refactor: Replace PromptTemplates with AgentPromptTemplates across agents and remove obsolete templates module
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william.dias
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70a7a4a12b
commit
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5 changed files with 25 additions and 68 deletions
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@ -1,7 +1,7 @@
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from agno.agent import Agent
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from agno.db.sqlite import SqliteDb
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from sql_optimizer_team.tools.engine.model_selector import get_model
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from sql_optimizer_team.tools.engine.prompt_tools.templates import PromptTemplates
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from sql_optimizer_team.agents.prompts import AgentPromptTemplates
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from sql_optimizer_team.tools.prompt_tools import supported_databases
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from sql_optimizer_team.tools.sql_tools import load_sql_from_file, ensure_non_empty
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import os
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@ -31,7 +31,7 @@ conservative_analysis_agent = Agent(
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"- Solicite banco e SQL se não estiverem presentes.",
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"- Se o usuário fornecer um caminho de arquivo, use load_sql_from_file().",
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"- Use a template oficial abaixo para a análise conservadora (sem reescrever a SQL).",
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PromptTemplates.CONSERVATIVE_ANALYSIS.template.strip(),
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AgentPromptTemplates.CONSERVATIVE_ANALYSIS.template.strip(),
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"- NÃO reescreva a SQL em hipótese alguma.",
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],
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)
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@ -1,18 +1,14 @@
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"""Prompt templates for SQL optimization.
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"""Prompt templates used by Agno agents.
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This module provides reusable prompt templates that can be customized
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for different database types.
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This module keeps the canonical prompts alongside the agents to ensure
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all prompt content is owned and maintained by the agent layer.
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"""
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from string import Template
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class PromptTemplates:
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"""Collection of prompt templates for SQL optimization.
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These templates use Python's string.Template for safe string substitution.
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Templates can be customized per database type while maintaining consistency.
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"""
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class AgentPromptTemplates:
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"""Collection of prompt templates for SQL optimization agents."""
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SQL_TO_NATURAL = Template("""
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You are an expert $database_name database analyst and performance specialist. Your task is to translate the SQL query below into a detailed, precise natural-language description that another agent will later use to reconstruct and optimize the query.
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@ -76,7 +72,6 @@ class PromptTemplates:
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Explanation:
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""")
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NATURAL_TO_SQL = Template("""
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You are an expert $database_name SQL developer and query performance specialist.
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Your task is to write an optimized SQL query based exclusively on the natural-language description provided below.
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@ -138,19 +133,18 @@ class PromptTemplates:
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Optimized SQL Query:
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""")
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CONSERVATIVE_ANALYSIS = Template("""
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You are an expert $database_name database analyst and performance specialist.
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Your task is to ANALYZE the SQL query below and provide SUGGESTIONS for improvement.
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⚠️ CRITICAL: You must NOT rewrite or modify the query. Only provide analysis and suggestions.
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$database_name SQL Query:
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```sql
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$query
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```
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Query Complexity Information:
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- Columns: $column_count
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- Tables: $table_count
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@ -158,31 +152,31 @@ class PromptTemplates:
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- CASE statements: $case_count
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- JOINs: $join_count
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- Complexity Level: $complexity_level
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Provide your analysis in the following structured format:
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## PERFORMANCE ISSUES
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List each performance issue found, with severity (CRITICAL/HIGH/MEDIUM/LOW):
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- [SEVERITY] Issue description
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- [SEVERITY] Issue description
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## SUGGESTED INDEXES
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List indexes that could improve this query:
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- CREATE INDEX idx_name ON table(columns) -- Reason
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## OPTIMIZATION SUGGESTIONS
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List specific suggestions WITHOUT rewriting the query:
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- Suggestion 1: Description of what could be improved and why
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- Suggestion 2: Description of what could be improved and why
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## RISK ASSESSMENT
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- WITH (NOLOCK) usage: [Yes/No] - If yes, explain the risks
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- Missing WHERE clause: [Yes/No] - If yes, explain the impact
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- Implicit conversions: [Yes/No] - If yes, list them
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## SUMMARY
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Brief summary of the most important findings and priority order for addressing them.
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Remember: DO NOT provide a rewritten query. Only analysis and suggestions.
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""")
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@ -190,17 +184,6 @@ class PromptTemplates:
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def render_sql_to_natural(
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cls, database_name: str, query: str, specific_features: str = "", analysis_requirements: str = ""
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) -> str:
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"""Render SQL-to-natural language prompt.
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Args:
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database_name: Name of database system
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query: SQL query to explain
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specific_features: Additional database-specific features to mention
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analysis_requirements: Additional performance analysis requirements
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Returns:
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Rendered prompt string
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"""
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return cls.SQL_TO_NATURAL.substitute(
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database_name=database_name,
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query=query,
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@ -212,17 +195,6 @@ class PromptTemplates:
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def render_natural_to_sql(
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cls, database_name: str, explanation: str, specific_requirements: str
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) -> str:
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"""Render natural-to-SQL prompt.
