The goal of this project is to develop an AI chatbot that can process legal documents (PDFs of corporate acts) submitted by users and identify predefined services from a company service menu. The chatbot will interact with users to gather missing information, answer questions, and finally provide a quote with the services and prices. If the user does not upload the legal document, they can still converse with the chatbot to explain their needs.
- Develop a text extraction model to process PDF documents and extract relevant information.
- Implement natural language processing (NLP) techniques to understand user queries and extract required details from conversations.
- Build a conversational interface for users to interact with the bot via text input, with an option to upload PDFs.
- Create a service menu database to map extracted information to predefined services.
- Develop a pricing algorithm to generate quotes based on the services required.
- Implement fallback mechanisms to query users for missing information.
- Ensure the chatbot can answer general questions about services offered.
- Test and evaluate the bot’s performance in accurately identifying services and generating quotes.
To enhance the project with LangChain, we will utilize LangChain agents and functions for various tasks:
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Text Extraction:
- Use LangChain functions to extract text from PDF documents.
- Implement LangChain agents for tokenization and information retrieval.
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NLP for User Queries:
- Utilize LangChain agents for understanding and processing user queries.
- Fine-tune pre-trained language models using LangChain for better query understanding.
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Conversational Interface:
- Design conversational flows using LangChain agents to handle user interactions and route queries to the appropriate processing modules.
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Service Mapping and Pricing:
- Develop LangChain agents to map extracted information to services.
- Implement a pricing algorithm using LangChain functions.
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Fallback Mechanisms:
- Use LangChain to develop fallback mechanisms for querying users about missing information.
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General Question Answering:
- Integrate LangChain agents to answer general questions about services offered.
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Evaluation and Deployment:
- Use LangSmith platform for testing, evaluation, and deployment of the AI chatbot.
- Source code for the AI chatbot implementation, including LangChain integration.
- Documentation detailing the project architecture, methodology, and LangChain usage.
- Presentation slides summarizing the project objectives, process, and results.
- Deployment of the chatbot as a web/mobile app.
- Day 1-2: Project kickoff, data collection (PDF documents), and text extraction using LangChain functions.
- Day 3-4: NLP model development with LangChain agents for user query understanding.
- Day 5-6: Conversational interface development with LangChain agents, service mapping, and pricing algorithm implementation.
- Day 7: Testing, evaluation, documentation, and presentation preparation.
- PDF text extraction libraries (e.g., PyMuPDF, pdfplumber).
- Pre-trained language models available in libraries like HuggingFace Transformers.
- LangChain for text extraction, NLP, and conversational interface design.
- LangSmith for testing, performance checks, and deploying your model and app.
- Accuracy in extracting relevant information from PDF documents.
- Effectiveness in understanding and processing user queries.
- Usability and responsiveness of the conversational interface.
- Accuracy in mapping extracted information to predefined services.
- Precision in generating quotes based on identified services.
- Quality and clarity of documentation and presentation slides.
This project offers an exciting opportunity to explore the intersection of NLP, document processing, and conversational AI in building an AI chatbot for legal services automation. By leveraging state-of-the-art techniques and technologies, including LangChain, you will gain valuable hands-on experience in developing innovative AI applications with real-world impact. Feel free to use other data sources or additional functionalities as needed to build something you will be proud of.