Ci/unit tests for tool (#66)

* remove responses models

* adding tests to the other tools

* refactor tests

* add pytest-async

* replace logging with custom logger

Author: Rodriguespn

src/api/common.py

@@ -1,15 +1,15 @@
 from typing import List
 import requests
 import json
-import logging
 
 from starlette.exceptions import HTTPException
 
 from src.api.types import MCPConcept, AVAILABLE_FLAGS
 from src.config.config import get_session_request, get_settings
+from src.logger import get_logger
 
 # Set up logger for this module
-logger = logging.getLogger(__name__)
+logger = get_logger()
 
 
 def filter_mcp_concepts(mcp_concepts: List[MCPConcept], **flags) -> List[MCPConcept]:

src/api/prompts/prompts.py

@@ -1,95 +1,6 @@
 from src.api.prompts.types import Prompt
-from src.api.responses import prompt_response
 
-
-@prompt_response
-def sql_optimization_prompt(query: str, database_type: str = "singlestore") -> str:
-    """
-    Generate a prompt for SQL query optimization analysis.
-
-    Args:
-        query: The SQL query to optimize
-        database_type: The type of database (default: singlestore)
-    """
-    return f"""
-    Please analyze and optimize the following {database_type.upper()} SQL query:
-
-    ```sql
-    {query}
-    ```
-
-    Consider the following optimization strategies:
-    1. Index usage and recommendations
-    2. Query structure improvements
-    3. JOIN optimization
-    4. WHERE clause efficiency
-    5. SingleStore-specific optimizations (if applicable)
-
-    Provide:
-    - Optimized query version
-    - Explanation of changes
-    - Performance impact estimation
-    - Index recommendations
-    """
-
-
-@prompt_response
-def data_modeling_prompt(
-    table_description: str, use_case: str = "analytics", scale: str = "medium"
-) -> str:
-    """
-    Generate a prompt for SingleStore data modeling guidance.
-
-    Args:
-        table_description: Description of the data to model
-        use_case: The primary use case (analytics, transactional, hybrid)
-        scale: Expected data scale (small, medium, large, enterprise)
-    """
-    return f"""
-    Design an optimal SingleStore data model for the following requirements:
-
-    **Data Description:** {table_description}
-    **Use Case:** {use_case}
-    **Scale:** {scale}
-
-    Please provide:
-    1. **Table Schema Design**
-       - Column definitions with appropriate data types
-       - Primary key strategy
-       - Distribution key recommendations
-       - Sort key optimization
-
-    2. **SingleStore-Specific Optimizations**
-       - Columnstore vs Rowstore recommendations
-       - Partitioning strategy
-       - Shard key selection
-       - Reference table considerations
-
-    3. **Performance Considerations**
-       - Query pattern optimization
-       - Index strategy
-       - Memory usage optimization
-       - Scaling recommendations
-
-    4. **Best Practices**
-       - Data ingestion patterns
-       - ETL considerations
-       - Monitoring and maintenance
-
-    Ensure the design leverages SingleStore's distributed architecture and hybrid transactional/analytical capabilities.
-    """
-
-
-prompts_definitions = [
-    {
-        "title": "SQL Query Optimization Assistant",
-        "func": sql_optimization_prompt,
-    },
-    {
-        "title": "SingleStore Data Modeling Guide",
-        "func": data_modeling_prompt,
-    },
-]
+prompts_definitions = []
 
 # Export the prompts using create_from_dict for consistency
 prompts = [Prompt.create_from_dict(prompt) for prompt in prompts_definitions]

src/api/resources/resources.py

@@ -1,10 +1,8 @@
 from pathlib import Path
 from src.api.resources.types import Resource
-from src.api.responses import resource_response
 
 
-@resource_response
-def get_singlestore_drizzle_guide() -> str:
+def get_singlestore_drizzle_guide() -> dict:
     """
     SingleStore and Drizzle ORM Integration Guide
 
@@ -21,9 +19,26 @@ def get_singlestore_drizzle_guide() -> str:
 
     try:
         with open(docs_path, "r", encoding="utf-8") as f:
-            return f.read()
+            content = f.read()
+            return {
+                "status": "success",
+                "message": "SingleStore Drizzle integration guide retrieved successfully",
+                "content": content,
+                "uri": "docs://singlestore/drizzle-integration",
+                "metadata": {
+                    "content_length": len(content),
+                    "file_path": str(docs_path),
+                },
+            }
     except FileNotFoundError:
-        return "SingleStore Drizzle integration guide not found."
+        return {
+            "status": "error",
+            "message": "SingleStore Drizzle integration guide not found",
+            "content": "SingleStore Drizzle integration guide not found.",
+            "uri": "docs://singlestore/drizzle-integration",
+            "error_code": "FileNotFound",
+            "error_details": {"file_path": str(docs_path)},
+        }
 
 
 resources_definitions = [