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Advanced Fast Line Pro: streaming and completion

Optional track — for those who already completed basic Fastline (action_fastline_pro) and want to understand production-ready patterns. Not required to complete the core track.

Required permissions and access

Module / setting Why you need it
Scenario Builder Reverse engineering existing sections
Fast Line Pro Agent vs Chatbot, streaming
Runs / Chat preview Trace edges and variables
Access to a production/dev scenario (optional) RE lab on a real flow

Business context

In production scenarios, Fastline often uses not only action_fastline_pro, but also completion nodes, streaming replies, and multi-step agent chains. This Use Case teaches you to read and understand such patterns through reverse engineering — without a mandatory from-scratch build.

Expected result

  • You understand the difference between Chatbot and Agent in Fast Line Pro
  • You can explain where fastline_completion / streaming appear in a scenario
  • Reverse engineering: 10 control questions for a production section (or RE lab)
  • Self-check without escalating to a mentor

Key concepts

Pattern Purpose Core track
action_fastline_pro FAQ, categorizer Use Case 1, 10
fastline_completion Completing a multi-turn agent loop Optional
Streaming Partial reply in the channel before full completion Optional
Agent (Fast Line Pro) Tools + advanced modes When tools are needed, not “just FAQ”
Symptom Solution
Unclear, Chatbot or Agent FAQ / categorizer → Chatbot; tools / streaming → Agent (step 5 below)
Confusion about streaming / completion This optional Use Case

Fast Line Pro action

Step-by-step implementation (reverse engineering)

Step 1. Baseline — your Use Case 1

Open the Use Case 1 flow in Scenario Builder:

Question Your answer (write it down)
Which agent_name?
Which variable for the reply?
How many edges on action_fastline_pro?
What happens without a fallback edge?

Verify the answers in Runs.


Step 2. Find completion in the documentation

  1. Open the actions reference.
  2. Find fastline_completion (or the current equivalent on your instance).
  3. Write down: input parameters, output edges, difference from action_fastline_pro.
Criterion action_fastline_pro fastline_completion
Typical use case One request → reply Completing an agent session
Streaming Usually no May be related
Core training Yes Optional

Step 3. RE lab — production section

Use the reverse-engineering-lab or a production section you have read-only access to:

  1. Find all Fastline nodes (pro, completion, others).
  2. Draw a text data flow (Start → … → End).
  3. For each Action node — list of edges (success, error, fallback).

10 control questions (example):

  1. Where is conversation_id stored?
  2. Which edge on an empty AI reply?
  3. Is there a streaming parameter in node_params?
  4. How many Fastline nodes are in the chain?
  5. Where is handoff to an operator?
  6. Which variables land in constants after completion?
  7. Is there a retry loop?
  8. Fallback at section or node level?
  9. Agent or Chatbot in Fast Line Pro?
  10. What happens on timeout?

Step 4. Streaming (theory + Runs)

Streaming in a channel means: the customer sees parts of the reply before generation finishes.

Self-check Action
Find streaming in docs Fast Line Pro
Compare with non-streaming Runs One Run with pro without streaming
Record the UX difference In the result template — 2–3 sentences

If streaming is unavailable on the training instance — record that in the self-check (not a blocker).


Step 5. Chatbot vs Agent (capability-based decision)

Type What it can do When to choose
Chatbot Replies from KB/prompt; no tools FAQ, categorizer, typical action_fastline_pro
Agent Same + Tools and advanced modes (streaming, etc.) When AI must call tools / external actions

Rule: do not pick Agent “just in case”. If you only need KB replies — Chatbot is enough (as in Use Case 1).

Troubleshooting

Symptom What to check
Completion is not called Node order: pro → completion; conversation_id
Streaming is “choppy” Channel (TG vs widget); streaming docs
RE lab is unclear Start from Use Case 1 baseline; smaller section

Self-check

Independent task

In a production scenario (or RE lab), find one node that can be replaced with action_fastline_pro + fallback without losing the happy path — justify in 5 sentences.

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