Feat: Pulumi S3
This commit is contained in:
@@ -1,6 +1,5 @@
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import os
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TABLE = os.environ["TABLE"]
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REGION = os.environ["REGION"]
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AWS_ACCOUNT = os.environ["AWS_ACCOUNT"]
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SECRET_NAME = os.environ["SECRET_NAME"]
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KNOWLEDGE_BASE_ID = os.environ["KNOWLEDGE_BASE_ID"]
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@@ -4,9 +4,8 @@ import os
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from botocore.exceptions import ClientError
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from langfuse import Langfuse
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from .config import REGION, TABLE, SECRET_NAME
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from .config import REGION, SECRET_NAME
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dynamodb = boto3.resource("dynamodb", region_name=REGION)
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def get_secret() -> str:
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@@ -19,35 +18,9 @@ def get_secret() -> str:
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return response["SecretString"]
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secrets = json.loads(get_secret())
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langfuse = Langfuse(
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public_key=secrets["LANGFUSE-PUBLIC-KEY"],
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secret_key=secrets["LANGFUSE-SECRET-KEY"],
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host=os.environ["LANGFUSE_HOST"],
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)
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def get_contexto(dashboard: str) -> dict:
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"""
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Get contexto, filter, and items_disponiveis from DynamoDB for a given dashboard.
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Returns:
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Dict with 'contexto', 'filter', and 'items_disponiveis' keys
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"""
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try:
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table = dynamodb.Table(TABLE)
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response = table.get_item(Key={"id": dashboard + "_contexto"})
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if "Item" not in response:
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return {"contexto": "", "filter": "", "items_disponiveis": {}}
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item = response["Item"]
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return {
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"contexto": item.get("contexto", ""),
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"filter": item.get("filter_key", ""),
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"items_disponiveis": item.get("itens_disponiveis", {}),
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}
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except ClientError as e:
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error_message = e.response["Error"]["Message"]
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return {"contexto": f"Error: {error_message}", "filter": "", "items_disponiveis": {}}
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#secrets = json.loads(get_secret())
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#langfuse = Langfuse(
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# public_key=secrets["LANGFUSE-PUBLIC-KEY"],
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# secret_key=secrets["LANGFUSE-SECRET-KEY"],
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# host=os.environ["LANGFUSE_HOST"],
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#)
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@@ -2,17 +2,16 @@ from langchain_core.messages import HumanMessage, AIMessage, SystemMessage
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from langfuse.langchain import CallbackHandler
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from .config import REGION
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from .dynamo import langfuse, get_contexto
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from .agent_bedrock import create_agent
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from .tools import ReportTools
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from .tools import build_knowledge_base_tool
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def main(user_query, history, model, base):
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def main(user_query, history, model="anthropic.claude-sonnet-4-5-20250929-v1:0"):
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"""Main execution function."""
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report_tools = []
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report_tools = [build_knowledge_base_tool()]
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SYSTEM_PROMPT = """"""
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SYSTEM_PROMPT = """Você é um assistente de matrículas para o campus capivari do instituo federal de são paulo, tem acesso a uma tool que acessa uma knowledge base com informações sobre tanto a matricula dos alunos do técnico quanto superior do procedimento iterno, não responda perguntas sobre o meio de ingresso SISU."""
