Answer HR and IT policy questions on Telegram with OpenAI and Postgres PGVector
Embeddings OpenAI
HTTP RequestOpenAI
OpenAI Chat Model
Postgres Chat Memory
Postgres PGVector Store
Recursive Character Text Splitter
Telegram
Vector Store Question Answer ToolQuick overview This workflow builds a searchable HR policy knowledge base from a PDF and runs a Telegram helpdesk bot that answers employee questions from that content, handling both text messages and voice notes via OpenAI transcription and retrieval from a Postgres PGVector vector store. How it works Manually runs once to download an HR policy PDF over HTTP and extract its text. Splits the extracted policy text into chunks, generates OpenAI embeddings, and inserts the vectors into a Postgres PGVector store. Triggers on new Telegram messages sent to your bot. Routes incoming Telegram updates by type, sending text directly to the assistant, transcribing voice messages with OpenAI, or replying that other formats are unsupported. Uses an OpenAI chat model with Postgres-backed chat memory and a PGVector retrieval tool to answer questions grounded in the stored policy content. Sends the final answer back to the user in Telegram. Setup Add an OpenAI API key for embeddings, chat completions, and audio transcription. Set up a Postgres database with the PGVector extension enabled and add the Postgres credentials for both the vector store and chat memory.
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Embeddings OpenAIWHTTP RequestOpenAIOpenAI Chat ModelRelated workflows
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