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Don't repeat the prompt in the response.

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This commit is contained in:
Adam Treat 2023-04-09 01:11:52 -04:00
parent 0903da3afa
commit 02e13737f3
2 changed files with 9 additions and 5 deletions
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7
gptj.cpp
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@ -700,6 +700,7 @@ void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::strin
n_predict = std::min(n_predict, d_ptr->model.hparams.n_ctx - (int) embd_inp.size());
std::vector<gpt_vocab::id> embd;
std::vector<gpt_vocab::id> resp;
// determine the required inference memory per token:
size_t mem_per_token = 0;
@ -720,6 +721,7 @@ void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::strin
n_past += embd.size();
embd.clear();
resp.clear();
if (i >= embd_inp.size()) {
// sample next token
@ -738,6 +740,7 @@ void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::strin
// add it to the context
embd.push_back(id);
resp.push_back(id);
} else {
// if here, it means we are still processing the input prompt
for (int k = i; k < embd_inp.size(); k++) {
@ -750,7 +753,7 @@ void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::strin
}
// display text
for (auto id : embd) {
for (auto id : resp) {
if (!response(d_ptr->vocab.id_to_token[id]))
goto stop_generating;
}
@ -762,7 +765,7 @@ void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::strin
}
stop_generating:
#if 1
#if 0
// report timing
{
const int64_t t_main_end_us = ggml_time_us();

7
main.qml
View File

@ -80,7 +80,7 @@ Window {
model: chatModel
delegate: TextArea {
text: currentResponse ? LLM.response : value
width: parent.width
width: listView.width
color: "#d1d5db"
wrapMode: Text.WordWrap
focus: false
@ -204,11 +204,12 @@ Window {
listElement.currentResponse = false
listElement.value = LLM.response
}
var prompt = textInput.text + "\n"
chatModel.append({"name": qsTr("Prompt: "), "currentResponse": false, "value": textInput.text})
chatModel.append({"name": qsTr("Response: "), "currentResponse": true, "value": "", "prompt": textInput.text})
chatModel.append({"name": qsTr("Response: "), "currentResponse": true, "value": "", "prompt": prompt})
LLM.resetResponse()
LLM.prompt(textInput.text)
LLM.prompt(prompt)
textInput.text = ""
}