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langfuse_handler = CallbackHandler()
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agent = create_agent(model, REGION, tools=report_tools)
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@@ -24,7 +23,7 @@ def main(user_query, history, model, base):
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"current_step": "init",
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}
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config = {"callbacks": [langfuse_handler], "tags": [base]}
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config = {"callbacks": [langfuse_handler]}
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final_state = agent.invoke(initial_state, config=config)
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total_input_tokens = 0
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@@ -33,8 +32,6 @@ def main(user_query, history, model, base):
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if isinstance(msg, AIMessage) and hasattr(msg, "usage_metadata") and msg.usage_metadata:
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total_input_tokens += msg.usage_metadata.get("input_tokens", 0)
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total_output_tokens += msg.usage_metadata.get("output_tokens", 0)
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langfuse.flush()
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return {
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"response": final_state["messages"][-1].content,
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"input_tokens": total_input_tokens,
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@@ -1,85 +1,21 @@
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from botocore.exceptions import ClientError
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from langchain_core.tools import StructuredTool
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from langchain_aws import AmazonKnowledgeBasesRetriever
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from langchain_core.tools.retriever import create_retriever_tool
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from .config import TABLE
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from .dynamo import dynamodb
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from .config import REGION, KNOWLEDGE_BASE_ID
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class ReportTools:
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def __init__(self, id_mapping: dict[str, str]):
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self.id_mapping = id_mapping
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def get_variable_value(self, id: str, variable: str) -> str:
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"""
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Get a specific variable's value from DynamoDB for a specific id.
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Args:
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id: The id of the data
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variable: The variable/column name to retrieve from the table
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Returns:
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The content of the specified variable for the given id
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"""
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real_id = self.id_mapping.get(id, id)
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try:
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table = dynamodb.Table(TABLE)
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response = table.get_item(Key={"id": real_id})
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if "Item" not in response:
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return f"No report found for month: {id}"
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item = response["Item"]
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content = item.get(variable, "")
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if not content:
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return f"Variable '{variable}' not found for month: {id}"
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return f"<{id}>\n{content}\n</{id}>"
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except ClientError as e:
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error_message = e.response["Error"]["Message"]
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return f"Error fetching report: {error_message}"
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def get_variables_list(self, id: str) -> str:
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"""
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Get the list of variables available in the table for a specific month.
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Args:
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id: The id of the data
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Returns:
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The list of available variables/keys for the specified data
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"""
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real_id = self.id_mapping.get(id, id)
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try:
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table = dynamodb.Table(TABLE)
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response = table.get_item(Key={"id": real_id})
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if "Item" not in response:
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return f"No data found for month: {id}"
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item = response["Item"]
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chaves_consolidadas = item.get("chaves_consolidadas", "")
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if not chaves_consolidadas:
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return f"No consolidated keys found for id: {id}"
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return chaves_consolidadas
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except ClientError as e:
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error_message = e.response["Error"]["Message"]
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return f"Error fetching consolidated keys: {error_message}"
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def as_tools(self) -> list:
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return [
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StructuredTool.from_function(
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self.get_variable_value,
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name="get_variable_value",
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description="Get a specific variable's data from DynamoDB for a specific id.",
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),
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StructuredTool.from_function(
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self.get_variables_list,
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name="get_variable_list",
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description="Get the list of variables available in the table for a specific id.",
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),
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]
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def build_knowledge_base_tool():
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retriever = AmazonKnowledgeBasesRetriever(
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knowledge_base_id=KNOWLEDGE_BASE_ID,
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retrieval_config={"vectorSearchConfiguration": {"numberOfResults": 5}},
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region_name=REGION,
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)
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return create_retriever_tool(
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retriever,
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name="consultar_base_conhecimento",
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description=(
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"Consulta a base de conhecimento com informações sobre procedimentos internos de matrícula "
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"para cursos técnicos e superiores do campus Capivari do IFSP. "
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"Use esta ferramenta para responder dúvidas sobre matrícula."
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),
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)
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@@ -41,7 +41,7 @@ if prompt := st.chat_input("Type your message here..."):
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# Simulate streaming response (replace with actual API call)
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result = orquestrador.main(prompt,str(st.session_state.messages),selected_value,base)
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result = orquestrador.main(prompt,str(st.session_state.messages))
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full_response = result["response"]
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# Simulate typing effect
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@@ -1,8 +1,8 @@
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boto3==1.42.10
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langchain-aws==1.1.0
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langgraph==1.0.5
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langchain-aws==1.3.0
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langgraph==1.0.9
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langchain==1.2.0
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streamlit==1.52.2
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langfuse==3.11.2
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fastapi==0.129.0
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streamlit==1.54.0
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langfuse==3.14.5
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fastapi==0.133.0
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uvicorn==0.41.0
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