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Ajustes conforme relatorio de testes 2026-08-27

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Cristiano Hoshikawa
2026-08-29 21:04:31 -03:00
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README.md
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#### 5.1.1.21.3. Instrumentação automática do cliente OpenAI pelo Langfuse #### 5.1.1.21.3. Instrumentação automática do cliente OpenAI pelo Langfuse
O padrão oficial do framework é:
```python ```env
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
```
habilita a instrumentação automática do cliente OpenAI pelo Langfuse.
Quando habilitada, todas as chamadas realizadas através do cliente OpenAI instrumentado passam a gerar automaticamente spans e generations detalhadas no Langfuse.
Benefícios
Com a instrumentação automática ativada, o Langfuse passa a registrar informações como:
* OpenAI-generation
* Prompt enviado ao modelo
* Resposta retornada pelo modelo
* Modelo utilizado
* Quantidade de tokens
* Custos estimados
* Latência da chamada
* Erros de execução
Essas informações ficam associadas ao trace principal da conversa, facilitando análise, troubleshooting e auditoria.
Comportamento quando desabilitado
Quando:
```python
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
``` ```
ou a variável não está definida: O framework já instrumenta as chamadas LLM por meio de `Telemetry.generation(...)`, preservando `trace_id`, `session_id`, `user_id`, metadados, tokens, custos, latência e o relacionamento pai/filho dentro do trace de negócio. Por esse motivo, a auto-instrumentação do cliente OpenAI não é necessária no fluxo normal do framework.
* As chamadas LLM continuam funcionando normalmente. Quando `false`:
* Os spans customizados do framework continuam sendo emitidos.
* O Langfuse deixa de criar automaticamente as entradas OpenAI-generation.
* Menos detalhes ficam disponíveis para análise das chamadas ao modelo.
Quando utilizar * as chamadas LLM continuam funcionando normalmente;
* prompts, respostas, modelo, tokens, custos e latência continuam disponíveis pela telemetria explícita do framework;
* as generations permanecem correlacionadas ao trace principal da requisição;
* evita-se dupla instrumentação e `OpenAI-generation` como trace raiz separado.
Recomenda-se habilitar em: A opção `true` existe apenas para compatibilidade ou diagnóstico de código que chama diretamente o SDK OpenAI/OpenAI-compatible fora da camada de `Telemetry` do framework. Nesses casos, o wrapper `langfuse.openai` pode capturar automaticamente essas chamadas. Entretanto, em uma aplicação que já usa a instrumentação nativa do framework, mantê-la habilitada pode gerar duplicidade de observations, contagem duplicada de tokens/custos ou traces independentes quando não houver um parent Langfuse ativo.
* Ambientes de desenvolvimento. ```env
* Ambientes de homologação. # Padrão recomendado para todos os templates e ambientes do framework
* Ambientes de produção que necessitem observabilidade detalhada das chamadas LLM. ENABLE_LANGFUSE=true
* Cenários de troubleshooting, tuning de prompts e análise de custos. ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
```
Observação Todos os arquivos `.env.example` distribuídos pelo projeto mantêm essa opção explicitamente em `false`. Se um componente externo precisar de captura automática, habilite-a somente naquele deployment e valide a árvore de traces no Langfuse.
Esta configuração afeta apenas a telemetria automática do Langfuse.
Ela não altera:
* O comportamento dos agentes.
* O roteamento do Supervisor.
* Guardrails.
* Judges.
* MCP Tool Router.
* Fluxos LangGraph.
Seu único objetivo é enriquecer a observabilidade das chamadas realizadas ao modelo de linguagem.
---
### 5.1.1.22. Recomendações de arquitetura
#### 5.1.1.22.1. Para demos e desenvolvimento #### 5.1.1.22.1. Para demos e desenvolvimento

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README_en.md
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#### 5.1.1.21.3. Automatic Langfuse instrumentation for the OpenAI client #### 5.1.1.21.3. Automatic Langfuse instrumentation for the OpenAI client
```python The framework's official default is:
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
```
enables automatic Langfuse instrumentation for the OpenAI client. ```env
When enabled, every request executed through the Langfuse-instrumented OpenAI client automatically generates detailed spans and generations within Langfuse.
Benefits
With automatic instrumentation enabled, Langfuse can automatically capture and display information such as:
* OpenAI-generation
* Prompt sent to the model
* Model response
* Model name used
* Token consumption
* Estimated costs
* Request latency
* Execution errors
All of this information is linked to the main conversation trace, making troubleshooting, auditing, and performance analysis significantly easier.
Behavior When Disabled
When:
```python
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
``` ```
or when the variable is not defined: The framework already instruments LLM calls through `Telemetry.generation(...)`, preserving `trace_id`, `session_id`, `user_id`, metadata, token usage, cost, latency, and the parent/child relationship inside the business trace. Therefore, OpenAI client auto-instrumentation is not required in the normal framework path.
* LLM calls continue to function normally. When set to `false`:
* Custom framework spans are still emitted.
* Langfuse no longer automatically creates OpenAI-generation entries.
* Less detailed information is available for analyzing model interactions.
Recommended Usage * LLM calls continue to work normally;
* prompts, responses, model, tokens, costs, and latency remain available through the framework's explicit telemetry;
* generations remain correlated with the main request trace;
* duplicate instrumentation and standalone `OpenAI-generation` root traces are avoided.
It is recommended to enable this setting in: The `true` option exists only for compatibility or diagnostics for code that calls the OpenAI/OpenAI-compatible SDK directly outside the framework `Telemetry` layer. In such cases, the `langfuse.openai` wrapper can automatically capture those calls. In an application already using the framework's native instrumentation, keeping it enabled may create duplicate observations, duplicate token/cost accounting, or independent traces when no active Langfuse parent exists.
* Development environments ```env
* Testing and staging environments # Recommended default for every framework template and environment
* Production environments that require detailed LLM observability ENABLE_LANGFUSE=true
* Prompt engineering, troubleshooting, and cost analysis scenarios ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
```
Important Note Every `.env.example` distributed with the project explicitly keeps this option set to `false`. If an external component requires automatic capture, enable it only for that deployment and validate the trace tree in Langfuse.
This setting only affects Langfuse automatic telemetry and observability.
It does not change:
* Agent behavior
* Supervisor routing
* Guardrails
* Judges
* MCP Tool Router
* LangGraph workflows
Its sole purpose is to enrich the observability of language model interactions and provide more detailed execution insights within Langfuse.
---
### 5.1.1.22. Architecture recommendations
#### 5.1.1.22.1. For demos and development #### 5.1.1.22.1. For demos and development

211
Tuning-Performance/Deterministic_Transactional_Workflow/agent_template_backend/.env
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###############################################################################
# AI AGENT PLATFORM - CONFIGURAÇÃO ÚNICA
# Este arquivo é lido por Pydantic Settings no framework e no backend template.
###############################################################################
APP_NAME=ai-agent-template
APP_ENV=local
LOG_LEVEL=INFO
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
###############################################################################
# LLM - OCI Generative AI como provider principal
###############################################################################
# Opções: mock, oci_openai, oci_sdk, openai_compatible
LLM_PROVIDER=oci_sdk
LLM_TEMPERATURE=0.2
LLM_MAX_TOKENS=2048
LLM_TIMEOUT_SECONDS=120
# OCI OpenAI-compatible endpoint
OCI_GENAI_BASE_URL=https://inference.generativeai.us-chicago-1.oci.oraclecloud.com
OCI_GENAI_MODEL=openai.gpt-4.1
OCI_GENAI_API_KEY=sk-ph3FgX6iP3fxAQCXb9IpPIDTadkeeYAWntUWhzcWysIM6zsS
OCI_GENAI_PROJECT_OCID=
#OCI_GENAI_BASE_URL=https://pegruagntaiatenddev.pe.inference.generativeai.sa-saopaulo-1.oci.oraclecloud.com
#OCI_GENAI_MODEL=openai.gpt-4.1
#OCI_GENAI_API_KEY=
#OCI_GENAI_PROJECT_OCID=
# OCI_AUTH_MODE=config_file|instance_principal|resource_principal
OCI_AUTH_MODE=config_file
# OCI SDK / signer / profiles
OCI_CONFIG_FILE=~/.oci/config
OCI_PROFILE=LATINOAMERICA-Chicago
OCI_COMPARTMENT_ID=ocid1.compartment.oc1..aaaaaaaaexpiw4a7dio64mkfv2t273s2hgdl6mgfvvyv7tycalnjlvpvfl3q
OCI_REGION=us-chicago-1
###############################################################################
# Persistência
###############################################################################
# Opções: memory, autonomous, mongodb
SESSION_REPOSITORY_PROVIDER=autonomous
MEMORY_REPOSITORY_PROVIDER=autonomous
CHECKPOINT_REPOSITORY_PROVIDER=autonomous
# Autonomous Database
ADB_USER=admin
ADB_PASSWORD=Moniquinha19721972
ADB_DSN=oradb23ai_high
ADB_WALLET_LOCATION=/mnt/d/Dropbox/ORACLE/LatinoAmerica/Wallet_ORADB23ai
ADB_WALLET_PASSWORD=Moniquinha1972
ADB_TABLE_PREFIX=AGENTFW
# MongoDB - também pode representar Autonomous usando API compatível com Mongo, se habilitada no ambiente
MONGODB_URI=mongodb://mongo:mongopassword@localhost:27017
MONGODB_DATABASE=agent_platform
# Redis
REDIS_URL=redis://localhost:6379/0
ENABLE_REDIS_CACHE=false
###############################################################################
# RAG / Vector / Graph
###############################################################################
VECTOR_STORE_PROVIDER=autonomous
GRAPH_STORE_PROVIDER=autonomous
RAG_TOP_K=5
EMBEDDING_PROVIDER=oci
OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
RAG_FILE_GLOBS=*.md,*.txt,*.yaml,*.yml,*.json
###############################################################################
# Observabilidade
###############################################################################
ENABLE_LANGFUSE=true
# Opcional: verbose, compact
LANGFUSE_TRACE_MODE=compact
# Nome customizado do trace pai, ex.: backoffice.checklist.workflow ou backoffice.emulador.workflow
LANGFUSE_COMPACT_VISIBLE_EVENT_PREFIXES=AGA.,NOC., IC.
LANGFUSE_COMPACT_SUPPRESSED_PREFIXES=llm.chat_completion
LANGFUSE_IGNORE_HEALTHCHECKS=true
LANGFUSE_IGNORED_PATHS=/health,/ready,/metrics
LANGFUSE_PUBLIC_KEY=pk-lf-4a1e3921-5158-4fd3-a16d-7a77549fb312
LANGFUSE_SECRET_KEY=sk-lf-efc6fd59-c5ec-4858-b6ec-4aa129734915
LANGFUSE_HOST=http://localhost:3005
ENABLE_OTEL=false
OTEL_EXPORTER_OTLP_ENDPOINT=
OTEL_SERVICE_NAME=ai-agent-template
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
ENABLE_LANGFUSE_ANALYTICS_PUBLISHER=false
###############################################################################
# Analytics / Observer corporativo
###############################################################################
# Quando true, AgentObserver publica eventos IC.*, NOC.* e GRL.* nos providers abaixo.
ENABLE_ANALYTICS=false
# Providers aceitos: oci_streaming,pubsub,noop
ANALYTICS_PROVIDERS=oci_streaming
# Compatibilidade FIRST/TIM: pode informar AGENT_PUBSUB_TOPIC diretamente.
AGENT_PUBSUB_TOPIC=
GCP_PUBSUB_TOPIC_PATH=
GCP_PROJECT_ID=
GCP_PUBSUB_TOPIC=
GCP_PUBSUB_TIMEOUT_SECONDS=30
# Credencial GCP segue padrão Google:
# GOOGLE_APPLICATION_CREDENTIALS=/secrets/gcp-service-account.json
###############################################################################
# OCI Streaming
###############################################################################
ENABLE_OCI_STREAMING=false
OCI_STREAM_ENDPOINT=
OCI_STREAM_OCID=
OCI_STREAM_PARTITION_KEY=agent-events
###############################################################################
# Guardrails, Judges, Supervisor
###############################################################################
ENABLE_INPUT_GUARDRAILS=true
ENABLE_OUTPUT_GUARDRAILS=true
ENABLE_JUDGES=true
ENABLE_SUPERVISOR=true
ENABLE_OUTPUT_SUPERVISOR=true
ENABLE_PARALLEL_GUARDRAILS=true
GUARDRAILS_FAIL_FAST=true
OUTPUT_SUPERVISOR_MAX_RETRIES=3
GUARDRAILS_CONFIG_PATH=./config/guardrails.yaml
JUDGES_CONFIG_PATH=./config/judges.yaml
PROMPT_POLICY_PATH=./config/prompt_policy.yaml
###############################################################################
# Gateway de canais
###############################################################################
DEFAULT_CHANNEL=web
# embedded = backend may parse simple/native channel payloads.
# external = backend only accepts GatewayRequest normalized by an external Channel Gateway.
FRAMEWORK_CHANNEL_INPUT_MODE=embedded
ENABLE_VOICE_ADAPTER=true
ENABLE_WHATSAPP_ADAPTER=true
ENABLE_TEXT_ADAPTER=true
#################################################
# ENTERPRISE ROUTING
#################################################
# Arquivo YAML com intents, keywords, políticas de estado e fallback.
ROUTING_CONFIG_PATH=./config/routing.yaml
# true = usa LLM para classificar quando keywords/estado não resolverem.
# Em produção, costuma ser útil; em desenvolvimento, false evita custo e latência.
ENABLE_LLM_ROUTER=true
# Semantic route stickiness (optional).
# Uses a lightweight LLM profile to decide only CONTINUE vs ROUTE.
# There are no regexes or deterministic language rules.
ENABLE_ROUTE_STICKINESS=true
ROUTE_STICKINESS_LLM_PROFILE=route_continuity
ROUTE_STICKINESS_CONFIDENCE_THRESHOLD=0.90
ROUTE_STICKINESS_HISTORY_TURNS=2
ROUTE_STICKINESS_MAX_TOKENS=80
HUMAN_HANDOFF_MESSAGE=Vou encaminhar seu atendimento para uma pessoa.
END_SESSION_MESSAGE=Atendimento encerrado. Obrigado pelo contato.
ENABLE_TRANSACTIONAL_WORKFLOWS=true
WORKFLOWS_PATH=./workflows
###############################################################################
# MCP / Tools
###############################################################################
ENABLE_MCP_TOOLS=true
MCP_SERVERS_CONFIG_PATH=./config/mcp_servers.yaml
TOOLS_CONFIG_PATH=./config/tools.yaml
MCP_TOOL_TIMEOUT_SECONDS=30
# router = EnterpriseRouter seleciona um agente; supervisor = pode acionar múltiplos agentes
ROUTING_MODE=router
# Usage/cost accounting
USAGE_REPOSITORY_PROVIDER=autonomous
IDENTITY_CONFIG_PATH=./config/identity.yaml
MCP_PARAMETER_MAPPING_PATH=./config/mcp_parameter_mapping.yaml
# -----------------------------------------------------------------------------
# ConversationSummaryMemory / compressão de contexto conversacional
# -----------------------------------------------------------------------------
ENABLE_CONVERSATION_SUMMARY_MEMORY=true
MEMORY_CONTEXT_STRATEGY=summary
MEMORY_HISTORY_LIMIT=80
MEMORY_RECENT_MESSAGES_LIMIT=8
MEMORY_SUMMARY_TRIGGER_MESSAGES=20
MEMORY_MAX_SUMMARY_CHARS=6000
MEMORY_SUMMARY_USE_LLM=true
MEMORY_INJECT_RECENT_MESSAGES=true
MEMORY_INJECT_SUMMARY=true
###############################################################################
# LONG-TERM MEMORY
###############################################################################
ENABLE_LONG_TERM_MEMORY=true
LONG_TERM_MEMORY_PROVIDER=sqlite
LONG_TERM_MEMORY_SQLITE_PATH=./data/agent_framework.db
LONG_TERM_MEMORY_TABLE=agentfw_long_term_memory
# For Autonomous/Oracle, defaults to ${ADB_TABLE_PREFIX}_LONG_TERM_MEMORY
# LONG_TERM_MEMORY_ORACLE_TABLE=AGENTFW_LONG_TERM_MEMORY
LONG_TERM_MEMORY_MAX_CONTEXT_ITEMS=20
LONG_TERM_MEMORY_MIN_CONFIDENCE=0.70
LONG_TERM_MEMORY_AUTO_EXTRACT=true
LONG_TERM_MEMORY_INJECT_CONTEXT=true
ENABLE_TRANSACTIONAL_WORKFLOWS=true
WORKFLOWS_PATH=./workflows

