Initial agent submission

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+venvAgentsHf/
+venv/
+ENV/
+env.bak/
+venv.bak/
+*.egg
+*.egg-info/
+dist/
+build/
+.eggs/
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+
+# Pytest cache
+.pytest_cache/
+
+# MyPy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre
+.pyre/
+
+# Pytype
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# VSCode settings
+.vscode/
+
+# macOS
+.DS_Store
+
+# Jupyter
+.ipynb_checkpoints
+
+# dotenv
+.env
+.env.*
+
+# Local test/output files
+*.log
+*.out
+*.tmp
+
+# Obsidian vault temporary/backup files
+*.obsidian

agentsTools/toolVisitWebpage.py

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+from smolagents import tool
+import requests
+from bs4 import BeautifulSoup
+
+MAX_WEBPAGE_SIZE = 3000  # max characters to return from scraped content
+
+@tool
+def visit_webpage(url: str) -> dict:
+    """
+    Visits a webpage and extracts clean text from it.
+
+    Args:
+        url: The URL of the page to visit (e.g., https://en.wikipedia.org/wiki/OpenAI)
+
+    Returns:
+        dict: A dictionary containing:
+            - "text": Truncated page content
+            - "url": The original URL
+            - "status": HTTP status or error info
+    """
+    print(f" Tool:visit_webpage visiting {url}...")
+
+    try:
+        response = requests.get(url, timeout=10)
+        response.raise_for_status()
+
+        soup = BeautifulSoup(response.text, "html.parser")
+        text = soup.get_text(separator="\n", strip=True)
+        short_text = text[:MAX_WEBPAGE_SIZE]
+
+        print(f"✅ Extracted {len(short_text)} characters from {url}")
+        return {
+            "text": short_text,
+            "url": url,
+            "status": f"Success ({response.status_code})"
+        }
+
+    except Exception as e:
+        print(f"🚨 Error in visit_webpage: {e}")
+        return {
+            "text": "",
+            "url": url,
+            "status": f"Error: {e}"
+        }

agentsTools/tool_fetch_task_file.py

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+from smolagents import tool
+import os
+import requests
+
+DEFAULT_API_URL = os.getenv("AGENT_API_URL", "https://agents-course-unit4-scoring.hf.space")
+
+@tool
+def fetch_task_file(task_id: str) -> dict:
+    """
+    Fetches the file associated with a task ID using the API URL from env.
+
+    Args:
+        task_id: The task ID to fetch.
+
+    Returns:
+        dict: task_id, content, status
+    """
+    full_url = f"{DEFAULT_API_URL}/files/{task_id}"
+    print(f"📥 Tool:fetch_task_file requesting {full_url}")
+
+    try:
+        response = requests.get(full_url, timeout=10)
+
+        if response.status_code == 200:
+            return {
+                "task_id": task_id,
+                "content": response.text[:5000],
+                "status": "Success"
+            }
+
+        return {
+            "task_id": task_id,
+            "content": "",
+            "status": f"{response.status_code} - {response.reason}"
+        }
+
+    except Exception as e:
+        return {
+            "task_id": task_id,
+            "content": "",
+            "status": f"Error: {str(e)}"
+        }

agentsTools/tool_read_excel_as_json.py

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+from smolagents import tool
+import os
+import requests
+import pandas as pd
+from io import BytesIO
+
+DEFAULT_API_URL = os.getenv("AGENT_API_URL", "https://agents-course-unit4-scoring.hf.space")
+
+@tool
+def read_excel_as_json(task_id: str) -> dict:
+    """
+    Fetches and parses an Excel file as structured JSON for a given task_id.
+    
+    Args:
+        task_id: The task ID to fetch.
+        
+    Returns:
+        {
+            "task_id": str,
+            "sheets": {
+                "SheetName1": [ {col1: val1, col2: val2, ...}, ... ],
+                ...
+            },
+            "status": "Success" | "Error"
+        }
+    """
+    url = f"{DEFAULT_API_URL}/files/{task_id}"
+
+    try:
+        response = requests.get(url, timeout=10)
+        if response.status_code != 200:
+            return {"task_id": task_id, "sheets": {}, "status": f"{response.status_code} - Failed"}
+
+        xls = pd.ExcelFile(BytesIO(response.content))
+        sheets_json = {}
+
+        for sheet in xls.sheet_names:
+            df = xls.parse(sheet)
+            df = df.dropna(how="all")  # Remove completely empty rows
+            rows = df.head(20).to_dict(orient="records")  # limit to first 20 rows
+            sheets_json[sheet] = rows
+
+        return {
+            "task_id": task_id,
+            "sheets": sheets_json,
+            "status": "Success"
+        }
+
+    except Exception as e:
+        return {
+            "task_id": task_id,
+            "sheets": {},
+            "status": f"Error: {str(e)}"
+        }

