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https://github.com/aljazceru/dev-gpt.git
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🔎 feat: search fix web search
This commit is contained in:
Florian Hönicke
@@ -5,7 +5,8 @@ from dev_gpt.options.generate.chains.question_answering import is_question_true
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from dev_gpt.options.generate.chains.translation import translation
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from dev_gpt.options.generate.chains.user_confirmation_feedback_loop import user_feedback_loop
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from dev_gpt.options.generate.chains.get_user_input_if_needed import get_user_input_if_needed
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from dev_gpt.options.generate.parser import identity_parser
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from dev_gpt.options.generate.parser import identity_parser, json_parser
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from dev_gpt.options.generate.pm.task_tree_schema import TaskTree
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from dev_gpt.options.generate.prompt_factory import make_prompt_friendly
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from dev_gpt.options.generate.ui import get_random_employee
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@@ -35,9 +36,9 @@ Description of the microservice:
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def refine(self, microservice_description):
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microservice_description, test_description = self.refine_description(microservice_description)
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return microservice_description, test_description
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# sub_task_tree = self.construct_sub_task_tree(microservice_description)
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# sub_task_tree = construct_sub_task_tree(microservice_description)
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# return sub_task_tree
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return microservice_description, test_description
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def refine_description(self, microservice_description):
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context = {'microservice_description': microservice_description}
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@@ -128,44 +129,44 @@ Example:
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# microservice_description=microservice_description
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# )
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#
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# def construct_sub_task_tree(self, microservice_description):
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# """
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# takes a microservice description and recursively constructs a tree of sub-tasks that need to be done to implement the microservice
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# """
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# #
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# # nlp_fns = self.get_nlp_fns(
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# # microservice_description
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# # )
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#
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# sub_task_tree_dict = ask_gpt(
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# construct_sub_task_tree_prompt, json_parser,
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# microservice_description=microservice_description,
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# # nlp_fns=nlp_fns
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# )
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# reflections = ask_gpt(
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# sub_task_tree_reflections_prompt, identity_parser,
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# microservice_description=microservice_description,
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# # nlp_fns=nlp_fns,
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# sub_task_tree=sub_task_tree_dict,
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# )
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# solutions = ask_gpt(
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# sub_task_tree_solutions_prompt, identity_parser,
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# # nlp_fns=nlp_fns,
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# microservice_description=microservice_description, sub_task_tree=sub_task_tree_dict,
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# reflections=reflections,
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# )
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# sub_task_tree_updated = ask_gpt(
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# sub_task_tree_update_prompt,
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# json_parser,
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# microservice_description=microservice_description,
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# # nlp_fns=nlp_fns,
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# sub_task_tree=sub_task_tree_dict, solutions=solutions
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# )
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# # for task_dict in self.iterate_over_sub_tasks(sub_task_tree_updated):
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# # task_dict.update(self.get_additional_task_info(task_dict['task']))
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#
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# sub_task_tree = TaskTree.parse_obj(sub_task_tree_updated)
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# return sub_task_tree
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def construct_sub_task_tree(self, microservice_description):
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"""
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takes a microservice description and recursively constructs a tree of sub-tasks that need to be done to implement the microservice
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"""
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#
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# nlp_fns = self.get_nlp_fns(
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# microservice_description
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# )
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sub_task_tree_dict = ask_gpt(
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construct_sub_task_tree_prompt, json_parser,
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microservice_description=microservice_description,
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# nlp_fns=nlp_fns
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)
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reflections = ask_gpt(
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sub_task_tree_reflections_prompt, identity_parser,
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microservice_description=microservice_description,
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# nlp_fns=nlp_fns,
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sub_task_tree=sub_task_tree_dict,
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)
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solutions = ask_gpt(
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sub_task_tree_solutions_prompt, identity_parser,
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# nlp_fns=nlp_fns,
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microservice_description=microservice_description, sub_task_tree=sub_task_tree_dict,
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reflections=reflections,
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)
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sub_task_tree_updated = ask_gpt(
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sub_task_tree_update_prompt,
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json_parser,
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microservice_description=microservice_description,
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# nlp_fns=nlp_fns,
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sub_task_tree=sub_task_tree_dict, solutions=solutions
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)
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# for task_dict in self.iterate_over_sub_tasks(sub_task_tree_updated):
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# task_dict.update(self.get_additional_task_info(task_dict['task']))
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sub_task_tree = TaskTree.parse_obj(sub_task_tree_updated)
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return sub_task_tree
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# def get_additional_task_info(self, sub_task_description):
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# additional_info_dict = self.get_additional_infos(
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@@ -281,71 +282,71 @@ Example:
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# Note: You must ignore facts that are unknown.
