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Botpress: Funktionen, Einsatzbereiche und Quellen

Most AI platforms pass instructions to a model and call it an agent. The Botpress Engine is the infrastructure we built to do something fundamentally different.

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Über dieses Tool

Most AI platforms pass instructions to a model and call it an agent. The Botpress Engine is the infrastructure we built to do something fundamentally different. Hauptfunktionen: But that doesn’t mean they all provide the same quality of AI to their customers, 9k stars on GitHub LLMzframeworkReplaces tool-calling with direct code execution for every agent action, ZUIlibraryA schema library that tells the LLM exactly what to expect from every tool, ZAIlearning loopLearns from human feedback to improve agent accuracy over time, Why? Because LLMs are way better at writing code than tool-calling, ‍So instead of tool-calling, on the LLMz Framework, your plain langauge instructions are turned into code, ZUI LibraryExact outputs, not best guessesYour AI agents use tools to help your customers — like using a CRM to fetch a customer record, When a request involves multiple tools (like fetching a customer record and then checking an order status), LLMs sometimes guess at what the tool will return.

Anwendungsfälle
  • But that doesn’t mean they all provide the same quality of AI to their customers
  • 9k stars on GitHub LLMzframeworkReplaces tool-calling with direct code execution for every agent action
  • ZUIlibraryA schema library that tells the LLM exactly what to expect from every tool
  • ZAIlearning loopLearns from human feedback to improve agent accuracy over time
  • Why? Because LLMs are way better at writing code than tool-calling
  • ‍So instead of tool-calling, on the LLMz Framework, your plain langauge instructions are turned into code
  • ZUI LibraryExact outputs, not best guessesYour AI agents use tools to help your customers — like using a CRM to fetch a customer record
  • When a request involves multiple tools (like fetching a customer record and then checking an order status), LLMs sometimes guess at what the tool will return

Funktionen & Anwendungsfälle

But that doesn’t mean they all provide the same quality of AI to their customers9k stars on GitHub LLMzframeworkReplaces tool-calling with direct code execution for every agent actionZUIlibraryA schema library that tells the LLM exactly what to expect from every toolZAIlearning loopLearns from human feedback to improve agent accuracy over timeWhy? Because LLMs are way better at writing code than tool-calling‍So instead of tool-calling, on the LLMz Framework, your plain langauge instructions are turned into codeZUI LibraryExact outputs, not best guessesYour AI agents use tools to help your customers — like using a CRM to fetch a customer recordWhen a request involves multiple tools (like fetching a customer record and then checking an order status), LLMs sometimes guess at what the tool will return

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