Port mtrix DiscordClient class to mindtrace

mindtrace/core/mindtrace/core/config/config.ini

@@ -3,6 +3,9 @@ OPENAI = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
 DISCORD = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
 ROBOFLOW = XXXXXXXXXXXXXXXXXXXX
 
+[MINDTRACE_TESTING_API_KEYS]
+DISCORD = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
+
 [MINDTRACE_DIR_PATHS]
 ROOT = ~/.cache/mindtrace
 TEMP_DIR = ${MINDTRACE_DIR_PATHS:ROOT}/temp

mindtrace/core/mindtrace/core/config/config.py

@@ -16,6 +16,10 @@ class MINDTRACE_API_KEYS(BaseModel):
     ROBOFLOW: Optional[SecretStr]
 
 
+class MINDTRACE_TESTING_API_KEYS(BaseModel):
+    DISCORD: Optional[SecretStr]
+
+
 class MINDTRACE_DIR_PATHS(BaseModel):
     ROOT: str
     TEMP_DIR: str
@@ -72,6 +76,7 @@ def load_ini_settings() -> Dict[str, Any]:
 
 class CoreSettings(BaseSettings):
     MINDTRACE_API_KEYS: MINDTRACE_API_KEYS
+    MINDTRACE_TESTING_API_KEYS: MINDTRACE_TESTING_API_KEYS
     MINDTRACE_DIR_PATHS: MINDTRACE_DIR_PATHS
     MINDTRACE_DEFAULT_HOST_URLS: MINDTRACE_DEFAULT_HOST_URLS
     MINDTRACE_MINIO: MINDTRACE_MINIO

mindtrace/services/README.md

@@ -183,7 +183,7 @@ The Model Context Protocol (MCP) is a protocol for exposing service functionalit
 ### Example: EchoService with MCP
 See [`mindtrace/services/sample/echo_mcp.py`](./mindtrace/services/sample/echo_mcp.py):
 ```python
-from mindtrace.services.sample.echo_mcp import EchoService
+from mindtrace.services.samples.echo_mcp import EchoService
 
 # Launch the service
 connection_manager = EchoService.launch(port=8080, host="localhost", wait_for_launch=True, timeout=30)
@@ -225,7 +225,7 @@ Each `Service` subclass automatically receives a class-level `mcp` helper (MCPCl
 Connect to a running service:
 
 ```python
-from mindtrace.services.sample.echo_mcp import EchoService
+from mindtrace.services.samples.echo_mcp import EchoService
 import asyncio
 
 async def main():
@@ -243,7 +243,7 @@ asyncio.run(main())
 Launch a new service and get a connected client:
 
 ```python
-from mindtrace.services.sample.echo_mcp import EchoService
+from mindtrace.services.samples.echo_mcp import EchoService
 import asyncio
 
 async def main():
@@ -265,7 +265,7 @@ asyncio.run(main())
 Get the MCP client from a connection manager instance:
 
 ```python
-from mindtrace.services.sample.echo_mcp import EchoService
+from mindtrace.services.samples.echo_mcp import EchoService
 import asyncio
 
 async def main():
@@ -304,7 +304,7 @@ Follow these steps to set up and use a remote MCP server with Cursor:
    Start your Mindtrace service with MCP enabled. For example, to launch the EchoService:
 
    ```python
-   from mindtrace.services.sample.echo_mcp import EchoService
+   from mindtrace.services.samples.echo_mcp import EchoService
    connection_manager = EchoService.launch(port=8080, host="localhost")
    ```
 

mindtrace/services/mindtrace/services/__init__.py

@@ -14,7 +14,7 @@
 from mindtrace.services.gateway.gateway import Gateway
 from mindtrace.services.gateway.proxy_connection_manager import ProxyConnectionManager
 from mindtrace.services.gateway.types import AppConfig, RegisterAppTaskSchema
-from mindtrace.services.sample.echo_service import EchoService
+from mindtrace.services.samples.echo_service import EchoService
 
 __all__ = [
     "AppConfig",

mindtrace/services/mindtrace/services/core/mcp_client_manager.py

@@ -33,7 +33,7 @@ def connect(self, url: str | Url | None = None) -> "Client":
             FastMCP Client instance for MCP protocol communication
 
         Example::
-            from mindtrace.services.sample.echo_mcp import EchoService
+            from mindtrace.services.samples.echo_mcp import EchoService
             # Connect to a running EchoService
             mcp_client = EchoService.mcp.connect("http://localhost:8000")
 
@@ -65,7 +65,7 @@ def launch(self, **launch_kwargs) -> "Client":
             FastMCP Client instance connected to the newly launched service
 
         Example::
-            from mindtrace.services.sample.echo_mcp import EchoService
+            from mindtrace.services.samples.echo_mcp import EchoService
 
             mcp_client = EchoService.mcp.launch(
                                                 host="localhost",

mindtrace/services/mindtrace/services/core/utils.py

@@ -207,15 +207,19 @@ async def amethod(self, *args, validate_input: bool = True, validate_output: boo
 
         method, amethod = make_method(endpoint_path, endpoint.input_schema, endpoint.output_schema)
 
+        # Replace dots with underscores to make it a valid identifier
+        method_name = endpoint_name.replace(".", "_")
+
         # Set up sync method
-        method.__name__ = endpoint_name
+        method.__name__ = method_name
         method.__doc__ = f"Calls the `{endpoint_name}` pipeline at `{endpoint_path}`"
-        setattr(ServiceConnectionManager, endpoint_name, method)
+        setattr(ServiceConnectionManager, method_name, method)
 
         # Set up async method
-        amethod.__name__ = f"a{endpoint_name}"
+        async_method_name = f"a{method_name}"
+        amethod.__name__ = async_method_name
         amethod.__doc__ = f"Async version: Calls the `{endpoint_name}` pipeline at `{endpoint_path}`"
-        setattr(ServiceConnectionManager, f"a{endpoint_name}", amethod)
+        setattr(ServiceConnectionManager, async_method_name, amethod)
 
     ServiceConnectionManager.__name__ = class_name
     return ServiceConnectionManager