wehub-resource-sync
39 lines
1.5 KiB
Go
39 lines
1.5 KiB
Go
package localai
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import (
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"net/http"
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"github.com/labstack/echo/v4"
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"github.com/mudler/LocalAI/core/config"
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"github.com/mudler/LocalAI/core/services/modeladmin"
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)
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// VRAMEstimateEndpoint returns a handler that estimates VRAM usage for an
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// installed model configuration at multiple context sizes.
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// @Summary Estimate VRAM usage for a model
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// @Description Estimates VRAM based on model weight files at multiple context sizes
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// @Tags config
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// @Accept json
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// @Produce json
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// @Param request body modeladmin.VRAMRequest true "VRAM estimation parameters"
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// @Success 200 {object} modeladmin.VRAMResponse "VRAM estimate"
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// @Router /api/models/vram-estimate [post]
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func VRAMEstimateEndpoint(cl *config.ModelConfigLoader, appConfig *config.ApplicationConfig) echo.HandlerFunc {
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return func(c echo.Context) error {
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var req modeladmin.VRAMRequest
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if err := c.Bind(&req); err != nil {
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return c.JSON(http.StatusBadRequest, map[string]any{"error": "invalid request body"})
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}
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resp, err := modeladmin.EstimateVRAM(c.Request().Context(), req, cl, appConfig.SystemState)
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if err != nil {
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return c.JSON(httpStatusForModelAdminError(err), map[string]any{"error": err.Error()})
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}
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// Backwards compat: when there are no weight files, the previous
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// handler returned {"message": "..."} rather than a typed response.
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if resp.ContextNote == "no weight files found for estimation" && resp.EstimateResult.SizeBytes == 0 {
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return c.JSON(http.StatusOK, map[string]any{"message": resp.ContextNote})
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}
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return c.JSON(http.StatusOK, resp)
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}
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}
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