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Tuning-Performance/External_Guardrails_Judges/agent_template_backend/.env
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###############################################################################
# AI AGENT PLATFORM - CONFIGURAÇÃO ÚNICA
# Este arquivo é lido por Pydantic Settings no framework e no backend template.
###############################################################################
APP_NAME=ai-agent-template
APP_ENV=local
LOG_LEVEL=INFO
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
###############################################################################
# LLM - OCI Generative AI como provider principal
###############################################################################
# Opções: mock, oci_openai, oci_sdk, openai_compatible
LLM_PROVIDER=oci_openai
LLM_TEMPERATURE=0.2
LLM_MAX_TOKENS=2048
LLM_TIMEOUT_SECONDS=120
# OCI OpenAI-compatible endpoint
OCI_GENAI_BASE_URL=https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1
OCI_GENAI_MODEL=openai.gpt-4.1
OCI_GENAI_API_KEY=sk-ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6
OCI_GENAI_PROJECT_OCID=
# OCI SDK / signer / profiles
OCI_CONFIG_FILE=~/.oci/config
OCI_PROFILE=DEFAULT
OCI_COMPARTMENT_ID=ocid1.compartment.oc1..aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
OCI_REGION=us-chicago-1
###############################################################################
# Persistência
###############################################################################
# Opções: memory, autonomous, mongodb
SESSION_REPOSITORY_PROVIDER=sqlite
MEMORY_REPOSITORY_PROVIDER=sqlite
CHECKPOINT_REPOSITORY_PROVIDER=sqlite
SQLITE_DB_PATH=./data/agent_framework.db
# Autonomous Database
ADB_USER=admin
ADB_PASSWORD=fjhsdf04954hf
ADB_DSN=oradb23aidev_high
ADB_WALLET_LOCATION=/ORACLE/DEFAULT/Wallet_ORADB23aiDev
ADB_WALLET_PASSWORD=fjhsdf04954hf
ADB_TABLE_PREFIX=AGENTFW
# MongoDB - também pode representar Autonomous usando API compatível com Mongo, se habilitada no ambiente
MONGODB_URI=mongodb://mongo:mongopassword@localhost:27017
MONGODB_DATABASE=agent_platform
# Redis
REDIS_URL=redis://localhost:6379/0
ENABLE_REDIS_CACHE=false
###############################################################################
# RAG / Vector / Graph
###############################################################################
VECTOR_STORE_PROVIDER=sqlite
GRAPH_STORE_PROVIDER=sqlite
RAG_TOP_K=5
EMBEDDING_PROVIDER=mock
OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
RAG_FILE_GLOBS=*.md,*.txt,*.yaml,*.yml,*.json
###############################################################################
# Observabilidade
###############################################################################
ENABLE_LANGFUSE=true
LANGFUSE_TRACE_MODE=compact # Opcional: verbose, compact
LANGFUSE_PUBLIC_KEY=pk-lf-2f9da109-5b0f-4c78-b61d-9598ed787eba
LANGFUSE_SECRET_KEY=sk-lf-a4cb0cdd-f2ea-4468-9911-cebeb91ba944
LANGFUSE_HOST=http://localhost:3005
ENABLE_OTEL=false
OTEL_EXPORTER_OTLP_ENDPOINT=
OTEL_SERVICE_NAME=ai-agent-template
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
###############################################################################
# Analytics / Observer corporativo
###############################################################################
# Quando true, AgentObserver publica eventos IC.*, NOC.* e GRL.* nos providers abaixo.
ENABLE_ANALYTICS=false
# Providers aceitos: oci_streaming,pubsub,noop
ANALYTICS_PROVIDERS=pubsub
# Compatibilidade FIRST/TIM: pode informar AGENT_PUBSUB_TOPIC diretamente.
AGENT_PUBSUB_TOPIC=
GCP_PUBSUB_TOPIC_PATH=
GCP_PROJECT_ID=
GCP_PUBSUB_TOPIC=
GCP_PUBSUB_TIMEOUT_SECONDS=30
# Credencial GCP segue padrão Google:
# GOOGLE_APPLICATION_CREDENTIALS=/secrets/gcp-service-account.json
###############################################################################
# OCI Streaming
###############################################################################
ENABLE_OCI_STREAMING=false
OCI_STREAM_ENDPOINT=
OCI_STREAM_OCID=
OCI_STREAM_PARTITION_KEY=agent-events
###############################################################################
# Guardrails, Judges, Supervisor
###############################################################################
ENABLE_INPUT_GUARDRAILS=true
ENABLE_OUTPUT_GUARDRAILS=true
ENABLE_JUDGES=true
ENABLE_SUPERVISOR=true
ENABLE_OUTPUT_SUPERVISOR=true
ENABLE_PARALLEL_GUARDRAILS=true
GUARDRAILS_FAIL_FAST=true
OUTPUT_SUPERVISOR_MAX_RETRIES=3
GUARDRAILS_CONFIG_PATH=./config/guardrails.yaml
JUDGES_CONFIG_PATH=./config/judges.yaml
PROMPT_POLICY_PATH=./config/prompt_policy.yaml
###############################################################################
# Gateway de canais
###############################################################################
DEFAULT_CHANNEL=web
# embedded = backend may parse simple/native channel payloads.
# external = backend only accepts GatewayRequest normalized by an external Channel Gateway.
FRAMEWORK_CHANNEL_INPUT_MODE=embedded
ENABLE_VOICE_ADAPTER=true
ENABLE_WHATSAPP_ADAPTER=true
ENABLE_TEXT_ADAPTER=true
#################################################
# ENTERPRISE ROUTING
#################################################
# Arquivo YAML com intents, keywords, políticas de estado e fallback.
ROUTING_CONFIG_PATH=./config/routing.yaml
# true = usa LLM para classificar quando keywords/estado não resolverem.
# Em produção, costuma ser útil; em desenvolvimento, false evita custo e latência.
ENABLE_LLM_ROUTER=true
###############################################################################
# MCP / Tools
###############################################################################
ENABLE_MCP_TOOLS=true
MCP_SERVERS_CONFIG_PATH=./config/mcp_servers.yaml
TOOLS_CONFIG_PATH=./config/tools.yaml
TOOL_POLICIES_PATH=./config/tool_policies.yaml
MCP_TOOL_TIMEOUT_SECONDS=30
# router = EnterpriseRouter seleciona um agente; supervisor = pode acionar múltiplos agentes
ROUTING_MODE=router
# Usage/cost accounting
USAGE_REPOSITORY_PROVIDER=sqlite
IDENTITY_CONFIG_PATH=./config/identity.yaml
MCP_PARAMETER_MAPPING_PATH=./config/mcp_parameter_mapping.yaml
# -----------------------------------------------------------------------------
# ConversationSummaryMemory / compressão de contexto conversacional
# -----------------------------------------------------------------------------
ENABLE_CONVERSATION_SUMMARY_MEMORY=true
MEMORY_CONTEXT_STRATEGY=summary
MEMORY_HISTORY_LIMIT=80
MEMORY_RECENT_MESSAGES_LIMIT=8
MEMORY_SUMMARY_TRIGGER_MESSAGES=20
MEMORY_MAX_SUMMARY_CHARS=6000
MEMORY_SUMMARY_USE_LLM=true
MEMORY_INJECT_RECENT_MESSAGES=true
MEMORY_INJECT_SUMMARY=true
###############################################################################
# MCP Gateway
###############################################################################
# true = framework routes tool calls to the dedicated MCP Gateway.
# false = framework calls MCP servers directly from mcp_servers.yaml.
MCP_GATEWAY_ENABLED=true
MCP_GATEWAY_URL=http://localhost:8300
MCP_GATEWAY_TIMEOUT_SECONDS=60
# MCP_GATEWAY_TOKEN=
MCP_GATEWAY_AGENT_ID=telecom_contas
MCP_GATEWAY_TENANT_ID=default
###############################################################################
# LONG-TERM MEMORY
###############################################################################
ENABLE_LONG_TERM_MEMORY=true
LONG_TERM_MEMORY_PROVIDER=sqlite
LONG_TERM_MEMORY_SQLITE_PATH=./data/agent_framework.db
LONG_TERM_MEMORY_TABLE=agentfw_long_term_memory
# For Autonomous/Oracle, defaults to ${ADB_TABLE_PREFIX}_LONG_TERM_MEMORY
# LONG_TERM_MEMORY_ORACLE_TABLE=AGENTFW_LONG_TERM_MEMORY
LONG_TERM_MEMORY_MAX_CONTEXT_ITEMS=20
LONG_TERM_MEMORY_MIN_CONFIDENCE=0.70
LONG_TERM_MEMORY_AUTO_EXTRACT=true
LONG_TERM_MEMORY_INJECT_CONTEXT=true

