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How do we migrate our existing customer chatbot from Dialogflow to a modern LLM-powered agent without losing our conversation history

ChatGPTgpt-61 query11/1/2026
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Fan-out diagram

The searches the AI actually ran for this prompt.

SEED QUERY
How do we migrate our existing customer chatbot from Dialogflow to a modern LLM-powered agent without losing our conversation history
1 real search · 1 real-search pass
Google Dialogflow CX export conversation history interaction logs BigQuery export agents documentation; Dialogflow ES conversation history export logs documentation; Google Cloud migrate Dialogflow to generative AI agent architectureGoogle ↗
OBSERVEDInstruction

Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.

Query classes

Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.

ChatGPT real searches (1)
Short factOther / navigationalComparisonConsequenceReasonDefinitionInstruction100%Yes / no

Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.

Searches and sources

ChatGPT1 real searches · gpt-6
Google Dialogflow CX export conversation history interaction logs BigQuery export agents documentation; Dialogflow ES conversation history export logs documentation; Google Cloud migrate Dialogflow to generative AI agent architecture Google ↗

Queries

1 queries · click a column to sort
Query / typeSearchIntentQuery classRouting formatClusterFreq ↓Weight
Google Dialogflow CX export conversation history interaction logs BigQuery export agents documentation; Dialogflow ES conversation history export logs documentation; Google Cloud migrate Dialogflow to generative AI agent architecture
OBSERVED
Google ↗
AI Mode ↗
—Instruction——1x
of 1