AI research assistant

✅ VBT now supports function calling across all LLMs, allowing you to use the MCP server and define custom functions that the model can invoke, and all of this without any additional setup! This feature is particularly useful for complex queries, agentic workflows, and interactive applications where you want the model to perform specific tasks or calculations on your behalf.

env["OPENAI_API_KEY"] = "<YOUR_OPENAI_API_KEY>"

vbt.interact(  
    "How to backtest a weekly rebalancing strategy with vbt.PF.from_orders?",
    tool_display_format="compact",  
    formatter="html",
)

✅ VBT now supports reasoning steps across all LLMs, allowing you to see how the model arrived at its conclusion. This is particularly useful for complex queries that require multiple steps to answer.

env["GITHUB_TOKEN"] = "<YOUR_GITHUB_TOKEN>"
env["OPENAI_API_KEY"] = "<YOUR_OPENAI_API_KEY>"

vbt.chat(
    "How to backtest a weekly rebalancing strategy with vbt.PF.from_orders?",
    reasoning=dict(effort="low", summary="auto"),  
    formatter="html"
)

✅ Similar to SearchVBT, ChatVBT takes search results and forwards them to an LLM for completion. This allows you to interact seamlessly with the entire VBT knowledge base, receiving detailed and context-aware responses.

env["GITHUB_TOKEN"] = "<YOUR_GITHUB_TOKEN>"
env["OPENAI_API_KEY"] = "<YOUR_OPENAI_API_KEY>"

vbt.chat("How to rebalance weekly?", formatter="html")

✅ Each VBT class offers methods to explore its features, including its API, associated documentation, Discord messages, and code examples. You can even interact with it directly via an LLM!

env["GITHUB_TOKEN"] = "<YOUR_GITHUB_TOKEN>"
env["OPENAI_API_KEY"] = "<YOUR_API_KEY>"

vbt.PortfolioOptimizer.find_assets().get("link")

['https://members.vectorbt.pro/api/portfolio/pfopt/base/#vectorbtpro.portfolio.pfopt.base',
 'https://members.vectorbt.pro/api/generic/analyzable/#vectorbtpro.generic.analyzable.Analyzable',
 'https://members.vectorbt.pro/api/base/wrapping/#vectorbtpro.base.wrapping.Wrapping',
 ...
 'https://members.vectorbt.pro/features/optimization/portfolio-optimization/#riskfolio-lib',
 'https://members.vectorbt.pro/features/optimization/portfolio-optimization/#portfolio-optimization',
 'https://members.vectorbt.pro/features/optimization/portfolio-optimization/#pyportfolioopt',
 ...
 'https://discord.com/channels/x/918629995415502888/1064943203071045753',
 'https://discord.com/channels/x/918629995415502888/1067718833646874634',
 'https://discord.com/channels/x/918629995415502888/1067718855734075403',
 ...]

vbt.PortfolioOptimizer.chat("How to rebalance weekly?", formatter="html")