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🧼 refactor: clean prompt

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This commit is contained in:
Florian Hönicke
2023-05-23 23:57:19 +02:00
parent 7414018285
commit 4953bc9c16
1 changed files with 5 additions and 11 deletions
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16
dev_gpt/options/generate/templates_user.py
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@@ -2,10 +2,10 @@ from langchain import PromptTemplate
from dev_gpt.constants import IMPLEMENTATION_FILE_NAME
general_guidelines_string = '''The code you write is production ready. Every file starts with comments describing what the code is doing before the first import. Comments can only be written within code blocks.
Then all imports are listed.
Start from top-level and then fully implement all methods.'''
general_guidelines_string = '''\
The code you write is production ready.
Every file starts with comments describing what the code is doing before the first import.
Comments can only be written within code blocks.'''
not_allowed_docker_string = '''Note that the Dockerfile only has access to the files: microservice.py, requirements.txt, config.yml, test_microservice.py.
@@ -90,7 +90,7 @@ Note that you must obey the double asterisk and triple backtick syntax from like
You must provide the complete {file_name} wrapped with the exact syntax shown above.'''
gpt_35_turbo_usage_string = """If you need to use gpt_3_5_turbo, then use it like shown in the following example:
gpt_35_turbo_usage_string = """Use the gpt_3_5_turbo like shown in the following example:
```
from .gpt_3_5_turbo import GPT_3_5_Turbo
@@ -135,7 +135,6 @@ outputs a json dictionary string (that can be parsed with the python function js
The function is called 'func' and has the following signature:
def func(input_json_dict_string: str) -> str:
The function must fulfill the following description: '{{microservice_description}}'.
It will be tested with the following scenario: '{{test_description}}'.
For the implementation use the following package(s): '{{packages}}'.
The code must start with the following imports:
@@ -146,11 +145,6 @@ import requests
Obey the following rules:
{not_allowed_function_string}
Your approach:
1. Identify the core challenge when implementing the function.
2. Think about solutions for these challenges.
3. Decide for one of the solutions.
4. Write the code for the function. Don't write code for the test.
{gpt_35_turbo_usage_string if is_using_gpt_3_5_turbo else ''}
{google_custom_search_usage_string if is_using_google_custom_search else ''}
{template_code_wrapping_string}'''