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feat(functions): relax mixedgrammars (#2365)
* feat(functions): relax mixedgrammars Extend even more the functionalities and when mixed mode is enabled, tolerate also both strings and JSON in the result - in this case we make sure that the JSON can be correctly parsed. This also updates the examples and the gallery model to configure the grammar. The changeset also breaks current function/grammar configuration as it reserves now a stanza in the YAML config. For example: ```yaml function: grammar: # This allows the grammar to also return messages mixed_mode: true # Suffix to add to the grammar # prefix: '<tool_call>\n' # Force parallel calls in the grammar # parallel_calls: true ``` Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor, add a way to disable mixed json and freestring Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fix linting issues Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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@ -4,7 +4,61 @@ f16: false
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parameters:
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model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
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stopwords:
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- "<|im_end|>"
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- "<dummy32000>"
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- "</tool_call>"
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- "<|eot_id|>"
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- "<|end_of_text|>"
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function:
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# disable injecting the "answer" tool
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disable_no_action: true
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grammar:
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# This allows the grammar to also return messages
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mixed_mode: true
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# Suffix to add to the grammar
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#prefix: '<tool_call>\n'
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# Force parallel calls in the grammar
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# parallel_calls: true
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return_name_in_function_response: true
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# Without grammar uncomment the lines below
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# Warning: this is relying only on the capability of the
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# LLM model to generate the correct function call.
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json_regex_match:
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- "(?s)<tool_call>(.*?)</tool_call>"
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- "(?s)<tool_call>(.*?)"
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replace_llm_results:
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# Drop the scratchpad content from responses
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- key: "(?s)<scratchpad>.*</scratchpad>"
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value: ""
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replace_function_results:
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# Replace everything that is not JSON array or object
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#
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- key: '(?s)^[^{\[]*'
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value: ""
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- key: '(?s)[^}\]]*$'
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value: ""
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- key: "'([^']*?)'"
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value: "_DQUOTE_${1}_DQUOTE_"
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- key: '\\"'
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value: "__TEMP_QUOTE__"
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- key: "\'"
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value: "'"
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- key: "_DQUOTE_"
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value: '"'
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- key: "__TEMP_QUOTE__"
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value: '"'
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# Drop the scratchpad content from responses
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- key: "(?s)<scratchpad>.*</scratchpad>"
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value: ""
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template:
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chat: |
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{{.Input -}}
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<|im_start|>assistant
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chat_message: |
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<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
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{{- if .FunctionCall }}
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@ -23,37 +77,25 @@ template:
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{{- else if eq .RoleName "tool" }}
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</tool_response>
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{{- end }}<|im_end|>
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# https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B-GGUF#prompt-format-for-function-calling
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function: |
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completion: |
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{{.Input}}
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function: |-
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<|im_start|>system
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You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
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You are a function calling AI model.
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Here are the available tools:
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<tools>
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{{range .Functions}}
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{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
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{{end}}
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</tools>
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Use the following pydantic model json schema for each tool call you will make:
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{'title': 'FunctionCall', 'type': 'object', 'properties': {'arguments': {'title': 'Arguments', 'type': 'object'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['arguments', 'name']}
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For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
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You should call the tools provided to you sequentially
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Please use <scratchpad> XML tags to record your reasoning and planning before you call the functions as follows:
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<scratchpad>
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{step-by-step reasoning and plan in bullet points}
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</scratchpad>
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For each function call return a json object with function name and arguments within <tool_call> XML tags as follows:
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<tool_call>
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{'arguments': <args-dict>, 'name': <function-name>}
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{"arguments": <args-dict>, "name": <function-name>}
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</tool_call><|im_end|>
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{{.Input -}}
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<|im_start|>assistant
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<tool_call>
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chat: |
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{{.Input -}}
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<|im_start|>assistant
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completion: |
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{{.Input}}
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context_size: 4096
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stopwords:
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- <|im_end|>
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- "\n</tool_call>"
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- <dummy32000>
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- "\n\n\n"
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usage: |
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curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
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"model": "gpt-4",
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"messages": [{"role": "user", "content": "How are you doing?", "temperature": 0.1}]
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}'
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