wehub-resource-sync
113 lines
4.3 KiB
Python
113 lines
4.3 KiB
Python
import json
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from bfcl_eval.constants.type_mappings import GORILLA_TO_OPENAPI
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from bfcl_eval.model_handler.local_inference.base_oss_handler import OSSHandler
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from bfcl_eval.constants.enums import ModelStyle
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from bfcl_eval.model_handler.utils import convert_to_tool
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from overrides import override
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class GraniteFunctionCallingHandler(OSSHandler):
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def __init__(
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self,
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model_name,
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temperature,
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registry_name,
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is_fc_model,
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dtype="bfloat16",
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**kwargs,
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) -> None:
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super().__init__(model_name, temperature, registry_name, is_fc_model, **kwargs)
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@override
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def _format_prompt(self, messages, function):
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"""
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"chat_template": "{% set function_str = messages.get('functions_str', {}) %}\n{% set query = messages['query'] %}\n{% set sys_prompt = 'You are a helpful assistant with access to the following function calls. Your task is to produce a sequence of function calls necessary to generate response to the user utterance. Use the following function calls as required. ' %}\n{% set funcstr = function_str|join('\n') %}\n{{ 'SYSTEM: ' + sys_prompt + '\n<|function_call_library|>\n' + funcstr + '\n\nIf none of the functions are relevant or the given question lacks the parameters required by the function, please output \"<function_call> {\"name\": \"no_function\", \"arguments\": {}}\".\n\nUSER: ' + query}}\n{% if add_generation_prompt %}\n{{ 'ASSISTANT:' }}{% endif %}",
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"""
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prompt_str = (
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"SYSTEM: You are a helpful assistant with access to the following function calls. "
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"Your task is to produce a sequence of function calls necessary to generate response to the user utterance. "
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"Use the following function calls as required."
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"\n<|function_call_library|>\n{functions_str}\n"
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'If none of the functions are relevant or the given question lacks the parameters required by the function, please output "<function_call> {"name": "no_function", "arguments": {}}".\n\n'
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)
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function = convert_to_tool(
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function, GORILLA_TO_OPENAPI, model_style=ModelStyle.OSSMODEL
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)
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functions_str = "\n".join([json.dumps(func) for func in function])
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prompt_str = prompt_str.replace("{functions_str}", functions_str)
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for message in messages:
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prompt_str += f"{message['role'].upper()}:\n{message['content']}\n\n"
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prompt_str += "ASSISTANT: "
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return prompt_str
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@override
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def _pre_query_processing_prompting(self, test_entry: dict) -> dict:
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functions: list = test_entry["function"]
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# Granite use its own system prompt
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return {"message": [], "function": functions}
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@override
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def decode_ast(self, result, language, has_tool_call_tag):
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decoded_outputs = []
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result = [
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call.strip()
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for call in result.split("<function_call>")
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if len(call.strip()) > 0
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]
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for res in result:
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try:
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res = json.loads(res.strip())
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except:
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decoded_outputs.append(res)
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else:
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fnname = res.get("name", "").strip()
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args = res.get("arguments", {})
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if fnname == "no_function":
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decoded_outputs.append("No function is called")
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continue
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decoded_outputs.append({fnname: args})
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return decoded_outputs
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@override
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def decode_execute(self, result, has_tool_call_tag):
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decoded_outputs = []
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result = [
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call.strip()
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for call in result.split("<function_call>")
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if len(call.strip()) > 0
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]
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for res in result:
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try:
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res = json.loads(res.strip())
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except:
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decoded_outputs.append(res)
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else:
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fnname = res.get("name", "").strip()
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args = res.get("arguments", {})
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if fnname == "no_function":
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decoded_outputs.append("No function is called")
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continue
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# decoded_outputs.append({fnname: args})
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args_str = ",".join(
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[f"{argname}={repr(argval)}" for argname, argval in args.items()]
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)
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decoded_outputs.append(f"{fnname}({args_str})")
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return decoded_outputs
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