Merge branch 'main' of hf.co:spaces/y-playground/leaderboard

app.py

@@ -375,40 +375,80 @@ def main():
                                     return data.iloc[row_idx, 0]  # 返回模型名
                                 return ""
 
-                            search_name.change(fn=search_models, inputs=search_name, outputs=table)
-                            table.select(fn=on_select, inputs=table, outputs=model_name_textbox)
+                        search_name.change(fn=search_models, inputs=search_name, outputs=table)
+                        table.select(fn=on_select, inputs=table, outputs=model_name_textbox)
+
+                        def file_to_json_str(file) -> str:
+                            """
+                            读取上传的 JSON 文件并返回字符串
+                            如果解析失败，抛出异常以阻止上传成功
+                            """
+                            if file is None:
+                                return ""
+                            try:
+                                import json
+                                # file 是文件路径字符串（当 type="filepath" 时）
+                                file_path = file if isinstance(file, str) else file.name
+                                with open(file_path, 'r', encoding='utf-8') as f:
+                                    json_data = json.load(f)
+                                    # 将 JSON 对象转换为格式化的字符串
+                                    json_str = json.dumps(json_data, indent=2, ensure_ascii=False)
+                                    return json_str
+                            except Exception as e:
+                                raise gr.Error(f"Error reading JSON file: {str(e)}")
+
+                        json_upload = gr.File(
+                            label="Upload JSON file",
+                            file_types=[".json"],
+                            type="filepath",
+                        )
+                        json_str = gr.Textbox(
+                            label="JSON Content",
+                            placeholder="JSON content will appear here after upload",
+                            lines=10,
+                            interactive=True,
+                            visible=False,
+                        )
+                        json_upload.upload(
+                            fn=file_to_json_str,
+                            inputs=json_upload,
+                            outputs=json_str,
+                        )
 
-                        with gr.Column():
-                            precision = gr.Dropdown(
-                                choices=[i.value.name for i in Precision if i != Precision.Unknown],
-                                label="Precision",
-                                multiselect=False,
-                                value="float16",
-                                interactive=True,
-                            )
-                            weight_type = gr.Dropdown(
-                                choices=[i.value.name for i in WeightType],
-                                label="Weights type",
-                                multiselect=False,
-                                value="Original",
-                                interactive=True,
-                            )
-                            base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
-
-                    submit_button = gr.Button("Submit Eval")
-                    submission_result = gr.Markdown()
-                    submit_button.click(
-                        add_new_eval,
-                        [
-                            model_name_textbox,
-                            base_model_name_textbox,
-                            revision_name_textbox,
-                            precision,
-                            weight_type,
-                            model_type,
-                        ],
-                        submission_result,
-                    )
+
+                    with gr.Column():
+                        precision = gr.Dropdown(
+                            choices=[i.value.name for i in Precision if i != Precision.Unknown],
+                            label="Precision",
+                            multiselect=False,
+                            value="float16",
+                            interactive=True,
+                        )
+                        weight_type = gr.Dropdown(
+                            choices=[i.value.name for i in WeightType],
+                            label="Weights type",
+                            multiselect=False,
+                            value="Original",
+                            interactive=True,
+                        )
+                        base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
+                        commit_textbox = gr.Textbox(label="Commits")
+
+                submit_button = gr.Button("Submit Eval")
+                submission_result = gr.Markdown()
+                submit_button.click(
+                    add_new_submit,
+                    [
+                        model_name_textbox,
+                        base_model_name_textbox,
+                        revision_name_textbox,
+                        precision,
+                        weight_type,
+                        json_str,
+                        commit_textbox,
+                    ],
+                    submission_result,
+                )
 
                     # Backend status indicator
                     backend_status = gr.HTML(

src/assets/css/custom.css

@@ -14,7 +14,7 @@
     font-size: 16px !important;
 }
 
-#citation-button > label > button {
+#citation-button>label>button {
     margin: 6px;
     transform: scale(1.3);
 }
@@ -27,7 +27,7 @@
     margin-top: 15px
 }
 
-#search-bar-table-box > div:first-child {
+#search-bar-table-box>div:first-child {
     background: none;
     border: none;
 }
@@ -60,36 +60,45 @@
 #scale-logo .download {
     display: none;
 }
-#filter_type{
+
+#filter_type {
     border: 0;
     padding-left: 0;
     padding-top: 0;
 }
+
 #filter_type label {
     display: flex;
 }
-#filter_type label > span{
+
+#filter_type label>span {
     margin-top: var(--spacing-lg);
     margin-right: 0.5em;
 }
-#filter_type label > .wrap{
+
+#filter_type label>.wrap {
     width: 103px;
 }
-#filter_type label > .wrap .wrap-inner{
+
+#filter_type label>.wrap .wrap-inner {
     padding: 2px;
 }
-#filter_type label > .wrap .wrap-inner input{
+
+#filter_type label>.wrap .wrap-inner input {
     width: 1px
 }
-#filter-columns-type{
-    border:0;
-    padding:0.5;
+
+#filter-columns-type {
+    border: 0;
+    padding: 0.5;
 }
-#filter-columns-size{
-    border:0;
-    padding:0.5;
+
+#filter-columns-size {
+    border: 0;
+    padding: 0.5;
 }
-#box-filter > .form{
+
+#box-filter>.form {
     border: 0
 }
 