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Tuning-Performance/Long_Term_Memory/templates/agent_template_backend/.env
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@@ -1,207 +0,0 @@
###############################################################################
# AI AGENT PLATFORM - CONFIGURAÇÃO ÚNICA
# Este arquivo é lido por Pydantic Settings no framework e no backend template.
###############################################################################
APP_NAME=ai-agent-template
APP_ENV=local
LOG_LEVEL=INFO
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
###############################################################################
# LLM - OCI Generative AI como provider principal
###############################################################################
# Opções: mock, oci_openai, oci_sdk, openai_compatible
LLM_PROVIDER=oci_sdk
LLM_TEMPERATURE=0.2
LLM_MAX_TOKENS=2048
LLM_TIMEOUT_SECONDS=120
# OCI OpenAI-compatible endpoint
OCI_GENAI_BASE_URL=https://inference.generativeai.us-chicago-1.oci.oraclecloud.com
OCI_GENAI_MODEL=openai.gpt-4.1
OCI_GENAI_API_KEY=sk-ph3FgX6iP3fxAQCXb9IpPIDTadkeeYAWntUWhzcWysIM6zsS
OCI_GENAI_PROJECT_OCID=
#OCI_GENAI_BASE_URL=https://pegruagntaiatenddev.pe.inference.generativeai.sa-saopaulo-1.oci.oraclecloud.com
#OCI_GENAI_MODEL=openai.gpt-4.1
#OCI_GENAI_API_KEY=
#OCI_GENAI_PROJECT_OCID=
# OCI_AUTH_MODE=config_file|instance_principal|resource_principal
OCI_AUTH_MODE=config_file
# OCI SDK / signer / profiles
OCI_CONFIG_FILE=~/.oci/config
OCI_PROFILE=LATINOAMERICA-Chicago
OCI_COMPARTMENT_ID=ocid1.compartment.oc1..aaaaaaaaexpiw4a7dio64mkfv2t273s2hgdl6mgfvvyv7tycalnjlvpvfl3q
OCI_REGION=us-chicago-1
###############################################################################
# Persistência
###############################################################################
# Opções: memory, autonomous, mongodb
SESSION_REPOSITORY_PROVIDER=autonomous
MEMORY_REPOSITORY_PROVIDER=autonomous
CHECKPOINT_REPOSITORY_PROVIDER=autonomous
# Autonomous Database
ADB_USER=admin
ADB_PASSWORD=Moniquinha19721972
ADB_DSN=oradb23ai_high
ADB_WALLET_LOCATION=/mnt/d/Dropbox/ORACLE/LatinoAmerica/Wallet_ORADB23ai
ADB_WALLET_PASSWORD=Moniquinha1972
ADB_TABLE_PREFIX=AGENTFW
# MongoDB - também pode representar Autonomous usando API compatível com Mongo, se habilitada no ambiente
MONGODB_URI=mongodb://mongo:mongopassword@localhost:27017
MONGODB_DATABASE=agent_platform
# Redis
REDIS_URL=redis://localhost:6379/0
ENABLE_REDIS_CACHE=false
###############################################################################
# RAG / Vector / Graph
###############################################################################
VECTOR_STORE_PROVIDER=autonomous
GRAPH_STORE_PROVIDER=autonomous
RAG_TOP_K=5
EMBEDDING_PROVIDER=oci
OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
RAG_FILE_GLOBS=*.md,*.txt,*.yaml,*.yml,*.json
###############################################################################
# Observabilidade
###############################################################################
ENABLE_LANGFUSE=true
# Opcional: verbose, compact
LANGFUSE_TRACE_MODE=compact
# Nome customizado do trace pai, ex.: backoffice.checklist.workflow ou backoffice.emulador.workflow
LANGFUSE_COMPACT_VISIBLE_EVENT_PREFIXES=AGA.,NOC., IC.
LANGFUSE_COMPACT_SUPPRESSED_PREFIXES=llm.chat_completion
LANGFUSE_IGNORE_HEALTHCHECKS=true
LANGFUSE_IGNORED_PATHS=/health,/ready,/metrics
LANGFUSE_PUBLIC_KEY=pk-lf-4a1e3921-5158-4fd3-a16d-7a77549fb312
LANGFUSE_SECRET_KEY=sk-lf-efc6fd59-c5ec-4858-b6ec-4aa129734915
LANGFUSE_HOST=http://localhost:3005
ENABLE_OTEL=false
OTEL_EXPORTER_OTLP_ENDPOINT=
OTEL_SERVICE_NAME=ai-agent-template
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
ENABLE_LANGFUSE_ANALYTICS_PUBLISHER=false
###############################################################################
# Analytics / Observer corporativo
###############################################################################
# Quando true, AgentObserver publica eventos IC.*, NOC.* e GRL.* nos providers abaixo.
ENABLE_ANALYTICS=false
# Providers aceitos: oci_streaming,pubsub,noop
ANALYTICS_PROVIDERS=oci_streaming
# Compatibilidade FIRST/TIM: pode informar AGENT_PUBSUB_TOPIC diretamente.
AGENT_PUBSUB_TOPIC=
GCP_PUBSUB_TOPIC_PATH=
GCP_PROJECT_ID=
GCP_PUBSUB_TOPIC=
GCP_PUBSUB_TIMEOUT_SECONDS=30
# Credencial GCP segue padrão Google:
# GOOGLE_APPLICATION_CREDENTIALS=/secrets/gcp-service-account.json
###############################################################################
# OCI Streaming
###############################################################################
ENABLE_OCI_STREAMING=false
OCI_STREAM_ENDPOINT=
OCI_STREAM_OCID=
OCI_STREAM_PARTITION_KEY=agent-events
###############################################################################
# Guardrails, Judges, Supervisor
###############################################################################
ENABLE_INPUT_GUARDRAILS=true
ENABLE_OUTPUT_GUARDRAILS=true
ENABLE_JUDGES=true
ENABLE_SUPERVISOR=true
ENABLE_OUTPUT_SUPERVISOR=true
ENABLE_PARALLEL_GUARDRAILS=true
GUARDRAILS_FAIL_FAST=true
OUTPUT_SUPERVISOR_MAX_RETRIES=3
GUARDRAILS_CONFIG_PATH=./config/guardrails.yaml
JUDGES_CONFIG_PATH=./config/judges.yaml
PROMPT_POLICY_PATH=./config/prompt_policy.yaml
###############################################################################
# Gateway de canais
###############################################################################
DEFAULT_CHANNEL=web
# embedded = backend may parse simple/native channel payloads.
# external = backend only accepts GatewayRequest normalized by an external Channel Gateway.
FRAMEWORK_CHANNEL_INPUT_MODE=embedded
ENABLE_VOICE_ADAPTER=true
ENABLE_WHATSAPP_ADAPTER=true
ENABLE_TEXT_ADAPTER=true
#################################################
# ENTERPRISE ROUTING
#################################################
# Arquivo YAML com intents, keywords, políticas de estado e fallback.
ROUTING_CONFIG_PATH=./config/routing.yaml
# true = usa LLM para classificar quando keywords/estado não resolverem.
# Em produção, costuma ser útil; em desenvolvimento, false evita custo e latência.
ENABLE_LLM_ROUTER=true
# Semantic route stickiness (optional).
# Uses a lightweight LLM profile to decide only CONTINUE vs ROUTE.
# There are no regexes or deterministic language rules.
ENABLE_ROUTE_STICKINESS=true
ROUTE_STICKINESS_LLM_PROFILE=route_continuity
ROUTE_STICKINESS_CONFIDENCE_THRESHOLD=0.90
ROUTE_STICKINESS_HISTORY_TURNS=2
ROUTE_STICKINESS_MAX_TOKENS=80
HUMAN_HANDOFF_MESSAGE=Vou encaminhar seu atendimento para uma pessoa.
END_SESSION_MESSAGE=Atendimento encerrado. Obrigado pelo contato.
###############################################################################
# MCP / Tools
###############################################################################
ENABLE_MCP_TOOLS=true
MCP_SERVERS_CONFIG_PATH=./config/mcp_servers.yaml
TOOLS_CONFIG_PATH=./config/tools.yaml
MCP_TOOL_TIMEOUT_SECONDS=30
# router = EnterpriseRouter seleciona um agente; supervisor = pode acionar múltiplos agentes
ROUTING_MODE=router
# Usage/cost accounting
USAGE_REPOSITORY_PROVIDER=autonomous
IDENTITY_CONFIG_PATH=./config/identity.yaml
MCP_PARAMETER_MAPPING_PATH=./config/mcp_parameter_mapping.yaml
# -----------------------------------------------------------------------------
# ConversationSummaryMemory / compressão de contexto conversacional
# -----------------------------------------------------------------------------
ENABLE_CONVERSATION_SUMMARY_MEMORY=true
MEMORY_CONTEXT_STRATEGY=summary
MEMORY_HISTORY_LIMIT=80
MEMORY_RECENT_MESSAGES_LIMIT=8
MEMORY_SUMMARY_TRIGGER_MESSAGES=20
MEMORY_MAX_SUMMARY_CHARS=6000
MEMORY_SUMMARY_USE_LLM=true
MEMORY_INJECT_RECENT_MESSAGES=true
MEMORY_INJECT_SUMMARY=true
###############################################################################
# LONG-TERM MEMORY
###############################################################################
ENABLE_LONG_TERM_MEMORY=true
LONG_TERM_MEMORY_PROVIDER=sqlite
LONG_TERM_MEMORY_SQLITE_PATH=./data/agent_framework.db
LONG_TERM_MEMORY_TABLE=agentfw_long_term_memory
# For Autonomous/Oracle, defaults to ${ADB_TABLE_PREFIX}_LONG_TERM_MEMORY
# LONG_TERM_MEMORY_ORACLE_TABLE=AGENTFW_LONG_TERM_MEMORY
LONG_TERM_MEMORY_MAX_CONTEXT_ITEMS=20
LONG_TERM_MEMORY_MIN_CONFIDENCE=0.70
LONG_TERM_MEMORY_AUTO_EXTRACT=true
LONG_TERM_MEMORY_INJECT_CONTEXT=true

