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bug fixes and updates

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This commit is contained in:
Krrish Dholakia
2023-08-03 16:05:46 -07:00
parent 102edcdcf1
commit ed8554699b
7 changed files with 42 additions and 23 deletions
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4
pr_agent/algo/__init__.py
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@ -7,4 +7,8 @@ MAX_TOKENS = {
'gpt-4': 8000,
'gpt-4-0613': 8000,
'gpt-4-32k': 32000,
'claude-instant-1': 100000,
'claude-2': 100000,
'command-nightly': 4096,
'replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1': 4096,
}

13
pr_agent/algo/ai_handler.py
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@ -3,6 +3,7 @@ import logging
import openai
from openai.error import APIError, RateLimitError, Timeout, TryAgain
from retry import retry
import litellm
from litellm import acompletion
from pr_agent.config_loader import get_settings
@ -22,6 +23,7 @@ class AiHandler:
"""
try:
openai.api_key = get_settings().openai.key
litellm.openai_key = get_settings().openai.key
if get_settings().get("OPENAI.ORG", None):
openai.organization = get_settings().openai.org
self.deployment_id = get_settings().get("OPENAI.DEPLOYMENT_ID", None)
@ -31,6 +33,9 @@ class AiHandler:
openai.api_version = get_settings().openai.api_version
if get_settings().get("OPENAI.API_BASE", None):
openai.api_base = get_settings().openai.api_base
litellm.api_base = get_settings().openai.api_base
if get_settings().get("LITE.KEY", None):
self.llm_api_key = get_settings().lite.key
except AttributeError as e:
raise ValueError("OpenAI key is required") from e
@ -65,6 +70,7 @@ class AiHandler:
{"role": "user", "content": user}
],
temperature=temperature,
api_key=self.llm_api_key
)
except (APIError, Timeout, TryAgain) as e:
logging.error("Error during OpenAI inference: ", e)
@ -75,8 +81,9 @@ class AiHandler:
except (Exception) as e:
logging.error("Unknown error during OpenAI inference: ", e)
raise TryAgain from e
if response is None or len(response.choices) == 0:
if response is None or len(response["choices"]) == 0:
raise TryAgain
resp = response.choices[0]['message']['content']
finish_reason = response.choices[0].finish_reason
resp = response["choices"][0]['message']['content']
finish_reason = response["choices"][0]["finish_reason"]
print(resp, finish_reason)
return resp, finish_reason

4
pr_agent/algo/pr_processing.py
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@ -1,5 +1,5 @@
from __future__ import annotations
import traceback
import logging
from typing import Callable, Tuple
@ -221,6 +221,6 @@ async def retry_with_fallback_models(f: Callable):
try:
return await f(model)
except Exception as e:
logging.warning(f"Failed to generate prediction with {model}: {e}")
logging.warning(f"Failed to generate prediction with {model}: {traceback.format_exc()}")
if i == len(all_models) - 1: # If it's the last iteration
raise # Re-raise the last exception

5
pr_agent/algo/token_handler.py
View File

@ -1,5 +1,5 @@
from jinja2 import Environment, StrictUndefined
from tiktoken import encoding_for_model
from tiktoken import encoding_for_model, get_encoding
from pr_agent.config_loader import get_settings
@ -27,7 +27,7 @@ class TokenHandler:
- system: The system string.
- user: The user string.
"""
self.encoder = encoding_for_model(get_settings().config.model)
self.encoder = encoding_for_model(get_settings().config.model) if "gpt" in get_settings().config.model else get_encoding("cl100k_base")
self.prompt_tokens = self._get_system_user_tokens(pr, self.encoder, vars, system, user)
def _get_system_user_tokens(self, pr, encoder, vars: dict, system, user):
@ -47,7 +47,6 @@ class TokenHandler:
environment = Environment(undefined=StrictUndefined)
system_prompt = environment.from_string(system).render(vars)
user_prompt = environment.from_string(user).render(vars)
system_prompt_tokens = len(encoder.encode(system_prompt))
user_prompt_tokens = len(encoder.encode(user_prompt))
return system_prompt_tokens + user_prompt_tokens

