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🛺 fix: auto refinement parsing

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This commit is contained in:
Florian Hönicke
2023-05-24 17:50:31 +02:00
parent 9086c4292d
commit 3e62a999b6
5 changed files with 27 additions and 22 deletions
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15
dev_gpt/options/generate/chains/auto_refine_description.py
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@@ -1,7 +1,7 @@
import json
from dev_gpt.apis.gpt import ask_gpt
from dev_gpt.options.generate.parser import identity_parser
from dev_gpt.options.generate.parser import identity_parser, optional_tripple_back_tick_parser
from dev_gpt.options.generate.prompt_factory import context_to_string
from dev_gpt.options.generate.tools.tools import get_available_tools
@@ -14,12 +14,12 @@ def auto_refine_description(context):
)
context['request_schema'] = ask_gpt(
generate_request_schema_prompt,
identity_parser,
optional_tripple_back_tick_parser,
context_string=context_to_string(context)
)
context['response_schema'] = ask_gpt(
generate_output_schema_prompt,
identity_parser,
optional_tripple_back_tick_parser,
context_string=context_to_string(context)
)
context['microservice_description'] = ask_gpt(
@@ -36,12 +36,13 @@ def auto_refine_description(context):
better_description_prompt = f'''{{context_string}}
Update the description of the Microservice to make it more precise without adding or removing information.
Note: the output must be a list of tasks the Microservice has to perform.
Note: you can uses two tools if necessary:
Note: you can uses the following tools if necessary:
{get_available_tools()}
Example for the description: "return an image representing the current weather for a given location."
Example for the description: "return an image representing the current weather for a given location." \
when the tools gpt-3.5-turbo and google-search are available:
1. get the current weather information from the https://openweathermap.org/ API
2. generate a Google search query to find the image matching the weather information and the location by using gpt-3.5-turbo
3. find the image by using the Google search API
2. generate a Google search query to find the image matching the weather information and the location by using gpt-3.5-turbo (a)
3. find the image by using the Google search API (b)
4. return the image as a base64 encoded string'''
generate_request_schema_prompt = '''{context_string}