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added logging

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This commit is contained in:
Siddhesh Agarwal
2024-11-01 11:07:04 +05:30
parent caceba381d
commit 92c10fc41e
7 changed files with 62 additions and 4 deletions
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simplemind/logging.py
+28
View File
@@ -0,0 +1,28 @@
import time
from typing import Any, Callable
import logfire
from .settings import settings
def logger(func: Callable[..., Any]) -> Callable[..., Any]:
"""A @logger decorator that logs the function parameters, function returns, and exceptions raised if logging is enabled."""
is_logging_enabled = settings.logging.enabled
def wrapper(*args, **kwargs) -> Any:
if not is_logging_enabled:
return func(*args, **kwargs)
logfire.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}")
t1 = time.perf_counter()
try:
result = func(*args, **kwargs)
t2 = time.perf_counter()
logfire.info(f"{func.__name__} returned: {result} in {t2-t1} seconds")
return result
except Exception as e:
t2 = time.perf_counter()
logfire.error(f"Error in {func.__name__}: {e} in {t2-t1} seconds")
raise e
return wrapper
simplemind/providers/anthropic.py
+4
View File
@@ -5,6 +5,7 @@ import anthropic
import instructor
from pydantic import BaseModel
from ..logging import logger
from ..settings import settings
from ._base import BaseProvider
@@ -37,6 +38,7 @@ class Anthropic(BaseProvider):
"""A client patched with Instructor."""
return instructor.from_anthropic(self.client)
@logger
def send_conversation(self, conversation: "Conversation", **kwargs):
"""Send a conversation to the Anthropic API."""
from ..models import Message
@@ -63,6 +65,7 @@ class Anthropic(BaseProvider):
llm_provider=PROVIDER_NAME,
)
@logger
def structured_response(
self, response_model: Type[T], *, llm_model: str | None = None, **kwargs
) -> T:
@@ -82,6 +85,7 @@ class Anthropic(BaseProvider):
)
return response
@logger
def generate_text(self, prompt: str, *, llm_model: str, **kwargs):
messages = [
{"role": "user", "content": prompt},
simplemind/providers/gemini.py
+4
View File
@@ -8,6 +8,7 @@ import google.generativeai as genai
import instructor
from pydantic import BaseModel
from ..logging import logger
from ..settings import settings
from ._base import BaseProvider
@@ -38,6 +39,7 @@ class Gemini(BaseProvider):
"""A Gemini client patched with Instructor."""
return instructor.from_gemini(self.client)
@logger
def send_conversation(self, conversation: "Conversation") -> "Message":
"""Send a conversation to the Gemini API."""
from ..models import Message
@@ -64,6 +66,7 @@ class Gemini(BaseProvider):
llm_provider=PROVIDER_NAME,
)
@logger
def structured_response(self, prompt: str, response_model: Type[T], **kwargs) -> T:
"""Send a structured response to the Gemini API."""
llm_model = kwargs.pop("llm_model", self.model_name)
@@ -81,6 +84,7 @@ class Gemini(BaseProvider):
) from e
return response
@logger
def generate_text(self, prompt: str, **kwargs) -> str:
"""Generate text using the Gemini API."""
llm_model = kwargs.pop("llm_model", self.model_name)
simplemind/providers/groq.py
+4
View File
@@ -5,6 +5,7 @@ import groq
import instructor
from pydantic import BaseModel
from ..logging import logger
from ..settings import settings
from ._base import BaseProvider
@@ -36,6 +37,7 @@ class Groq(BaseProvider):
"""A client patched with Instructor."""
return instructor.from_groq(self.client)
@logger
def send_conversation(
self,
conversation: "Conversation",
@@ -66,6 +68,7 @@ class Groq(BaseProvider):
llm_provider=PROVIDER_NAME,
)
@logger
def structured_response(self, prompt: str, response_model: Type[T], **kwargs) -> T:
# Ensure messages are provided in kwargs
messages = [
@@ -80,6 +83,7 @@ class Groq(BaseProvider):
)
return response
@logger
def generate_text(
self,
prompt: str,
simplemind/providers/ollama.py
+4
View File
@@ -6,6 +6,7 @@ import ollama as ol
from openai import OpenAI
from pydantic import BaseModel
from ..logging import logger
from ..settings import settings
from ._base import BaseProvider
@@ -45,6 +46,7 @@ class Ollama(BaseProvider):
mode=instructor.Mode.JSON,
)
@logger
def send_conversation(self, conversation: "Conversation", **kwargs) -> "Message":
"""Send a conversation to the Ollama API."""
