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Merge branch 'main' into tr/pydantic

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This commit is contained in:
mrT23
2023-11-25 21:36:16 -08:00
committed by GitHub
parent 0df0542958 46d4d04e94
commit fdfd6247fb
36 changed files with 819 additions and 165 deletions
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6
pr_agent/algo/__init__.py
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@ -13,5 +13,9 @@ MAX_TOKENS = {
'claude-2': 100000,
'command-nightly': 4096,
'replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1': 4096,
'meta-llama/Llama-2-7b-chat-hf': 4096
'meta-llama/Llama-2-7b-chat-hf': 4096,
'vertex_ai/codechat-bison': 6144,
'vertex_ai/codechat-bison-32k': 32000,
'codechat-bison': 6144,
'codechat-bison-32k': 32000,
}

66
pr_agent/algo/ai_handler.py
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@ -23,39 +23,43 @@ class AiHandler:
Initializes the OpenAI API key and other settings from a configuration file.
Raises a ValueError if the OpenAI key is missing.
"""
try:
self.azure = False
if get_settings().get("OPENAI.KEY", None):
openai.api_key = get_settings().openai.key
litellm.openai_key = get_settings().openai.key
if get_settings().get("litellm.use_client"):
litellm_token = get_settings().get("litellm.LITELLM_TOKEN")
assert litellm_token, "LITELLM_TOKEN is required"
os.environ["LITELLM_TOKEN"] = litellm_token
litellm.use_client = True
self.azure = False
if get_settings().get("OPENAI.ORG", None):
litellm.organization = get_settings().openai.org
if get_settings().get("OPENAI.API_TYPE", None):
if get_settings().openai.api_type == "azure":
self.azure = True
litellm.azure_key = get_settings().openai.key
if get_settings().get("OPENAI.API_VERSION", None):
litellm.api_version = get_settings().openai.api_version
if get_settings().get("OPENAI.API_BASE", None):
litellm.api_base = get_settings().openai.api_base
if get_settings().get("ANTHROPIC.KEY", None):
litellm.anthropic_key = get_settings().anthropic.key
if get_settings().get("COHERE.KEY", None):
litellm.cohere_key = get_settings().cohere.key
if get_settings().get("REPLICATE.KEY", None):
litellm.replicate_key = get_settings().replicate.key
if get_settings().get("REPLICATE.KEY", None):
litellm.replicate_key = get_settings().replicate.key
if get_settings().get("HUGGINGFACE.KEY", None):
litellm.huggingface_key = get_settings().huggingface.key
if get_settings().get("HUGGINGFACE.API_BASE", None):
litellm.api_base = get_settings().huggingface.api_base
except AttributeError as e:
raise ValueError("OpenAI key is required") from e
if get_settings().get("litellm.use_client"):
litellm_token = get_settings().get("litellm.LITELLM_TOKEN")
assert litellm_token, "LITELLM_TOKEN is required"
os.environ["LITELLM_TOKEN"] = litellm_token
litellm.use_client = True
if get_settings().get("OPENAI.ORG", None):
litellm.organization = get_settings().openai.org
if get_settings().get("OPENAI.API_TYPE", None):
if get_settings().openai.api_type == "azure":
self.azure = True
litellm.azure_key = get_settings().openai.key
if get_settings().get("OPENAI.API_VERSION", None):
litellm.api_version = get_settings().openai.api_version
if get_settings().get("OPENAI.API_BASE", None):
litellm.api_base = get_settings().openai.api_base
if get_settings().get("ANTHROPIC.KEY", None):
litellm.anthropic_key = get_settings().anthropic.key
if get_settings().get("COHERE.KEY", None):
litellm.cohere_key = get_settings().cohere.key
if get_settings().get("REPLICATE.KEY", None):
litellm.replicate_key = get_settings().replicate.key
if get_settings().get("REPLICATE.KEY", None):
litellm.replicate_key = get_settings().replicate.key
if get_settings().get("HUGGINGFACE.KEY", None):
litellm.huggingface_key = get_settings().huggingface.key
if get_settings().get("HUGGINGFACE.API_BASE", None):
litellm.api_base = get_settings().huggingface.api_base
if get_settings().get("VERTEXAI.VERTEX_PROJECT", None):
litellm.vertex_project = get_settings().vertexai.vertex_project
litellm.vertex_location = get_settings().get(
"VERTEXAI.VERTEX_LOCATION", None
)
@property
def deployment_id(self):

