dev

.gitignore

@@ -1 +0,0 @@
-*.csv

README.md

@@ -1,15 +1,14 @@
 ---
 title: WebSearch
-emoji: 🌍
+emoji: 💬
 colorFrom: yellow
 colorTo: purple
 sdk: gradio
-sdk_version: 5.33.1
+sdk_version: 5.0.1
 app_file: app.py
+pinned: false
 license: apache-2.0
 short_description: Web Searcher MCP Server
-pinned: true
-tags:
-- Agents-MCP-Hackathon
-- mcp-server-track
----
+---
+
+An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).

app.py

@@ -1,40 +1,64 @@
 import gradio as gr
+from huggingface_hub import InferenceClient
 
-from langchain_community.tools import DuckDuckGoSearchResults
-from typing import Literal, List, Dict
+"""
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-def search(input_query : str, max_results : int = 5) -> List[Dict[Literal["snippet", "title", "link"], str]]:
 
-  
-    """
-    Perform a web search using DuckDuckGo.
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
 
-    Args:
-        input_query: The query to search for.
-        max_results: The maximum number of results to return. Defaults to 5.
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
 
-    Returns:
-        A list of dictionaries, each containing "snippet", "title", and "link" keys.
-    """
+    messages.append({"role": "user", "content": message})
 
-    search = DuckDuckGoSearchResults(output_format="list", num_results = max_results)
-    
-    results = search.invoke(input_query)
+    response = ""
 
-    return results
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
 
-demo = gr.Interface(
-    fn = search,
-    inputs=[
-        gr.Textbox(value="Ahly SC of Egypt matches.", label="Search query"),
-        gr.Slider(minimum=1, maximum=20, value=5, step=1, label="Max results"),
+        response += token
+        yield response
+
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
     ],
-    outputs=gr.JSON(label="Search results"),
-    title = "Web Searcher using DuckDuckGo",
-    description = "Search the web using DuckDuckGo.",
 )
 
 
-# Launch the interface and MCP server
 if __name__ == "__main__":
-    demo.launch(mcp_server=True)
+    demo.launch()

requirements.txt

@@ -1,3 +1 @@
-gradio[mcp]
-duckduckgo-search 
-langchain-community
+huggingface_hub==0.25.2