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Args:
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database_name: Name of database system
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explanation: Natural language description
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specific_requirements: Database-specific optimization requirements
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Returns:
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Rendered prompt string
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"""
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# Format requirements as bullet points
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return cls.NATURAL_TO_SQL.substitute(
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database_name=database_name,
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explanation=explanation,
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@ -243,21 +215,6 @@ class PromptTemplates:
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join_count: int = 0,
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complexity_level: str = "unknown",
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) -> str:
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"""Render conservative analysis prompt (no query rewriting).
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Args:
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database_name: Name of database system
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query: SQL query to analyze
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column_count: Number of columns in query
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table_count: Number of tables in query
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subquery_count: Number of subqueries
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case_count: Number of CASE statements
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join_count: Number of JOINs
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complexity_level: Detected complexity level
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Returns:
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Rendered prompt string
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"""
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return cls.CONSERVATIVE_ANALYSIS.substitute(
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database_name=database_name,
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query=query,
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@ -2,7 +2,7 @@ from agno.agent import Agent
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from agno.db.sqlite import SqliteDb
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from sql_optimizer_team.tools.engine.model_selector import get_model
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from sql_optimizer_team.tools.core_tools import explain_query_core
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from sql_optimizer_team.tools.engine.prompt_tools.templates import PromptTemplates
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from sql_optimizer_team.agents.prompts import AgentPromptTemplates
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from sql_optimizer_team.tools.prompt_tools import supported_databases
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from sql_optimizer_team.tools.sql_tools import load_sql_from_file, ensure_non_empty
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import os
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@ -33,7 +33,7 @@ sql_analyst_agent = Agent(
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"- Se o usuário fornecer um caminho de arquivo, use load_sql_from_file().",
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"- Preferência: use explain_query_core(database_type, sql) para gerar a explicação via core de negócio.",
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"- Use a template oficial abaixo para estruturar a explicação (SQL → natural).",
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PromptTemplates.SQL_TO_NATURAL.template.strip(),
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AgentPromptTemplates.SQL_TO_NATURAL.template.strip(),
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"- Entregue apenas a explicação natural estruturada conforme a prompt; não reescreva a SQL.",
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"- Identifique problemas críticos de performance conforme a prompt.",
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],
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@ -2,7 +2,7 @@ from agno.agent import Agent
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from agno.db.sqlite import SqliteDb
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from sql_optimizer_team.tools.engine.model_selector import get_model
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from sql_optimizer_team.tools.core_tools import optimize_query_core
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from sql_optimizer_team.tools.engine.prompt_tools.templates import PromptTemplates
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from sql_optimizer_team.agents.prompts import AgentPromptTemplates
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from sql_optimizer_team.tools.prompt_tools import supported_databases
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from sql_optimizer_team.tools.sql_tools import load_sql_from_file, ensure_non_empty
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import os
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@ -32,7 +32,7 @@ sql_optimizer_agent = Agent(
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"- Exija banco alvo e SQL antes de otimizar.",
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"- Use optimize_query_core(database_type, sql) para executar o core de negócio.",
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"- Use a template oficial abaixo para reescrever (natural → SQL) mantendo 100% da lógica.",
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PromptTemplates.NATURAL_TO_SQL.template.strip(),
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AgentPromptTemplates.NATURAL_TO_SQL.template.strip(),
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"- Extraia e devolva SOMENTE optimized_query (sem explicações, sem markdown).",
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"- Preserve 100% da lógica, colunas, aliases, filtros, joins e subqueries.",
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],
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@ -7,7 +7,7 @@ reducing code duplication and ensuring consistency.
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from abc import ABC, abstractmethod
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from sql_optimizer_team.tools.engine.tools_api.prompt_tool import PromptGeneratorTool
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from sql_optimizer_team.tools.engine.prompt_tools.templates import PromptTemplates
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from sql_optimizer_team.agents.prompts import AgentPromptTemplates
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class BasePromptGenerator(PromptGeneratorTool, ABC):
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@ -70,7 +70,7 @@ class BasePromptGenerator(PromptGeneratorTool, ABC):
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Returns:
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Formatted prompt for LLM
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"""
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return PromptTemplates.render_sql_to_natural(
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return AgentPromptTemplates.render_sql_to_natural(
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database_name=self.get_database_name(),
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query=query,
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specific_features=self.get_specific_features(),
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@ -86,7 +86,7 @@ class BasePromptGenerator(PromptGeneratorTool, ABC):
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Returns:
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Formatted prompt for LLM
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"""
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return PromptTemplates.render_natural_to_sql(
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return AgentPromptTemplates.render_natural_to_sql(
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database_name=self.get_database_name(),
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explanation=explanation,
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specific_requirements=self.get_specific_requirements(),
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