7
pr_agent/algo/file_filter.py
View File

@ -11,7 +11,12 @@ def filter_ignored(files):
try:
# load regex patterns, and translate glob patterns to regex
patterns = get_settings().ignore.regex
patterns += [fnmatch.translate(glob) for glob in get_settings().ignore.glob]
if isinstance(patterns, str):
patterns = [patterns]
glob_setting = get_settings().ignore.glob
if isinstance(glob_setting, str): # --ignore.glob=[.*utils.py], --ignore.glob=.*utils.py
glob_setting = glob_setting.strip('[]').split(",")
patterns += [fnmatch.translate(glob) for glob in glob_setting]
# compile all valid patterns
compiled_patterns = []

2
pr_agent/algo/pr_processing.py
View File

@ -282,7 +282,7 @@ def find_line_number_of_relevant_line_in_file(diff_files: List[FilePatchInfo],
r"^@@ -(\d+)(?:,(\d+))? \+(\d+)(?:,(\d+))? @@[ ]?(.*)")
for file in diff_files:
if file.filename.strip() == relevant_file:
if file.filename and (file.filename.strip() == relevant_file):
patch = file.patch
patch_lines = patch.splitlines()

38
pr_agent/algo/utils.py
View File

@ -282,41 +282,43 @@ def _fix_key_value(key: str, value: str):
try:
value = yaml.safe_load(value)
except Exception as e:
get_logger().error(f"Failed to parse YAML for config override {key}={value}", exc_info=e)
get_logger().debug(f"Failed to parse YAML for config override {key}={value}", exc_info=e)
return key, value
def load_yaml(review_text: str) -> dict:
review_text = review_text.removeprefix('```yaml').rstrip('`')
def load_yaml(response_text: str) -> dict:
response_text = response_text.removeprefix('```yaml').rstrip('`')
try:
data = yaml.safe_load(review_text)
data = yaml.safe_load(response_text)
except Exception as e:
get_logger().error(f"Failed to parse AI prediction: {e}")
data = try_fix_yaml(review_text)
data = try_fix_yaml(response_text)
return data
def try_fix_yaml(review_text: str) -> dict:
review_text_lines = review_text.split('\n')
def try_fix_yaml(response_text: str) -> dict:
response_text_lines = response_text.split('\n')
keys = ['relevant line:', 'suggestion content:', 'relevant file:']
# first fallback - try to convert 'relevant line: ...' to relevant line: |-\n ...'
review_text_lines_copy = review_text_lines.copy()
for i in range(0, len(review_text_lines_copy)):
if 'relevant line:' in review_text_lines_copy[i] and not '|-' in review_text_lines_copy[i]:
review_text_lines_copy[i] = review_text_lines_copy[i].replace('relevant line: ',
'relevant line: |-\n ')
response_text_lines_copy = response_text_lines.copy()
for i in range(0, len(response_text_lines_copy)):
for key in keys:
if key in response_text_lines_copy[i] and not '|-' in response_text_lines_copy[i]:
response_text_lines_copy[i] = response_text_lines_copy[i].replace(f'{key}',
f'{key} |-\n ')
try:
data = yaml.load('\n'.join(review_text_lines_copy), Loader=yaml.SafeLoader)
get_logger().info(f"Successfully parsed AI prediction after adding |-\n to relevant line")
data = yaml.safe_load('\n'.join(response_text_lines_copy))
get_logger().info(f"Successfully parsed AI prediction after adding |-\n")
return data
except:
get_logger().debug(f"Failed to parse AI prediction after adding |-\n to relevant line")
get_logger().info(f"Failed to parse AI prediction after adding |-\n")
# second fallback - try to remove last lines
data = {}
for i in range(1, len(review_text_lines)):
review_text_lines_tmp = '\n'.join(review_text_lines[:-i])
for i in range(1, len(response_text_lines)):
response_text_lines_tmp = '\n'.join(response_text_lines[:-i])
try:
data = yaml.load(review_text_lines_tmp, Loader=yaml.SafeLoader)
data = yaml.safe_load(response_text_lines_tmp,)
get_logger().info(f"Successfully parsed AI prediction after removing {i} lines")
break
except: