Building an intelligent customer service bot requires three steps to automate tool integration:
- environmental preparation: Be sure to enable the API service when you start it
--enable-auto-tool-choicecap (a poem)--tool-call-parser seed_ossparameter, it is recommended to match theserved-model-nameDefine the service endpoint. - Tool Registration: inGitHub repository(used form a nominal expression)
tools/directory to add custom tools (e.g., order lookup API) that need to implement the standard__call__method and register it to the model configuration. - Dialogue Design: When a user asks a question, the model automatically selects the tool. For example, if a customer asks "My order 123 status", the system will:
- Automatically call OrderQueryTool(123)
- Get the results and generate a response in natural language
- pass (a bill or inspection etc)
temperature=0.7Control Answer Stability
Advanced Tips: For complex work orders, you can set up thethinking_budget=640and open a multi-tool chain call (first query → then analyze → finally recommend), the practice needs to pay attention to the settingsmax_tool_calls=3Preventing Dead Loops.
This answer comes from the articleSeed-OSS: Open Source Large Language Model for Long Context Reasoning and Versatile ApplicationsThe
May not be reproduced without permission:AI productivity tools " How to apply Seed-OSS's automated tool invocation feature in a customer service bot scenario?
