https://github.com/styleebender/careersync_chatbot
Your AI-Powered LinkedIn and Career Strategist!!
https://github.com/styleebender/careersync_chatbot
chatbot langchain langgraph langgraph-agents langgraph-chabot multi-agent multiagent-systems streamlit
Last synced: about 1 month ago
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Your AI-Powered LinkedIn and Career Strategist!!
- Host: GitHub
- URL: https://github.com/styleebender/careersync_chatbot
- Owner: Styleebender
- License: mit
- Created: 2025-02-14T06:26:46.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-14T06:38:55.000Z (over 1 year ago)
- Last Synced: 2025-02-14T07:30:42.253Z (over 1 year ago)
- Topics: chatbot, langchain, langgraph, langgraph-agents, langgraph-chabot, multi-agent, multiagent-systems, streamlit
- Language: Python
- Homepage: https://careersync-chatbot.streamlit.app/
- Size: 382 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# CareerSync_Chatbot
Your AI-Powered LinkedIn and Career Strategist!!
AI-powered chatbot that helps users optimize their LinkedIn profiles, analyze job fit, including personalized cover letters and career guidance.
# Documentation:
Architecture and approach overview
# Prerequisites
Python 3.11 (preferred Python version)
# Setup Instructions
**1. Clone the Repository**
```git clone https://github.com/Styleebender/CareerSync_Chatbot.git```
**2. Create a Virtual Environment**
```
python -m venv venv
venv\Scripts\activate
```
**3. Configure Environment Variables**
Create a .env file in the root directory of your project
to store API keys.
```
GEMINI_API_KEY=your_gemini_api_key_here
SCRAPIN_API_KEY=your_scrapin_api_key_here
TAVILY_API_KEY=your_tavily_api_key_here
```
**4. Install Dependencies**
Install the required Python packages using the requirements.txt file:
```
pip install -r requirements.txt
```
**5. Running the Application**
To run the langGraph script manually
```
python graph.py
```
**Streamlit Application:**
```
streamlit run streamlit_app.py
```