Welcome to the PDF Chatbot project! This application allows users to interact with a conversational AI that can answer questions based on the content of multiple PDF documents. The chatbot is built using Streamlit and integrates various LangChain components, Hugging Face models, and PDF processing libraries.
https://www.loom.com/share/2f8a3f04763347ba9c3200ab9d675fb3?sid=590c5096-84c2-4a26-abf2-40e20e411edc
This Streamlit application is a chatbot that can respond to user queries based on the content of an uploaded PDF file. It utilizes the ollama library for generating responses and PyPDF2 for PDF text extraction.
Ensure you have the following installed:
If you have a Git repository, clone it using:
git clone <repository-url>
cd <repository-directory>
2. Create and Activate a Virtual Environment
Create a virtual environment (optional but recommended):
Copy code
python -m venv venv
Activate the virtual environment:
On Windows:
Copy code
venv\Scripts\activate
On macOS/Linux:
Copy code
source venv/bin/activate
3. Install Dependencies
Install the required Python libraries:
Copy code
pip install streamlit ollama PyPDF2
4.Setting Up Ollama and Downloading the Model
1. Install Ollama CLI
Download and install the Ollama CLI by following the instructions on the Ollama website ["https://ollama.com/download"]. The installation process may vary based on your operating system:
For Windows:
Download the installer from the Ollama website and follow the installation instructions.
For macOS/Linux:
Use Homebrew or download the binary from the Ollama website.
2. Download the gemma:2b Model
Once you have Ollama installed, use the following command to download the gemma:2b model:
Copy code in cmd prompt:
ollama run gemma:2b
Running the Application
Save Your Code
Save the provided code in a file, e.g., chatbot.py.
Start the Ollama server:
in cmd promt:
ollam serve
Start the Streamlit Application
Run the Streamlit application with:
Copy code
python -m streamlit run chatbot.py
Access the Application
Open your web browser and navigate to the URL provided in the terminal, usually http://localhost:8501.
How to Use the Application
Upload a PDF
Use the "Upload a PDF file" button to upload a PDF. The application will process the PDF and extract text from it.
Interact with the Chatbot
Type your queries into the chat input box and press Enter. The chatbot will respond based on the content of the uploaded PDF.
Handling Responses
If the chatbot cannot find relevant information in the PDF, it will prompt you to contact the administrator or the company.
Welcome to the PDF Chatbot project! This application allows users to interact with a conversational AI that can answer questions based on the content of multiple PDF documents. The chatbot is built using Streamlit and integrates various LangChain components, Hugging Face models, and PDF processing libraries.
https://www.loom.com/share/2f8a3f04763347ba9c3200ab9d675fb3?sid=590c5096-84c2-4a26-abf2-40e20e411edc
This Streamlit application is a chatbot that can respond to user queries based on the content of an uploaded PDF file. It utilizes the ollama library for generating responses and PyPDF2 for PDF text extraction.
Ensure you have the following installed:
If you have a Git repository, clone it using:
git clone <repository-url>
cd <repository-directory>
2. Create and Activate a Virtual Environment
Create a virtual environment (optional but recommended):
Copy code
python -m venv venv
Activate the virtual environment:
On Windows:
Copy code
venv\Scripts\activate
On macOS/Linux:
Copy code
source venv/bin/activate
3. Install Dependencies
Install the required Python libraries:
Copy code
pip install streamlit ollama PyPDF2
4.Setting Up Ollama and Downloading the Model
1. Install Ollama CLI
Download and install the Ollama CLI by following the instructions on the Ollama website ["https://ollama.com/download"]. The installation process may vary based on your operating system:
For Windows:
Download the installer from the Ollama website and follow the installation instructions.
For macOS/Linux:
Use Homebrew or download the binary from the Ollama website.
2. Download the gemma:2b Model
Once you have Ollama installed, use the following command to download the gemma:2b model:
Copy code in cmd prompt:
ollama run gemma:2b
Running the Application
Save Your Code
Save the provided code in a file, e.g., chatbot.py.
Start the Ollama server:
in cmd promt:
ollam serve
Start the Streamlit Application
Run the Streamlit application with:
Copy code
python -m streamlit run chatbot.py
Access the Application
Open your web browser and navigate to the URL provided in the terminal, usually http://localhost:8501.
How to Use the Application
Upload a PDF
Use the "Upload a PDF file" button to upload a PDF. The application will process the PDF and extract text from it.
Interact with the Chatbot
Type your queries into the chat input box and press Enter. The chatbot will respond based on the content of the uploaded PDF.
Handling Responses
If the chatbot cannot find relevant information in the PDF, it will prompt you to contact the administrator or the company.