPU)
sb.WriteString("\n")
sb.WriteString("CPU: ")
sb.WriteString(benchmarkRun.SpecCPU)
sb.WriteString("\n")
sb.WriteString("RAM: ")
sb.WriteString(benchmarkRun.SpecRAM)
sb.WriteString("\n")
sb.WriteString("Linux kernel: ")
sb.WriteString(benchmarkRun.SpecLinuxKernel)
sb.WriteString("\n")
sb.WriteString("Linux scheduler: ")
sb.WriteString(benchmarkRun.SpecLinuxScheduler)
sb.WriteString("\n")
// FPS
stats := calculateAIPromptArrayStats(benchmarkRun.DataFPS)
sb.WriteString("FPS: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// Frame time
stats = calculateAIPromptArrayStats(benchmarkRun.DataFrameTime)
sb.WriteString("Frame time: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// CPU load
stats = calculateAIPromptArrayStats(benchmarkRun.DataCPULoad)
sb.WriteString("CPU load: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// GPU load
stats = calculateAIPromptArrayStats(benchmarkRun.DataGPULoad)
sb.WriteString("GPU load: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// CPU temp
stats = calculateAIPromptArrayStats(benchmarkRun.DataCPUTemp)
sb.WriteString("CPU temp: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// GPU temp
stats = calculateAIPromptArrayStats(benchmarkRun.DataGPUTemp)
sb.WriteString("GPU temp: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// GPU core clock
stats = calculateAIPromptArrayStats(benchmarkRun.DataGPUCoreClock)
sb.WriteString("GPU core clock: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// GPU mem clock
stats = calculateAIPromptArrayStats(benchmarkRun.DataGPUMemClock)
sb.WriteString("GPU mem clock: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// GPU VRAM used
stats = calculateAIPromptArrayStats(benchmarkRun.DataGPUVRAMUsed)
sb.WriteString("GPU VRAM used: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// GPU power
stats = calculateAIPromptArrayStats(benchmarkRun.DataGPUPower)
sb.WriteString("GPU power: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// RAM used
stats = calculateAIPromptArrayStats(benchmarkRun.DataRAMUsed)
sb.WriteString("RAM used: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
// Swap used
stats = calculateAIPromptArrayStats(benchmarkRun.DataSwapUsed)
sb.WriteString("Swap used: ")
sb.WriteString(stats.String())
sb.WriteString("\n")
}
return sb.String()
}
type AIPromptArrayStats struct {
Count int
Lowest float64
Low1Percent float64
Mean float64
Median float64
Top97Percent float64
Highest float64
StdDev float64
Variance float64
}
func calculateAIPromptArrayStats(data []float64) AIPromptArrayStats {
if len(data) == 0 {
return AIPromptArrayStats{}
}
sort.Float64s(data)
count := len(data)
lowest := data[0]
highest := data[count-1]
low1PercentIndex := int(math.Ceil(0.01*float64(count))) - 1
if low1PercentIndex < 0 {
low1PercentIndex = 0
}
low1Percent := data[low1PercentIndex]
top97PercentIndex := int(math.Ceil(0.97*float64(count))) - 1
if top97PercentIndex < 0 {
top97PercentIndex = 0
}
top97Percent := data[top97PercentIndex]
mean := 0.0
for _, value := range data {
mean += value
}
mean /= float64(count)
median := 0.0
if count%2 == 0 {
median = (data[count/2-1] + data[count/2]) / 2
} else {
median = data[count/2]
}
variance := 0.0
for _, value := range data {
variance += (value - mean) * (value - mean)
}
variance /= float64(count)
stdDev := math.Sqrt(variance)
return AIPromptArrayStats{
Count: count,
Lowest: lowest,
Low1Percent: low1Percent,
Mean: mean,
Median: median,
Top97Percent: top97Percent,
Highest: highest,
StdDev: stdDev,
Variance: variance,
}
}
func (as AIPromptArrayStats) String() string {
return strings.Join([]string{
"Count: " + strconv.Itoa(as.Count),
"Lowest: " + strconv.FormatFloat(as.Lowest, 'f', -1, 64),
"Low1Percent: " + strconv.FormatFloat(as.Low1Percent, 'f', -1, 64),
"Mean: " + strconv.FormatFloat(as.Mean, 'f', -1, 64),
"Median: " + strconv.FormatFloat(as.Median, 'f', -1, 64),
"Top97Percent: " + strconv.FormatFloat(as.Top97Percent, 'f', -1, 64),
"Highest: " + strconv.FormatFloat(as.Highest, 'f', -1, 64),
"StdDev: " + strconv.FormatFloat(as.StdDev, 'f', -1, 64),
"Variance: " + strconv.FormatFloat(as.Variance, 'f', -1, 64),
}, ", ")
}