195
Tuning-Performance/Normal/templates/agent_template_backend/.env
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@@ -1,195 +0,0 @@
###############################################################################
# AI AGENT PLATFORM - CONFIGURAÇÃO ÚNICA
# Este arquivo é lido por Pydantic Settings no framework e no backend template.
###############################################################################
APP_NAME=ai-agent-template
APP_ENV=local
LOG_LEVEL=INFO
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
###############################################################################
# LLM - OCI Generative AI como provider principal
###############################################################################
# Opções: mock, oci_openai, oci_sdk, openai_compatible
LLM_PROVIDER=oci_openai
LLM_TEMPERATURE=0.2
LLM_MAX_TOKENS=2048
LLM_TIMEOUT_SECONDS=120
# OCI OpenAI-compatible endpoint
OCI_GENAI_BASE_URL=https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1
OCI_GENAI_MODEL=openai.gpt-4.1
OCI_GENAI_API_KEY=sk-ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6
OCI_GENAI_PROJECT_OCID=
# OCI SDK / signer / profiles
OCI_CONFIG_FILE=~/.oci/config
OCI_PROFILE=DEFAULT
OCI_COMPARTMENT_ID=ocid1.compartment.oc1..aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
OCI_REGION=us-chicago-1
###############################################################################
# Persistência
###############################################################################
# Opções: memory, autonomous, mongodb
SESSION_REPOSITORY_PROVIDER=sqlite
MEMORY_REPOSITORY_PROVIDER=sqlite
CHECKPOINT_REPOSITORY_PROVIDER=sqlite
SQLITE_DB_PATH=./data/agent_framework.db
# Autonomous Database
ADB_USER=admin
ADB_PASSWORD=fjhsdf04954hf
ADB_DSN=oradb23aidev_high
ADB_WALLET_LOCATION=/ORACLE/DEFAULT/Wallet_ORADB23aiDev
ADB_WALLET_PASSWORD=fjhsdf04954hf
ADB_TABLE_PREFIX=AGENTFW
# MongoDB - também pode representar Autonomous usando API compatível com Mongo, se habilitada no ambiente
MONGODB_URI=mongodb://mongo:mongopassword@localhost:27017
MONGODB_DATABASE=agent_platform
# Redis
REDIS_URL=redis://localhost:6379/0
ENABLE_REDIS_CACHE=false
###############################################################################
# RAG / Vector / Graph
###############################################################################
VECTOR_STORE_PROVIDER=sqlite
GRAPH_STORE_PROVIDER=sqlite
RAG_TOP_K=5
EMBEDDING_PROVIDER=mock
OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
RAG_FILE_GLOBS=*.md,*.txt,*.yaml,*.yml,*.json
###############################################################################
# Observabilidade
###############################################################################
ENABLE_LANGFUSE=true
LANGFUSE_TRACE_MODE=compact # Opcional: verbose, compact
LANGFUSE_PUBLIC_KEY=pk-lf-2f9da109-5b0f-4c78-b61d-9598ed787eba
LANGFUSE_SECRET_KEY=sk-lf-a4cb0cdd-f2ea-4468-9911-cebeb91ba944
LANGFUSE_HOST=http://localhost:3005
ENABLE_OTEL=false
OTEL_EXPORTER_OTLP_ENDPOINT=
OTEL_SERVICE_NAME=ai-agent-template
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
###############################################################################
# Analytics / Observer corporativo
###############################################################################
# Quando true, AgentObserver publica eventos IC.*, NOC.* e GRL.* nos providers abaixo.
ENABLE_ANALYTICS=false
# Providers aceitos: oci_streaming,pubsub,noop
ANALYTICS_PROVIDERS=pubsub
# Compatibilidade FIRST/TIM: pode informar AGENT_PUBSUB_TOPIC diretamente.
AGENT_PUBSUB_TOPIC=
GCP_PUBSUB_TOPIC_PATH=
GCP_PROJECT_ID=
GCP_PUBSUB_TOPIC=
GCP_PUBSUB_TIMEOUT_SECONDS=30
# Credencial GCP segue padrão Google:
# GOOGLE_APPLICATION_CREDENTIALS=/secrets/gcp-service-account.json
###############################################################################
# OCI Streaming
###############################################################################
ENABLE_OCI_STREAMING=false
OCI_STREAM_ENDPOINT=
OCI_STREAM_OCID=
OCI_STREAM_PARTITION_KEY=agent-events
###############################################################################
# Guardrails, Judges, Supervisor
###############################################################################
ENABLE_INPUT_GUARDRAILS=true
ENABLE_OUTPUT_GUARDRAILS=true
ENABLE_JUDGES=true
ENABLE_SUPERVISOR=true
ENABLE_OUTPUT_SUPERVISOR=true
ENABLE_PARALLEL_GUARDRAILS=true
GUARDRAILS_FAIL_FAST=true
OUTPUT_SUPERVISOR_MAX_RETRIES=3
GUARDRAILS_CONFIG_PATH=./config/guardrails.yaml
JUDGES_CONFIG_PATH=./config/judges.yaml
PROMPT_POLICY_PATH=./config/prompt_policy.yaml
###############################################################################
# Gateway de canais
###############################################################################
DEFAULT_CHANNEL=web
# embedded = backend may parse simple/native channel payloads.
# external = backend only accepts GatewayRequest normalized by an external Channel Gateway.
FRAMEWORK_CHANNEL_INPUT_MODE=embedded
ENABLE_VOICE_ADAPTER=true
ENABLE_WHATSAPP_ADAPTER=true
ENABLE_TEXT_ADAPTER=true
#################################################
# ENTERPRISE ROUTING
#################################################
# Arquivo YAML com intents, keywords, políticas de estado e fallback.
ROUTING_CONFIG_PATH=./config/routing.yaml
# true = usa LLM para classificar quando keywords/estado não resolverem.
# Em produção, costuma ser útil; em desenvolvimento, false evita custo e latência.
ENABLE_LLM_ROUTER=true
###############################################################################
# MCP / Tools
###############################################################################
ENABLE_MCP_TOOLS=true
MCP_SERVERS_CONFIG_PATH=./config/mcp_servers.yaml
TOOLS_CONFIG_PATH=./config/tools.yaml
TOOL_POLICIES_PATH=./config/tool_policies.yaml
MCP_TOOL_TIMEOUT_SECONDS=30
# router = EnterpriseRouter seleciona um agente; supervisor = pode acionar múltiplos agentes
ROUTING_MODE=router
# Usage/cost accounting
USAGE_REPOSITORY_PROVIDER=sqlite
IDENTITY_CONFIG_PATH=./config/identity.yaml
MCP_PARAMETER_MAPPING_PATH=./config/mcp_parameter_mapping.yaml
# -----------------------------------------------------------------------------
# ConversationSummaryMemory / compressão de contexto conversacional
# -----------------------------------------------------------------------------
ENABLE_CONVERSATION_SUMMARY_MEMORY=true
MEMORY_CONTEXT_STRATEGY=summary
MEMORY_HISTORY_LIMIT=80
MEMORY_RECENT_MESSAGES_LIMIT=8
MEMORY_SUMMARY_TRIGGER_MESSAGES=20
MEMORY_MAX_SUMMARY_CHARS=6000
MEMORY_SUMMARY_USE_LLM=true
MEMORY_INJECT_RECENT_MESSAGES=true
MEMORY_INJECT_SUMMARY=true
###############################################################################
# MCP Gateway
###############################################################################
# true = framework routes tool calls to the dedicated MCP Gateway.
# false = framework calls MCP servers directly from mcp_servers.yaml.
MCP_GATEWAY_ENABLED=true
MCP_GATEWAY_URL=http://localhost:8300
MCP_GATEWAY_TIMEOUT_SECONDS=60
# MCP_GATEWAY_TOKEN=
MCP_GATEWAY_AGENT_ID=telecom_contas
MCP_GATEWAY_TENANT_ID=default
###############################################################################
# LONG-TERM MEMORY
###############################################################################
ENABLE_LONG_TERM_MEMORY=true
LONG_TERM_MEMORY_PROVIDER=sqlite
LONG_TERM_MEMORY_SQLITE_PATH=./data/agent_framework.db
LONG_TERM_MEMORY_TABLE=agentfw_long_term_memory
# For Autonomous/Oracle, defaults to ${ADB_TABLE_PREFIX}_LONG_TERM_MEMORY
# LONG_TERM_MEMORY_ORACLE_TABLE=AGENTFW_LONG_TERM_MEMORY
LONG_TERM_MEMORY_MAX_CONTEXT_ITEMS=20
LONG_TERM_MEMORY_MIN_CONFIDENCE=0.70
LONG_TERM_MEMORY_AUTO_EXTRACT=true
LONG_TERM_MEMORY_INJECT_CONTEXT=true

192
Tuning-Performance/Normal/templates/agent_template_backend_day_zero/.env
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@@ -1,192 +0,0 @@
###############################################################################
# AI AGENT PLATFORM - CONFIGURAÇÃO ÚNICA
# Este arquivo é lido por Pydantic Settings no framework e no backend template.
###############################################################################
APP_NAME=ai-agent-template
APP_ENV=local
LOG_LEVEL=INFO
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
###############################################################################
# LLM - OCI Generative AI como provider principal
###############################################################################
# Opções: mock, oci_openai, oci_sdk, openai_compatible
LLM_PROVIDER=oci_openai
LLM_TEMPERATURE=0.2
LLM_MAX_TOKENS=2048
LLM_TIMEOUT_SECONDS=120
# OCI OpenAI-compatible endpoint
OCI_GENAI_BASE_URL=https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1
OCI_GENAI_MODEL=openai.gpt-4.1
OCI_GENAI_API_KEY=sk-ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6
OCI_GENAI_PROJECT_OCID=
# OCI SDK / signer / profiles
OCI_CONFIG_FILE=~/.oci/config
OCI_PROFILE=DEFAULT
OCI_COMPARTMENT_ID=ocid1.compartment.oc1..aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
OCI_REGION=us-chicago-1
###############################################################################
# Persistência
###############################################################################
# Opções: memory, autonomous, mongodb
SESSION_REPOSITORY_PROVIDER=sqlite
MEMORY_REPOSITORY_PROVIDER=sqlite
CHECKPOINT_REPOSITORY_PROVIDER=sqlite
SQLITE_DB_PATH=./data/agent_framework.db
# Autonomous Database
ADB_USER=admin
ADB_PASSWORD=fjhsdf04954hf
ADB_DSN=oradb23aidev_high
ADB_WALLET_LOCATION=/ORACLE/DEFAULT/Wallet_ORADB23aiDev
ADB_WALLET_PASSWORD=fjhsdf04954hf
ADB_TABLE_PREFIX=AGENTFW
# MongoDB - também pode representar Autonomous usando API compatível com Mongo, se habilitada no ambiente
MONGODB_URI=mongodb://mongo:mongopassword@localhost:27017
MONGODB_DATABASE=agent_platform
# Redis
REDIS_URL=redis://localhost:6379/0
ENABLE_REDIS_CACHE=false
###############################################################################
# RAG / Vector / Graph
###############################################################################
VECTOR_STORE_PROVIDER=sqlite
GRAPH_STORE_PROVIDER=sqlite
RAG_TOP_K=5
EMBEDDING_PROVIDER=mock
OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
RAG_FILE_GLOBS=*.md,*.txt,*.yaml,*.yml,*.json
###############################################################################
# Observabilidade
###############################################################################
ENABLE_LANGFUSE=true
LANGFUSE_TRACE_MODE=compact # Opcional: verbose, compact
LANGFUSE_PUBLIC_KEY=pk-lf-2f9da109-5b0f-4c78-b61d-9598ed787eba
LANGFUSE_SECRET_KEY=sk-lf-a4cb0cdd-f2ea-4468-9911-cebeb91ba944
LANGFUSE_HOST=http://localhost:3005
ENABLE_OTEL=false
OTEL_EXPORTER_OTLP_ENDPOINT=
OTEL_SERVICE_NAME=ai-agent-template
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
###############################################################################
# Analytics / Observer corporativo
###############################################################################
# Quando true, AgentObserver publica eventos IC.*, NOC.* e GRL.* nos providers abaixo.
ENABLE_ANALYTICS=false
# Providers aceitos: oci_streaming,pubsub,noop
ANALYTICS_PROVIDERS=pubsub
# Compatibilidade FIRST/TIM: pode informar AGENT_PUBSUB_TOPIC diretamente.
AGENT_PUBSUB_TOPIC=
GCP_PUBSUB_TOPIC_PATH=
GCP_PROJECT_ID=
GCP_PUBSUB_TOPIC=
GCP_PUBSUB_TIMEOUT_SECONDS=30
# Credencial GCP segue padrão Google:
# GOOGLE_APPLICATION_CREDENTIALS=/secrets/gcp-service-account.json
###############################################################################
# OCI Streaming
###############################################################################
ENABLE_OCI_STREAMING=false
OCI_STREAM_ENDPOINT=
OCI_STREAM_OCID=
OCI_STREAM_PARTITION_KEY=agent-events
###############################################################################
# Guardrails, Judges, Supervisor
###############################################################################
ENABLE_INPUT_GUARDRAILS=true
ENABLE_OUTPUT_GUARDRAILS=true
ENABLE_JUDGES=true
ENABLE_SUPERVISOR=true
ENABLE_OUTPUT_SUPERVISOR=true
ENABLE_PARALLEL_GUARDRAILS=true
GUARDRAILS_FAIL_FAST=true
OUTPUT_SUPERVISOR_MAX_RETRIES=3
GUARDRAILS_CONFIG_PATH=./config/guardrails.yaml
JUDGES_CONFIG_PATH=./config/judges.yaml
PROMPT_POLICY_PATH=./config/prompt_policy.yaml
###############################################################################
# Gateway de canais
###############################################################################
DEFAULT_CHANNEL=web
ENABLE_VOICE_ADAPTER=true
ENABLE_WHATSAPP_ADAPTER=true
ENABLE_TEXT_ADAPTER=true
#################################################
# ENTERPRISE ROUTING
#################################################
# Arquivo YAML com intents, keywords, políticas de estado e fallback.
ROUTING_CONFIG_PATH=./config/routing.yaml
# true = usa LLM para classificar quando keywords/estado não resolverem.
# Em produção, costuma ser útil; em desenvolvimento, false evita custo e latência.
ENABLE_LLM_ROUTER=true
###############################################################################
# MCP / Tools
###############################################################################
ENABLE_MCP_TOOLS=true
MCP_SERVERS_CONFIG_PATH=./config/mcp_servers.yaml
TOOLS_CONFIG_PATH=./config/tools.yaml
TOOL_POLICIES_PATH=./config/tool_policies.yaml
MCP_TOOL_TIMEOUT_SECONDS=30
# router = EnterpriseRouter seleciona um agente; supervisor = pode acionar múltiplos agentes
ROUTING_MODE=router
# Usage/cost accounting
USAGE_REPOSITORY_PROVIDER=sqlite
IDENTITY_CONFIG_PATH=./config/identity.yaml
MCP_PARAMETER_MAPPING_PATH=./config/mcp_parameter_mapping.yaml
# -----------------------------------------------------------------------------
# ConversationSummaryMemory / compressão de contexto conversacional
# -----------------------------------------------------------------------------
ENABLE_CONVERSATION_SUMMARY_MEMORY=true
MEMORY_CONTEXT_STRATEGY=summary
MEMORY_HISTORY_LIMIT=80
MEMORY_RECENT_MESSAGES_LIMIT=8
MEMORY_SUMMARY_TRIGGER_MESSAGES=20
MEMORY_MAX_SUMMARY_CHARS=6000
MEMORY_SUMMARY_USE_LLM=true
MEMORY_INJECT_RECENT_MESSAGES=true
MEMORY_INJECT_SUMMARY=true
###############################################################################
# MCP Gateway
###############################################################################
# true = framework routes tool calls to the dedicated MCP Gateway.
# false = framework calls MCP servers directly from mcp_servers.yaml.
MCP_GATEWAY_ENABLED=true
MCP_GATEWAY_URL=http://localhost:8300
MCP_GATEWAY_TIMEOUT_SECONDS=60
# MCP_GATEWAY_TOKEN=
MCP_GATEWAY_AGENT_ID=telecom_contas
MCP_GATEWAY_TENANT_ID=default
###############################################################################
# LONG-TERM MEMORY
###############################################################################
ENABLE_LONG_TERM_MEMORY=true
LONG_TERM_MEMORY_PROVIDER=sqlite
LONG_TERM_MEMORY_SQLITE_PATH=./data/agent_framework.db
LONG_TERM_MEMORY_TABLE=agentfw_long_term_memory
# For Autonomous/Oracle, defaults to ${ADB_TABLE_PREFIX}_LONG_TERM_MEMORY
# LONG_TERM_MEMORY_ORACLE_TABLE=AGENTFW_LONG_TERM_MEMORY
LONG_TERM_MEMORY_MAX_CONTEXT_ITEMS=20
LONG_TERM_MEMORY_MIN_CONFIDENCE=0.70
LONG_TERM_MEMORY_AUTO_EXTRACT=true
LONG_TERM_MEMORY_INJECT_CONTEXT=true

