Please stand by @vinodvarma24 as I search the knowledge base. We are experiencing especially high traffic right now and might take longer than usual. :wave:
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To get the results from the SQL Query Engine without synthesizing the response, you can set the
synthesize_response
parameter to
False
when initializing the query engine. This will return the raw SQL query result. Here is an example of how to do this:
from llama_index.indices.struct_store.sql_query import NLSQLTableQueryEngine
from IPython.display import Markdown, display
query_engine = NLSQLTableQueryEngine(
sql_database=sql_database,
synthesize_response=False,
tables=["github_issues", "github_comments", "github_users"],
)
query_str = (
"Which issues have the most comments? Give the top 10 and use a join on url."
)
response = query_engine.query(query_str)
display(Markdown(f"<b>{response}</b>"))
In this example,
response
will contain the raw SQL query result. If you want to display the original SQL query, you can do so by accessing the
metadata
attribute of the response:
sql_query = response.metadata["sql_query"]
display(Markdown(f"<b>{sql_query}</b>"))
Please note that the actual structure of the result may depend on the specific SQL database you are using. For more details, you can refer to the
SQL Query Engine documentation ().
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@kapa.ai I understand that, but if enable the option synthesize_response=False
, the response i get is not having the header with column names from the sql query output
Let me check the knowledge base for you. One moment! :books:
----------------------
I'm sorry for the confusion, but based on the provided extracts, there's no explicit information on how to include the column names or headers in the raw SQL query result when synthesize_response=False
is set in the NLSQLTableQueryEngine
.
However, typically, when working with SQL databases, the column names are included in the result set by default. If they are not included in your case, it might be due to the specific way the sql_database
object or the query
method is implemented.
I recommend checking the documentation or the implementation of these components for more details. If you're using a custom SQL database interface, make sure it's configured to include column names in the result set.
If you're still having trouble, you might want to consider reaching out to the maintainers of the LlamaIndex project or the community for more specific guidance.
----------------------
Note: you can ask me a follow up question by @ mentioning me again
:speech_balloon:
----------------------
@kapa.ai @Logan M Currently, when I run this: query_engine = SQLTableRetrieverQueryEngine(
sql_database,
object_index.as_retriever(similarity_top_k=3),
synthesize_response = False,
# response_synthesis_prompt=sql_response_synthesis_prompt,
service_context=service_context
)
response = query_engine.query("Give me the sales by each country")
Let me check the knowledge base for you. One moment! :books:
------- I'm getting this response without the column headers in the response: Response(response="[('USA', 523.0600000000003), ('Canada', 303.9599999999999), ('France', 195.09999999999994), ('Brazil', 190.09999999999997), ('Germany', 156.48), ('United Kingdom', 112.85999999999999), ('Czech Republic', 90.24000000000001), ('Portugal', 77.23999999999998), ('India', 75.25999999999999), ('Chile', 46.62), ('Ireland', 45.62), ('Hungary', 45.62), ('Austria', 42.62), ('Finland', 41.620000000000005), ('Netherlands', 40.62), ('Norway', 39.62), ('Sweden', 38.620000000000005), ('Poland', 37.620000000000005), ('Italy', 37.620000000000005), ('Denmark', 37.620000000000005), ('Australia', 37.620000000000005), ('Argentina', 37.620000000000005), ('Spain', 37.62), ('Belgium', 37.62)]", source_nodes=[], metadata={'result': [('USA', 523.0600000000003), ('Canada', 303.9599999999999), ('France', 195.09999999999994), ('Brazil', 190.09999999999997), ('Germany', 156.48), ('United Kingdom', 112.85999999999999), ('Czech Republic', 90.24000000000001), ('Portugal', 77.23999999999998), ('India', 75.25999999999999), ('Chile', 46.62), ('Ireland', 45.62), ('Hungary', 45.62), ('Austria', 42.62), ('Finland', 41.620000000000005), ('Netherlands', 40.62), ('Norway', 39.62), ('Sweden', 38.620000000000005), ('Poland', 37.620000000000005), ('Italy', 37.620000000000005), ('Denmark', 37.620000000000005), ('Australia', 37.620000000000005), ('Argentina', 37.620000000000005), ('Spain', 37.62), ('Belgium', 37.62)], 'sql_query': 'SELECT BillingCountry, SUM(Total) as TotalSales\nFROM Invoice\nGROUP BY BillingCountry\nORDER BY TotalSales DESC;'})
-----------is there a way to get the headers also with the sql results in thr Response() object, so that i can display it in a table ?
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Based on the provided extracts, it seems like you're using the
SQLTableRetrieverQueryEngine
from LlamaIndex to execute a SQL query. The
synthesize_response = False
parameter indicates that you want the raw SQL query result without any additional processing or formatting.
Here's the code you're currently running:
from llama_index.indices.struct_store.sql_query import SQLTableRetrieverQueryEngine
query_engine = SQLTableRetrieverQueryEngine(
sql_database,
object_index.as_retriever(similarity_top_k=3),
synthesize_response = False,
# response_synthesis_prompt=sql_response_synthesis_prompt,
service_context=service_context
)
response = query_engine.query("Give me the sales by each country")
However, without a specific question or issue, it's hard to provide a more detailed answer. If you're encountering an error, please provide the error message. If you're unsure about a specific part of the code, please clarify which part you're having trouble with.
For more information about the
SQLTableRetrieverQueryEngine
and other components of LlamaIndex, you can refer to the
LlamaIndex documentation ().
