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Updated 2 years ago

How to get the header also from the results of the SQL Query Engine ? I’m trying to get th

At a glance

The community member @kapa.ai is trying to get the header (column names) from the results of the SQL Query Engine without the response being synthesized. The community members provide some suggestions, such as setting the synthesize_response parameter to False when initializing the query engine. However, this does not seem to include the column names in the raw SQL query result.

The community members discuss that the column names may not be included due to the specific implementation of the SQL database interface or the query method. They recommend checking the documentation or implementation for more details. If the community member is using a custom SQL database interface, they should ensure it is configured to include column names in the result set.

The community members also suggest that the community member may need to parse the headers out of the SQL query itself and append them to the response data.

There is no explicitly marked answer in the provided information.

@kapa.ai How to get the header also from the results of the SQL Query Engine ? I’m trying to get the results with out the result synthesized.
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21 comments
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:

Plain Text
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:

Plain Text
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:
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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.
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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@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:

Plain Text
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:
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@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:
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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:
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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 ?
That's what I think yea
@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:

Plain Text
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:

Plain Text
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.
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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@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?
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