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Add support for fallback models

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This commit is contained in:
Ori Kotek
2023-07-23 16:16:36 +03:00
parent e34f9d8d1c
commit 02a1d8dbfc
8 changed files with 75 additions and 52 deletions
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16
pr_agent/tools/pr_description.py
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@ -5,7 +5,7 @@ import logging
from jinja2 import Environment, StrictUndefined
from pr_agent.algo.ai_handler import AiHandler
from pr_agent.algo.pr_processing import get_pr_diff
from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
from pr_agent.algo.token_handler import TokenHandler
from pr_agent.config_loader import settings
from pr_agent.git_providers import get_git_provider
@ -37,10 +37,7 @@ class PRDescription:
logging.info('Generating a PR description...')
if settings.config.publish_output:
self.git_provider.publish_comment("Preparing pr description...", is_temporary=True)
logging.info('Getting PR diff...')
self.patches_diff = get_pr_diff(self.git_provider, self.token_handler)
logging.info('Getting AI prediction...')
self.prediction = await self._get_prediction()
await retry_with_fallback_models(self._prepare_prediction)
logging.info('Preparing answer...')
pr_title, pr_body, pr_types, markdown_text = self._prepare_pr_answer()
if settings.config.publish_output:
@ -53,7 +50,13 @@ class PRDescription:
self.git_provider.remove_initial_comment()
return ""
async def _get_prediction(self):
async def _prepare_prediction(self, model: str):
logging.info('Getting PR diff...')
self.patches_diff = get_pr_diff(self.git_provider, self.token_handler, model)
logging.info('Getting AI prediction...')
self.prediction = await self._get_prediction(model)
async def _get_prediction(self, model: str):
variables = copy.deepcopy(self.vars)
variables["diff"] = self.patches_diff # update diff
environment = Environment(undefined=StrictUndefined)
@ -62,7 +65,6 @@ class PRDescription:
if settings.config.verbosity_level >= 2:
logging.info(f"\nSystem prompt:\n{system_prompt}")
logging.info(f"\nUser prompt:\n{user_prompt}")
model = settings.config.model
response, finish_reason = await self.ai_handler.chat_completion(model=model, temperature=0.2,
system=system_prompt, user=user_prompt)
return response