----------------------
Note: you can ask me a follow up question by @ mentioning me again
:speech_balloon:
----------------------
@kapa.ai I'm getting this response without the column headers in the response: Response(response="[('USA', 523.0600000000003), ('Canada', 303.9599999999999), ('France', 195.09999999999994), ('Brazil', 190.09999999999997), ('Germany', 156.48), ('United Kingdom', 112.85999999999999), ('Czech Republic', 90.24000000000001), ('Portugal', 77.23999999999998), ('India', 75.25999999999999), ('Chile', 46.62), ('Ireland', 45.62), ('Hungary', 45.62), ('Austria', 42.62), ('Finland', 41.620000000000005), ('Netherlands', 40.62), ('Norway', 39.62), ('Sweden', 38.620000000000005), ('Poland', 37.620000000000005), ('Italy', 37.620000000000005), ('Denmark', 37.620000000000005), ('Australia', 37.620000000000005), ('Argentina', 37.620000000000005), ('Spain', 37.62), ('Belgium', 37.62)]", source_nodes=[], metadata={'result': [('USA', 523.0600000000003), ('Canada', 303.9599999999999), ('France', 195.09999999999994), ('Brazil', 190.09999999999997), ('Germany', 156.48), ('United Kingdom', 112.85999999999999), ('Czech Republic', 90.24000000000001), ('Portugal', 77.23999999999998), ('India', 75.25999999999999), ('Chile', 46.62), ('Ireland', 45.62), ('Hungary', 45.62), ('Austria', 42.62), ('Finland', 41.620000000000005), ('Netherlands', 40.62), ('Norway', 39.62), ('Sweden', 38.620000000000005), ('Poland', 37.620000000000005), ('Italy', 37.620000000000005), ('Denmark', 37.620000000000005), ('Australia', 37.620000000000005), ('Argentina', 37.620000000000005), ('Spain', 37.62), ('Belgium', 37.62)], 'sql_query': 'SELECT BillingCountry, SUM(Total) as TotalSales\nFROM Invoice\nGROUP BY BillingCountry\nORDER BY TotalSales DESC;'}) -----------is there a way to get the headers also with the sql results in thr Response() object, so that i can display it in a table ?
Let me check the knowledge base for you. One moment! :books:
----------------------
Based on the provided extracts, there's no explicit information on how to include the column names or headers in the raw SQL query result when using the SQLTableRetrieverQueryEngine
with synthesize_response=False
.
However, the response
object you're getting is a Response
object from LlamaIndex, and the actual SQL results are stored in the metadata
attribute under the key result
. This result
is a list of tuples, where each tuple represents a row from the SQL query result.
Unfortunately, the column names are not included in this result based on the information provided. This might be due to the specific way the sql_database
object or the query
method is implemented.
I recommend checking the documentation or the implementation of these components for more details. If you're using a custom SQL database interface, make sure it's configured to include column names in the result set.
If you're still having trouble, you might want to consider reaching out to the maintainers of the LlamaIndex project or the community for more specific guidance.
----------------------
Note: you can ask me a follow up question by @ mentioning me again
:speech_balloon:
----------------------
I think you'll just have to parse the headers out of the sql query itself tbh
You mean use the headers from the sql query(SELECT BillingCountry, SUM(Total) as TotalSales\nFROM Invoice\nGROUP BY BillingCountry\nORDER BY TotalSales DESC;') and append it to the response data ?
@kapa.ai How to use Pandas Query Engine with GuidancePydanticProgram?
Let me check the knowledge base for you. One moment! :books:
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To use the Pandas Query Engine with GuidancePydanticProgram, you would first need to set up your DataFrame and the Pandas Query Engine. Then, you would define your Pydantic models and the GuidancePydanticProgram. Here's an example of how you might do this:
First, set up your DataFrame and the Pandas Query Engine:
import pandas as pd
from llama_index.query_engine import PandasQueryEngine
# Test on some sample data
df = pd.DataFrame(
{"city": ["Toronto", "Tokyo", "Berlin"], "population": [2930000, 13960000, 3645000]}
)
query_engine = PandasQueryEngine(df=df, verbose=True)
Then, define your Pydantic models and the GuidancePydanticProgram:
from pydantic import BaseModel
from typing import List
from guidance.llms import OpenAI
from llama_index.program import GuidancePydanticProgram
class Song(BaseModel):
title: str
length_seconds: int
class Album(BaseModel):
name: str
artist: str
songs: List[Song]
program = GuidancePydanticProgram(
output_cls=Album,
prompt_template_str="Generate an example album, with an artist and a list of songs. Using the movie {{movie_name}} as inspiration",
guidance_llm=OpenAI("text-davinci-003"),
verbose=True,
)
Now, you can use the
query_engine
to query your DataFrame, and the
program
to generate structured data based on the query results.
Please note that this is a simplified example. The actual implementation might require additional steps or adjustments based on your specific use case.
For more information, you can refer to the Pandas Query Engine () and Guidance Pydantic Program () examples in the LlamaIndex documentation.
----------------------
Note: you can ask me a follow up question by @ mentioning me again
:speech_balloon:
----------------------
@Logan M Any help here with using GuidancePydanticProgram alogn with any other exisitng tools(specifically Pandas Query Engine and SQL Query Engine), Can i replace guidance_llm=OpenAI("text-davinci-003") with PandasQueryEngine(df=df, verbose=True) here to combine both ?
What's the intended use case here? Are you using an agent or?