207
Tuning-Performance/Route_Stickness/templates/agent_template_backend/.env
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@@ -1,207 +0,0 @@
###############################################################################
# AI AGENT PLATFORM - CONFIGURAÇÃO ÚNICA
# Este arquivo é lido por Pydantic Settings no framework e no backend template.
###############################################################################
APP_NAME=ai-agent-template
APP_ENV=local
LOG_LEVEL=INFO
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
###############################################################################
# LLM - OCI Generative AI como provider principal
###############################################################################
# Opções: mock, oci_openai, oci_sdk, openai_compatible
LLM_PROVIDER=oci_openai
LLM_TEMPERATURE=0.2
LLM_MAX_TOKENS=2048
LLM_TIMEOUT_SECONDS=120
# OCI OpenAI-compatible endpoint
OCI_GENAI_BASE_URL=https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1
OCI_GENAI_MODEL=openai.gpt-4.1
OCI_GENAI_API_KEY=sk-ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6
OCI_GENAI_PROJECT_OCID=
# OCI SDK / signer / profiles
OCI_CONFIG_FILE=~/.oci/config
OCI_PROFILE=DEFAULT
OCI_COMPARTMENT_ID=ocid1.compartment.oc1..aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
OCI_REGION=us-chicago-1
###############################################################################
# Persistência
###############################################################################
# Opções: memory, autonomous, mongodb
SESSION_REPOSITORY_PROVIDER=sqlite
MEMORY_REPOSITORY_PROVIDER=sqlite
CHECKPOINT_REPOSITORY_PROVIDER=sqlite
SQLITE_DB_PATH=./data/agent_framework.db
# Autonomous Database
ADB_USER=admin
ADB_PASSWORD=fjhsdf04954hf
ADB_DSN=oradb23aidev_high
ADB_WALLET_LOCATION=/ORACLE/DEFAULT/Wallet_ORADB23aiDev
ADB_WALLET_PASSWORD=fjhsdf04954hf
ADB_TABLE_PREFIX=AGENTFW
# MongoDB - também pode representar Autonomous usando API compatível com Mongo, se habilitada no ambiente
MONGODB_URI=mongodb://mongo:mongopassword@localhost:27017
MONGODB_DATABASE=agent_platform
# Redis
REDIS_URL=redis://localhost:6379/0
ENABLE_REDIS_CACHE=false
###############################################################################
# RAG / Vector / Graph
###############################################################################
VECTOR_STORE_PROVIDER=sqlite
GRAPH_STORE_PROVIDER=sqlite
RAG_TOP_K=5
EMBEDDING_PROVIDER=mock
OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
RAG_FILE_GLOBS=*.md,*.txt,*.yaml,*.yml,*.json
###############################################################################
# Observabilidade
###############################################################################
ENABLE_LANGFUSE=true
LANGFUSE_TRACE_MODE=compact # Opcional: verbose, compact
LANGFUSE_PUBLIC_KEY=pk-lf-2f9da109-5b0f-4c78-b61d-9598ed787eba
LANGFUSE_SECRET_KEY=sk-lf-a4cb0cdd-f2ea-4468-9911-cebeb91ba944
LANGFUSE_HOST=http://localhost:3005
ENABLE_OTEL=false
OTEL_EXPORTER_OTLP_ENDPOINT=
OTEL_SERVICE_NAME=ai-agent-template
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
###############################################################################
# Analytics / Observer corporativo
###############################################################################
# Quando true, AgentObserver publica eventos IC.*, NOC.* e GRL.* nos providers abaixo.
ENABLE_ANALYTICS=false
# Providers aceitos: oci_streaming,pubsub,noop
ANALYTICS_PROVIDERS=pubsub
# Compatibilidade FIRST/TIM: pode informar AGENT_PUBSUB_TOPIC diretamente.
AGENT_PUBSUB_TOPIC=
GCP_PUBSUB_TOPIC_PATH=
GCP_PROJECT_ID=
GCP_PUBSUB_TOPIC=
GCP_PUBSUB_TIMEOUT_SECONDS=30
# Credencial GCP segue padrão Google:
# GOOGLE_APPLICATION_CREDENTIALS=/secrets/gcp-service-account.json
###############################################################################
# OCI Streaming
###############################################################################
ENABLE_OCI_STREAMING=false
OCI_STREAM_ENDPOINT=
OCI_STREAM_OCID=
OCI_STREAM_PARTITION_KEY=agent-events
###############################################################################
# Guardrails, Judges, Supervisor
###############################################################################
ENABLE_INPUT_GUARDRAILS=true
ENABLE_OUTPUT_GUARDRAILS=true
ENABLE_JUDGES=true
ENABLE_SUPERVISOR=true
ENABLE_OUTPUT_SUPERVISOR=true
ENABLE_PARALLEL_GUARDRAILS=true
GUARDRAILS_FAIL_FAST=true
OUTPUT_SUPERVISOR_MAX_RETRIES=3
GUARDRAILS_CONFIG_PATH=./config/guardrails.yaml
JUDGES_CONFIG_PATH=./config/judges.yaml
PROMPT_POLICY_PATH=./config/prompt_policy.yaml
###############################################################################
# Gateway de canais
###############################################################################
DEFAULT_CHANNEL=web
# embedded = backend may parse simple/native channel payloads.
# external = backend only accepts GatewayRequest normalized by an external Channel Gateway.
FRAMEWORK_CHANNEL_INPUT_MODE=embedded
ENABLE_VOICE_ADAPTER=true
ENABLE_WHATSAPP_ADAPTER=true
ENABLE_TEXT_ADAPTER=true
#################################################
# ENTERPRISE ROUTING
#################################################
# Arquivo YAML com intents, keywords, políticas de estado e fallback.
ROUTING_CONFIG_PATH=./config/routing.yaml
# true = usa LLM para classificar quando keywords/estado não resolverem.
# Em produção, costuma ser útil; em desenvolvimento, false evita custo e latência.
ENABLE_LLM_ROUTER=true
# Semantic route stickiness (optional).
# Uses a lightweight LLM profile to decide only CONTINUE vs ROUTE.
# There are no regexes or deterministic language rules.
ENABLE_ROUTE_STICKINESS=true
ROUTE_STICKINESS_LLM_PROFILE=route_continuity
ROUTE_STICKINESS_CONFIDENCE_THRESHOLD=0.90
ROUTE_STICKINESS_HISTORY_TURNS=2
ROUTE_STICKINESS_MAX_TOKENS=80
HUMAN_HANDOFF_MESSAGE=Vou encaminhar seu atendimento para uma pessoa.
END_SESSION_MESSAGE=Atendimento encerrado. Obrigado pelo contato.
SESSION_ALREADY_ENDED_MESSAGE=Este atendimento já foi encerrado. Inicie uma nova sessão para continuar.
###############################################################################
# MCP / Tools
###############################################################################
ENABLE_MCP_TOOLS=true
MCP_SERVERS_CONFIG_PATH=./config/mcp_servers.yaml
TOOLS_CONFIG_PATH=./config/tools.yaml
TOOL_POLICIES_PATH=./config/tool_policies.yaml
MCP_TOOL_TIMEOUT_SECONDS=30
# router = EnterpriseRouter seleciona um agente; supervisor = pode acionar múltiplos agentes
ROUTING_MODE=router
# Usage/cost accounting
USAGE_REPOSITORY_PROVIDER=sqlite
IDENTITY_CONFIG_PATH=./config/identity.yaml
MCP_PARAMETER_MAPPING_PATH=./config/mcp_parameter_mapping.yaml
# -----------------------------------------------------------------------------
# ConversationSummaryMemory / compressão de contexto conversacional
# -----------------------------------------------------------------------------
ENABLE_CONVERSATION_SUMMARY_MEMORY=true
MEMORY_CONTEXT_STRATEGY=summary
MEMORY_HISTORY_LIMIT=80
MEMORY_RECENT_MESSAGES_LIMIT=8
MEMORY_SUMMARY_TRIGGER_MESSAGES=20
MEMORY_MAX_SUMMARY_CHARS=6000
MEMORY_SUMMARY_USE_LLM=true
MEMORY_INJECT_RECENT_MESSAGES=true
MEMORY_INJECT_SUMMARY=true
###############################################################################
# MCP Gateway
###############################################################################
# true = framework routes tool calls to the dedicated MCP Gateway.
# false = framework calls MCP servers directly from mcp_servers.yaml.
MCP_GATEWAY_ENABLED=true
MCP_GATEWAY_URL=http://localhost:8300
MCP_GATEWAY_TIMEOUT_SECONDS=60
# MCP_GATEWAY_TOKEN=
MCP_GATEWAY_AGENT_ID=telecom_contas
MCP_GATEWAY_TENANT_ID=default
###############################################################################
# LONG-TERM MEMORY
###############################################################################
ENABLE_LONG_TERM_MEMORY=true
LONG_TERM_MEMORY_PROVIDER=sqlite
LONG_TERM_MEMORY_SQLITE_PATH=./data/agent_framework.db
LONG_TERM_MEMORY_TABLE=agentfw_long_term_memory
# For Autonomous/Oracle, defaults to ${ADB_TABLE_PREFIX}_LONG_TERM_MEMORY
# LONG_TERM_MEMORY_ORACLE_TABLE=AGENTFW_LONG_TERM_MEMORY
LONG_TERM_MEMORY_MAX_CONTEXT_ITEMS=20
LONG_TERM_MEMORY_MIN_CONFIDENCE=0.70
LONG_TERM_MEMORY_AUTO_EXTRACT=true
LONG_TERM_MEMORY_INJECT_CONTEXT=true

