chat-with-pdf 0.3.2

Chat with your PDFs using local embedding search and OpenAI.

📄 Chat with PDF

Chat with your PDF documents easily using local embeddings and powerful LLMs like OpenAI's GPT models.

Chat with your PDF documents easily using local embeddings and powerful LLMs like OpenAI's GPT models.

Upload any PDF and ask natural language questions about its content — powered by semantic search and AI.

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🛠️ Installation

pip install chat-with-pdf

Or using Poetry:

poetry add chat-with-pdf

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✨ Quickstart Example

from chat_with_pdf import PDFChat

chat = PDFChat('path/to/your/document.pdf')


response = chat.ask("Summarize the introduction section.")
print(response)

You can pass a file path, URL, or binary bytes of the PDF to PDFChat.

Example:

chat = PDFChat("path/to/file.pdf")
chat = PDFChat("https://example.com/file.pdf")
chat = PDFChat(binary_pdf_data)

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⚙️ Configuration Options

You can configure your usage via arguments, environment variables, or let it fallback to defaults.

Priority:

1. Arguments passed to PDFChat
2. Environment Variables
3. Library defaults

Supported Environment Variables:

Variable	Purpose	Default
OPENAI_API_KEY	Your OpenAI API key	"" (empty)
OPENAI_MODEL	GPT model name to use	"gpt-3.5-turbo"
EMBEDDING_MODEL	Embedding model for vector search	"all-MiniLM-L6-v2"
DEFAULT_CHUNK_SIZE	Number of characters per text chunk	500
TOP_K_RETRIEVAL	Number of similar chunks to retrieve per question	5

Example .env file:

OPENAI_API_KEY=sk-xxxxx
OPENAI_MODEL=gpt-4
DEFAULT_CHUNK_SIZE=600
TOP_K_RETRIEVAL=8
EMBEDDING_MODEL=all-mpnet-base-v2

If you have a .env file at your project root, chat-with-pdf will automatically load it.

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🔥 Advanced Usage Example

Explicitly passing all settings:

from chat_with_pdf import PDFChat

chat = PDFChat(
    'path/to/your/document.pdf',
    openai_api_key="sk-your-openai-key",
    model="gpt-4",
    embedding_model="all-mpnet-base-v2",
    chunk_size=600,
    top_k_retrieval=8
)

response = chat.ask("Summarize the key points.")
print(response)

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📝 License

This project is licensed under the MIT License.

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🌟 Acknowledgements

• OpenAI
• HuggingFace Sentence Transformers
• PyMuPDF