Update README.md

README.md

@@ -1,67 +1,17 @@
-# Hugging Face AI Agents Course - Final Exam Agent
-
-This project contains an AI agent developed for the final exam of the Hugging Face AI Agents Course. The agent is designed to answer a variety of questions by leveraging a suite of powerful tools and a language model.
-
-##  Overview
-
-This agent is built using the `LangGraph` library to create a robust and stateful agent. It can perform a variety of tasks, including web searches, calculations, code execution, and processing different types of media like audio, images, and documents. The project includes a Gradio application for evaluating the agent's performance on a set of questions provided by the course.
-
-##  Features
-
-*   **Multi-tool Integration**: The agent can use a wide range of tools to solve complex problems.
-*   **Conversational AI**: Powered by a capable language model from OpenRouter.
-*   **Stateful Execution**: Uses `LangGraph` to manage the conversation flow and tool execution in a structured manner.
-*   **Web Interface**: A Gradio app (`app.py`) is provided to test and evaluate the agent.
-*   **Extensible**: New tools can be easily added to enhance the agent's capabilities.
-
-##  Tools
-
-The agent has access to the following tools:
-
-### Community Tools
-
-*   **Brave Search**: Performs web searches to find up-to-date information.
-*   **Python REPL**: Executes Python code to solve logic and math problems.
-
-### Custom Tools
-
-*   **Calculator**:
-    *   `add(a, b)`: Adds two numbers.
-    *   `subtract(a, b)`: Subtracts two numbers.
-    *   `multiply(a, b)`: Multiplies two numbers.
-    *   `divide(a, b)`: Divides two numbers.
-    *   `power(a, b)`: Calculates `a` to the power of `b`.
-*   **Date & Time**:
-    *   `current_date()`: Returns the current date.
-    *   `day_of_week()`: Returns the current day of the week.
-    *   `days_until(date_str)`: Calculates the number of days until a given date.
-*   **Media Processing**:
-    *   `transcribe_audio(audio_file, file_extension)`: Transcribes audio files.
-    *   `transcribe_youtube(youtube_url)`: Transcribes YouTube videos.
-    *   `query_image(query, image_url)`: Answers questions about an image.
-*   **Web & Document Content**:
-    *   `webpage_content(url)`: Extracts text from webpages and PDF files.
-    *   `read_excel(file_path, sheet_name, query)`: Reads data from an Excel file and answers a query about it.
-
-##  How It Works
-
-The agent's logic is defined in `agent.py`. It uses a `StateGraph` from the `LangGraph` library to manage its execution flow. The graph has two main nodes:
-
-1.  **`llm_call`**: This node calls the language model with the current conversation history and a system prompt (`prompt.py`). The LLM decides whether to respond directly to the user or to use one of the available tools.
-2.  **`environment`**: If the LLM decides to use a tool, this node executes the tool with the arguments provided by the LLM.
-
-The agent alternates between these two nodes until the LLM generates a final answer for the user.
-
-## Usage
-
-### 1. Installation
-
-Clone the repository and install the required dependencies:
-
-```bash
-git clone https://huggingface.co/spaces/YOUR_SPACE_HERE
-cd YOUR_REPO
-pip install -r requirements.txt
-```
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Template Final Assignment
+emoji: 🕵🏻‍♂️
+sdk: gradio
+colorFrom: indigo
+colorTo: indigo
+---
+title: Template Final Assignment
+emoji: 🕵🏻‍♂️
+colorFrom: indigo
+colorTo: indigo
+sdk: gradio
+sdk_version: 5.25.2
+app_file: app.py
+pinned: false
+hf_oauth: true
+hf_oauth_expiration_minutes: 480