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Docs in this repo say that when using custom tool calling with JSON one should use Environment: ipython and expect <|python_tag|>{ "type": "function", "name": ...
Docs on the website say you should not use Environment: ipython and expect just plain text, without "type":"function" (ie. just {"name": "...", "parameters": ...})
Unconstrained llama 3.1 70B, with Environment: ipython outputs according to the repo docs. However, 3.3 70B outputs something like <|python_tag|>get_weather(location=...).
I'm trying to implement tool calling with OpenAI-compatible interface and need to know how to prompt the model and what to expect in answer. Note that I have a fancy constraint engine so I can actually force the model to output JSON (with the right schema) after <|python_tag|>, but I would rather avoid going off-distribution.
This is relevant for llama models hosted in Azure.
Docs in this repo say that when using custom tool calling with JSON one should use
Environment: ipython
and expect<|python_tag|>{ "type": "function", "name": ...
Docs on the website say you should not use
Environment: ipython
and expect just plain text, without"type":"function"
(ie. just{"name": "...", "parameters": ...}
)Unconstrained llama 3.1 70B, with
Environment: ipython
outputs according to the repo docs. However, 3.3 70B outputs something like<|python_tag|>get_weather(location=...)
.I'm trying to implement tool calling with OpenAI-compatible interface and need to know how to prompt the model and what to expect in answer. Note that I have a fancy constraint engine so I can actually force the model to output JSON (with the right schema) after
<|python_tag|>
, but I would rather avoid going off-distribution.This is relevant for llama models hosted in Azure.
cc @datdo-msft @tot0
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