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Address PR review feedback: move constants to class level, add error handling, enhance logging

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Co-Authored-By: Joe Moura <joao@crewai.com>
This commit is contained in:
Devin AI
2025-05-10 11:00:51 +00:00
parent ee308ed322
commit 5b03d0e0db
1 changed files with 29 additions and 10 deletions
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39
src/crewai/llm.py
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@@ -246,6 +246,9 @@ class AccumulatedToolArgs(BaseModel):
class LLM(BaseLLM): class LLM(BaseLLM):
ANTHROPIC_PREFIXES = ("anthropic/", "claude-", "claude/")
GEMINI_IDENTIFIERS = ("gemini", "gemma-")
def __init__( def __init__(
self, self,
model: str, model: str,
@@ -319,8 +322,9 @@ class LLM(BaseLLM):
Returns: Returns:
bool: True if the model is from Anthropic, False otherwise. bool: True if the model is from Anthropic, False otherwise.
""" """
ANTHROPIC_PREFIXES = ("anthropic/", "claude-", "claude/") if not isinstance(model, str):
return any(prefix in model.lower() for prefix in ANTHROPIC_PREFIXES) return False
return any(prefix in model.lower() for prefix in self.ANTHROPIC_PREFIXES)
def _is_gemini_model(self, model: str) -> bool: def _is_gemini_model(self, model: str) -> bool:
"""Determine if the model is from Google Gemini provider. """Determine if the model is from Google Gemini provider.
@@ -331,8 +335,9 @@ class LLM(BaseLLM):
Returns: Returns:
bool: True if the model is from Gemini, False otherwise. bool: True if the model is from Gemini, False otherwise.
""" """
GEMINI_IDENTIFIERS = ("gemini", "gemma-") if not isinstance(model, str):
return any(identifier in model.lower() for identifier in GEMINI_IDENTIFIERS) return False
return any(identifier in model.lower() for identifier in self.GEMINI_IDENTIFIERS)
def _normalize_gemini_model(self, model: str) -> str: def _normalize_gemini_model(self, model: str) -> str:
"""Normalize Gemini model name to the format expected by LiteLLM. """Normalize Gemini model name to the format expected by LiteLLM.
@@ -345,7 +350,16 @@ class LLM(BaseLLM):
Returns: Returns:
str: Normalized model name. str: Normalized model name.
Raises:
ValueError: If model is not a string or is empty.
""" """
if not isinstance(model, str):
raise ValueError(f"Model must be a string, got {type(model)}")
if not model.strip():
raise ValueError("Model name cannot be empty")
if model.startswith("gemini/"): if model.startswith("gemini/"):
return model return model
@@ -381,12 +395,17 @@ class LLM(BaseLLM):
model = self.model model = self.model
if self._is_gemini_model(model): if self._is_gemini_model(model):
model = self._normalize_gemini_model(model) try:
model = self._normalize_gemini_model(model)
# --- 2.1) Map GOOGLE_API_KEY to GEMINI_API_KEY if needed logging.info(f"Normalized Gemini model name from '{self.model}' to '{model}'")
if not os.environ.get("GEMINI_API_KEY") and os.environ.get("GOOGLE_API_KEY"):
os.environ["GEMINI_API_KEY"] = os.environ["GOOGLE_API_KEY"] # --- 2.1) Map GOOGLE_API_KEY to GEMINI_API_KEY if needed
logging.info("Mapped GOOGLE_API_KEY to GEMINI_API_KEY for Gemini model") if not os.environ.get("GEMINI_API_KEY") and os.environ.get("GOOGLE_API_KEY"):
os.environ["GEMINI_API_KEY"] = os.environ["GOOGLE_API_KEY"]
logging.info("Mapped GOOGLE_API_KEY to GEMINI_API_KEY for Gemini model")
except ValueError as e:
logging.error(f"Error normalizing Gemini model: {str(e)}")
model = self.model
# --- 3) Prepare the parameters for the completion call # --- 3) Prepare the parameters for the completion call
params = { params = {