Auto-translate natural language prompts to DSL via vtk-mcp

README.md

@@ -108,7 +108,7 @@ vtk-prompt "Create a red sphere" -t $API_KEY
 # Advanced options
 vtk-prompt "Create a textured cone with 32 resolution" \
   --provider anthropic \
-  --model claude-opus-4-7 \
+  --model claude-opus-5 \
   --max-tokens 4000 \
   --mcp-url http://localhost:8000 \
   --verbose \
@@ -156,7 +156,7 @@ print(code)
 
 ```yaml
 # Model and parameter configuration
-model: anthropic/claude-opus-4-1-20250805
+model: anthropic/claude-opus-5
 modelParameters:
   temperature: 0.2
   max_tokens: 6000
@@ -215,7 +215,7 @@ uv pip install -e ".[test]" && pytest
 
 | Provider      | Default Model                  | Base URL                            |
 | ------------- | ------------------------------ | ----------------------------------- |
-| **anthropic** | claude-sonnet-4-6              | https://api.anthropic.com/v1        |
+| **anthropic** | claude-sonnet-5                | https://api.anthropic.com/v1        |
 | **openai**    | gpt-4.1                        | https://api.openai.com/v1           |
 | **gemini**    | gemini-2.5-pro                 | https://generativelanguage.googleapis.com/v1beta |
 | **nim**       | meta/llama-3.3-70b-instruct    | https://integrate.api.nvidia.com/v1 |

src/vtk_prompt/cli.py

@@ -5,15 +5,15 @@
 It handles argument parsing, validation, and orchestrates the VTKPromptClient.
 
 Example:
-    >>> vtk-prompt "create sphere" --mcp-url http://localhost:8000 --model claude-sonnet-4-6
+    >>> vtk-prompt "create sphere" --mcp-url http://localhost:8000 --model claude-sonnet-5
 """
 
 import sys
 
 import click
 
 from . import get_logger
-from .client import VTKPromptClient
+from .client import VTKPromptClient, load_conversation, save_conversation
 from .provider_utils import DEFAULT_MODEL, DEFAULT_PROVIDER, get_default_model, supports_temperature
 
 logger = get_logger(__name__)
@@ -54,6 +54,16 @@
     "--prompt-file",
     help="Path to custom YAML prompt file (overrides built-in prompts and defaults)",
 )
+@click.option(
+    "--dsl-translation/--no-dsl-translation",
+    default=True,
+    help="Auto-translate natural language prompts to the VTK pipeline DSL via vtk-mcp",
+)
+@click.option(
+    "--debug",
+    is_flag=True,
+    help="Dump the full LLM conversation (context and vtk-mcp tool calls included) to stdout",
+)
 def main(
     input_string: str,
     provider: str,
@@ -68,6 +78,8 @@ def main(
     retry_attempts: int,
     conversation: str | None,
     prompt_file: str | None,
+    dsl_translation: bool,
+    debug: bool,
 ) -> None:
     """
     Generate and execute VTK code using LLMs.
@@ -138,13 +150,12 @@ def main(
         temperature = 1.0
 
     try:
-        client = VTKPromptClient(
-            verbose=verbose,
-            conversation_file=conversation,
-            mcp_url=mcp_url,
-        )
+        client = VTKPromptClient(verbose=verbose, mcp_url=mcp_url)
+        # The caller owns the conversation: load it, hand it to query, save it back.
+        messages = load_conversation(conversation)
         result = client.query(
             input_string,
+            conversation=messages,
             api_key=token,
             model=model,
             base_url=base_url,
@@ -154,7 +165,10 @@ def main(
             retry_attempts=retry_attempts,
             provider=provider,
             custom_prompt=custom_prompt_data,
+            dsl_translation=dsl_translation,
+            debug=debug,
         )
+        save_conversation(conversation, messages)
 
         # Handle result with optional validation warnings
         if isinstance(result, tuple):