https://github.com/code-master-harsh/study-crew-v2
An AI-powered study assistant using CrewAI that extracts text from PDFs and generates structured summaries and notes. Modular agent-based design with YAML-configured tasks and tools.
https://github.com/code-master-harsh/study-crew-v2
ai-assistant automation crewai langchain llm modular-ai openai-api poetry python study-tool
Last synced: 3 days ago
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An AI-powered study assistant using CrewAI that extracts text from PDFs and generates structured summaries and notes. Modular agent-based design with YAML-configured tasks and tools.
- Host: GitHub
- URL: https://github.com/code-master-harsh/study-crew-v2
- Owner: code-master-harsh
- Created: 2025-06-17T09:03:28.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-06-18T07:35:19.000Z (10 months ago)
- Last Synced: 2025-06-18T08:31:53.041Z (10 months ago)
- Topics: ai-assistant, automation, crewai, langchain, llm, modular-ai, openai-api, poetry, python, study-tool
- Language: Python
- Homepage:
- Size: 407 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# study-crew-v2
AI-powered study assistant built with CrewAI.
Upload study materials (PDFs), and interact with an intelligent agent crew to generate summaries and structured notes.
---
## 🚀 Features
- 🧠 Extracts text from PDF study material
- ✍️ Generates concise summaries and structured notes
- 🤖 Modular CrewAI agent orchestration
- ⚙️ Extensible tool setup and agent config via YAML
---
## 📁 Project Structure
```
study_crew_v2/
├── pyproject.toml
├── poetry.lock
├── knowledge/ # Upload your PDF files here
├── src/
│ └── study_crew_v2/
│ ├── main.py # Entrypoint to run the crew
│ ├── crew.py # Crew and agent assembly
│ ├── config/
│ │ ├── agents.yaml
│ │ └── tasks.yaml
│ └── tools/
│ └── custom_tool.py
├── .env.example # Example environment variables
```
---
## 🛠️ Installation
> This project uses [Poetry](https://python-poetry.org/) for dependency management.
### 1. Clone the repo
```bash
git clone https://github.com/YOUR-USERNAME/study-crew-v2.git
cd study-crew-v2
```
### 2. Install Poetry (if not already installed)
```bash
curl -sSL https://install.python-poetry.org | python3 -
```
Or via pipx:
```bash
pipx install poetry
```
### 3. Install dependencies
```bash
poetry install
```
### 4. Create `.env` file
Duplicate the `.env.example` file and fill in your API keys and configuration:
```bash
cp .env.example .env
```
Edit `.env` with your Azure OpenAI details.
---
## 🧪 Running the Project
### Upload study materials
Place all your `.pdf` files in the `knowledge/` directory.
### Start the AI Crew
```bash
poetry run run_crew
```
---
## 🔐 .env Configuration
Example `.env.example`:
```
model=azure/gpt-35-turbo
AZURE_OPENAI_API_KEY=your_azure_api_key_here
AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com/
AZURE_OPENAI_API_VERSION=2024-05-01-preview # API version for Azure OpenAI
AZURE_OPENAI_DEPLOYMENT_NAME=gpt-35-turbo # Deployment name for Azure OpenAI
OPENAI_API_KEY=your_azure_api_key_here
```
> Both Azure OpenAI and OpenAI key fields are set for compatibility. Use Azure credentials for both.
---
## 🧩 Dependencies
- `crewai[tools]`
- `openai`, `langchain`, `langchain-openai`, `langchain-core`, `langchain-tools`
- `pymupdf` for PDF parsing
All handled via Poetry in `pyproject.toml`.
---
## ✍️ Author
**Harsh Vardhan Sharma**
[GitHub Profile](https://github.com/code-master-harsh)
---