fix FE and move prompts to text file

backend/dataall/modules/worksheets/aws/bedrock_client.py

@@ -3,11 +3,11 @@
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import PromptTemplate
 from dataall.base.db import exceptions
-from dataall.modules.worksheets.aws.bedrock_prompts import (
-    SQL_EXAMPLES,
-    TEXT_TO_SQL_PROMPT_TEMPLATE,
-    PROCESS_TEXT_PROMPT_TEMPLATE,
-)
+import os
+
+TEXT_TO_SQL_EXAMPLES_PATH = os.path.join(os.path.dirname(__file__), 'bedrock_prompts', 'text_to_sql_examples.txt')
+TEXT_TO_SQL_TEMPLATE_PATH = os.path.join(os.path.dirname(__file__), 'bedrock_prompts', 'test_to_sql_template.txt')
+PROCESS_TEXT_TEMPLATE_PATH = os.path.join(os.path.dirname(__file__), 'bedrock_prompts', 'process_text_template.txt')
 
 
 class BedrockClient:
@@ -29,16 +29,19 @@ def __init__(self):
         )
 
     def invoke_model_text_to_sql(self, prompt: str, metadata: str):
-        prompt_template = PromptTemplate.from_template(TEXT_TO_SQL_PROMPT_TEMPLATE)
-
+        prompt_template = PromptTemplate.from_file(TEXT_TO_SQL_TEMPLATE_PATH)
         chain = prompt_template | self._model | StrOutputParser()
-        response = chain.invoke({'prompt': prompt, 'context': metadata, 'examples': SQL_EXAMPLES})
+
+        with open(TEXT_TO_SQL_EXAMPLES_PATH, 'r') as f:
+            examples = f.read()
+
+        response = chain.invoke({'prompt': prompt, 'context': metadata, 'examples': examples})
         if response.startswith('Error:'):
             raise exceptions.ModelGuardrailException(response)
         return response
 
     def invoke_model_process_text(self, prompt: str, content: str):
-        prompt_template = PromptTemplate.from_template(PROCESS_TEXT_PROMPT_TEMPLATE)
+        prompt_template = PromptTemplate.from_file(PROCESS_TEXT_TEMPLATE_PATH)
 
         chain = prompt_template | self._model | StrOutputParser()
         response = chain.invoke({'prompt': prompt, 'content': content})

backend/dataall/modules/worksheets/aws/bedrock_prompts/process_text_template.txt

@@ -0,0 +1,14 @@
+You are an AI assistant tasked with analyzing and processing text content. Your goal is to provide accurate and helpful responses based on the given content and user prompt. 
+You must follow the steps:
+
+1. Detetermine if the document has the information to be able to answer the question. If not respond with "Error: The Document does not provide the information needed to answer you question"
+2. I want you to answer the question based on the information in the document.
+3. At the bottom I want you to provide the sources (the parts of the document where you found the results). The sources should be listed in order
+
+
+Content to analyze:
+{content}
+
+User prompt: {prompt}
+
+Please provide a response that addresses the user's prompt in the context of the given content. Be thorough, accurate, and helpful in your analysis.

backend/dataall/modules/worksheets/aws/bedrock_prompts/test_to_sql_template.txt

@@ -0,0 +1,38 @@
+You will be given the name of an AWS Glue Database, metadata from one or more AWS Glue Table(s) and a user prompt from a user. 
+
+Based on this information your job is to turn the prompt into a SQL query that will be sent to query the data within the tables in Amazon Athena.
+
+Take the following points into consideration. It is crucial that you follow them:
+
+- I only want you to return the SQL needed (NO EXPLANATION or anything else).
+
+- Tables are referenced on the following form 'database_name.table_name' (for example 'Select * FROM database_name.table_name ...' and not 'SELECT * FROM table_name ...) since we dont have access to the table name directly since its not global variable.
+
+- Take relations between tables into consideration, for example if you have a table with columns that might reference the other tables, you would need to join them in the query.
+
+- The generate SQL statement MUST be Read only (no WRITE, INSERT, ALTER or DELETE keywords)
+
+- Answer on the same form as the examples given below.
+
+Examples:
+{examples}
+
+
+I want you to follow the following steps when generating the SQL statement: 
+
+Step 1: Determine if the given tables columns are suitable to answer the question.
+If not respond with "Error: The tables provided does not give enough information"
+
+Step 2: Determine if the user wants to perform any mutations, if so return "Error: Only READ queries are allowed"
+
+Step 3: Determine if joins will be needed.
+
+Step 4: Generate the SQL in order to solve the problem.
+
+
+Based on the following metadata: 
+{context}
+
+
+User prompt: {prompt}
+

