added readme

README.md

@@ -1,6 +1,6 @@
 ---
 title: Clip Search Agent
-emoji: 🐠
+emoji: 🎬
 colorFrom: blue
 colorTo: pink
 sdk: gradio
@@ -8,7 +8,153 @@ sdk_version: 5.33.0
 app_file: app.py
 pinned: false
 license: apache-2.0
+tags:
+    - agent-demo-track
 short_description: An agent that allows chatting with parts of video
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Excellent point. A good README must include the setup instructions. I will generate a `requirements.txt` file based on the library imports in your Python scripts and then integrate it into a more complete "Getting Started" section in the README.
+
+---
+
+### 1. `requirements.txt`
+
+Based on a thorough analysis of `video_pipeline.py` and `app.py`, here is the consolidated `requirements.txt` file.
+
+```txt
+# Core Libraries
+openai
+gradio
+pandas
+numpy
+lancedb
+langchain-openai
+langchain-core
+huggingface_hub
+Pillow
+scikit-learn
+nltk
+sentence-transformers
+tqdm
+
+# Optional, but recommended for full functionality
+pydantic-settings  # Assuming this is used by your config.py
+python-dotenv      # Also common for config management
+```
+**Note:** The user's `config.py` likely uses `pydantic-settings` or `python-dotenv` to manage secrets. I've included them as recommended packages.
+
+---
+
+### 2. `packages.txt` (for system-level dependencies)
+
+This is crucial for environments like Docker or cloud deployments where you need to install system packages. Based on the use of `ffmpeg` and some common Python library dependencies:
+
+```txt
+# System dependencies for media processing and building Python packages
+ffmpeg
+build-essential
+```
+
+---
+
+### 3. Updated README.md
+
+Here is the revised README that incorporates these setup instructions into a comprehensive "Getting Started" section.
+
+---
+
+# 🎬 HyperClipper: Your AI Video Librarian 🤖
+
+Tired of scrubbing through hours of video to find that *one* perfect moment? HyperClipper is your personal AI video librarian that watches, understands, and catalogs your entire video library, making every second instantly searchable.
+
+<br>
+
+## ✨ What It Does
+
+HyperClipper ingests your videos and uses a sophisticated AI pipeline to automatically:
+
+-   **👁️ Watch Everything:** It analyzes video frames to detect scene changes and logical breaks.
+-   **👂 Listen to Conversations:** It transcribes all spoken dialogue with pinpoint accuracy.
+-   **🧠 Understand Content:** It combines visual and audio context to generate rich, meaningful summaries for each detected clip.
+-   **🗂️ Create a Smart Index:** It stores everything in a high-speed vector database, turning your video content into a searchable knowledge base.
+
+The result? A powerful, conversational AI agent you can chat with to find exactly what you're looking for, instantly.
+
+<br>
+
+## 🚀 Key Features
+
+*   **Conversational Search:** Just ask! "Find clips where they discuss Qwen models" or "Show me the part about cooking pasta."
+*   **Multimodal Understanding:** The agent doesn't just search text; it understands the *content* of the clips, leveraging both visuals and audio.
+*   **Instant Previews:** See search results with summaries, relevance scores, and playable video clips directly in the chat.
+*   **Drop-and-Go Analysis:** Simply upload a new video, and HyperClipper automatically processes and adds it to your searchable library.
+
+<br>
+
+## 🛠️ Getting Started
+
+Follow these steps to set up and run HyperClipper on your local machine.
+
+### Step 1: System Dependencies
+
+This project requires `ffmpeg` for video and audio processing. Install it using your system's package manager.
+
+*   **On macOS (using Homebrew):**
+    ```bash
+    brew install ffmpeg
+    ```
+*   **On Debian/Ubuntu:**
+    ```bash
+    sudo apt-get update && sudo apt-get install ffmpeg
+    ```
+
+### Step 2: Clone the Repository
+
+```bash
+git clone https://huggingface.co/spaces/Agents-MCP-Hackathon/Clip-Search-Agent/
+cd Clip-Search-Agent # or your project directory name
+```
+
+### Step 3: Install Python Packages
+
+Create a virtual environment and install the required Python libraries.
+
+```bash
+# Create a virtual environment
+python3 -m venv venv
+source venv/bin/activate
+
+# Install all dependencies
+pip install -r requirements.txt
+```
+
+### Step 4: Configure Environment Variables
+
+Create a `.env` file in the root of the project directory and add your API keys and model endpoints. Your `config.py` will load these variables.
+
+```env
+# .env file
+HF_API_KEY="hf_..."
+NEBIUS_API_KEY="your_nebius_key"
+MODAL_VLM_URL="https://your-modal-endpoint-url..."
+# ... add any other secrets or configuration variables here
+```
+
+### Step 5: Launch the Application
+
+With all dependencies installed and configurations set, launch the Gradio web server.
+
+```bash
+gradio app.py
+```
+You should see a message like `🚀 Starting Video Search Agent...` and a local URL (e.g., `http://127.0.0.1:7860`). Open this URL in your browser.
+
+### Step 6: Analyze & Search
+
+1.  Navigate to the **"Video Analyzer"** tab in the web UI.
+2.  Upload your first video file and click "Analyze Video".
+3.  Once processing is complete, go to the **"Chat with Clips"** tab and start a conversation with your new AI video librarian!
+
+---
+
+**HyperClipper: Don't just watch your videos. Understand them.**