202
Tuning-Performance/Route_Stickness/templates/agent_template_backend_day_zero/.env
View File

@@ -1,202 +0,0 @@
###############################################################################
# AI AGENT PLATFORM - CONFIGURAÇÃO ÚNICA
# Este arquivo é lido por Pydantic Settings no framework e no backend template.
###############################################################################
APP_NAME=ai-agent-template
APP_ENV=local
LOG_LEVEL=INFO
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
###############################################################################
# LLM - OCI Generative AI como provider principal
###############################################################################
# Opções: mock, oci_openai, oci_sdk, openai_compatible
LLM_PROVIDER=oci_openai
LLM_TEMPERATURE=0.2
LLM_MAX_TOKENS=2048
LLM_TIMEOUT_SECONDS=120
# OCI OpenAI-compatible endpoint
OCI_GENAI_BASE_URL=https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/openai/v1
OCI_GENAI_MODEL=openai.gpt-4.1
OCI_GENAI_API_KEY=sk-ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6ph3FgX6
OCI_GENAI_PROJECT_OCID=
# OCI SDK / signer / profiles
OCI_CONFIG_FILE=~/.oci/config
OCI_PROFILE=DEFAULT
OCI_COMPARTMENT_ID=ocid1.compartment.oc1..aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
OCI_REGION=us-chicago-1
###############################################################################
# Persistência
###############################################################################
# Opções: memory, autonomous, mongodb
SESSION_REPOSITORY_PROVIDER=sqlite
MEMORY_REPOSITORY_PROVIDER=sqlite
CHECKPOINT_REPOSITORY_PROVIDER=sqlite
SQLITE_DB_PATH=./data/agent_framework.db
# Autonomous Database
ADB_USER=admin
ADB_PASSWORD=fjhsdf04954hf
ADB_DSN=oradb23aidev_high
ADB_WALLET_LOCATION=/ORACLE/DEFAULT/Wallet_ORADB23aiDev
ADB_WALLET_PASSWORD=fjhsdf04954hf
ADB_TABLE_PREFIX=AGENTFW
# MongoDB - também pode representar Autonomous usando API compatível com Mongo, se habilitada no ambiente
MONGODB_URI=mongodb://mongo:mongopassword@localhost:27017
MONGODB_DATABASE=agent_platform
# Redis
REDIS_URL=redis://localhost:6379/0
ENABLE_REDIS_CACHE=false
###############################################################################
# RAG / Vector / Graph
###############################################################################
VECTOR_STORE_PROVIDER=sqlite
GRAPH_STORE_PROVIDER=sqlite
RAG_TOP_K=5
EMBEDDING_PROVIDER=mock
OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
RAG_FILE_GLOBS=*.md,*.txt,*.yaml,*.yml,*.json
###############################################################################
# Observabilidade
###############################################################################
ENABLE_LANGFUSE=true
LANGFUSE_TRACE_MODE=compact # Opcional: verbose, compact
LANGFUSE_PUBLIC_KEY=pk-lf-2f9da109-5b0f-4c78-b61d-9598ed787eba
LANGFUSE_SECRET_KEY=sk-lf-a4cb0cdd-f2ea-4468-9911-cebeb91ba944
LANGFUSE_HOST=http://localhost:3005
ENABLE_OTEL=false
OTEL_EXPORTER_OTLP_ENDPOINT=
OTEL_SERVICE_NAME=ai-agent-template
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
###############################################################################
# Analytics / Observer corporativo
###############################################################################
# Quando true, AgentObserver publica eventos IC.*, NOC.* e GRL.* nos providers abaixo.
ENABLE_ANALYTICS=false
# Providers aceitos: oci_streaming,pubsub,noop
ANALYTICS_PROVIDERS=pubsub
# Compatibilidade FIRST/TIM: pode informar AGENT_PUBSUB_TOPIC diretamente.
AGENT_PUBSUB_TOPIC=
GCP_PUBSUB_TOPIC_PATH=
GCP_PROJECT_ID=
GCP_PUBSUB_TOPIC=
GCP_PUBSUB_TIMEOUT_SECONDS=30
# Credencial GCP segue padrão Google:
# GOOGLE_APPLICATION_CREDENTIALS=/secrets/gcp-service-account.json
###############################################################################
# OCI Streaming
###############################################################################
ENABLE_OCI_STREAMING=false
OCI_STREAM_ENDPOINT=
OCI_STREAM_OCID=
OCI_STREAM_PARTITION_KEY=agent-events
###############################################################################
# Guardrails, Judges, Supervisor
###############################################################################
ENABLE_INPUT_GUARDRAILS=true
ENABLE_OUTPUT_GUARDRAILS=true
ENABLE_JUDGES=true
ENABLE_SUPERVISOR=true
ENABLE_OUTPUT_SUPERVISOR=true
ENABLE_PARALLEL_GUARDRAILS=true
GUARDRAILS_FAIL_FAST=true
OUTPUT_SUPERVISOR_MAX_RETRIES=3
GUARDRAILS_CONFIG_PATH=./config/guardrails.yaml
JUDGES_CONFIG_PATH=./config/judges.yaml
PROMPT_POLICY_PATH=./config/prompt_policy.yaml
###############################################################################
# Gateway de canais
###############################################################################
DEFAULT_CHANNEL=web
ENABLE_VOICE_ADAPTER=true
ENABLE_WHATSAPP_ADAPTER=true
ENABLE_TEXT_ADAPTER=true
#################################################
# ENTERPRISE ROUTING
#################################################
# Arquivo YAML com intents, keywords, políticas de estado e fallback.
ROUTING_CONFIG_PATH=./config/routing.yaml
# true = usa LLM para classificar quando keywords/estado não resolverem.
# Em produção, costuma ser útil; em desenvolvimento, false evita custo e latência.
ENABLE_LLM_ROUTER=true
# Continuidade semântica, handoff humano e encerramento global.
ENABLE_ROUTE_STICKINESS=true
ROUTE_STICKINESS_LLM_PROFILE=route_continuity
ROUTE_STICKINESS_CONFIDENCE_THRESHOLD=0.90
ROUTE_STICKINESS_HISTORY_TURNS=2
ROUTE_STICKINESS_MAX_TOKENS=80
HUMAN_HANDOFF_MESSAGE=Vou encaminhar seu atendimento para uma pessoa.
END_SESSION_MESSAGE=Atendimento encerrado. Obrigado pelo contato.
SESSION_ALREADY_ENDED_MESSAGE=Este atendimento já foi encerrado. Inicie uma nova sessão para continuar.
###############################################################################
# MCP / Tools
###############################################################################
ENABLE_MCP_TOOLS=true
MCP_SERVERS_CONFIG_PATH=./config/mcp_servers.yaml
TOOLS_CONFIG_PATH=./config/tools.yaml
TOOL_POLICIES_PATH=./config/tool_policies.yaml
MCP_TOOL_TIMEOUT_SECONDS=30
# router = EnterpriseRouter seleciona um agente; supervisor = pode acionar múltiplos agentes
ROUTING_MODE=router
# Usage/cost accounting
USAGE_REPOSITORY_PROVIDER=sqlite
IDENTITY_CONFIG_PATH=./config/identity.yaml
MCP_PARAMETER_MAPPING_PATH=./config/mcp_parameter_mapping.yaml
# -----------------------------------------------------------------------------
# ConversationSummaryMemory / compressão de contexto conversacional
# -----------------------------------------------------------------------------
ENABLE_CONVERSATION_SUMMARY_MEMORY=true
MEMORY_CONTEXT_STRATEGY=summary
MEMORY_HISTORY_LIMIT=80
MEMORY_RECENT_MESSAGES_LIMIT=8
MEMORY_SUMMARY_TRIGGER_MESSAGES=20
MEMORY_MAX_SUMMARY_CHARS=6000
MEMORY_SUMMARY_USE_LLM=true
MEMORY_INJECT_RECENT_MESSAGES=true
MEMORY_INJECT_SUMMARY=true
###############################################################################
# MCP Gateway
###############################################################################
# true = framework routes tool calls to the dedicated MCP Gateway.
# false = framework calls MCP servers directly from mcp_servers.yaml.
MCP_GATEWAY_ENABLED=true
MCP_GATEWAY_URL=http://localhost:8300
MCP_GATEWAY_TIMEOUT_SECONDS=60
# MCP_GATEWAY_TOKEN=
MCP_GATEWAY_AGENT_ID=telecom_contas
MCP_GATEWAY_TENANT_ID=default
###############################################################################
# LONG-TERM MEMORY
###############################################################################
ENABLE_LONG_TERM_MEMORY=true
LONG_TERM_MEMORY_PROVIDER=sqlite
LONG_TERM_MEMORY_SQLITE_PATH=./data/agent_framework.db
LONG_TERM_MEMORY_TABLE=agentfw_long_term_memory
# For Autonomous/Oracle, defaults to ${ADB_TABLE_PREFIX}_LONG_TERM_MEMORY
# LONG_TERM_MEMORY_ORACLE_TABLE=AGENTFW_LONG_TERM_MEMORY
LONG_TERM_MEMORY_MAX_CONTEXT_ITEMS=20
LONG_TERM_MEMORY_MIN_CONFIDENCE=0.70
LONG_TERM_MEMORY_AUTO_EXTRACT=true
LONG_TERM_MEMORY_INJECT_CONTEXT=true

207
Tuning-Performance/Transaction_Pre_Validation/agent_template_backend/.env
View File

@@ -1,207 +0,0 @@
###############################################################################
# AI AGENT PLATFORM - CONFIGURAÇÃO ÚNICA
# Este arquivo é lido por Pydantic Settings no framework e no backend template.
###############################################################################
APP_NAME=ai-agent-template
APP_ENV=local
LOG_LEVEL=INFO
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:5173,http://127.0.0.1:5173
###############################################################################
# LLM - OCI Generative AI como provider principal
###############################################################################
# Opções: mock, oci_openai, oci_sdk, openai_compatible
LLM_PROVIDER=oci_sdk
LLM_TEMPERATURE=0.2
LLM_MAX_TOKENS=2048
LLM_TIMEOUT_SECONDS=120
# OCI OpenAI-compatible endpoint
OCI_GENAI_BASE_URL=https://inference.generativeai.us-chicago-1.oci.oraclecloud.com
OCI_GENAI_MODEL=openai.gpt-4.1
OCI_GENAI_API_KEY=sk-ph3FgX6iP3fxAQCXb9IpPIDTadkeeYAWntUWhzcWysIM6zsS
OCI_GENAI_PROJECT_OCID=
#OCI_GENAI_BASE_URL=https://pegruagntaiatenddev.pe.inference.generativeai.sa-saopaulo-1.oci.oraclecloud.com
#OCI_GENAI_MODEL=openai.gpt-4.1
#OCI_GENAI_API_KEY=
#OCI_GENAI_PROJECT_OCID=
# OCI_AUTH_MODE=config_file|instance_principal|resource_principal
OCI_AUTH_MODE=config_file
# OCI SDK / signer / profiles
OCI_CONFIG_FILE=~/.oci/config
OCI_PROFILE=LATINOAMERICA-Chicago
OCI_COMPARTMENT_ID=ocid1.compartment.oc1..aaaaaaaaexpiw4a7dio64mkfv2t273s2hgdl6mgfvvyv7tycalnjlvpvfl3q
OCI_REGION=us-chicago-1
###############################################################################
# Persistência
###############################################################################
# Opções: memory, autonomous, mongodb
SESSION_REPOSITORY_PROVIDER=autonomous
MEMORY_REPOSITORY_PROVIDER=autonomous
CHECKPOINT_REPOSITORY_PROVIDER=autonomous
# Autonomous Database
ADB_USER=admin
ADB_PASSWORD=Moniquinha19721972
ADB_DSN=oradb23ai_high
ADB_WALLET_LOCATION=/mnt/d/Dropbox/ORACLE/LatinoAmerica/Wallet_ORADB23ai
ADB_WALLET_PASSWORD=Moniquinha1972
ADB_TABLE_PREFIX=AGENTFW
# MongoDB - também pode representar Autonomous usando API compatível com Mongo, se habilitada no ambiente
MONGODB_URI=mongodb://mongo:mongopassword@localhost:27017
MONGODB_DATABASE=agent_platform
# Redis
REDIS_URL=redis://localhost:6379/0
ENABLE_REDIS_CACHE=false
###############################################################################
# RAG / Vector / Graph
###############################################################################
VECTOR_STORE_PROVIDER=autonomous
GRAPH_STORE_PROVIDER=autonomous
RAG_TOP_K=5
EMBEDDING_PROVIDER=oci
OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
RAG_FILE_GLOBS=*.md,*.txt,*.yaml,*.yml,*.json
###############################################################################
# Observabilidade
###############################################################################
ENABLE_LANGFUSE=true
# Opcional: verbose, compact
LANGFUSE_TRACE_MODE=compact
# Nome customizado do trace pai, ex.: backoffice.checklist.workflow ou backoffice.emulador.workflow
LANGFUSE_COMPACT_VISIBLE_EVENT_PREFIXES=AGA.,NOC., IC.
LANGFUSE_COMPACT_SUPPRESSED_PREFIXES=llm.chat_completion
LANGFUSE_IGNORE_HEALTHCHECKS=true
LANGFUSE_IGNORED_PATHS=/health,/ready,/metrics
LANGFUSE_PUBLIC_KEY=pk-lf-4a1e3921-5158-4fd3-a16d-7a77549fb312
LANGFUSE_SECRET_KEY=sk-lf-efc6fd59-c5ec-4858-b6ec-4aa129734915
LANGFUSE_HOST=http://localhost:3005
ENABLE_OTEL=false
OTEL_EXPORTER_OTLP_ENDPOINT=
OTEL_SERVICE_NAME=ai-agent-template
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
ENABLE_LANGFUSE_ANALYTICS_PUBLISHER=false
###############################################################################
# Analytics / Observer corporativo
###############################################################################
# Quando true, AgentObserver publica eventos IC.*, NOC.* e GRL.* nos providers abaixo.
ENABLE_ANALYTICS=false
# Providers aceitos: oci_streaming,pubsub,noop
ANALYTICS_PROVIDERS=oci_streaming
# Compatibilidade FIRST/TIM: pode informar AGENT_PUBSUB_TOPIC diretamente.
AGENT_PUBSUB_TOPIC=
GCP_PUBSUB_TOPIC_PATH=
GCP_PROJECT_ID=
GCP_PUBSUB_TOPIC=
GCP_PUBSUB_TIMEOUT_SECONDS=30
# Credencial GCP segue padrão Google:
# GOOGLE_APPLICATION_CREDENTIALS=/secrets/gcp-service-account.json
###############################################################################
# OCI Streaming
###############################################################################
ENABLE_OCI_STREAMING=false
OCI_STREAM_ENDPOINT=
OCI_STREAM_OCID=
OCI_STREAM_PARTITION_KEY=agent-events
###############################################################################
# Guardrails, Judges, Supervisor
###############################################################################
ENABLE_INPUT_GUARDRAILS=true
ENABLE_OUTPUT_GUARDRAILS=true
ENABLE_JUDGES=true
ENABLE_SUPERVISOR=true
ENABLE_OUTPUT_SUPERVISOR=true
ENABLE_PARALLEL_GUARDRAILS=true
GUARDRAILS_FAIL_FAST=true
OUTPUT_SUPERVISOR_MAX_RETRIES=3
GUARDRAILS_CONFIG_PATH=./config/guardrails.yaml
JUDGES_CONFIG_PATH=./config/judges.yaml
PROMPT_POLICY_PATH=./config/prompt_policy.yaml
###############################################################################
# Gateway de canais
###############################################################################
DEFAULT_CHANNEL=web
# embedded = backend may parse simple/native channel payloads.
# external = backend only accepts GatewayRequest normalized by an external Channel Gateway.
FRAMEWORK_CHANNEL_INPUT_MODE=embedded
ENABLE_VOICE_ADAPTER=true
ENABLE_WHATSAPP_ADAPTER=true
ENABLE_TEXT_ADAPTER=true
#################################################
# ENTERPRISE ROUTING
#################################################
# Arquivo YAML com intents, keywords, políticas de estado e fallback.
ROUTING_CONFIG_PATH=./config/routing.yaml
# true = usa LLM para classificar quando keywords/estado não resolverem.
# Em produção, costuma ser útil; em desenvolvimento, false evita custo e latência.
ENABLE_LLM_ROUTER=true
# Semantic route stickiness (optional).
# Uses a lightweight LLM profile to decide only CONTINUE vs ROUTE.
# There are no regexes or deterministic language rules.
ENABLE_ROUTE_STICKINESS=true
ROUTE_STICKINESS_LLM_PROFILE=route_continuity
ROUTE_STICKINESS_CONFIDENCE_THRESHOLD=0.90
ROUTE_STICKINESS_HISTORY_TURNS=2
ROUTE_STICKINESS_MAX_TOKENS=80
HUMAN_HANDOFF_MESSAGE=Vou encaminhar seu atendimento para uma pessoa.
END_SESSION_MESSAGE=Atendimento encerrado. Obrigado pelo contato.
###############################################################################
# MCP / Tools
###############################################################################
ENABLE_MCP_TOOLS=true
MCP_SERVERS_CONFIG_PATH=./config/mcp_servers.yaml
TOOLS_CONFIG_PATH=./config/tools.yaml
MCP_TOOL_TIMEOUT_SECONDS=30
# router = EnterpriseRouter seleciona um agente; supervisor = pode acionar múltiplos agentes
ROUTING_MODE=router
# Usage/cost accounting
USAGE_REPOSITORY_PROVIDER=autonomous
IDENTITY_CONFIG_PATH=./config/identity.yaml
MCP_PARAMETER_MAPPING_PATH=./config/mcp_parameter_mapping.yaml
# -----------------------------------------------------------------------------
# ConversationSummaryMemory / compressão de contexto conversacional
# -----------------------------------------------------------------------------
ENABLE_CONVERSATION_SUMMARY_MEMORY=true
MEMORY_CONTEXT_STRATEGY=summary
MEMORY_HISTORY_LIMIT=80
MEMORY_RECENT_MESSAGES_LIMIT=8
MEMORY_SUMMARY_TRIGGER_MESSAGES=20
MEMORY_MAX_SUMMARY_CHARS=6000
MEMORY_SUMMARY_USE_LLM=true
MEMORY_INJECT_RECENT_MESSAGES=true
MEMORY_INJECT_SUMMARY=true
###############################################################################
# LONG-TERM MEMORY
###############################################################################
ENABLE_LONG_TERM_MEMORY=true
LONG_TERM_MEMORY_PROVIDER=sqlite
LONG_TERM_MEMORY_SQLITE_PATH=./data/agent_framework.db
LONG_TERM_MEMORY_TABLE=agentfw_long_term_memory
# For Autonomous/Oracle, defaults to ${ADB_TABLE_PREFIX}_LONG_TERM_MEMORY
# LONG_TERM_MEMORY_ORACLE_TABLE=AGENTFW_LONG_TERM_MEMORY
LONG_TERM_MEMORY_MAX_CONTEXT_ITEMS=20
LONG_TERM_MEMORY_MIN_CONFIDENCE=0.70
LONG_TERM_MEMORY_AUTO_EXTRACT=true
LONG_TERM_MEMORY_INJECT_CONTEXT=true

13
docs/developer/en/11_observability_persistence_and_operational_readiness.md
View File

@@ -200,6 +200,19 @@ request_id → tenant_id → agent_id → session_id → user_id → channel →
The context uses `ContextVar`, so it works across async calls, FastAPI, LangGraph, and LLM providers. The context uses `ContextVar`, so it works across async calls, FastAPI, LangGraph, and LLM providers.
### Langfuse OpenAI auto-instrumentation policy
The official framework template configuration is:
```env
ENABLE_LANGFUSE=true
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
```
The `false` value is intentional. The framework already records model calls through `Telemetry.generation(...)` and keeps each generation inside the request trace. Enabling `langfuse.openai` at the same time adds a second instrumentation layer and may produce standalone `OpenAI-generation` root traces, duplicate observations, and duplicate token/cost accounting.
Use `true` only to capture direct OpenAI/OpenAI-compatible SDK calls that occur outside the framework telemetry layer. This is a compatibility/diagnostic mode, not the operational default. Every `.env.example` in the repository must explicitly keep the value set to `false`.
### Langfuse ### Langfuse
Enable in `.env`: Enable in `.env`:

13
docs/developer/pt/11_observability_persistence_and_operational_readiness.md
View File

@@ -201,6 +201,19 @@ request_id → tenant_id → agent_id → session_id → user_id → channel →
O contexto usa `ContextVar`, portanto funciona em chamadas assíncronas, FastAPI, LangGraph e providers LLM. O contexto usa `ContextVar`, portanto funciona em chamadas assíncronas, FastAPI, LangGraph e providers LLM.
### Política de auto-instrumentação OpenAI no Langfuse
A configuração oficial dos templates do framework é:
```env
ENABLE_LANGFUSE=true
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
```
O `false` é intencional. O framework já registra as chamadas ao modelo usando `Telemetry.generation(...)` e mantém a generation dentro do trace da requisição. Habilitar simultaneamente `langfuse.openai` cria uma segunda camada de instrumentação e pode resultar em `OpenAI-generation` como trace raiz, observations duplicadas e dupla contabilização de tokens/custos.
Use `true` somente para capturar chamadas diretas ao SDK OpenAI/OpenAI-compatible que ocorram fora da telemetria do framework. Esse é um modo de compatibilidade/diagnóstico, não o padrão operacional. Todos os `.env.example` do repositório devem permanecer explicitamente com o valor `false`.
### Langfuse ### Langfuse
Ative no `.env`: Ative no `.env`:

11
libs/agent_framework/build/lib/agent_framework/guardrails/calibrated/llm_client.py
View File

@@ -145,8 +145,17 @@ class GuardrailLLMClient:
except RuntimeError: except RuntimeError:
return asyncio.run(_call()) return asyncio.run(_call())
# ``ContextVar`` values do not cross ThreadPoolExecutor boundaries by
# default. Preserve the framework request/trace/parent observation when
# this legacy sync bridge needs a worker thread; otherwise a provider
# created inside the worker sees no active correlation context and the
# optional langfuse.openai wrapper may emit a standalone OpenAI-generation
# trace.
from contextvars import copy_context
context = copy_context()
with ThreadPoolExecutor(max_workers=1, thread_name_prefix="guardrail-compat") as executor: with ThreadPoolExecutor(max_workers=1, thread_name_prefix="guardrail-compat") as executor:
return executor.submit(lambda: asyncio.run(_call())).result() return executor.submit(context.run, lambda: asyncio.run(_call())).result()
def classify( def classify(
self, self,