backend/dataall/modules/worksheets/aws/bedrock_prompts/text_to_sql_examples.txt

@@ -0,0 +1,49 @@
+Example 1.
+User prompt: I want to get the average area of all listings
+
+Context: Based on on the following metadata 
+Database Name : dataall_homes_11p3uu8f
+Table Name: listings 
+Column Metadata: [{'Name': 'price', 'Type': 'bigint'}, {'Name': 'area', 'Type': 'bigint'}, {'Name': 'bedrooms', 'Type': 'bigint'}, {'Name': 'bathrooms', 'Type': 'bigint'}, {'Name': 'stories', 'Type': 'bigint'}, {'Name': 'mainroad', 'Type': 'string'}, {'Name': 'guestroom', 'Type': 'string'}, {'Name': 'basement', 'Type': 'string'}, {'Name': 'hotwaterheating', 'Type': 'string'}, {'Name': 'airconditioning', 'Type': 'string'}, {'Name': 'parking', 'Type': 'bigint'}, {'Name': 'prefarea', 'Type': 'string'}, {'Name': 'furnishingstatus', 'Type': 'string'}, {'Name': 'passengerid', 'Type': 'bigint'}, {'Name': 'survived', 'Type': 'bigint'}, {'Name': 'pclass', 'Type': 'bigint'}, {'Name': 'name', 'Type': 'string'}, {'Name': 'sex', 'Type': 'string'}, {'Name': 'age', 'Type': 'double'}, {'Name': 'sibsp', 'Type': 'bigint'}, {'Name': 'parch', 'Type': 'bigint'}, {'Name': 'ticket', 'Type': 'string'}, {'Name': 'fare', 'Type': 'double'}, {'Name': 'cabin', 'Type': 'string'}, {'Name': 'embarked', 'Type': 'string'}]
+Partition Metadata: []           
+
+Response: SELECT AVG(CAST(area AS DOUBLE)) FROM dataall_homes_11p3uu8f.listings WHERE area IS NOT NULL;
+
+
+Example 2.
+User prompt: I want to get the average of the 3 most expensive listings with less than 3 bedrooms
+
+Context: Based on on the following metadata         
+Database Name : dataall_homes_11p3uu8f
+Table Name: listings 
+Column Metadata: [{'Name': 'price', 'Type': 'bigint'}, {'Name': 'area', 'Type': 'bigint'}, {'Name': 'bedrooms', 'Type': 'bigint'}, {'Name': 'bathrooms', 'Type': 'bigint'}, {'Name': 'stories', 'Type': 'bigint'}, {'Name': 'mainroad', 'Type': 'string'}, {'Name': 'guestroom', 'Type': 'string'}, {'Name': 'basement', 'Type': 'string'}, {'Name': 'hotwaterheating', 'Type': 'string'}, {'Name': 'airconditioning', 'Type': 'string'}, {'Name': 'parking', 'Type': 'bigint'}, {'Name': 'prefarea', 'Type': 'string'}, {'Name': 'furnishingstatus', 'Type': 'string'}, {'Name': 'passengerid', 'Type': 'bigint'}, {'Name': 'survived', 'Type': 'bigint'}, {'Name': 'pclass', 'Type': 'bigint'}, {'Name': 'name', 'Type': 'string'}, {'Name': 'sex', 'Type': 'string'}, {'Name': 'age', 'Type': 'double'}, {'Name': 'sibsp', 'Type': 'bigint'}, {'Name': 'parch', 'Type': 'bigint'}, {'Name': 'ticket', 'Type': 'string'}, {'Name': 'fare', 'Type': 'double'}, {'Name': 'cabin', 'Type': 'string'}, {'Name': 'embarked', 'Type': 'string'}]
+Partition Metadata: []
+
+Response: SELECT AVG(price) AS average_price FROM (SELECT price FROM dataall_homes_11p3uu8f.listings WHERE bedrooms > 3 ORDER BY price DESC LIMIT 3);
+
+
+Example 3.
+User prompt: I want to see if any letter has been sent from 900 Somerville Avenue to 2 Finnigan Street and what is the content
+
+Context: Based on the following metadata  
+Database Name : dataall_packages_omf768qq
+Table name: packages
+Column Metadata: [{'Name': 'id', 'Type': 'bigint'}, {'Name': 'contents', 'Type': 'string'}, {'Name': 'from_address_id', 'Type': 'bigint'}, {'Name': 'to_address_id', 'Type': 'bigint'}]\n    
+Partition Metadata: []
+
+Database Name : dataall_packages_omf768qq
+Table name: addresses
+Column Metadata: [{'Name': 'id', 'Type': 'bigint'}, {'Name': 'address', 'Type': 'string'}, {'Name': 'type', 'Type': 'string'}]
+Partition Metadata: []
+
+Database Name : dataall_packages_omf768qq
+Table name: drivers    
+Column Metadata: [{'Name': 'id', 'Type': 'bigint'}, {'Name': 'name', 'Type': 'string'}]
+Partition Metadata: []
+
+Database Name : dataall_packages_omf768qq
+Table name: scans
+Column Metadata: [{'Name': 'id', 'Type': 'bigint'}, {'Name': 'driver_id', 'Type': 'bigint'}, {'Name': 'package_id', 'Type': 'bigint'}, {'Name': 'address_id', 'Type': 'bigint'}, {'Name': 'action', 'Type': 'string'}, {'Name': 'timestamp', 'Type': 'string'}]
+Partition Metadata: []
+
+Response: SELECT p.contents FROM dataall_packages_omf768qq.packages p JOIN dataall_packages_omf768qq.addresses a1 ON p.from_address_id = a1.id JOIN dataall_packages_omf768qq.addresses a2 ON p.to_address_id = a2.id WHERE a1.address = '900 Somerville Avenue' AND a2.address = '2 Finnigan Street';

