Add Bright Data Dataset Tool

app.py

@@ -1,5 +1,36 @@
-from smolagents import launch_gradio_demo
+import gradio as gr
 from tool import BrightDataDatasetTool
 
 tool = BrightDataDatasetTool()
-launch_gradio_demo(tool)
+
+def run(dataset, url, keyword, first_name, last_name, days_limit, num_of_reviews, num_of_comments):
+    return tool(
+        dataset=dataset,
+        url=url,
+        keyword=keyword,
+        first_name=first_name,
+        last_name=last_name,
+        days_limit=days_limit,
+        num_of_reviews=num_of_reviews,
+        num_of_comments=num_of_comments,
+    )
+
+with gr.Blocks() as demo:
+    gr.Markdown("### Bright Data dataset fetch")
+    dataset = gr.Dropdown(choices=['amazon_product', 'amazon_product_reviews', 'amazon_product_search', 'apple_app_store', 'bestbuy_products', 'booking_hotel_listings', 'crunchbase_company', 'ebay_product', 'etsy_products', 'facebook_company_reviews', 'facebook_events', 'facebook_marketplace_listings', 'facebook_posts', 'github_repository_file', 'google_maps_reviews', 'google_play_store', 'google_shopping', 'homedepot_products', 'instagram_comments', 'instagram_posts', 'instagram_profiles', 'instagram_reels', 'linkedin_company_profile', 'linkedin_job_listings', 'linkedin_people_search', 'linkedin_person_profile', 'linkedin_posts', 'reddit_posts', 'reuter_news', 'tiktok_comments', 'tiktok_posts', 'tiktok_profiles', 'tiktok_shop', 'walmart_product', 'walmart_seller', 'x_posts', 'yahoo_finance_business', 'youtube_comments', 'youtube_profiles', 'youtube_videos', 'zara_products', 'zillow_properties_listing', 'zoominfo_company_profile'], label="Dataset", multiselect=False)
+    url = gr.Textbox(label="URL", placeholder="https://...")
+    keyword = gr.Textbox(label="Keyword")
+    first_name = gr.Textbox(label="First name")
+    last_name = gr.Textbox(label="Last name")
+    days_limit = gr.Textbox(label="Days limit (e.g. 3)")
+    num_of_reviews = gr.Textbox(label="Number of reviews")
+    num_of_comments = gr.Textbox(label="Number of comments")
+    run_btn = gr.Button("Run")
+    output = gr.Textbox(label="Output", lines=12)
+    run_btn.click(
+        run,
+        inputs=[dataset, url, keyword, first_name, last_name, days_limit, num_of_reviews, num_of_comments],
+        outputs=output,
+    )
+
+demo.launch()

requirements.txt

@@ -1,2 +1,4 @@
+gradio
 requests
-smolagents
+smolagents
+{tool_module_name}

tool.py

@@ -1,9 +1,9 @@
 from typing import Any, Optional
 from smolagents.tools import Tool
-import json
+import requests
 import time
 import os
-import requests
+import json
 
 class BrightDataDatasetTool(Tool):
     name = "brightdata_dataset_fetch"
@@ -78,7 +78,6 @@ class BrightDataDatasetTool(Tool):
             else:
                 raise ValueError(f"Missing required field '{field}' for dataset '{dataset_key}'")
 
-        # Apply fixed values that should always be sent
         payload.update(fixed_values)
         return payload
 
@@ -160,7 +159,6 @@ class BrightDataDatasetTool(Tool):
         if not snapshot_id:
             raise RuntimeError("No snapshot ID returned from Bright Data.")
 
-        # Poll for completion (up to 10 minutes, matching MCP logic)
         snapshot_url = f"https://api.brightdata.com/datasets/v3/snapshot/{snapshot_id}"
         max_attempts = 600
         attempts = 0
@@ -174,7 +172,6 @@ class BrightDataDatasetTool(Tool):
                     timeout=30,
                 )
 
-                # If Bright Data returns an error response we don't want to loop forever
                 if response.status_code == 400:
                     response.raise_for_status()
 
@@ -190,10 +187,56 @@ class BrightDataDatasetTool(Tool):
                 time.sleep(1)
 
             except requests.exceptions.RequestException as exc:
-                # Mirror JS logic: tolerate transient failures, but break on 400
                 if getattr(getattr(exc, "response", None), "status_code", None) == 400:
                     raise
                 attempts += 1
                 time.sleep(1)
 
         raise TimeoutError(f"Timeout waiting for snapshot {snapshot_id} after {max_attempts} seconds")
+
+    def _get_gradio_app_code(self, tool_module_name: str = "tool") -> str:
+            """
+            Override the default app to render a dropdown for dataset selection
+            instead of a long text field. Kept minimal: single-select dropdown,
+            rest are simple text boxes.
+            """
+            choices = sorted(self.datasets.keys())
+            class_name = self.__class__.__name__
+            return f"""\
+    import gradio as gr
+    from {tool_module_name} import {class_name}
+
+    tool = {class_name}()
+
+    def run(dataset, url, keyword, first_name, last_name, days_limit, num_of_reviews, num_of_comments):
+        return tool(
+            dataset=dataset,
+            url=url,
+            keyword=keyword,
+            first_name=first_name,
+            last_name=last_name,
+            days_limit=days_limit,
+            num_of_reviews=num_of_reviews,
+            num_of_comments=num_of_comments,
+        )
+
+    with gr.Blocks() as demo:
+        gr.Markdown("### Bright Data dataset fetch")
+        dataset = gr.Dropdown(choices={choices}, label="Dataset", multiselect=False)
+        url = gr.Textbox(label="URL", placeholder="https://...")
+        keyword = gr.Textbox(label="Keyword")
+        first_name = gr.Textbox(label="First name")
+        last_name = gr.Textbox(label="Last name")
+        days_limit = gr.Textbox(label="Days limit (e.g. 3)")
+        num_of_reviews = gr.Textbox(label="Number of reviews")
+        num_of_comments = gr.Textbox(label="Number of comments")
+        run_btn = gr.Button("Run")
+        output = gr.Textbox(label="Output", lines=12)
+        run_btn.click(
+            run,
+            inputs=[dataset, url, keyword, first_name, last_name, days_limit, num_of_reviews, num_of_comments],
+            outputs=output,
+        )
+
+    demo.launch()
+    """