Upload tool

app.py

@@ -1,4 +1,4 @@
 from transformers import launch_gradio_demo
-from model_downloads import HFModelDownloadsTool
+from tool import HFModelDownloadsTool
 
 launch_gradio_demo(HFModelDownloadsTool)

requirements.txt

@@ -1,2 +1,2 @@
-transformers[agents]
+agents_package
 huggingface_hub

tool.py

@@ -0,0 +1,15 @@
+from agents import Tool
+
+    class HFModelDownloadsTool(Tool):
+        name = "model_download_counter"
+        description = "
+This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub.
+It returns the name of the checkpoint."
+        inputs = {"task":{"type":"string","description":"the task category (such as text-classification, depth-estimation, etc)"}}
+        output_type = "string"
+
+    def forward(self, task: str):
+            from huggingface_hub import list_models
+
+            model = next(iter(list_models(filter=task, sort="downloads", direction=-1)))
+            return model.id

tool_config.json

@@ -1,7 +1,12 @@
 {
-  "description": "This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub. It returns the name of the checkpoint.",
-  "inputs": "{'task': {'type': 'string', 'description': 'the task category (such as text-classification, depth-estimation, etc)'}}",
+  "description": "\n    This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub.\n    It returns the name of the checkpoint.",
+  "inputs": {
+    "task": {
+      "description": "the task category (such as text-classification, depth-estimation, etc)",
+      "type": "string"
+    }
+  },
   "name": "model_download_counter",
   "output_type": "string",
-  "tool_class": "model_downloads.HFModelDownloadsTool"
+  "tool_class": "HFModelDownloadsTool"
 }