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t
tushar
Offline, last seen 4 months ago
Joined September 25, 2024
Hi, I am not able to understand how does the Query Pipeline work w.r.t the DAG use case here: https://docs.llamaindex.ai/en/stable/examples/pipeline/query_pipeline_sql/
Once we add the chains and links for the DAG, how is the decision made to traverse a particular path. The following is the QP created:

qp.add_chain(["input", "table_retriever", "table_output_parser"])
qp.add_link("input", "text2sql_prompt", dest_key="query_str")
qp.add_link("table_output_parser", "text2sql_prompt", dest_key="schema")
qp.add_chain(
["text2sql_prompt", "text2sql_llm", "sql_output_parser", "sql_retriever"]
)
qp.add_link(
"sql_output_parser", "response_synthesis_prompt", dest_key="sql_query"
)
qp.add_link(
"sql_retriever", "response_synthesis_prompt", dest_key="context_str"
)
qp.add_link("input", "response_synthesis_prompt", dest_key="query_str")
qp.add_link("response_synthesis_prompt", "response_synthesis_llm")

Now when we run the query:

response = qp.run(
query="What was the year that The Notorious B.I.G was signed to Bad Boy?"
)
print(str(response))

How does the code know which path to take?
3 comments
L
t
t
tushar
·

Api

Can something be done about the API documentation structure? Why is it structured topic wise? In the API reference, viewing based on categories does not help. Please have a look at LangChain documentation.
2 comments
t
L