Update app.py

app.py

@@ -1,61 +1,126 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
+from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
 import datetime
 import requests
 import pytz
 import yaml
+import os
 from tools.final_answer import FinalAnswerTool
-
 from Gradio_UI import GradioUI
 
-# Below is an example of a tool that does nothing. Amaze us with your creativity !
-@tool
-def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
-    #Keep this format for the description / args / args description but feel free to modify the tool
-    """A tool that does nothing yet 
-    Args:
-        arg1: the first argument
-        arg2: the second argument
-    """
-    return "What magic will you build ?"
+# Fetch USGS API credentials from environment variables (set in Hugging Face Spaces secrets)
+USGS_USERNAME = os.getenv("USGS_USERNAME")
+USGS_TOKEN = os.getenv("USGS_TOKEN")
 
 @tool
-def get_current_time_in_timezone(timezone: str) -> str:
-    """A tool that fetches the current local time in a specified timezone.
+def fetch_landsat_image(lat_min: float, lon_min: float, lat_max: float, lon_max: float, start_date: str, end_date: str) -> str:
+    """Fetches download URLs for all available Landsat images from USGS M2M API and returns them as clickable HTML links.
     Args:
-        timezone: A string representing a valid timezone (e.g., 'America/New_York').
+        lat_min: Minimum latitude of the bounding box
+        lon_min: Minimum longitude of the bounding box
+        lat_max: Maximum latitude of the bounding box
+        lon_max: Maximum longitude of the bounding box
+        start_date: Start date in 'YYYY-MM-DD' format
+        end_date: End date in 'YYYY-MM-DD' format
     """
+    if not USGS_USERNAME or not USGS_TOKEN:
+        return "<p>Error: USGS_USERNAME or USGS_TOKEN not set in environment variables.</p>"
+
+    service_url = "https://m2m.cr.usgs.gov/api/api/json/stable/"
+
+    def send_request(url, data, api_key=None):
+        json_data = json.dumps(data)
+        headers = {'X-Auth-Token': api_key} if api_key else {}
+        response = requests.post(url, json_data, headers=headers)
+        output = response.json()
+        if output.get('errorCode'):
+            return f"Error: {output['errorCode']} - {output['errorMessage']}"
+        return output['data']
+
     try:
-        # Create timezone object
-        tz = pytz.timezone(timezone)
-        # Get current time in that timezone
-        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
-        return f"The current local time in {timezone} is: {local_time}"
+        # Step 1: Authenticate
+        login_payload = {'username': USGS_USERNAME, 'token': USGS_TOKEN}
+        api_key = send_request(service_url + "login-token", login_payload)
+        if not api_key or isinstance(api_key, str) and "Error" in api_key:
+            return "<p>Authentication failed. Check username and token in secrets.</p>"
+
+        # Step 2: Search scenes
+        spatial_filter = {
+            'filterType': "mbr",
+            'lowerLeft': {'latitude': lat_min, 'longitude': lon_min},
+            'upperRight': {'latitude': lat_max, 'longitude': lon_max}
+        }
+        temporal_filter = {'start': start_date, 'end': end_date}
+        search_payload = {
+            'datasetName': 'landsat_ot_c2_l1',
+            'spatialFilter': spatial_filter,
+            'temporalFilter': temporal_filter,
+            'maxResults': 50,
+            'sortField': 'cloudCover',
+            'sortDirection': 'ASC'
+        }
+        scenes = send_request(service_url + "scene-search", search_payload, api_key)
+        if isinstance(scenes, str) and "Error" in scenes:
+            return f"<p>{scenes}</p>"
+        if not scenes['results']:
+            return "<p>No Landsat scenes found for the given area and time range.</p>"
+
+        # Step 3: Get download options
+        entity_ids = [scene['entityId'] for scene in scenes['results']]
+        download_options_payload = {
+            'datasetName': 'landsat_ot_c2_l1',
+            'entityIds': entity_ids
+        }
+        download_options = send_request(service_url + "download-options", download_options_payload, api_key)
+        if isinstance(download_options, str) and "Error" in download_options:
+            return f"<p>{download_options}</p>"
+
+        # Step 4: Request downloads
+        downloads = [opt for opt in download_options if opt['available']]
+        if not downloads:
+            return "<p>No available downloads for these scenes.</p>"
+
+        label = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+        download_request_payload = {
+            'downloads': [{'entityId': opt['entityId'], 'productId': opt['id']} for opt in downloads],
+            'label': label
+        }
+        request_results = send_request(service_url + "download-request", download_request_payload, api_key)
+        if isinstance(request_results, str) and "Error" in request_results:
+            return f"<p>{request_results}</p>"
+
+        # Step 5: Generate HTML with clickable links
+        urls = [download['url'] for download in request_results['availableDownloads']]
+        if not urls:
+            return "<p>No download URLs immediately available. Try again later.</p>"
+
+        html_output = f"<p>Found {len(urls)} available Landsat scenes:</p><ul>"
+        for i, (scene, url) in enumerate(zip(scenes['results'][:len(urls)], urls)):
+            html_output += f'<li>Cloud Cover: {scene["cloudCover"]}% - <a href="{url}" target="_blank">Download Scene {i+1}</a></li>'
+        html_output += "</ul>"
+        return html_output
+
     except Exception as e:
-        return f"Error fetching time for timezone '{timezone}': {str(e)}"
+        return f"<p>Error fetching Landsat images: {str(e)}</p>"
 
 
-final_answer = FinalAnswerTool()
 
-# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
-# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 
+final_answer = FinalAnswerTool()
 
 model = HfApiModel(
-max_tokens=2096,
-temperature=0.5,
-model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
-custom_role_conversions=None,
+    max_tokens=2096,
+    temperature=0.5,
+    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+    custom_role_conversions=None,
 )
 
-
-# Import tool from Hub
 image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
 
-with open("prompts.yaml", 'r') as stream:
+with open("prompts.yaml", "r") as stream:
     prompt_templates = yaml.safe_load(stream)
-    
+
 agent = CodeAgent(
     model=model,
-    tools=[final_answer], ## add your tools here (don't remove final answer)
+    tools=[fetch_landsat_image, final_answer],
     max_steps=6,
     verbosity_level=1,
     grammar=None,
@@ -65,5 +130,6 @@ agent = CodeAgent(
     prompt_templates=prompt_templates
 )
 
-
-GradioUI(agent).launch()
+# Launch Gradio UI
+interface = GradioUI(agent)
+interface.launch(share=True)  # 'share=True' for public link in Spaces