Files

Roberto Musso 971f1dd84f feat(batch-agent): integrate Langfuse tracing

- tracing.py: init/shutdown, trace_span, get_langfuse_callback, prompt mgmt
- main.py: init_langfuse at startup, shutdown on teardown
- redis_consumer.py: trace_span around journey_start/message/agent_trigger
- agent_runner.py: thread langfuse_handler through classify + processing LLM
- journey.py: thread langfuse_handler through _call_llm_with_tools
- llm.py: accept callbacks param, forward to LLM constructors
- requirements.txt: add langfuse>=3.0.0

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app

feat(batch-agent): integrate Langfuse tracing

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Dockerfile

feat(batch-agent): extract Batch Agent Service (Step 3)

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README.md

docs: add Langfuse integration TODO for batch-agent service

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requirements.txt

feat(batch-agent): integrate Langfuse tracing

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README.md

Batch Agent Service

Owns: agent_runner, journey builder, filesystem_agent, integrations (Gmail, MS Graph).

Tables owned

local_agent_configs
cloud_agent_configs
agent_run_logs

Endpoints

GET /agents/catalog
POST /agents/can-create
POST /agents/trigger
GET /agents/{id}/history

Redis channels

Subscribe: batch:request:{user_id}
Publish: ws:out:{user_id} (journey replies + tool calls)
BRPOP: tool:result:{call_id} (30s timeout)
SET+EX: journey:{user_id} (session state, TTL 1800s)

TODO

Integrate Langfuse tracing (reuse services/chat/app/tracing.py pattern — trace_span(), get_langfuse_callback(), prompt management). Each batch agent run should create a trace with input/output, link prompts, and pass the LangChain CallbackHandler to LLM calls.