pass model and predict options

server/routes.go

@@ -26,12 +26,9 @@ var templatesFS embed.FS
 var templates = template.Must(template.ParseFS(templatesFS, "templates/*.prompt"))
 
 func generate(c *gin.Context) {
-	// TODO: these should be request parameters
-	gpulayers := 1
-	tokens := 512
-	threads := runtime.NumCPU()
-
 	var req api.GenerateRequest
+	req.ModelOptions = api.DefaultModelOptions
+	req.PredictOptions = api.DefaultPredictOptions
 	if err := c.ShouldBindJSON(&req); err != nil {
 		c.JSON(http.StatusBadRequest, gin.H{"message": err.Error()})
 		return
@@ -41,7 +38,10 @@ func generate(c *gin.Context) {
 		req.Model = remoteModel.FullName()
 	}
 
-	model, err := llama.New(req.Model, llama.EnableF16Memory, llama.SetContext(128), llama.EnableEmbeddings, llama.SetGPULayers(gpulayers))
+	modelOpts := getModelOpts(req)
+	modelOpts.NGPULayers = 1  // hard-code this for now
+
+	model, err := llama.New(req.Model, modelOpts)
 	if err != nil {
 		fmt.Println("Loading the model failed:", err.Error())
 		return
@@ -65,13 +65,16 @@ func generate(c *gin.Context) {
 	}
 
 	ch := make(chan string)
+	model.SetTokenCallback(func(token string) bool {
+		ch <- token
+		return true
+	})
+
+	predictOpts := getPredictOpts(req)
 
 	go func() {
 		defer close(ch)
-		_, err := model.Predict(req.Prompt, llama.Debug, llama.SetTokenCallback(func(token string) bool {
-			ch <- token
-			return true
-		}), llama.SetTokens(tokens), llama.SetThreads(threads), llama.SetTopK(90), llama.SetTopP(0.86), llama.SetStopWords("llama"))
+		_, err := model.Predict(req.Prompt, predictOpts)
 		if err != nil {
 			panic(err)
 		}
@@ -161,3 +164,53 @@ func matchRankOne(source string, targets []string) (bestMatch string, bestRank i
 
 	return
 }
+
+func getModelOpts(req api.GenerateRequest) llama.ModelOptions {
+	var opts llama.ModelOptions
+	opts.ContextSize = req.ModelOptions.ContextSize
+	opts.Seed = req.ModelOptions.Seed
+	opts.F16Memory = req.ModelOptions.F16Memory
+	opts.MLock = req.ModelOptions.MLock
+	opts.Embeddings = req.ModelOptions.Embeddings
+	opts.MMap = req.ModelOptions.MMap
+	opts.LowVRAM = req.ModelOptions.LowVRAM
+
+	opts.NBatch = req.ModelOptions.NBatch
+	opts.VocabOnly = req.ModelOptions.VocabOnly
+	opts.NUMA = req.ModelOptions.NUMA
+	opts.NGPULayers = req.ModelOptions.NGPULayers
+	opts.MainGPU = req.ModelOptions.MainGPU
+	opts.TensorSplit = req.ModelOptions.TensorSplit
+
+	return opts
+}
+
+func getPredictOpts(req api.GenerateRequest) llama.PredictOptions {
+	var opts llama.PredictOptions
+
+	if req.PredictOptions.Threads == -1 {
+		opts.Threads = runtime.NumCPU()
+	} else {
+		opts.Threads = req.PredictOptions.Threads
+	}
+
+	opts.Seed = req.PredictOptions.Seed
+	opts.Tokens = req.PredictOptions.Tokens
+	opts.Penalty = req.PredictOptions.Penalty
+	opts.Repeat = req.PredictOptions.Repeat
+	opts.Batch = req.PredictOptions.Batch
+	opts.NKeep = req.PredictOptions.NKeep
+	opts.TopK = req.PredictOptions.TopK
+	opts.TopP = req.PredictOptions.TopP
+	opts.TailFreeSamplingZ = req.PredictOptions.TailFreeSamplingZ
+	opts.TypicalP = req.PredictOptions.TypicalP
+	opts.Temperature = req.PredictOptions.Temperature
+	opts.FrequencyPenalty = req.PredictOptions.FrequencyPenalty
+	opts.PresencePenalty = req.PredictOptions.PresencePenalty
+	opts.Mirostat = req.PredictOptions.Mirostat
+	opts.MirostatTAU = req.PredictOptions.MirostatTAU
+	opts.MirostatETA = req.PredictOptions.MirostatETA
+	opts.MMap = req.PredictOptions.MMap
+
+	return opts
+}