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Stage 1 — Intent Parser
Model: DeepSeek R1 (reasoning model, ideal for structured analysis)
Input: raw user prompt
Output: structured intent dict used by the code generator
"""
import json
import re
from openai import OpenAI
from config import CRUSOE_API_KEY, CRUSOE_BASE_URL, INTENT_MODEL
client = OpenAI(api_key=CRUSOE_API_KEY, base_url=CRUSOE_BASE_URL)
SYSTEM_PROMPT = """You are an expert at analysing AI demo requests and mapping them to the right app template.
Given a user's demo idea, output a single JSON object with these fields:
REQUIRED (all templates):
- template_type: one of "chatbot" | "comparison" | "dashboard" | "form_wizard"
- title: short, catchy demo title (max 8 words)
- description: one-line description shown below the title
- system_prompt: detailed system prompt for the AI assistant inside the demo
- model: best Crusoe model for this demo:
• "deepseek-ai/DeepSeek-R1" — reasoning, analysis, step-by-step thinking
• "moonshotai/Kimi-K2-Instruct" — coding, long documents, structured output
• "Qwen/Qwen3-235B-A22B" — general purpose, fast responses, multilingual
- features: list of 2-4 key features to highlight
CONDITIONAL (chatbot only):
- chat_placeholder: placeholder text shown in the chat input box
CONDITIONAL (comparison only):
- model_a: first model ID (from the list above)
- model_a_label: friendly display name for model A
- model_b: second model ID
- model_b_label: friendly display name for model B
CONDITIONAL (dashboard only):
- input_label: label for the main input text area
- input_placeholder: placeholder text for that input
CONDITIONAL (form_wizard only):
- steps: list of 3-5 objects, each {"key": "snake_case_name", "question": "Question text?"}
Template selection guide:
- chatbot: conversational Q&A, support bots, advisors
- comparison: show two models side-by-side on the same prompt
- dashboard: analyze / summarize pasted text, data, or documents
- form_wizard: multi-step intake flows that end with AI recommendations
Output ONLY the JSON object. No markdown, no explanations."""
def parse_intent(prompt: str) -> dict:
response = client.chat.completions.create(
model=INTENT_MODEL,
messages=[
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": f"Create a demo for: {prompt}"},
],
temperature=0.3,
max_tokens=2000,
)
content = response.choices[0].message.content or ""
# Strip DeepSeek R1 chain-of-thought tags
content = re.sub(r"<think>.*?</think>", "", content, flags=re.DOTALL).strip()
# Extract the JSON block if surrounded by markdown fences
fenced = re.search(r"```(?:json)?\s*(\{.*?\})\s*```", content, re.DOTALL)
if fenced:
content = fenced.group(1)
else:
# Grab the outermost { ... }
brace = re.search(r"\{.*\}", content, re.DOTALL)
if brace:
content = brace.group()
intent = json.loads(content)
return _apply_defaults(intent)
def _apply_defaults(intent: dict) -> dict:
intent.setdefault("template_type", "chatbot")
intent.setdefault("title", "AI Demo")
intent.setdefault("description", "Powered by Crusoe Managed Inference")
intent.setdefault("system_prompt", "You are a helpful AI assistant.")
intent.setdefault("model", "Qwen/Qwen3-235B-A22B")
intent.setdefault("features", [])
# Chatbot defaults
intent.setdefault("chat_placeholder", "Ask me anything...")
# Comparison defaults
intent.setdefault("model_a", "deepseek-ai/DeepSeek-R1")
intent.setdefault("model_a_label", "DeepSeek R1")
intent.setdefault("model_b", "moonshotai/Kimi-K2-Instruct")
intent.setdefault("model_b_label", "Kimi K2")
# Dashboard defaults
intent.setdefault("input_label", "Paste your content here:")
intent.setdefault("input_placeholder", "Enter text to analyze...")
# Form wizard defaults
intent.setdefault("steps", [
{"key": "requirement", "question": "What is your main requirement?"},
{"key": "context", "question": "Can you describe your use case in more detail?"},
{"key": "constraints", "question": "Are there any constraints or preferences to keep in mind?"},
])
return intent
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