diff --git a/.github/mindmap_10-7-23_.png b/.github/mindmap.png similarity index 100% rename from .github/mindmap_10-7-23_.png rename to .github/mindmap.png diff --git a/HuggingFace/integrated_captioner.py/integratable_captioner.py b/HuggingFace/integrated_captioner.py/integrable_captioner.py similarity index 100% rename from HuggingFace/integrated_captioner.py/integratable_captioner.py rename to HuggingFace/integrated_captioner.py/integrable_captioner.py diff --git a/README.md b/README.md index 1c907bc..bcf98f1 100644 --- a/README.md +++ b/README.md @@ -1,54 +1,57 @@ -# 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` @@ -56,15 +59,34 @@ This module focuses on querying local documents and employs the following featur - 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 -
- Creation Date: Oct 7th, 2023 +
+ Creation Date: Oct 7th, 2023
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