Fixes

    renamed:    .github/mindmap_10-7-23_.png -> .github/mindmap.png
	renamed:    HuggingFace/integrated_captioner.py/integratable_captioner.py -> HuggingFace/integrated_captioner.py/integrable_captioner.py
	modified:   README.md

README.md

@@ -1,70 +1,92 @@
-# OpenAI Utility Toolkit (OUT)
+# LLM Utilikit
 
 ## Contents
+
 - [LICENSE - GNU Affero GPL](./LICENSE)
 
 ---
 
-#### 1. **[Auto-Embedder](./Auto-Embedder)**
+#### 1. **[OpenAI: Utilikit](./OpenAI/)**
 
-Provides an automated pipeline for retrieving embeddings from [OpenAI's `text-embedding-ada-002`](https://platform.openai.com/docs/guides/embeddings) and upserting them to a [Pinecone index](https://docs.pinecone.io/docs/indexes).
+   Contains `Auto-Embedder` and `GPT-Prompt-Examples`.
 
-   - **[pinembed.py](./Auto-Embedder/pinembed.py)**: A Python module to easily automate the retrieval of embeddings from OpenAI and storage in Pinecone.
-   - **[.env.template](./Auto-Embedder/.env.template)**: Template for environment variables.
+   A. **[Auto-Embedder](./Auto-Embedder)**
 
----
+    Provides an automated pipeline for retrieving embeddings from[OpenAI's `text-embedding-ada-002`](https://platform.openai.com/docs/guides/embeddings) and upserting them to a [Pinecone index](https://docs.pinecone.io/docs/indexes).
+
+    -**[pinembed.py](./Auto-Embedder/pinembed.py)**: A Python module to easily automate the retrieval of embeddings from OpenAI and storage in Pinecone.
+      - **[.env.template](./Auto-Embedder/.env.template)**: Template for environment variables.
+
+   B. **[GPT-Prompt-Examples](./GPT-Prompt-Examples)**
 
-#### 2. **[GPT-Prompt-Examples](./GPT-Prompt-Examples)**
+    There are three main prompt types,[multi-shot](GPT-Prompt-Examples/multi-shot), [system-role](GPT-Prompt-Examples/system-role), [user-role](GPT-Prompt-Examples/user-role).
 
-There are three main prompt types, [multi-shot](GPT-Prompt-Examples/multi-shot), [system-role](GPT-Prompt-Examples/system-role), [user-role](GPT-Prompt-Examples/user-role).
+    Please also see the[OUT-prompt-cheatsheet](GPT-Prompt-Examples/OUT-prompt-cheatsheet.md).
 
-Please also see the [OUT-prompt-cheatsheet](GPT-Prompt-Examples/OUT-prompt-cheatsheet.md).
+    -**[Cheatsheet for quick power-prompts](./GPT-Prompt-Examples/OUT-prompt-cheatsheet.md)**: A cheatsheet for GPT prompts.
+      - **[multi-shot](./GPT-Prompt-Examples/multi-shot)**: Various markdown and text files for multi-shot prompts.
+      - **[system-role](./GPT-Prompt-Examples/system-role)**: Various markdown files for system-role prompts.
+      - **[user-role](./GPT-Prompt-Examples/user-role)**: Markdown files for user-role prompts.
+      - **[Reference Chatlogs with GPT4](./GPT-Prompt-Examples/ChatGPT_reference_chatlogs)**: Contains chat logs and shorthand prompts.
 
-   - **[Cheatsheet for quick power-prompts](./GPT-Prompt-Examples/OUT-prompt-cheatsheet.md)**: A cheatsheet for GPT prompts.
-   - **[multi-shot](./GPT-Prompt-Examples/multi-shot)**: Various markdown and text files for multi-shot prompts.
-   - **[system-role](./GPT-Prompt-Examples/system-role)**: Various markdown files for system-role prompts.
-   - **[user-role](./GPT-Prompt-Examples/user-role)**: Markdown files for user-role prompts.
-   - **[Reference Chatlogs with GPT4](./GPT-Prompt-Examples/ChatGPT_reference_chatlogs)**: Contains chat logs and shorthand prompts.
-
 ---
 
-#### 3. **[LangChain: Pluggable Components](./LangChain/)**
+#### 2. **[LangChain: Pluggable Components](./LangChain/)**
 
-This section describes the pre-built Python modules in the `LangChain` directory that can be side-loaded for various functionalities.
+This directory contains pre-built `LangChain` modules that can be side-loaded for various functionalities.
 
-`langchain_conv_agent.py`
+  A. **`langchain_conv_agent.py`**
 
-This module offers a set of functionalities for conversational agents in LangChain. Specifically, it provides:
+  This module offers a set of functionalities for conversational agents in LangChain. Specifically, it provides:
 
 - Argument parsing for configuring the agent
 - Document loading via `PyPDFDirectoryLoader`
 - Text splitting using `RecursiveCharacterTextSplitter`
 - Various embeddings options like `OpenAIEmbeddings`, `CacheBackedEmbeddings`, and `HuggingFaceEmbeddings`
 
-**Usage:**
-To use this module, simply import the functionalities you need and configure them accordingly.
+  **Usage:**
+  To use this module, simply import the functionalities you need and configure them accordingly.
 
 ---
 
-`query_local_docs.py`
+  B. **`query_local_docs.py`**
 
-This module focuses on querying local documents and employs the following features:
+  This module focuses on querying local documents and employs the following features:
 
 - Environment variable loading via `dotenv`
 - Document loading via `PyPDFLoader`
 - Text splitting through `RecursiveCharacterTextSplitter`
 - Vector storage options like `Chroma`
 - Embedding options via `OpenAIEmbeddings`
 
-**Usage:**
-Similar to `langchain_conv_agent.py`, you can import the functionalities you require.
+  **Usage:**
+  Similar to `langchain_conv_agent.py`, you can import the functionalities you require.
 
 These modules are designed to be extensible and can be easily integrated into your LangChain projects.
 
+---
+
+#### 3. **[HuggingFace: Pluggable Components](./HuggingFace/)**
+
+   A. **`integrable_captioner.py`**
+
+    This module focuses on generating captions for images using Hugging Face's transformer models. Specifically, it offers:
+
+    - Model and processor initialization via the`ImageCaptioner` class
+      - Image loading through the `load_image` method
+      - Asynchronous caption generation using the `generate_caption` method
+      - Caption caching for improved efficiency
+      - Device selection (CPU or GPU) based on availability
+
+    **Usage:**
+      To utilize this module, import the `ImageCaptioner` class and initialize it with a model of your choice. You can then use its methods to load images and generate captions.
+
+---
+
 ### Mindmap
 
-<div align="center">
-  <img src=".github\mindmap_10-7-23_.png" alt="Creation Date: Oct 7th, 2023" width="500"/>
+<div align="left">
+  <img src=".github\mindmap.png" alt="Creation Date: Oct 7th, 2023" width="500"/>
 </div>
 
----
+---