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f3bdba1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 | from langfuse import get_client, Langfuse, propagate_attributes
from langfuse.langchain import CallbackHandler
import os
from config.constant import LangfuseConstants
from pydantic import BaseModel
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import AzureChatOpenAI
from tenacity import (
retry,
stop_after_attempt,
wait_exponential,
retry_if_exception_type
)
from typing import Dict
from services.llms.LLM import model_5mini, model_4omini
from utils.decorator import trace_runtime
from utils.logger import get_logger
logger = get_logger("base generator")
# Set environment variables at module level
os.environ["LANGFUSE_PUBLIC_KEY"] = LangfuseConstants.PUBLIC_KEY
os.environ["LANGFUSE_SECRET_KEY"] = LangfuseConstants.SECRET_KEY
os.environ["LANGFUSE_HOST"] = LangfuseConstants.HOST or "https://us.cloud.langfuse.com"
class MetadataObservability(BaseModel):
fullname: str
task_id: str
agent: str
user_id: str
class BaseAIGenerator:
def __init__(self,
task_name: str,
prompt: ChatPromptTemplate,
input_llm: Dict,
metadata_observability: MetadataObservability,
llm: AzureChatOpenAI = model_5mini | model_4omini,
):
self.metadata_observability = metadata_observability
self.llm = llm
self.prompt = prompt
self.input_llm = input_llm
self.name = task_name
def _get_langfuse_client(self):
try:
# Environment variables already set at module level
return get_client()
except Exception as e:
logger.warning(f"⚠️ Langfuse unavailable, skipping observability: {e}")
return None
def _get_langfuse_config(self):
try:
# Environment variables already set at module level
handler = CallbackHandler()
return {
"callbacks": [handler],
"metadata": {
"langfuse_session_id": self.metadata_observability.task_id,
"langfuse_user_id": self.metadata_observability.user_id,
"langfuse_tags": [self.metadata_observability.agent],
},
}
except Exception as e:
logger.warning(f"⚠️ Langfuse unavailable, skipping observability: {e}")
return {}
@retry(
reraise=True,
stop=stop_after_attempt(2),
wait=wait_exponential(multiplier=1, min=1, max=5),
retry=retry_if_exception_type(Exception)
)
async def _asafe_invoke(self, chain, input_llm, config):
return await chain.ainvoke(input_llm, config=config)
@retry(
reraise=True,
stop=stop_after_attempt(2),
wait=wait_exponential(multiplier=1, min=1, max=5),
retry=retry_if_exception_type(Exception)
)
def _safe_invoke(self, chain, input_llm, config):
return chain.invoke(input_llm, config=config)
@trace_runtime
async def agenerate(self):
try:
config = self._get_langfuse_config()
chain = self.prompt | self.llm
langfuse_client = self._get_langfuse_client()
if not langfuse_client:
return await self._asafe_invoke(chain, self.input_llm, config)
trace_id = Langfuse.create_trace_id(seed=self.metadata_observability.task_id)
with langfuse_client.start_as_current_observation(
as_type="generation",
name=self.name,
trace_context={"trace_id": trace_id},
metadata=self.metadata_observability,
) as span:
with propagate_attributes(
user_id=self.metadata_observability.user_id,
session_id=self.metadata_observability.task_id,
tags=[self.metadata_observability.agent],
):
span.update_trace(
input=self.input_llm,
)
output = await self._asafe_invoke(
chain=chain,
input_llm=self.input_llm,
config=config,
)
span.update_trace(output=output)
return output
except Exception:
logger.exception("❌ BaseGenerator agenerate error")
return None
@trace_runtime
def generate(self):
try:
config = self._get_langfuse_config()
chain = self.prompt | self.llm
langfuse_client = self._get_langfuse_client()
if not langfuse_client:
return self._safe_invoke(chain, self.input_llm, config)
trace_id = Langfuse.create_trace_id(seed=self.metadata_observability.task_id)
with langfuse_client.start_as_current_observation(
as_type="generation",
name=self.name,
trace_context={"trace_id": trace_id},
metadata=self.metadata_observability,
) as span:
with propagate_attributes(
user_id=self.metadata_observability.user_id,
session_id=self.metadata_observability.task_id,
tags=[self.metadata_observability.agent],
):
span.update_trace(
input=self.input_llm,
)
output = self._safe_invoke(
chain=chain,
input_llm=self.input_llm,
config=config,
)
span.update_trace(output=output)
return output
except Exception:
logger.exception("❌ BaseGenerator generate error")
return None |