Telegram PDF Processing and Chat System

This workflow is ideal for:

• Developers looking to integrate Telegram with AI capabilities.
• Data Scientists who need to process and analyze documents sent via Telegram.
• Businesses seeking to automate document handling and retrieval processes.
• Educators who want to create interactive chatbots for student engagement.
• Researchers needing a streamlined way to interact with a database through chat.

This workflow addresses the challenge of efficiently managing and retrieving document-based information sent through Telegram. It automates the process of:

• Receiving documents from users.
• Converting them into a usable format.
• Storing the data in a vector database for quick retrieval.
• Responding to user queries based on the stored data, thereby enhancing the interaction experience and ensuring accurate information delivery.

1. Trigger: The workflow begins with a Telegram Trigger that listens for incoming messages.
2. Document Check: It checks if the incoming message contains a document.
3. File Retrieval: If a document is detected, it retrieves the file using Telegram get File.
4. File Processing: The file is processed to ensure it is in PDF format using the Change to application/pdf node.
5. Data Loading: The processed document is then loaded into a Pinecone vector store for storage.
6. Embedding Generation: The document is embedded using OpenAI to facilitate efficient querying.
7. Query Handling: When users send queries, the system retrieves relevant information from the vector store using Vector Store Retriever.
8. Response Generation: The information is processed using a language model to generate a coherent response.
9. Response Delivery: The response is sent back to the user via Telegram Response.
10. Completion Notification: Users are notified about the successful storage of their documents with the total pages saved.