backend/dataall/modules/worksheets/aws/glue_client.py

@@ -25,8 +25,8 @@ def get_table_metadata(self, database, table_name):
             column_metadata = table_metadata['Table']['StorageDescriptor']['Columns']
             partition_metadata = table_metadata['Table']['PartitionKeys']
             meta_data = f"""
-            Database name: {database}
-            Table name: {table_name} 
+            Database Name: {database}
+            Table Name: {table_name} 
             Column Metadata: {column_metadata}
             Partition Metadata: {partition_metadata}
             """

frontend/src/modules/DatasetsBase/components/DatasetGovernance.js

@@ -9,9 +9,8 @@ import {
   Typography
 } from '@mui/material';
 import PropTypes from 'prop-types';
-import { Label } from 'design';
+import { Label, UserModal } from 'design';
 import { isFeatureEnabled } from 'utils';
-import { UserModal } from 'design';
 import { useState } from 'react';
 
 export const DatasetGovernance = (props) => {

frontend/src/modules/Environments/components/EnvironmentOverview.js

@@ -1,8 +1,7 @@
 import React, { useState } from 'react';
 import { Box, Grid } from '@mui/material';
 import PropTypes from 'prop-types';
-import { ObjectBrief, ObjectMetadata } from 'design';
-import { UserModal } from 'design';
+import { ObjectBrief, ObjectMetadata, UserModal } from 'design';
 import { EnvironmentConsoleAccess } from './EnvironmentConsoleAccess';
 import { EnvironmentFeatures } from './EnvironmentFeatures';
 

frontend/src/modules/Organizations/components/OrganizationOverview.js

@@ -1,8 +1,7 @@
 import React, { useState } from 'react';
 import { Box, Grid } from '@mui/material';
 import PropTypes from 'prop-types';
-import { ObjectBrief, ObjectMetadata } from 'design';
-import { UserModal } from 'design';
+import { ObjectBrief, ObjectMetadata, UserModal } from 'design';
 
 export const OrganizationOverview = (props) => {
   const { organization, ...other } = props;

frontend/src/modules/Worksheets/components/WorksheetTextToSQLEditor.js

@@ -210,6 +210,12 @@ export const WorksheetTextToSQLEditor = ({
             </Box>
             <Box sx={{ p: 2 }}>
               <LoadingButton
+                disabled={
+                  !currentEnv ||
+                  !selectedDatabase ||
+                  !selectedTables.length ||
+                  !prompt
+                }
                 loading={invoking}
                 variant="contained"
                 onClick={handleSubmit}

frontend/src/modules/Worksheets/components/index.js

@@ -2,7 +2,6 @@ export * from './SQLQueryEditor';
 export * from './WorksheetEditFormModal';
 export * from './WorksheetListItem';
 export * from './WorksheetResult';
-export * from './TextDisplay';
 export * from './WorksheetSQLEditor';
 export * from './WorksheetTextToSQLEditor';
 export * from './WorksheetDocAnalyzer';

frontend/src/modules/Worksheets/views/WorksheetView.js

@@ -57,7 +57,7 @@ const tabs = [
     active: true
   },
   {
-    label: 'TextToSQL Editor',
+    label: 'Text-To-SQL Editor',
     value: 'TextToSQL',
     active: isFeatureEnabled('worksheets', 'nlq')
   },