[Frontend][Feature] Add jamba tool parser (#9154)
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@@ -157,7 +157,7 @@ vLLM will use guided decoding to ensure the response matches the tool parameter
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To enable this feature, you should set the following flags:
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* `--enable-auto-tool-choice` -- **mandatory** Auto tool choice. tells vLLM that you want to enable the model to generate its own tool calls when it
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deems appropriate.
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* `--tool-call-parser` -- select the tool parser to use - currently either `hermes` or `mistral` or `llama3_json` or `internlm`. Additional tool parsers
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* `--tool-call-parser` -- select the tool parser to use (listed below). Additional tool parsers
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will continue to be added in the future, and also can register your own tool parsers in the `--tool-parser-plugin`.
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* `--tool-parser-plugin` -- **optional** tool parser plugin used to register user defined tool parsers into vllm, the registered tool parser name can be specified in `--tool-call-parser`.
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* `--chat-template` -- **optional** for auto tool choice. the path to the chat template which handles `tool`-role messages and `assistant`-role messages
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@@ -168,7 +168,7 @@ from HuggingFace; and you can find an example of this in a `tokenizer_config.jso
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If your favorite tool-calling model is not supported, please feel free to contribute a parser & tool use chat template!
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#### Hermes Models
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#### Hermes Models (`hermes`)
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All Nous Research Hermes-series models newer than Hermes 2 Pro should be supported.
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* `NousResearch/Hermes-2-Pro-*`
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* `NousResearch/Hermes-2-Theta-*`
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@@ -180,7 +180,7 @@ step in their creation_.
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Flags: `--tool-call-parser hermes`
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#### Mistral Models
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#### Mistral Models (`mistral`)
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Supported models:
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* `mistralai/Mistral-7B-Instruct-v0.3` (confirmed)
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* Additional mistral function-calling models are compatible as well.
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@@ -199,7 +199,7 @@ when tools are provided, that results in much better reliability when working wi
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Recommended flags: `--tool-call-parser mistral --chat-template examples/tool_chat_template_mistral_parallel.jinja`
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#### Llama Models
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#### Llama Models (`llama3_json`)
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Supported models:
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* `meta-llama/Meta-Llama-3.1-8B-Instruct`
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* `meta-llama/Meta-Llama-3.1-70B-Instruct`
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@@ -219,16 +219,24 @@ it works better with vLLM.
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Recommended flags: `--tool-call-parser llama3_json --chat-template examples/tool_chat_template_llama3_json.jinja`
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#### Internlm Models
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#### InternLM Models (`internlm`)
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Supported models:
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* `internlm/internlm2_5-7b-chat` (confirmed)
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* Additional internlm2.5 function-calling models are compatible as well
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Known issues:
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* Although this implementation also supports Internlm2, the tool call results are not stable when testing with the `internlm/internlm2-chat-7b` model.
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* Although this implementation also supports InternLM2, the tool call results are not stable when testing with the `internlm/internlm2-chat-7b` model.
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Recommended flags: `--tool-call-parser internlm --chat-template examples/tool_chat_template_internlm2_tool.jinja`
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#### Jamba Models (`jamba`)
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AI21's Jamba-1.5 models are supported.
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* `ai21labs/AI21-Jamba-1.5-Mini`
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* `ai21labs/AI21-Jamba-1.5-Large`
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Flags: `--tool-call-parser jamba`
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### How to write a tool parser plugin
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