Added tools to BasicAgent

app.py

@@ -3,23 +3,127 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from smolagents import OpenAIServerModel, DuckDuckGoSearchTool, CodeAgent, WikipediaSearchTool
+from smolagents.tools import Tool
 
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
+class TextSummarizationTool(Tool):
+    """Summarize long texts using a simple algorithm."""
+
+    name = "text_summarization"
+    description = "Summarize a long text into a shorter version."
+
+    inputs = {
+        "text": {
+            "type": "string",
+            "description": "The text to summarize.",
+        }
+    }
+    output_type = "string"
+
+    def forward(self, text: str) -> str:
+        """Summarize the text using a simple algorithm."""
+        try:
+            # Simple summarization by taking the first few sentences
+            sentences = text.split('. ')
+            summary = '. '.join(sentences[:3]) + '.'
+            return summary
+        except Exception as exc:
+            return f"Error summarizing text: {exc}"
+
+class KeywordExtractorTool(Tool):
+    """Extract keywords from a text."""
+
+    name = "keyword_extractor"
+    description = "Extract keywords from a given text."
+
+    inputs = {
+        "text": {
+            "type": "string",
+            "description": "The text from which to extract keywords.",
+        }
+    }
+    output_type = "string"
+
+    def forward(self, text: str) -> str:
+        """Extract keywords from the text."""
+        try:
+            # Simple keyword extraction based on word frequency
+            words = re.findall(r'\b\w+\b', text.lower())
+            common_words = ['the', 'and', 'is', 'in', 'it', 'of', 'to', 'a']
+            filtered_words = [word for word in words if word not in common_words]
+            word_counts = Counter(filtered_words)
+            keywords = ', '.join([word for word, count in word_counts.most_common(5)])
+            return keywords
+        except Exception as exc:
+            return f"Error extracting keywords: {exc}"
+
+class TextTranslationTool(Tool):
+    """Translate text using a simple dictionary-based approach."""
+
+    name = "text_translation"
+    description = "Translate a given text from one language to another using a simple dictionary."
+
+    inputs = {
+        "text": {
+            "type": "string",
+            "description": "The text to translate.",
+        },
+        "source_lang": {
+            "type": "string",
+            "description": "The source language (e.g., 'en' for English).",
+        },
+        "target_lang": {
+            "type": "string",
+            "description": "The target language (e.g., 'es' for Spanish).",
+        }
+    }
+    output_type = "string"
+
+    def __init__(self):
+        self.translation_dict = {
+            'hello': 'hola',
+            'world': 'mundo',
+            'goodbye': 'adiós',
+            # Add more translations as needed
+        }
+
+    def forward(self, text: str, source_lang: str, target_lang: str) -> str:
+        """Translate the text using a simple dictionary-based approach."""
+        try:
+            words = text.split()
+            translated_words = [self.translation_dict.get(word, word) for word in words]
+            return ' '.join(translated_words)
+        except Exception as exc:
+            return f"Error translating text: {exc}"
+
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
+        self.agent = CodeAgent(
+            model=OpenAIServerModel(model_id="gpt-4o-mini"),
+            tools=[
+                DuckDuckGoSearchTool(),
+                WikipediaSearchTool(),
+                TextSummarizationTool(),
+                KeywordExtractorTool(),
+                TextTranslationTool()
+            ],
+            add_base_tools=True,
+        )
         print("BasicAgent initialized.")
+
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
+        fixed_answer = self.agent.run(question)
+        print(f"Agent returning answer: {fixed_answer}")
         return fixed_answer
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
@@ -91,7 +195,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission 
+    # 4. Prepare Submission
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
@@ -139,7 +243,6 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
 
-
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
@@ -193,4 +296,4 @@ if __name__ == "__main__":
     print("-"*(60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)

requirements.txt

@@ -1,2 +1,9 @@
+# Core dependencies
 gradio
-requests
+requests
+smolagents
+python-dotenv
+pandas
+
+# Additional dependencies for new tools
+tabulate