wehub-resource-sync
171 lines
6.0 KiB
Python
171 lines
6.0 KiB
Python
# Copyright 2023 https://github.com/ShishirPatil/gorilla
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import json
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from tree_sitter import Language, Parser
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# Get all the subtrees given a root_node
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def get_all_sub_trees(root_node):
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node_stack = []
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sub_tree_sexp_list = []
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depth = 1
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text = root_node.text
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node_stack.append([root_node, depth])
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while len(node_stack) != 0:
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cur_node, cur_depth = node_stack.pop()
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if cur_node.child_count > 0:
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sub_tree_sexp_list.append([cur_node.sexp(), cur_depth, cur_node, cur_node.children[0].text])
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else:
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sub_tree_sexp_list.append([cur_node.sexp(), cur_depth, cur_node, None])
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for child_node in cur_node.children:
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if len(child_node.children) != 0:
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depth = cur_depth + 1
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node_stack.append([child_node, depth])
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return sub_tree_sexp_list
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# Parse the program into AST trees
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def ast_parse(candidate, lang='python'):
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LANGUAGE = Language('codebleu/parser/my-languages.so', lang)
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parser = Parser()
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parser.set_language(LANGUAGE)
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candidate_tree = parser.parse(bytes(candidate,'utf8')).root_node
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return candidate_tree
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# Get all the arguments in the ast tree
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def get_args(node):
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if node.child_count == 0:
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return []
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args_list = []
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for child in node.children[0].children[0].children[1].children:
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if 'model=' in child.text.decode() or 'model =' in child.text.decode():
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args_list.append(child.children[2].text)
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elif child.text.decode() != "(" and child.text.decode() != ")" and child.text.decode() != ",":
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args_list.append(child.text)
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return args_list
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# Check if there is an api match
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def ast_check(candidate_subtree_list, base_tree_list):
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for idx, base_tree in enumerate(base_tree_list):
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if base_tree.children[0].children[0].child_count == 0:
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continue
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api_name = base_tree.children[0].children[0].children[0].text
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for candidate_tree in candidate_subtree_list:
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if candidate_tree[3] == api_name:
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break
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# Now we have a sub-tree
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candidate_tree = candidate_tree[2]
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args_list = get_args(base_tree)
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if len(args_list) == 0:
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continue
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ast_match = True
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for arg in args_list:
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if arg.decode().lstrip("'").rstrip("'") not in candidate_tree.text.decode():
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ast_match = False
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break
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if ast_match:
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return idx
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return -1
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# Parse the dataset
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def parse_dataset(args):
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# Read the api datasest
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api_database = []
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with open(args.api_dataset, 'r') as f:
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for line in f:
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api_database.append(json.loads(line))
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# Read the question answer pair datasest
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qa_pairs = []
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with open(args.apibench, 'r') as f:
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for line in f:
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qa_pairs.append(json.loads(line)["api_data"])
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# Read the language model response datasest
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llm_responses = []
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with open(args.llm_responses, 'r') as f:
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for line in f:
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llm_responses.append(json.loads(line))
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# Parse all apis to ast trees
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ast_database = []
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for data in api_database:
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ast_tree = ast_parse(data['api_call'])
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ast_database.append(ast_tree)
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return api_database, qa_pairs, llm_responses, ast_database
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def main(args):
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# Read datsets
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api_database, qa_pairs, llm_responses, ast_database = parse_dataset(args)
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# Check correctness
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total_correct = 0
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total_hallucination = 0
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for idx, response in enumerate(llm_responses):
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try:
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output = response['text']
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except:
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print('Error: cannot parse line ', idx)
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continue
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# Index the "api_call" domain
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output = output.split("api_call")
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if len(output) == 1:
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# print('Error: line ', idx, ' is not the right format')
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# continue
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api_call = output[0]
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else:
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# Parse the output
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output = output[1].split("api_provider")[0]
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if ":" not in output:
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start = 0
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else:
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start = output.index(":")
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if ")" not in output:
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end = -2
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else:
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end = output.rindex(")")
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api_call = output[start+2:end+1]
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# Parse the api_call into AST tree
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ast_tree = ast_parse(api_call)
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# Search for a subtree
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ast_subtree_list = get_all_sub_trees(ast_tree)
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# Check which ast tree is matching
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database_index = ast_check(ast_subtree_list, ast_database)
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# We cannot index this ast in our database
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if database_index == -1:
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total_hallucination += 1
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continue
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# We index our reference api_call
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ref_api_call = api_database[database_index]
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# Check for functionality
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if ref_api_call['domain'] == qa_pairs[response['question_id'] - 1]['domain']:
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total_correct += 1
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else:
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pass
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print('Final Functionality accuracy: ', total_correct / len(llm_responses))
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print('Final hallucination: ', total_hallucination/len(llm_responses))
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--api_dataset", type=str, default=None, help="path to your api dataset")
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parser.add_argument("--apibench", type=str, default=None, help="path to your apibench dataset including the question and answer pairs")
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parser.add_argument("--llm_responses", type=str, default=None, help="path to the language model responses")
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args = parser.parse_args()
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main(args) |