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78 lines
1.7 KiB
78 lines
1.7 KiB
package main
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import (
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"strconv"
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llama "github.com/go-skynet/llama/go"
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"github.com/gofiber/fiber/v2"
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)
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func api(l *llama.LLama, listenAddr string, threads int) error {
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app := fiber.New()
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/*
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curl --location --request POST 'http://localhost:8080/predict' --header 'Content-Type: application/json' --data-raw '{
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"text": "What is an alpaca?",
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"topP": 0.8,
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"topK": 50,
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"temperature": 0.7,
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"tokens": 100
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}'
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*/
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// Endpoint to generate the prediction
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app.Post("/predict", func(c *fiber.Ctx) error {
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// Get input data from the request body
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input := new(struct {
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Text string `json:"text"`
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})
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if err := c.BodyParser(input); err != nil {
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return err
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}
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// Set the parameters for the language model prediction
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topP, err := strconv.ParseFloat(c.Query("topP", "0.9"), 64) // Default value of topP is 0.9
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if err != nil {
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return err
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}
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topK, err := strconv.Atoi(c.Query("topK", "40")) // Default value of topK is 40
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if err != nil {
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return err
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}
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temperature, err := strconv.ParseFloat(c.Query("temperature", "0.5"), 64) // Default value of temperature is 0.5
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if err != nil {
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return err
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}
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tokens, err := strconv.Atoi(c.Query("tokens", "128")) // Default value of tokens is 128
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if err != nil {
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return err
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}
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// Generate the prediction using the language model
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prediction, err := l.Predict(
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input.Text,
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llama.SetTemperature(temperature),
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llama.SetTopP(topP),
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llama.SetTopK(topK),
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llama.SetTokens(tokens),
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llama.SetThreads(threads),
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)
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if err != nil {
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return err
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}
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// Return the prediction in the response body
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return c.JSON(struct {
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Prediction string `json:"prediction"`
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}{
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Prediction: prediction,
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})
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})
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// Start the server
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app.Listen(":8080")
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return nil
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}
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