The GPT-4 paper even has an example of this exact approach. See section 2.10:
The red teamer augmented GPT-4 with a set of tools:
• A literature search and embeddings tool (searches papers and embeds all text in vectorDB,
searches through DB with a vector embedding of the questions, summarizes context with LLM,
then uses LLM to take all context into an answer)
• A molecule search tool (performs a webquery to PubChem to get SMILES from plain text)
• A web search
• A purchase check tool (checks if a SMILES21 string is purchasable against a known commercial
catalog)
• A chemical synthesis planner (proposes synthetically feasible modification to a compound, giving
purchasable analogs)
The GPT-4 paper even has an example of this exact approach. See section 2.10:
The red teamer augmented GPT-4 with a set of tools:
• A literature search and embeddings tool (searches papers and embeds all text in vectorDB, searches through DB with a vector embedding of the questions, summarizes context with LLM, then uses LLM to take all context into an answer)
• A molecule search tool (performs a webquery to PubChem to get SMILES from plain text)
• A web search
• A purchase check tool (checks if a SMILES21 string is purchasable against a known commercial catalog)
• A chemical synthesis planner (proposes synthetically feasible modification to a compound, giving purchasable analogs)