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# Note: You must ignore facts that are unclear.'''
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# construct_sub_task_tree_prompt = client_description + '''
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# Recursively constructs a tree of functions that need to be implemented for the endpoint_function that retrieves a json string and returns a json string.
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# Example:
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# Input: "Input: list of integers, Output: Audio file of short story where each number is mentioned exactly once."
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# Output:
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# {{
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# "description": "Create an audio file containing a short story in which each integer from the provided list is seamlessly incorporated, ensuring that every integer is mentioned exactly once.",
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# "python_fn_signature": "def generate_integer_story_audio(numbers: List[int]) -> str:",
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# "sub_fns": [
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# {{
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# "description": "Generate sentence from integer.",
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# "python_fn_signature": "def generate_sentence_from_integer(number: int) -> int:",
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# "sub_fns": []
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# }},
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# {{
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# "description": "Convert the story into an audio file.",
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# "python_fn_signature": "def convert_story_to_audio(story: str) -> bytes:",
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# "sub_fns": []
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# }}
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# ]
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# }}
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#
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# Note: you must only output the json string - nothing else.
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# Note: you must pretty print the json string.'''
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construct_sub_task_tree_prompt = client_description + '''
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Recursively constructs a tree of functions that need to be implemented for the endpoint_function that retrieves a json string and returns a json string.
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Example:
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Input: "Input: list of integers, Output: Audio file of short story where each number is mentioned exactly once."
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Output:
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{{
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"description": "Create an audio file containing a short story in which each integer from the provided list is seamlessly incorporated, ensuring that every integer is mentioned exactly once.",
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"python_fn_signature": "def generate_integer_story_audio(numbers: List[int]) -> str:",
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"sub_fns": [
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{{
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"description": "Generate sentence from integer.",
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"python_fn_signature": "def generate_sentence_from_integer(number: int) -> int:",
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"sub_fns": []
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}},
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{{
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"description": "Convert the story into an audio file.",
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"python_fn_signature": "def convert_story_to_audio(story: str) -> bytes:",
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"sub_fns": []
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}}
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]
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}}
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# sub_task_tree_reflections_prompt = client_description + '''
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# Sub task tree:
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# ```
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# {sub_task_tree}
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# ```
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# Write down 3 arguments why the sub task tree might not perfectly represents the information mentioned in the microservice description. (5 words per argument)'''
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#
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# sub_task_tree_solutions_prompt = client_description + '''
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# Sub task tree:
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# ```
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# {sub_task_tree}
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# ```
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# Reflections:
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# ```
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# {reflections}
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# ```
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# For each constructive criticism, write a solution (5 words) that address the criticism.'''
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#
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# sub_task_tree_update_prompt = client_description + '''
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# Sub task tree:
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# ```
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# {sub_task_tree}
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# ```
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# Solutions:
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# ```
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# {solutions}
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# ```
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# Update the sub task tree by applying the solutions. (pretty print the json string)'''
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#
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# ask_questions_prompt = client_description + '''
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# Request json schema:
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# ```
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# {request_schema}
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# ```
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# Response json schema:
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# ```
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# {response_schema}
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# ```
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# Ask the user up to 5 unique detailed questions (5 words) about the microservice description that are not yet answered.
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# '''
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Note: you must only output the json string - nothing else.
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Note: you must pretty print the json string.'''
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sub_task_tree_reflections_prompt = client_description + '''
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Sub task tree:
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```
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{sub_task_tree}
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```
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Write down 3 arguments why the sub task tree might not perfectly represents the information mentioned in the microservice description. (5 words per argument)'''
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sub_task_tree_solutions_prompt = client_description + '''
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Sub task tree:
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```
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{sub_task_tree}
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```
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Reflections:
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```
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{reflections}
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```
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For each constructive criticism, write a solution (5 words) that address the criticism.'''
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sub_task_tree_update_prompt = client_description + '''
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Sub task tree:
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```
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{sub_task_tree}
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```
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Solutions:
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```
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{solutions}
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```
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Update the sub task tree by applying the solutions. (pretty print the json string)'''
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ask_questions_prompt = client_description + '''
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Request json schema:
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```
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{request_schema}
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```
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Response json schema:
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```
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{response_schema}
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```
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Ask the user up to 5 unique detailed questions (5 words) about the microservice description that are not yet answered.
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'''
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# answer_questions_prompt = client_description + '''
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# Request json schema:
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