app.py

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+import os
+import gradio as gr
+import requests
+import pandas as pd
+
+from smolagents import ToolCallingAgent, OpenAIServerModel
+from smolagents import DuckDuckGoSearchTool, PythonInterpreterTool
+from agentsTools.toolVisitWebpage import visit_webpage
+from agentsTools.tool_fetch_task_file import fetch_task_file
+from agentsTools.tool_read_excel_as_json import read_excel_as_json
+
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+
+class GeminiReActAgent:
+    def __init__(self):
+        self.model = OpenAIServerModel(
+            model_id="gemini-2.5-pro-preview-03-25",
+            api_base="https://generativelanguage.googleapis.com/v1beta/",
+            api_key=os.getenv("GEMINI_API_KEY_1")
+        )
+        self.agent = ToolCallingAgent(
+            tools=[
+                DuckDuckGoSearchTool(),
+                PythonInterpreterTool(),
+                visit_webpage,
+                fetch_task_file,
+                read_excel_as_json,
+            ],
+            model=self.model,
+            max_steps=8
+        )
+
+    def __call__(self, question: str, taskid: str) -> str:
+        prompt = """
+        You are an intelligent assistant answering questions step-by-step.
+        Use tools only when necessary. You can take up to 8 steps.
+        You have access to tools such as a web search, Python execution, and file reading.
+        Use the task ID {tid} if you need to fetch additional data.
+
+        Think aloud, justify each step. Conclude your process with:
+        FINAL ANSWER = [your answer here]  
+
+        Question: {q}
+        """.format(tid=taskid, q=question)
+
+        result = self.agent.run(prompt)
+        return result
+
+def submit_eval_run(profile: gr.OAuthProfile | None):
+    space_id = os.getenv("SPACE_ID")
+    if profile:
+        username = profile.username
+    else:
+        return "Please login to Hugging Face first.", None
+
+    agent = GeminiReActAgent()
+    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
+
+    try:
+        response = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
+        response.raise_for_status()
+        questions_data = response.json()
+    except Exception as e:
+        return f"Failed to fetch questions: {e}", None
+
+    results_log = []
+    answers_payload = []
+    for item in questions_data:
+        task_id = item.get("task_id")
+        question_text = item.get("question")
+        if not task_id or question_text is None:
+            continue
+        try:
+            submitted_answer = agent(question_text, task_id)
+            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
+        except Exception as e:
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"ERROR: {e}"})
+
+    if not answers_payload:
+        return "Agent did not return any answers.", pd.DataFrame(results_log)
+
+    submission_data = {
+        "username": username,
+        "agent_code": agent_code,
+        "answers": answers_payload
+    }
+
+    try:
+        response = requests.post(f"{DEFAULT_API_URL}/submit", json=submission_data, timeout=60)
+        response.raise_for_status()
+        result = response.json()
+        summary = (
+            f"Submission Successful!\n"
+            f"User: {result.get('username')}\n"
+            f"Score: {result.get('score')}% ({result.get('correct_count')}/{result.get('total_attempted')})\n"
+            f"Message: {result.get('message', 'No message received.')}"
+        )
+        return summary, pd.DataFrame(results_log)
+    except Exception as e:
+        return f"Submission failed: {e}", pd.DataFrame(results_log)
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Gemini Agent Submission Tool")
+    gr.LoginButton()
+    btn = gr.Button("Submit Answers")
+    status = gr.Textbox(label="Submission Status")
+    table = gr.DataFrame(label="Answers Log")
+    btn.click(fn=submit_eval_run, outputs=[status, table])
+
+demo.launch(debug=True, share=False)

requirements.txt

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+aiofiles==24.1.0
+annotated-types==0.7.0
+anyio==4.9.0
+Authlib==1.5.2
+beautifulsoup4==4.13.4
+bs4==0.0.2
+certifi==2025.1.31
+cffi==1.17.1
+charset-normalizer==3.4.1
+click==8.1.8
+colorama==0.4.6
+cryptography==44.0.2
+distro==1.9.0
+duckduckgo_search==8.0.1
+fastapi==0.115.12
+ffmpy==0.5.0
+filelock==3.18.0
+fsspec==2025.3.2
+gradio==5.26.0
+gradio_client==1.9.0
+groovy==0.1.2
+h11==0.16.0
+httpcore==1.0.9
+httpx==0.28.1
+huggingface-hub==0.30.2
+idna==3.10
+itsdangerous==2.2.0
+Jinja2==3.1.6
+jiter==0.9.0
+lxml==5.4.0
+markdown-it-py==3.0.0
+markdownify==1.1.0
+MarkupSafe==3.0.2
+mdurl==0.1.2
+numpy==2.2.5
+openai==1.76.0
+orjson==3.10.16
+packaging==25.0
+pandas==2.2.3
+pillow==11.2.1
+primp==0.15.0
+pycparser==2.22
+pydantic==2.11.3
+pydantic_core==2.33.1
+pydub==0.25.1
+Pygments==2.19.1
+python-dateutil==2.9.0.post0
+python-dotenv==1.1.0
+python-multipart==0.0.20
+pytz==2025.2
+PyYAML==6.0.2
+requests==2.32.3
+rich==14.0.0
+ruff==0.11.7
+safehttpx==0.1.6
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.17.0
+smolagents==1.14.0
+sniffio==1.3.1
+soupsieve==2.7
+starlette==0.46.2
+tomlkit==0.13.2
+tqdm==4.67.1
+typer==0.15.2
+typing-inspection==0.4.0
+typing_extensions==4.13.2
+tzdata==2025.2
+urllib3==2.4.0
+uvicorn==0.34.2
+websockets==15.0.1