AgentExecutor.invoke несколько раз вызывает мою конечную точку Azure. «HTTP/1.1 429 Слишком много запросов» ⇐ Python

[Anonymous]

Код: Выделить всё

from db import get_connection
import os
import logging
from template import template_func
from langchain_community.utilities import SQLDatabase
from six.moves import urllib
from langchain_community.agent_toolkits.sql.prompt import SQL_FUNCTIONS_SUFFIX
from langchain_community.agent_toolkits import SQLDatabaseToolkit
from langchain.agents import create_openai_tools_agent
from langchain.agents.agent import AgentExecutor
from langchain_core.messages import AIMessage
from langchain_core.prompts.chat import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
MessagesPlaceholder,
)
from langchain_openai import AzureChatOpenAI

host = os.environ["Host"]

OPENAI_API_TYPE = os.environ["OPENAI_API_TYPE"]
OPENAI_API_VERSION = os.environ["OPENAI_API_VERSION"]
AZURE_ENDPOINT = os.environ["AZURE_ENDPOINT"]
AZURE_OPENAI_API_KEY = os.environ["AZURE_OPENAI_API_KEY"]
OPENAI_CHAT_MODEL = os.environ["OPENAI_CHAT_MODEL"]

def create_agent_executor(TENANT, user_input):
try:
# Logging setup
logging.basicConfig(level=logging.DEBUG)  # Set logging level to DEBUG

# Get the connection string
logging.debug(f"Getting connection string for tenant: {TENANT}")
connection_string = get_connection(host, TENANT)

schemas = os.environ.get(f'DB_{TENANT.upper()}_SCHEMA')
if not schemas:
raise RuntimeError(f"Environment variable DB_{TENANT.upper()}_SCHEMA not found")

logging.debug(f"DB schema found: {schemas}")

connection_string = urllib.parse.quote_plus(connection_string)
connection_string = "mssql+pyodbc:///?odbc_connect=%s" % connection_string

# Initialize the SQL database
logging.debug("Initializing SQL database connection...")
db = SQLDatabase.from_uri(
connection_string,
schema=schemas,
include_tables=['chatBotDataForTrack_duplicate'],
view_support=True
)

# Ensure no conflicting parameters
logging.debug("Configuring AzureChatOpenAI...")
llm = AzureChatOpenAI(
deployment_name="GS-chb-model-eastus-common-001",
temperature=0.7,
max_tokens=4096,
azure_endpoint=AZURE_ENDPOINT
)

toolkit = SQLDatabaseToolkit(db=db, llm=llm)
context = toolkit.get_context()

# Create the prompt
logging.debug("Creating prompt for user input...")
messages = [
HumanMessagePromptTemplate.from_template("{input}"),
AIMessage(content=SQL_FUNCTIONS_SUFFIX),
MessagesPlaceholder(variable_name="agent_scratchpad"),
]
prompt = ChatPromptTemplate.from_messages(messages).partial(**context)

# Get tools and create the agent
logging.debug("Creating OpenAI tools agent...")
tools = toolkit.get_tools()
agent = create_openai_tools_agent(llm, tools, prompt)

# Define MSSQL prompt
MSSQL_PROMPT = template_func('Track')

# Create the agent executor
logging.debug("Creating agent executor...")
agent_executor = AgentExecutor(
agent=agent,
tools=tools,
verbose=True,
max_iterations=10,
prompt=MSSQL_PROMPT,
handle_parsing_errors="I'm sorry, but the question you have asked is not available within the dataset.  Is there anything else I can help you with?"
)

logging.info('Agent executor successfully created.')

# Get the input from the user
logging.debug(f"Invoking agent executor with input: {user_input}")
answer = agent_executor.invoke({"input": user_input})

return answer

Код: Выделить всё

import azure.functions as func
import logging
from dbagent import create_agent_executor

app = func.FunctionApp()
@app.route(route="http_trigger", methods=['POST'])
def http_trigger(req: func.HttpRequest) -> func.HttpResponse:
logging.info('Processing http_trigger function...')

try:
req_body = req.get_json()
logging.info(f'Received request body: {req_body}')
except ValueError:
logging.error('Invalid JSON in request body.')
return func.HttpResponse(
"Invalid JSON in request body.",
status_code=400
)

TENANT = req_body.get('tenant')
question = req_body.get('question')

if not TENANT or not question:
logging.error("Missing 'tenant' or 'question' in request body.")
return func.HttpResponse(
"Please provide both 'tenant' and 'question' in the request body.",
status_code=400
)

try:
logging.info(f'Calling create_agent_executor with tenant: {TENANT} and question: {question}')
answer = create_agent_executor(TENANT, question)
logging.info(f'Received answer from create_agent_executor: {answer}')

# Extract the output from the answer dictionary
if isinstance(answer, dict) and "output" in answer:
output = answer["output"]
else:
output = str(answer)

logging.info(f'Response output: {output}')
return func.HttpResponse(output, status_code=200)
except Exception as e:
logging.error(f'Error processing request: {e}')
return func.HttpResponse(
f"An unexpected error occurred: {e}",
status_code=500
)

Для формирования ответа требуется около 2 минут:

Код: Выделить всё

agent_executor.invoke()

и многократное обращение к конечной точке Azure

Код: Выделить всё

"HTTP/1.1 429 Too Many Requests"
Retrying request to /chat/completions in 2.000000 seconds

HTTP-запрос: POST https://gs-chb-chatbot-eastus-common-00 ... el-eastus- common-001/chat/completions?api-version=2024-02-01
Без функции Azure она прекрасно работает в моем локальном блокноте Jupyter.

Подробнее здесь: https://stackoverflow.com/questions/787 ... tp-1-1-429