added reverse_string tool

app.py

@@ -6,7 +6,17 @@ import pandas as pd
 
 
 from smolagents import LiteLLMModel
-from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, WikipediaSearchTool
+from smolagents import (
+    CodeAgent,
+    DuckDuckGoSearchTool,
+    HfApiModel,
+    WikipediaSearchTool,
+    PythonInterpreterTool,
+    CodeAgent,
+    FinalAnswerTool,
+    load_tool,
+    tool,
+)
 
 
 # (Keep Constants as is)
@@ -14,6 +24,71 @@ from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, WikipediaSea
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 
+@tool
+def reverse_string(input_string: str) -> str:
+    """A tool that reverses the characters in a string.
+
+    Args:
+        input_string: The string to be reversed
+    """
+    return input_string[::-1]
+
+
+@tool
+def optimized_web_search(
+    search_query: str, important_words: list, batch_size: int = 500
+) -> str:
+    """A tool that performs a web search and filters the results to only include content chunks that contain important keywords.
+
+    Args:
+        search_query: The search query to use (e.g., 'Beatles albums Wikipedia')
+        important_words: List of important keywords to filter by (e.g., ['Abbey Road', 'Let It Be', '1970'])
+        batch_size: The size of content chunks to process (default: 500 characters)
+    """
+    try:
+        # Perform the search using DuckDuckGoSearchTool (assuming it's available in the environment)
+        search_tool = DuckDuckGoSearchTool()
+        search_results = search_tool.forward(search_query)
+
+        # If no results found, return early
+        if not search_results or len(search_results) == 0:
+            return "No search results found."
+
+        # Process the search results content
+        # Assuming search_results is a list of dictionaries with a 'content' field
+        # or a string with all content combined
+        if isinstance(search_results, list):
+            all_content = " ".join(
+                [result.get("content", "") for result in search_results]
+            )
+        else:
+            all_content = search_results
+
+        # Split the content into batches
+        batches = []
+        for i in range(0, len(all_content), batch_size):
+            batches.append(all_content[i : i + batch_size])
+
+        # Filter batches to only include those containing important words
+        filtered_batches = []
+        for batch in batches:
+            # Check if any important word is in the batch
+            if any(word.lower() in batch.lower() for word in important_words):
+                filtered_batches.append(batch)
+
+        # Join the filtered batches
+        filtered_content = "\n\n".join(filtered_batches)
+
+        # If no content remains after filtering, provide a helpful message
+        if not filtered_content:
+            return f"No content containing the important words {important_words} was found in the search results."
+
+        return filtered_content
+
+    except Exception as e:
+        return f"Error during optimized web search: {str(e)}"
+
+
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
@@ -30,17 +105,24 @@ class BasicAgent:
 class MyAgent:
     def __init__(self):
         model = LiteLLMModel(
-            model_id="ollama_chat/gemma3:4b",  # Or try other Ollama-supported models
+            model_id="ollama_chat/gemma3:12b",  # Or try other Ollama-supported models
             api_base="http://127.0.0.1:11434",  # Default Ollama local server
             num_ctx=8192,
         )
         # model = HfApiModel()
 
         self.agent = CodeAgent(
-            tools=[DuckDuckGoSearchTool(), WikipediaSearchTool()],
+            tools=[
+                DuckDuckGoSearchTool(),
+                PythonInterpreterTool(),
+                # optimized_web_search,
+                reverse_string,
+                FinalAnswerTool(),
+            ],
             model=model,
-            max_steps=5,
+            max_steps=3,
             add_base_tools=True,
+            additional_authorized_imports=["pandas", "*"],
         )
         print("BasicAgent initialized.")
 
@@ -53,15 +135,32 @@ class MyAgent:
             ""
             # "Ignore all previous instructions. "
             "I will ask you a question. Report your thoughts step by step. "
+            
             # "Don't generate code, don't execute code, don't write explanations. "
             # "Stop on the first step"
-            "Finish your answer only with the final answer. In the final answer don't write explanations, don't write anything else. "
+            "Finish your answer only with the final answer. In the final answer don't write explanations. "
             "The answer should be a number OR as few words as possible OR a comma separated list of numbers and/or strings."
             " If you are asked for a number, don't use comma to write your number neither use units such as $ or "
             "percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither "
             "abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. "
             "If you are asked for a comma separated list, apply the above rules depending of whether the element "
             "to be put in the list is a number or a string."
+            "Pay attention that the questions are specifically designed to be tricky. "
+            "Think about each sentence in the question and verify the answer against every sentence. "
+            "Follow the instructions in the question precisely.  "
+            # "You have access to optimized_web_search, a powerful tool for efficient research:"
+            # "1. Use this tool whenever you need web information without context overload"
+            # "2. Required parameters:"
+            # "- search_query: Specific search terms (e.g., "
+            # "Beatles albums Wikipedia"
+            # ")"
+            # "- important_words: List of keywords ["
+            # "Abbey Road"
+            # ", "
+            # "Let It Be"
+            # "] to filter relevant content"
+            # "3. The tool will return only text chunks containing your keywords, saving context space"
+            # "Use this tool strategically when researching topics that need web information."
         )
 
         prompt = system_instruction + "\n" + question
@@ -126,7 +225,8 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     results_log = []
     answers_payload = []
     print(f"Running agent on {len(questions_data)} questions...")
-    for item in questions_data[:1]:
+    # array
+    for item in questions_data[2:3]:
         task_id = item.get("task_id")
         question_text = item.get("question")
         if not task_id or question_text is None:
@@ -211,8 +311,16 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         return status_message, results_df
 
 
+# Custom CSS to make table content copyable
+custom_css = """
+.table-wrap table td {
+    user-select: text !important;
+    cursor: text !important;
+}
+"""
+
 # --- Build Gradio Interface using Blocks ---
-with gr.Blocks() as demo:
+with gr.Blocks(css=custom_css) as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
     gr.Markdown(
         """
@@ -237,15 +345,19 @@ with gr.Blocks() as demo:
         label="Run Status / Submission Result", lines=5, interactive=False
     )
     # Removed max_rows=10 from DataFrame constructor
-    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
+    results_table = gr.DataFrame(
+        label="Questions and Agent Answers", wrap=True, interactive=True
+    )
 
     run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
+
 if __name__ == "__main__":
     print("\n" + "-" * 30 + " App Starting " + "-" * 30)
     # Check for SPACE_HOST and SPACE_ID at startup for information
     space_host_startup = os.getenv("SPACE_HOST")
     space_id_startup = os.getenv("SPACE_ID")  # Get SPACE_ID at startup
+    space_id_startup = "gmykola/Final_Assignment_Template"
 
     if space_host_startup:
         print(f"✅ SPACE_HOST found: {space_host_startup}")