mellea.formatters.granite.granite3.granite32.input
Input and output processing for the Granite 3.2 family of models.
Classes
CLASS Granite32InputProcessor
Input processor for version 3.2 of the main Granite models, all sizes.
This input processor is based on the Jinja template that was used during supervised fine tuning of these models. This template is as follows:
{{%- if messages[0]['role'] == 'system' %}}
{{%- set system_message = messages[0]['content'] %}}
{{%- set loop_messages = messages[1:] %}}
{{%- else %}}
{{%- set system_message = \"Knowledge Cutoff Date: April 2024.\nToday's Date: \"
+ strftime_now('%B %d, %Y') + \".\nYou are Granite, developed by IBM.\" %}}
{{%- if tools and documents %}}
{{%- set system_message = system_message + \" You are a helpful AI
assistant with access to the following tools.
When a tool is required to answer the user's query, respond with
<|tool_call|> followed by a JSON list of tools used. If a tool does
not exist in the provided list of tools, notify the user that you do
not have the ability to fulfill the request.\n\nWrite the response to
the user's input by strictly aligning with the facts in the provided
documents. If the information needed to answer the question is not
available in the documents, inform the user that the question cannot
be answered based on the available data.\" %}}
{{%- elif tools %}}
{{%- set system_message = system_message + \" You are a helpful AI
assistant with access to the following tools. When a tool is required to
answer the user's query, respond with <|tool_call|> followed by a JSON
list of tools used. If a tool does not exist in the provided list of
tools, notify the user that you do not have the ability to fulfill the
request.\" %}}
{{%- elif documents %}}
{{%- set system_message = system_message + \" Write the response to the
user's input by strictly aligning with the facts in the provided
documents. If the information needed to answer the question is not
available in the documents, inform the user that the question cannot be
answered based on the available data.\" %}}
{{%- elif thinking %}}
{{%- set system_message = system_message + \" You are a helpful AI
assistant.\nRespond to every user query in a comprehensive and detailed
way. You can write down your thoughts and reasoning process before
responding. In the thought process, engage in a comprehensive cycle of
analysis, summarization, exploration, reassessment, reflection,
backtracing, and iteration to develop well-considered thinking process.
In the response section, based on various attempts, explorations, and
reflections from the thoughts section, systematically present the final
solution that you deem correct. The response should summarize the
thought process. Write your thoughts after 'Here is my thought process:'
and write your response after 'Here is my response:' for each user
query.\" %}}
{{%- else %}}
{{%- set system_message = system_message + \" You are a helpful AI
assistant.\" %}}
{{%- endif %}}
{{%- if 'citations' in controls and documents %}}
{{%- set system_message = system_message + '\n\nIn your response, use the
symbols <co> and </co> to indicate when a fact comes from a document in the
search result, e.g <co>0</co> for a fact from document 0. Afterwards, list
all the citations with their corresponding documents in an ordered list.' %}}
{{%- endif %}}
{{%- if 'hallucinations' in controls and documents %}}
{{%- set system_message = system_message + '\n\nFinally, after the response
is written, include a numbered list of sentences from the response that are
potentially hallucinated and not based in the documents.' %}}
{{%- endif %}}
{{%- set loop_messages = messages %}}
{{%- endif %}}
{{{{- '<|start_of_role|>system<|end_of_role|>' + system_message +
'<|end_of_text|>\n' }}}}
{{%- if tools %}}
{{{{- '<|start_of_role|>tools<|end_of_role|>' }}}}
{{{{- tools | tojson(indent=4) }}}}
{{{{- '<|end_of_text|>\n' }}}}
{{%- endif %}}
{{%- if documents %}}
{{{{- '<|start_of_role|>documents<|end_of_role|>' }}}}
{{%- for document in documents %}}
{{{{- 'Document ' + loop.index0 | string + '\n' }}}}
{{{{- document['text'] }}}}
{{%- if not loop.last %}}
{{{{- '\n\n'}}}}
{{%- endif%}}
{{%- endfor %}}
{{{{- '<|end_of_text|>\n' }}}}
{{%- endif %}}
{{%- for message in loop_messages %}}
{{{{- '<|start_of_role|>' + message['role'] + '<|end_of_role|>' +
message['content'] + '<|end_of_text|>\n' }}}}
{{%- if loop.last and add_generation_prompt %}}
{{{{- '<|start_of_role|>assistant' }}}}
{{%- if controls %}}
{{{{- ' ' + controls | tojson()}}}}
{{%- endif %}}
{{{{- '<|end_of_role|>' }}}}
{{%- endif %}}
{{%- endfor %}}
Methods:
FUNC sanitize
sanitize(cls, chat_completion: Granite3ChatCompletion, parts: list[str] | str = 'all') -> Granite3ChatCompletion
Sanitize the chat completion by removing Granite 3.2 special tokens.
Args:
chat_completion: The chat completion request to sanitize.parts: Which parts of the chat completion to sanitize; defaults to"all".
Returns:
- The sanitized chat completion with all Granite 3.2 special tokens
- removed from the specified parts.
FUNC transform
transform(self, chat_completion: ChatCompletion, add_generation_prompt: bool = True) -> str
Transform the chat completion request into a Granite 3.2 prompt string.
Args:
chat_completion: The structured chat completion request to convert into a tokenizer-ready prompt string.add_generation_prompt: WhenTrue, appends the assistant role header to the end of the prompt to trigger generation. Defaults toTrue.
Returns:
- The prompt string formatted for the Granite 3.2 model tokenizer.
Raises:
ValueError: If conflicting options are specified, such as enablingthinkingmode together with documents, tools, or a custom system message; or enablingcitationsorhallucinationswith a custom system message.