9
pr_agent/settings/.secrets_template.toml
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@ -7,17 +7,20 @@
# See README for details about GitHub App deployment.
[openai]
key = "<API_KEY>" # Acquire through https://platform.openai.com
org = "<ORGANIZATION>" # Optional, may be commented out.
key = "" # Acquire through https://platform.openai.com
#org = "<ORGANIZATION>" # Optional, may be commented out.
# Uncomment the following for Azure OpenAI
#api_type = "azure"
#api_version = '2023-05-15' # Check Azure documentation for the current API version
#api_base = "<API_BASE>" # The base URL for your Azure OpenAI resource. e.g. "https://<your resource name>.openai.azure.com"
#deployment_id = "<DEPLOYMENT_ID>" # The deployment name you chose when you deployed the engine
[lite]
key = "YOUR_LLM_API_KEY" # Optional, use this if you'd like to use Anthropic, Llama2 (Replicate), or Cohere models
[github]
# ---- Set the following only for deployment type == "user"
user_token = "<TOKEN>" # A GitHub personal access token with 'repo' scope.
user_token = "" # A GitHub personal access token with 'repo' scope.
deployment_type = "user" #set to user by default
# ---- Set the following only for deployment type == "app", see README for details.
private_key = """\

27
pr_agent/tools/pr_reviewer.py
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@ -160,12 +160,12 @@ class PRReviewer:
the feedback.
"""
review = self.prediction.strip()
print(f"review: {review}")
try:
data = json.loads(review)
except json.decoder.JSONDecodeError:
data = try_fix_json(review)
print(f"data: {data}")
# Move 'Security concerns' key to 'PR Analysis' section for better display
if 'PR Feedback' in data and 'Security concerns' in data['PR Feedback']:
val = data['PR Feedback']['Security concerns']
@ -173,14 +173,15 @@ class PRReviewer:
data['PR Analysis']['Security concerns'] = val
# Filter out code suggestions that can be submitted as inline comments
if get_settings().config.git_provider != 'bitbucket' and get_settings().pr_reviewer.inline_code_comments \
and 'Code suggestions' in data['PR Feedback']:
data['PR Feedback']['Code suggestions'] = [
d for d in data['PR Feedback']['Code suggestions']
if any(key not in d for key in ('relevant file', 'relevant line in file', 'suggestion content'))
]
if not data['PR Feedback']['Code suggestions']:
del data['PR Feedback']['Code suggestions']
if 'PR Feedback' in data:
if get_settings().config.git_provider != 'bitbucket' and get_settings().pr_reviewer.inline_code_comments \
and 'Code suggestions' in data['PR Feedback']:
data['PR Feedback']['Code suggestions'] = [
d for d in data['PR Feedback']['Code suggestions']
if any(key not in d for key in ('relevant file', 'relevant line in file', 'suggestion content'))
]
if not data['PR Feedback']['Code suggestions']:
del data['PR Feedback']['Code suggestions']
# Add incremental review section
if self.incremental.is_incremental:
@ -205,7 +206,11 @@ class PRReviewer:
# Log markdown response if verbosity level is high
if get_settings().config.verbosity_level >= 2:
logging.info(f"Markdown response:\n{markdown_text}")
if markdown_text == None or len(markdown_text) == 0:
markdown_text = review
print(f"markdown text: {markdown_text}")
return markdown_text
def _publish_inline_code_comments(self) -> None:

3
pyproject.toml
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@ -41,7 +41,8 @@ dependencies = [
"aiohttp~=3.8.4",
"atlassian-python-api==3.39.0",
"GitPython~=3.1.32",
"starlette-context==0.3.6"
"starlette-context==0.3.6",
"litellm==0.1.2291"
]
[project.urls]