from ..models import Message
@@ -68,6 +70,7 @@ class Ollama(BaseProvider):
llm_provider=PROVIDER_NAME,
)
@logger
def structured_response(
self,
prompt: str,
@@ -89,6 +92,7 @@ class Ollama(BaseProvider):
)
return response
@logger
def generate_text(
self, prompt: str, *, llm_model: str | None = None, **kwargs
) -> str:
simplemind/providers/openai.py
+7 -3
View File
@@ -5,6 +5,7 @@ import instructor
import openai as oa
from pydantic import BaseModel
from ..logging import logger
from ..settings import settings
from ._base import BaseProvider
@@ -36,6 +37,7 @@ class OpenAI(BaseProvider):
"""A OpenAI client with Instructor."""
return instructor.from_openai(self.client)
@logger
def send_conversation(self, conversation: "Conversation", **kwargs):
"""Send a conversation to the OpenAI API."""
from ..models import Message
@@ -47,7 +49,7 @@ class OpenAI(BaseProvider):
response = self.client.chat.completions.create(
model=conversation.llm_model or DEFAULT_MODEL,
messages=messages,
**{**self.DEFAULT_KWARGS, **kwargs}
**{**self.DEFAULT_KWARGS, **kwargs},
)
# Get the response content from the OpenAI response
@@ -62,6 +64,7 @@ class OpenAI(BaseProvider):
llm_provider=PROVIDER_NAME,
)
@logger
def structured_response(
self,
prompt: str,
@@ -79,10 +82,11 @@ class OpenAI(BaseProvider):
messages=messages,
model=llm_model or self.DEFAULT_MODEL,
response_model=response_model,
**{**self.DEFAULT_KWARGS, **kwargs}
**{**self.DEFAULT_KWARGS, **kwargs},
)
return response
@logger
def generate_text(self, prompt: str, *, llm_model: str | None = None, **kwargs):
"""Generate text using the OpenAI API."""
messages = [
@@ -91,6 +95,6 @@ class OpenAI(BaseProvider):
response = self.client.chat.completions.create(
messages=messages,
model=llm_model or self.DEFAULT_MODEL,
**{**self.DEFAULT_KWARGS, **kwargs}
**{**self.DEFAULT_KWARGS, **kwargs},
)
return response.choices[0].message.content
simplemind/providers/xai.py
+11 -1
View File
@@ -1,8 +1,11 @@
from functools import cached_property
from typing import Type, TypeVar
import instructor
import openai as oa
from pydantic import BaseModel
from ..logging import logger
from ..settings import settings
from ._base import BaseProvider
@@ -12,6 +15,8 @@ BASE_URL = "https://api.x.ai/v1"
DEFAULT_MAX_TOKENS = 1000
DEFAULT_KWARGS = {"max_tokens": DEFAULT_MAX_TOKENS}
T = TypeVar("T", bound=BaseModel)
class XAI(BaseProvider):
NAME = PROVIDER_NAME
@@ -36,6 +41,7 @@ class XAI(BaseProvider):
"""A client patched with Instructor."""
return instructor.from_openai(self.client)
@logger
def send_conversation(self, conversation: "Conversation", **kwargs):
"""Send a conversation to the OpenAI API."""
from ..models import Message
@@ -62,9 +68,13 @@ class XAI(BaseProvider):
llm_provider=PROVIDER_NAME,
)
def structured_response(self, prompt: str, response_model, *, llm_model: str):
@logger
def structured_response(
self, prompt: str, response_model: Type[T], *, llm_model: str
) -> T:
raise NotImplementedError("XAI does not support structured responses")
@logger
def generate_text(self, prompt: str, *, llm_model: str, **kwargs):
messages = [
{"role": "user", "content": prompt},