improve parameters controllable range

backend-python/utils/rwkv.py

@@ -667,7 +667,7 @@ def RWKV(model: str, strategy: str, tokenizer: Union[str, None]) -> AbstractRWKV
 
 class ModelConfigBody(BaseModel):
     max_tokens: int = Field(default=None, gt=0, le=102400)
-    temperature: float = Field(default=None, ge=0, le=2)
+    temperature: float = Field(default=None, ge=0, le=3)
     top_p: float = Field(default=None, ge=0, le=1)
     presence_penalty: float = Field(default=None, ge=-2, le=2)
     frequency_penalty: float = Field(default=None, ge=-2, le=2)

frontend/src/pages/Chat.tsx

@@ -247,7 +247,7 @@ const SidePanel: FC = observer(() => {
       <Labeled flex breakline label={t('Temperature')}
         desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
         content={
-          <ValuedSlider value={params.temperature} min={0} max={2} step={0.1}
+          <ValuedSlider value={params.temperature} min={0} max={3} step={0.1}
             input
             onChange={(e, data) => {
               commonStore.setChatParams({
@@ -258,7 +258,7 @@ const SidePanel: FC = observer(() => {
       <Labeled flex breakline label={t('Top_P')}
         desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
         content={
-          <ValuedSlider value={params.topP} min={0} max={1} step={0.1} input
+          <ValuedSlider value={params.topP} min={0} max={1} step={0.05} input
             onChange={(e, data) => {
               commonStore.setChatParams({
                 topP: data.value

frontend/src/pages/Completion.tsx

@@ -188,7 +188,7 @@ const CompletionPanel: FC = observer(() => {
           <Labeled flex breakline label={t('Temperature')}
             desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
             content={
-              <ValuedSlider value={params.temperature} min={0} max={2} step={0.1}
+              <ValuedSlider value={params.temperature} min={0} max={3} step={0.1}
                 input
                 onChange={(e, data) => {
                   setParams({
@@ -199,7 +199,7 @@ const CompletionPanel: FC = observer(() => {
           <Labeled flex breakline label={t('Top_P')}
             desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
             content={
-              <ValuedSlider value={params.topP} min={0} max={1} step={0.1} input
+              <ValuedSlider value={params.topP} min={0} max={1} step={0.05} input
                 onChange={(e, data) => {
                   setParams({
                     topP: data.value

frontend/src/pages/Composition.tsx

@@ -275,7 +275,7 @@ const CompositionPanel: FC = observer(() => {
             <Labeled flex breakline label={t('Temperature')}
               desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
               content={
-                <ValuedSlider value={params.temperature} min={0} max={2} step={0.1}
+                <ValuedSlider value={params.temperature} min={0} max={3} step={0.1}
                   input
                   onChange={(e, data) => {
                     setParams({
@@ -286,7 +286,7 @@ const CompositionPanel: FC = observer(() => {
             <Labeled flex breakline label={t('Top_P')}
               desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
               content={
-                <ValuedSlider value={params.topP} min={0} max={1} step={0.1} input
+                <ValuedSlider value={params.topP} min={0} max={1} step={0.05} input
                   onChange={(e, data) => {
                     setParams({
                       topP: data.value

frontend/src/pages/Configs.tsx

@@ -176,7 +176,7 @@ const Configs: FC = observer(() => {
                 <Labeled label={t('Temperature') + ' *'}
                   desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
                   content={
-                    <ValuedSlider value={selectedConfig.apiParameters.temperature} min={0} max={2} step={0.1}
+                    <ValuedSlider value={selectedConfig.apiParameters.temperature} min={0} max={3} step={0.1}
                       input
                       onChange={(e, data) => {
                         setSelectedConfigApiParams({
@@ -187,7 +187,7 @@ const Configs: FC = observer(() => {
                 <Labeled label={t('Top_P') + ' *'}
                   desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
                   content={
-                    <ValuedSlider value={selectedConfig.apiParameters.topP} min={0} max={1} step={0.1} input
+                    <ValuedSlider value={selectedConfig.apiParameters.topP} min={0} max={1} step={0.05} input
                       onChange={(e, data) => {
                         setSelectedConfigApiParams({
                           topP: data.value