@@ -104,4 +113,4 @@
     white-space: nowrap !important;
     overflow: hidden !important;
     text-overflow: ellipsis !important;
-}
+}

src/backend/routes/hf.py

@@ -95,7 +95,7 @@ async def upload_file_content_handler(
 
 @router.post("/community/submit/")
 async def community_submit(
-    params: Annotated[CommunitySubmit_Params, Depends()],
+    params: CommunitySubmit_Params,
 ) -> ResponseData[UploadFileContent_RespData]:
     """Submit a new evaluation request to the Hugging Face repository."""
     file_obj = io.BytesIO(params.content.encode("utf-8"))

src/display/utils.py

@@ -153,6 +153,13 @@ class WeightType(Enum):
 class Precision(Enum):
     float16 = ModelDetails(name="float16")
     bfloat16 = ModelDetails(name="bfloat16")
+    float32 = ModelDetails(name="float32")
+    float64 = ModelDetails(name="float64")
+    int8 = ModelDetails(name="int8")
+    uint8 = ModelDetails(name="uint8")
+    int16 = ModelDetails(name="int16")
+    int32 = ModelDetails(name="int32")
+    int64 = ModelDetails(name="int64")
     Unknown = ModelDetails(name="?")
 
     @classmethod
@@ -161,6 +168,20 @@ class Precision(Enum):
             return Precision.float16
         if precision in ["torch.bfloat16", "bfloat16"]:
             return Precision.bfloat16
+        if precision in ["torch.float32", "float32"]:
+            return Precision.float32
+        if precision in ["torch.float64", "float64"]:
+            return Precision.float64
+        if precision in ["torch.int8", "int8"]:
+            return Precision.int8
+        if precision in ["torch.uint8", "uint8"]:
+            return Precision.uint8
+        if precision in ["torch.int16", "int16"]:
+            return Precision.int16
+        if precision in ["torch.int32", "int32"]:
+            return Precision.int32
+        if precision in ["torch.int64", "int64"]:
+            return Precision.int64
         return Precision.Unknown
 
 

src/submission/submit.py

@@ -2,6 +2,8 @@ import json
 import os
 import sys
 from datetime import datetime, timezone
+import requests 
+import json
 
 from src.display.formatting import styled_error, styled_message, styled_warning
 from src.envs import API, settings
@@ -20,6 +22,93 @@ else:
 REQUESTED_MODELS = None
 USERS_TO_SUBMISSION_DATES = None
 
+def add_new_submit(
+    model: str,
+    base_model: str,
+    revision: str,
+    precision: str,
+    weight_type: str,
+    json_str: str,
+    commit_message: str
+):
+    global REQUESTED_MODELS
+    global USERS_TO_SUBMISSION_DATES
+    if not REQUESTED_MODELS:
+        REQUESTED_MODELS, USERS_TO_SUBMISSION_DATES = already_submitted_models(settings.EVAL_REQUESTS_PATH)
+
+    user_name = ""
+    model_path = model
+    if "/" in model:
+        user_name = model.split("/")[0]
+        model_path = model.split("/")[1]
+
+    precision = precision.split(" ")[0]
+    # Does the model actually exist?
+    if revision == "":
+        revision = "main"
+
+    # Is the model on the hub?
+    if weight_type in ["Delta", "Adapter"]:
+        base_model_on_hub, error, _ = is_model_on_hub(
+            model_name=base_model, revision=revision, token=settings.TOKEN, test_tokenizer=True
+        )
+        if not base_model_on_hub:
+            return styled_error(f'Base model "{base_model}" {error}')
+
+    if not weight_type == "Adapter":
+        model_on_hub, error, _ = is_model_on_hub(
+            model_name=model, revision=revision, token=settings.TOKEN, test_tokenizer=True
+        )
+        if not model_on_hub:
+            return styled_error(f'Model "{model}" {error}')
+
+    # Is the model info correctly filled?
+    try:
+        model_info = API.model_info(repo_id=model, revision=revision)
+    except Exception:
+        return styled_error("Could not get your model information. Please fill it up properly.")
+
+    # Were the model card and license filled?
+    try:
+        license = model_info.cardData["license"]
+    except Exception:
+        return styled_error("Please select a license for your model")
+
+    request_json = {
+        "username": user_name,
+        "model_id": model,
+        "model_sha": revision,
+        "model_dtype": precision,
+        "content": json_str, 
+        "weight_type": weight_type,
+        "commit_message":commit_message
+    }
+
+    # Check for duplicate submission
+    if f"{model}_{revision}_{precision}" in REQUESTED_MODELS:
+        return styled_warning("This model has been already submitted.")
+    
+    try:
+        response = requests.post(
+            url=f"http://localhost:{settings.BACKEND_PORT}/api/v1/hf/community/submit/",
+            json=request_json,  # 使用 json 参数发送 JSON body
+            headers={"Content-Type": "application/json"}
+        )
+        print("response: ", response) #print response content for debugging
+        if response.status_code == 200:
+            data = response.json()
+            print("returned data: ", data)
+            if data.get("code") == 0:
+                return styled_message(
+                    "Your request has been submitted to the evaluation queue!\nPlease wait for the model to show in the PENDING list."
+                )
+        return styled_error(
+                    "Submission unsuccessful."
+                )
+    except Exception:
+        return styled_error(
+                    "Submission unsuccessful."
+                )
 
 def add_new_eval(
     model: str,