test

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 from typing import TypedDict, Annotated
-from huggingface_hub import InferenceClient, login
+from huggingface_hub import InferenceClient, login, list_models
 from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint, HuggingFacePipeline
 #from langchain.schema import AIMessage, HumanMessage
 from langgraph.graph.message import add_messages
@@ -12,7 +12,7 @@ import datasets
 import os
 from langgraph.graph import START, StateGraph
 from langchain.tools import Tool
-from mytools import search_tool, weather_info_tool, hub_stats_tool
+from mytools import search_tool, weather_info_tool
 #from dotenv import load_dotenv
 
 #load_dotenv()
@@ -68,6 +68,28 @@ guest_info_tool = Tool(
     description="Retrieves detailed information about gala guests based on their name or relation."
 )
 
+
+def get_hub_stats(author: str) -> str:
+    """Fetches the most downloaded model from a specific author on the Hugging Face Hub."""
+    try:
+        # List models from the specified author, sorted by downloads
+        models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))
+
+        if models:
+            model = models[0]
+            return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
+        else:
+            return f"No models found for author {author}."
+    except Exception as e:
+        return f"Error fetching models for {author}: {str(e)}"
+
+# Initialize the tool
+hub_stats_tool = Tool(
+    name="get_hub_stats",
+    func=get_hub_stats,
+    description="Fetches the most downloaded model from a specific author on the Hugging Face Hub."
+)
+
 def predict(message, history):
     # Convert Gradio history to LangChain message format
     history_langchain_format = []

mytools.py

@@ -1,7 +1,6 @@
 from langchain.tools import Tool
 from langchain_community.tools import DuckDuckGoSearchRun
 import random
-from huggingface_hub import list_models
 
 
 search_tool = DuckDuckGoSearchRun()
@@ -25,24 +24,3 @@ weather_info_tool = Tool(
     description="Fetches dummy weather information for a given location."
 )
 
-
-def get_hub_stats(author: str) -> str:
-    """Fetches the most downloaded model from a specific author on the Hugging Face Hub."""
-    try:
-        # List models from the specified author, sorted by downloads
-        models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))
-
-        if models:
-            model = models[0]
-            return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
-        else:
-            return f"No models found for author {author}."
-    except Exception as e:
-        return f"Error fetching models for {author}: {str(e)}"
-
-# Initialize the tool
-hub_stats_tool = Tool(
-    name="get_hub_stats",
-    func=get_hub_stats,
-    description="Fetches the most downloaded model from a specific author on the Hugging Face Hub."
-)