PR: minor bug fixes and update README

fix: minor bug fixes and update README

README.md

@@ -8,21 +8,25 @@
 ![GitHub](https://img.shields.io/github/license/NotShrirang/LoomRAG)
 ![GitHub last commit](https://img.shields.io/github/last-commit/NotShrirang/LoomRAG)
 ![GitHub repo size](https://img.shields.io/github/repo-size/NotShrirang/LoomRAG)
-<a href="https://loomrag.streamlit.app/"><img src="https://img.shields.io/badge/Streamlit%20App-red?style=flat-rounded-square&logo=streamlit&labelColor=white"/></a>
+<a href="https://huggingface.co/spaces/NotShrirang/LoomRAG"><img src="https://img.shields.io/badge/Streamlit%20App-red?style=flat-rounded-square&logo=streamlit&labelColor=white"/></a>
 
-This project implements a Multimodal Retrieval-Augmented Generation (RAG) system, named **LoomRAG**, that leverages OpenAI's CLIP model for neural cross-modal retrieval and semantic search. The system allows users to input text queries and retrieve both text and image responses seamlessly through vector embeddings. It also supports uploading images and PDFs for enhanced interaction and intelligent retrieval capabilities through a Streamlit-based interface.
+This project implements a Multimodal Retrieval-Augmented Generation (RAG) system, named **LoomRAG**, that leverages OpenAI's CLIP model for neural cross-modal retrieval and semantic search. The system allows users to input text queries and retrieve both text and image responses seamlessly through vector embeddings. It features a comprehensive annotation interface for creating custom datasets and supports CLIP model fine-tuning with configurable parameters for domain-specific applications. The system also supports uploading images and PDFs for enhanced interaction and intelligent retrieval capabilities through a Streamlit-based interface.
 
 Experience the project in action:
 
-[![LoomRAG Streamlit App](https://img.shields.io/badge/Streamlit%20App-red?style=for-the-badge&logo=streamlit&labelColor=white)](https://loomrag.streamlit.app/)
+[![LoomRAG Streamlit App](https://img.shields.io/badge/Streamlit%20App-red?style=for-the-badge&logo=streamlit&labelColor=white)](https://huggingface.co/spaces/NotShrirang/LoomRAG)
 
 ---
 
 ## 📸 Implementation Screenshots
 
-| ![Screenshot 2024-12-30 111906](https://github.com/user-attachments/assets/13c0bd0d-1569-4d9e-aae5-ea5801a69beb) | ![Screenshot 2024-12-30 114200](https://github.com/user-attachments/assets/d74e9d75-7716-4705-9564-0c6fdc26790b) |
+| ![Screenshot 2025-01-01 184852](https://github.com/user-attachments/assets/ad79d0f0-d200-4a82-8c2f-0890a9fe8189) | ![Screenshot 2025-01-01 222334](https://github.com/user-attachments/assets/7307857d-a41f-4f60-8808-00d6db6e8e3e) |
 | ---------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------- |
-| Screenshot 1                                                                                                     | Screenshot 2                                                                                                     |
+| Data Upload Page | Data Search / Retrieval |
+|  |  |
+| ![Screenshot 2025-01-01 222412](https://github.com/user-attachments/assets/e38273f4-426b-444d-80f0-501fa9563779) | ![Screenshot 2025-01-01 223948](https://github.com/user-attachments/assets/21724a92-ef79-44ae-83e6-25f8de29c45a)
+| Data Annotation Page | CLIP Fine-Tuning |
+
 
 ---
 
@@ -33,6 +37,9 @@ Experience the project in action:
 - 📤 **Upload Options**: Allows users to upload images and PDFs for AI-powered processing and retrieval
 - 🧠 **Embedding-Based Search**: Uses OpenAI's CLIP model to align text and image embeddings in a shared latent space
 - 🔍 **Augmented Text Generation**: Enhances text results using LLMs for contextually rich outputs
+- 🏷️ Image Annotation: Enables users to annotate uploaded images through an intuitive interface
+- 🎯 CLIP Fine-Tuning: Supports custom model training with configurable parameters including test dataset split size, learning rate, optimizer, and weight decay
+- 🔨 Fine-Tuned Model Integration: Seamlessly load and utilize fine-tuned CLIP models for enhanced search and retrieval
 
 ---
 
@@ -54,6 +61,17 @@ Experience the project in action:
    - For image results: Directly returned or enhanced with image captions
    - For PDFs: Extracts text content and provides relevant sections
 
+4. **Image Annotation**:
+   - Dedicated annotation page for managing uploaded images
+   - Support for creating and managing multiple datasets simultaneously
+   - Flexible annotation workflow for efficient data labeling
+   - Dataset organization and management capabilities
+
+5. **Model Fine-Tuning**:
+   - Custom CLIP model training on annotated images
+   - Configurable training parameters for optimization
+   - Integration of fine-tuned models into the search pipeline
+
 ---
 
 ## 🚀 Installation
@@ -85,6 +103,9 @@ Experience the project in action:
    - Access the interface in your browser to:
      - Submit natural language queries
      - Upload images or PDFs to retrieve contextually relevant results
+     - Annotate uploaded images
+     - Fine-tune CLIP models with custom parameters
+     - Use fine-tuned models for improved search results
 
 2. **Example Queries**:
    - **Text Query**: "sunset over mountains"  
@@ -99,12 +120,13 @@ Experience the project in action:
 - 📊 **Vector Database**: It uses FAISS for efficient similarity search
 - 🤖 **Model**: Uses OpenAI CLIP for neural embedding generation
 - ✍️ **Augmentation**: Optional LLM-based augmentation for text responses
+- 🎛️ Fine-Tuning: Configurable parameters for model training and optimization
 
 ---
 
 ## 🗺️ Roadmap
 
-- [ ] Fine-tuning CLIP for domain-specific datasets
+- [x] Fine-tuning CLIP for domain-specific datasets
 - [ ] Adding support for audio and video modalities
 - [ ] Improving the re-ranking system for better contextual relevance
 - [ ] Enhanced PDF parsing with semantic section segmentation
@@ -119,7 +141,7 @@ Contributions are welcome! Please open an issue or submit a pull request for any
 
 ## 📄 License
 
-This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
+This project is licensed under the Apache-2.0 License. See the [LICENSE](LICENSE) file for details.
 
 ---
 

app.py

@@ -21,8 +21,8 @@
 device = "cuda" if torch.cuda.is_available() else "cpu"
 clip_model, preprocess = load_clip_model()
 text_embedding_model = load_text_embedding_model()
-
-sidebar = st.sidebar
+os.makedirs("annotations/", exist_ok=True)
+os.makedirs("images/", exist_ok=True)
 
 with st.sidebar:
     st.title("LoomRAG")

data_search/data_search_page.py

@@ -21,6 +21,11 @@ def load_finetuned_model(file_name):
 
     st.title("Data Search")
 
+    images = os.listdir("images/")
+    if images == []:
+        st.warning("No Images Found! Please upload images to the database.")
+        return
+
     annotation_projects = get_local_files("annotations/", get_details=True)
 
     if annotation_projects or st.session_state.get('selected_annotation_project', None) is not None: