Ajustes conforme relatorio de testes 2026-08-27

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2026-08-29 21:04:31 -03:00
parent 83bf961185
commit c8c83981c4
18 changed files with 264 additions and 1743 deletions

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@@ -2171,71 +2171,30 @@ trace_id
#### 5.1.1.21.3. Instrumentação automática do cliente OpenAI pelo Langfuse
O padrão oficial do framework é:
```python
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
```env
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.
* 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 `false`:
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.
* Ambientes de homologação.
* Ambientes de produção que necessitem observabilidade detalhada das chamadas LLM.
* Cenários de troubleshooting, tuning de prompts e análise de custos.
```env
# Padrão recomendado para todos os templates e ambientes do framework
ENABLE_LANGFUSE=true
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
```
Observação
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
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.
#### 5.1.1.22.1. Para demos e desenvolvimento

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@@ -2167,71 +2167,30 @@ trace_id
#### 5.1.1.21.3. Automatic Langfuse instrumentation for the OpenAI client
```python
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true
```
The framework's official default is:
enables automatic Langfuse instrumentation for the OpenAI client.
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
```env
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.
* Custom framework spans are still emitted.
* Langfuse no longer automatically creates OpenAI-generation entries.
* Less detailed information is available for analyzing model interactions.
When set to `false`:
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
* Testing and staging environments
* Production environments that require detailed LLM observability
* Prompt engineering, troubleshooting, and cost analysis scenarios
```env
# Recommended default for every framework template and environment
ENABLE_LANGFUSE=true
ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=false
```
Important Note
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
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.
#### 5.1.1.22.1. For demos and development

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@@ -1,211 +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.
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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@@ -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

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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

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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

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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

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_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

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

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

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.
### 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
Enable in `.env`:

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.
### 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
Ative no `.env`:

View File

@@ -145,8 +145,17 @@ class GuardrailLLMClient:
except RuntimeError:
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:
return executor.submit(lambda: asyncio.run(_call())).result()
return executor.submit(context.run, lambda: asyncio.run(_call())).result()
def classify(
self,

View File

@@ -58,6 +58,55 @@ def _coerce_reasoning_text(value: Any) -> str | 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:
"""Best-effort extraction across OpenAI-compatible and OCI response shapes."""
if obj is None:
@@ -272,10 +321,27 @@ class OCICompatibleOpenAIProvider(LLMProvider):
getattr(settings, "ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", None)
or os.getenv("ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", "false")
).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(
"ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ignorado porque o provider já recebeu "
"Telemetry do framework; instrumentação dupla pode criar observations fora do contrato de mapping."
"ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ignorado durante execução correlacionada "
"do framework; langfuse.openai pode criar OpenAI-generation como trace raiz separado."
)
use_langfuse_wrapper = False
if getattr(settings, "ENABLE_LANGFUSE", False) and use_langfuse_wrapper:
@@ -432,9 +498,29 @@ class OCICompatibleOpenAIProvider(LLMProvider):
model_parameters=model_parameters,
) as generation:
resp = await client.chat.completions.create(**request_kwargs)
message = resp.choices[0].message
answer = message.content or ""
reasoning_content = _extract_reasoning_content(message)
choices = getattr(resp, "choices", None) or []
if not choices:
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.update({
@@ -445,8 +531,16 @@ class OCICompatibleOpenAIProvider(LLMProvider):
"component": component_name,
"model": model,
"provider": provider,
"finish_reason": finish_reason,
"content_length": len(answer),
"reasoning_content_length": len(reasoning_content or ""),
**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_usage(usage_metadata)
generation.set_metadata(**usage_metadata)

View File

@@ -47,13 +47,13 @@ internal steps = observations/spans/generations inside that trace
- 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.
- To re-enable wrapper-based auto-instrumentation, set:
- The supported framework default is:
```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
@@ -86,7 +86,7 @@ framework_judges
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.
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.

View File

@@ -145,8 +145,17 @@ class GuardrailLLMClient:
except RuntimeError:
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:
return executor.submit(lambda: asyncio.run(_call())).result()
return executor.submit(context.run, lambda: asyncio.run(_call())).result()
def classify(
self,

View File

@@ -321,10 +321,27 @@ class OCICompatibleOpenAIProvider(LLMProvider):
getattr(settings, "ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", None)
or os.getenv("ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION", "false")
).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(
"ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ignorado porque o provider já recebeu "
"Telemetry do framework; instrumentação dupla pode criar observations fora do contrato de mapping."
"ENABLE_LANGFUSE_OPENAI_AUTO_INSTRUMENTATION=true ignorado durante execução correlacionada "
"do framework; langfuse.openai pode criar OpenAI-generation como trace raiz separado."
)
use_langfuse_wrapper = False
if getattr(settings, "ENABLE_LANGFUSE", False) and use_langfuse_wrapper:

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()