106
libs/agent_framework/build/lib/agent_framework/llm/providers.py
View File

@@ -58,6 +58,55 @@ def _coerce_reasoning_text(value: Any) -> str | None:
return text or None return text or None
def _coerce_message_content(value: Any) -> str:
"""Normalize OpenAI-compatible message content without using reasoning as answer.
OpenAI-compatible implementations may expose ``message.content`` as a plain
string, a list of content parts, or SDK objects/dicts containing ``text``.
Unknown shapes fail closed to an empty string instead of serializing the raw
response object into the assistant answer.
"""
if value is None:
return ""
if isinstance(value, str):
return value
if isinstance(value, (list, tuple)):
chunks: list[str] = []
for item in value:
if isinstance(item, str):
chunks.append(item)
continue
if isinstance(item, dict):
text = item.get("text")
if isinstance(text, str):
chunks.append(text)
continue
text = getattr(item, "text", None)
if isinstance(text, str):
chunks.append(text)
return "".join(chunks)
if isinstance(value, dict):
text = value.get("text")
return text if isinstance(text, str) else ""
text = getattr(value, "text", None)
return text if isinstance(text, str) else ""
def _extract_openai_message_content(message: Any) -> str:
if message is None:
return ""
if isinstance(message, dict):
return _coerce_message_content(message.get("content"))
return _coerce_message_content(getattr(message, "content", None))
def _extract_finish_reason(choice: Any) -> str | None:
if choice is None:
return None
value = choice.get("finish_reason") if isinstance(choice, dict) else getattr(choice, "finish_reason", None)
return str(value) if value is not None else None
def _extract_reasoning_content(obj: Any) -> str | None: def _extract_reasoning_content(obj: Any) -> str | None:
"""Best-effort extraction across OpenAI-compatible and OCI response shapes.""" """Best-effort extraction across OpenAI-compatible and OCI response shapes."""
if obj is None: if obj is None:
@@ -272,10 +321,27 @@ class OCICompatibleOpenAIProvider(LLMProvider):
getattr(settings, "ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", None) getattr(settings, "ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", None)
or os.getenv("ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", "false") or os.getenv("ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", "false")
).strip().lower() in {"1", "true", "yes", "on", "y"} ).strip().lower() in {"1", "true", "yes", "on", "y"}
if self.telemetry is not None and use_langfuse_wrapper:
# The framework owns Langfuse correlation. Even compatibility paths may
# instantiate a provider without passing ``Telemetry`` explicitly while a
# request is already active (for example GuardrailLLMClient running in its
# sync bridge). In that situation langfuse.openai would auto-create an
# ``OpenAI-generation`` root trace instead of attaching to the business
# request. Treat an active framework observability context exactly like
# an injected Telemetry instance and keep the standard OpenAI client.
active_framework_trace = False
try:
from agent_framework.observability.context import get_observability_context
obs_ctx = get_observability_context()
active_framework_trace = bool(obs_ctx.trace_id or obs_ctx.request_id)
except Exception:
active_framework_trace = False
if use_langfuse_wrapper and (self.telemetry is not None or active_framework_trace):
logger.warning( logger.warning(
"ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ignorado porque o provider já recebeu " "ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ignorado durante execução correlacionada "
"Telemetry do framework; instrumentação dupla pode criar observations fora do contrato de mapping." "do framework; langfuse.openai pode criar OpenAI-generation como trace raiz separado."
) )
use_langfuse_wrapper = False use_langfuse_wrapper = False
if getattr(settings, "ENABLE_LANGFUSE", False) and use_langfuse_wrapper: if getattr(settings, "ENABLE_LANGFUSE", False) and use_langfuse_wrapper:
@@ -432,9 +498,29 @@ class OCICompatibleOpenAIProvider(LLMProvider):
model_parameters=model_parameters, model_parameters=model_parameters,
) as generation: ) as generation:
resp = await client.chat.completions.create(**request_kwargs) resp = await client.chat.completions.create(**request_kwargs)
message = resp.choices[0].message choices = getattr(resp, "choices", None) or []
answer = message.content or "" if not choices:
reasoning_content = _extract_reasoning_content(message) message = None
answer = ""
reasoning_content = None
finish_reason = None
logger.warning(
"OpenAI-compatible LLM returned no choices provider=%s model=%s profile=%s component=%s",
provider, model, resolved_profile_name, component_name,
)
else:
choice = choices[0]
message = choice.get("message") if isinstance(choice, dict) else getattr(choice, "message", None)
answer = _extract_openai_message_content(message)
reasoning_content = _extract_reasoning_content(message)
finish_reason = _extract_finish_reason(choice)
logger.info(
"OpenAI-compatible LLM response provider=%s model=%s profile=%s component=%s "
"finish_reason=%s content_len=%d reasoning_len=%d",
provider, model, resolved_profile_name, component_name,
finish_reason, len(answer), len(reasoning_content or ""),
)
usage_metadata = self.token_collector.enrich(model, getattr(resp, "usage", None)) usage_metadata = self.token_collector.enrich(model, getattr(resp, "usage", None))
usage_metadata.update({ usage_metadata.update({
@@ -445,8 +531,16 @@ class OCICompatibleOpenAIProvider(LLMProvider):
"component": component_name, "component": component_name,
"model": model, "model": model,
"provider": provider, "provider": provider,
"finish_reason": finish_reason,
"content_length": len(answer),
"reasoning_content_length": len(reasoning_content or ""),
**model_parameters, **model_parameters,
}) })
llm_metadata.update({
"finish_reason": finish_reason,
"content_length": len(answer),
"reasoning_content_length": len(reasoning_content or ""),
})
generation.set_output(answer) generation.set_output(answer)
generation.set_usage(usage_metadata) generation.set_usage(usage_metadata)
generation.set_metadata(**usage_metadata) generation.set_metadata(**usage_metadata)

8
libs/agent_framework/docs/LANGFUSE_TRACE_CORRELATION_FIX.md
View File

@@ -47,13 +47,13 @@ internal steps = observations/spans/generations inside that trace
- Langfuse OpenAI auto-instrumentation is now opt-in. - Langfuse OpenAI auto-instrumentation is now opt-in.
- Default behavior uses the standard `openai.AsyncOpenAI` client and relies on the framework's own `Telemetry.generation(...)` to create correlated Langfuse generations. - Default behavior uses the standard `openai.AsyncOpenAI` client and relies on the framework's own `Telemetry.generation(...)` to create correlated Langfuse generations.
- To re-enable wrapper-based auto-instrumentation, set: - The supported framework default is:
```env ```env
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
``` ```
For this framework, the recommended default is to keep it disabled. All `.env.example` files in the repository declare this value explicitly. Set it to `true` only for isolated compatibility/diagnostic deployments that intentionally need to capture OpenAI SDK calls outside the framework telemetry path.
## Expected result ## Expected result
@@ -86,7 +86,7 @@ framework_judges
Run the backend and execute one request. Then verify: Run the backend and execute one request. Then verify:
1. The `Traces` screen has one trace row for the request, not one row per node. 1. The `Traces` screen has one trace row for the request, not one row per node.
2. `OpenAI-generation` no longer appears as a separate top-level trace unless `ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true`. 2. `OpenAI-generation` no longer appears as a separate top-level trace with the supported default `ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false`.
3. LangGraph node events and IC/NOC/GRL events appear under the same request trace. 3. LangGraph node events and IC/NOC/GRL events appear under the same request trace.

11
libs/agent_framework/src/agent_framework/guardrails/calibrated/llm_client.py
View File

@@ -145,8 +145,17 @@ class GuardrailLLMClient:
except RuntimeError: except RuntimeError:
return asyncio.run(_call()) return asyncio.run(_call())
# ``ContextVar`` values do not cross ThreadPoolExecutor boundaries by
# default. Preserve the framework request/trace/parent observation when
# this legacy sync bridge needs a worker thread; otherwise a provider
# created inside the worker sees no active correlation context and the
# optional langfuse.openai wrapper may emit a standalone OpenAI-generation
# trace.
from contextvars import copy_context
context = copy_context()
with ThreadPoolExecutor(max_workers=1, thread_name_prefix="guardrail-compat") as executor: with ThreadPoolExecutor(max_workers=1, thread_name_prefix="guardrail-compat") as executor:
return executor.submit(lambda: asyncio.run(_call())).result() return executor.submit(context.run, lambda: asyncio.run(_call())).result()
def classify( def classify(
self, self,

23
libs/agent_framework/src/agent_framework/llm/providers.py
View File

@@ -321,10 +321,27 @@ class OCICompatibleOpenAIProvider(LLMProvider):
getattr(settings, "ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", None) getattr(settings, "ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", None)
or os.getenv("ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", "false") or os.getenv("ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", "false")
).strip().lower() in {"1", "true", "yes", "on", "y"} ).strip().lower() in {"1", "true", "yes", "on", "y"}
if self.telemetry is not None and use_langfuse_wrapper:
# The framework owns Langfuse correlation. Even compatibility paths may
# instantiate a provider without passing ``Telemetry`` explicitly while a
# request is already active (for example GuardrailLLMClient running in its
# sync bridge). In that situation langfuse.openai would auto-create an
# ``OpenAI-generation`` root trace instead of attaching to the business
# request. Treat an active framework observability context exactly like
# an injected Telemetry instance and keep the standard OpenAI client.
active_framework_trace = False
try:
from agent_framework.observability.context import get_observability_context
obs_ctx = get_observability_context()
active_framework_trace = bool(obs_ctx.trace_id or obs_ctx.request_id)
except Exception:
active_framework_trace = False
if use_langfuse_wrapper and (self.telemetry is not None or active_framework_trace):
logger.warning( logger.warning(
"ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ignorado porque o provider já recebeu " "ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ignorado durante execução correlacionada "
"Telemetry do framework; instrumentação dupla pode criar observations fora do contrato de mapping." "do framework; langfuse.openai pode criar OpenAI-generation como trace raiz separado."
) )
use_langfuse_wrapper = False use_langfuse_wrapper = False
if getattr(settings, "ENABLE_LANGFUSE", False) and use_langfuse_wrapper: if getattr(settings, "ENABLE_LANGFUSE", False) and use_langfuse_wrapper:

64
tests/unit/test_langfuse_openai_correlation_guardrail.py Normal file
View File

@@ -0,0 +1,64 @@
from __future__ import annotations
from types import ModuleType, SimpleNamespace
import sys
import pytest
from agent_framework.guardrails.calibrated.llm_client import GuardrailLLMClient
from agent_framework.llm.providers import OCICompatibleOpenAIProvider
from agent_framework.observability.context import (
clear_observability_context,
get_observability_context,
set_observability_context,
)
def test_openai_langfuse_wrapper_is_disabled_inside_active_framework_trace(monkeypatch):
"""A correlated request must never create a standalone OpenAI-generation trace."""
clear_observability_context()
set_observability_context(request_id="req-123", trace_id="trace-123")
monkeypatch.setenv("ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", "true")
provider = OCICompatibleOpenAIProvider.__new__(OCICompatibleOpenAIProvider)
provider.telemetry = None # compatibility path: no Telemetry explicitly injected
settings = SimpleNamespace(
ENABLE_LANGFUSE=True,
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=True,
)
fake_openai = ModuleType("openai")
class AsyncOpenAI:
pass
AsyncOpenAI.__module__ = "openai"
fake_openai.AsyncOpenAI = AsyncOpenAI
monkeypatch.setitem(sys.modules, "openai", fake_openai)
client_cls = provider._resolve_async_openai(settings)
# Standard OpenAI client = framework owns observability/correlation.
assert client_cls.__module__.startswith("openai")
assert "langfuse" not in client_cls.__module__
clear_observability_context()
@pytest.mark.asyncio
async def test_guardrail_sync_bridge_preserves_observability_context_in_worker(monkeypatch):
"""Legacy sync guardrail bridge must carry request/trace ContextVars to its worker."""
clear_observability_context()
set_observability_context(request_id="req-guardrail", trace_id="trace-guardrail")
import agent_framework.guardrails.framework_llm_client as framework_client
async def fake_classifier(llm, task, payload, **kwargs):
ctx = get_observability_context()
return {"request_id": ctx.request_id, "trace_id": ctx.trace_id, "task": task}
monkeypatch.setattr(framework_client, "classify_with_framework_llm", fake_classifier)
result = GuardrailLLMClient._run_framework_classifier("TOX", {"text": "ok"})
assert result["request_id"] == "req-guardrail"
assert result["trace_id"] == "trace-guardrail"
assert result["task"] == "TOX"
clear_observability_context()