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minor fixes

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Concedo 2025-07-18 13:22:59 +08:00
parent 1ca666f9c1
commit b028dd4e84
3 changed files with 12 additions and 10 deletions
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16
gpttype_adapter.cpp
View file

@ -3059,6 +3059,7 @@ static void PrepareMediaEmbds(const int nctx, const std::vector<int> & media_int
}
else
{
media_composite_image_signature = ""; //force invalidate
printf("\nWarning: Vision Image excluded - Context size too low or not enough clip tokens! (needed %d)\nImage will be IGNORED! You probably want to relaunch with a larger context size!\n",cliptokensneeded);
}
media_objects[i].mediachunks.push_back(chunk);
@ -3112,6 +3113,7 @@ static void PrepareMediaEmbds(const int nctx, const std::vector<int> & media_int
}
else
{
media_composite_image_signature = ""; //force invalidate
printf("\nWarning: Audio Embd excluded - Context size too low or not enough clip tokens! (needed %d)\nAudio will be IGNORED! You probably want to relaunch with a larger context size!\n",cliptokensneeded);
}
@ -3315,7 +3317,7 @@ generation_outputs gpttype_generate(const generation_inputs inputs)
media_composite_image_signature = new_media_composite;
if(debugmode==1 && !is_quiet)
{
printf("\nLLAVA images changed, existing cache invalidated");
printf("\nAttached media changed, existing multimodal cache invalidated");
}
media_data_changed = true;
}
@ -3520,7 +3522,7 @@ generation_outputs gpttype_generate(const generation_inputs inputs)
{
if(last_media_mem.size() + kcpp_data->n_predict + 4 > nctx)
{
printf("\nWarning: Too many LLaVA tokens, max context exceeded! They will be ignored!\n");
printf("\nWarning: Too many multimodal tokens, max context exceeded! They will be ignored!\n");
}
else
{
@ -4266,7 +4268,7 @@ generation_outputs gpttype_generate(const generation_inputs inputs)
{
PrepareMediaEmbds(nctx, media_intro);
media_embds_built = true;
printf("\nSomehow vision embd was not prepared (maybe no fast forward), rebuilding it...\n");
printf("\nSomehow media embeds was not prepared (maybe no fast forward), rebuilding it...\n");
}
//if partial batch, dispatch existing first
@ -4301,11 +4303,11 @@ generation_outputs gpttype_generate(const generation_inputs inputs)
auto evr = llama_decode(llama_ctx_v4, batch.batch);
if(evr!=0)
{
printf("\nError when appending llava intro: %d\n",evr);
printf("\nError when appending media intro: %d\n",evr);
}
else
{
printf("\rProcessing LLaVa Intro (%d tokens)",introsize);
printf("\rProcessing Media Intro (%d tokens)",introsize);
}
n_past += introsize;
llavatokensevaled += introsize;
@ -4340,7 +4342,7 @@ generation_outputs gpttype_generate(const generation_inputs inputs)
if(!err)
{
media_composite_image_signature = ""; //force invalidate
fprintf(stderr, "\nFailed to eval llava image at %d!\n",n_past);
fprintf(stderr, "\nFailed to eval media tokens at %d!\n",n_past);
output.text = nullptr;
output.status = 0;
output.prompt_tokens = output.completion_tokens = 0;
@ -4370,7 +4372,7 @@ generation_outputs gpttype_generate(const generation_inputs inputs)
if(llavatokenscounted!=llavatokensevaled)
{
media_composite_image_signature = ""; //force invalidate
fprintf(stderr, "\nLLAVA image tokens mismatch at %d! (%d vs %d tokens)\n",n_past,llavatokenscounted,llavatokensevaled);
fprintf(stderr, "\nMedia tokens mismatch at %d! (%d vs %d tokens)\n",n_past,llavatokenscounted,llavatokensevaled);
output.text = nullptr;
output.status = 0;
output.prompt_tokens = output.completion_tokens = 0;

4
klite.embd
View file

@ -14734,11 +14734,11 @@ Current version indicated by LITEVER below.
function self_upload_file_dispatch(data,filename)
{
const maxSize = 20 * 1024 * 1024; // approx 20MB limit
const maxSize = 30 * 1024 * 1024; // approx 30MB limit
const dlen = (data.length*0.75);
const mbs = Math.ceil(dlen/1024/1024);
if (dlen > maxSize) {
msgbox(`Selected file exceeds 20MB size limit!\nSelected file was ${mbs}MB. Please try a smaller file.`, "File Too Large");
msgbox(`Selected file exceeds 30MB size limit!\nSelected file was ${mbs}MB. Please try a smaller file.`, "File Too Large");
return;
}

2
koboldcpp.py
View file

@ -5124,7 +5124,7 @@ def show_gui():
ctk.CTkButton(model_tab, width=70, text = "HF Search", command = model_searcher ).grid(row=1,column=0, stick="nw", padx=370, pady=2)
makefileentry(model_tab, "Text Lora:", "Select Lora File",lora_var, 3,width=160,singlerow=True,tooltiptxt="Select an optional GGML Text LoRA adapter to use.\nLeave blank to skip.")
makelabelentry(model_tab, "Multiplier: ", loramult_var, 3, 50,padx=390,singleline=True,tooltip="Scale multiplier for Text LoRA Strength. Default is 1.0", labelpadx=330)
makefileentry(model_tab, "Vision mmproj:", "Select Vision mmproj File", mmproj_var, 7,width=280,singlerow=True,tooltiptxt="Select a mmproj file to use for vision models like LLaVA.\nLeave blank to skip.")
makefileentry(model_tab, "Mmproj File:", "Select Audio or Vision mmproj File", mmproj_var, 7,width=280,singlerow=True,tooltiptxt="Select a mmproj file to use for multimodal models for vision and audio recognition.\nLeave blank to skip.")
makecheckbox(model_tab, "Vision Force CPU", mmprojcpu_var, 9, tooltiptxt="Force CLIP for Vision mmproj always on CPU.")
makelabelentry(model_tab, "Vision MaxRes:", visionmaxres_var, 9, padx=320, singleline=True, tooltip=f"Clamp MMProj vision maximum allowed resolution. Allowed values are between 512 to 2048 px (default {default_visionmaxres}).", labelpadx=220)
makefileentry(model_tab, "Draft Model:", "Select Speculative Text Model File", draftmodel_var, 11,width=280,singlerow=True,tooltiptxt="Select a draft text model file to use for speculative decoding.\nLeave blank to skip.")