125 lines
4.4 KiB
Python
125 lines
4.4 KiB
Python
import chainlit as cl
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import httpx
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import json
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@cl.on_chat_start
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async def on_chat_start():
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initial_state = {
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"user_input": "",
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"user_feedback": None,
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"chat_history": [],
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"spec": {},
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"status": "start",
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"loop_count": 0,
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"existing_project": None,
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"generated_code": None,
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"qa_result": None,
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"is_completed": False
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}
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cl.user_session.set("graph_state", initial_state)
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await cl.Message(
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content="Bonjour 👋 Je suis ARC. Décris-moi ton besoin logiciel."
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).send()
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@cl.on_message
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async def on_message(message: cl.Message):
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# 1. Récupérer le state actuel de la session
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state = cl.user_session.get("graph_state")
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if "chat_history" not in state:
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state["chat_history"] = []
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if "status" not in state:
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state["status"] = "start"
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# 2. Déterminer si le message est une réponse à une question ou un nouveau projet
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if state.get("status") == "spec_incomplete":
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state["user_feedback"] = message.content
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else:
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state["user_input"] = message.content
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state["user_feedback"] = None
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# 3. Appel de l'API en envoyant le state COMPLET
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async with httpx.AsyncClient() as client:
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response = await client.post(
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"http://127.0.0.1:8000/api/workflow/run",
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json=state,
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timeout=600.0
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)
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# 4. Enregistrer le nouvel état retourné par le serveur
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new_state = response.json()
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cl.user_session.set("graph_state", new_state)
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# 5. Rendu UI intelligent dans Chainlit
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if new_state.get("status") == "spec_incomplete":
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spec = new_state.get("spec", {})
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question = spec.get("clarifying_question")
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await cl.Message(content=f"**Spécifications incomplètes**\n\n{question}").send()
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elif new_state.get("status") == "spec_ready":
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spec = new_state.get("spec", {})
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summary = "### Éléments importants à retenir de ton projet :\n\n"
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summary+= f"- **Nom du projet** : {spec.get('title')}\n"
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summary+= f"- **Description** : {spec.get('description')}\n"
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summary += "- **Actions** :\n"
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summary += "\n".join(
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f" - {req}" for req in spec.get("requirements", [])
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) + "\n"
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summary += "- **Contraintes** :\n"
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summary += "\n".join(
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f" - {constraint}" for constraint in spec.get("constraints", [])
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) + "\n"
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summary+= f"- **Langage** : {spec.get('language')}\n"
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summary += "\n**Est-ce que cela vous convient ?**"
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res = await cl.AskActionMessage(
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content=summary,
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actions=[
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cl.Action(name="oui", payload={"value": "oui"}, label="Oui, c'est parfait 👍"),
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cl.Action(name="non", payload={"value": "non"}, label="Non, modifier ❌")
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],
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timeout=3600
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).send()
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if res is None:
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await cl.Message(
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content="⏰ **Session expirée.** Si tu es toujours là, envoie un message pour relancer l'analyse."
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).send()
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return
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if res and res.get("name") == "oui":
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await cl.Message(content="🚀 **Spécifications validées !** Lancement de la génération du code...").send()
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new_state["status"] = "spec_approved"
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cl.user_session.set("graph_state", new_state)
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async with httpx.AsyncClient() as client:
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response = await client.post(
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"http://127.0.0.1:8000/api/workflow/run",
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json=new_state,
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timeout=600.0
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)
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final_state = response.json()
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cl.user_session.set("graph_state", final_state)
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await cl.Message(
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content=f"Résultat workflow :\n```json\n{json.dumps(final_state, indent=2, ensure_ascii=False)}\n```"
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).send()
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else:
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new_state["status"] = "spec_incomplete"
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cl.user_session.set("graph_state", new_state)
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await cl.Message(
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content="🔄 **Compris.** Qu'est-ce qui ne convient pas ? S'il te plaît, précise les éléments manquants ou à corriger :"
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).send()
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else:
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await cl.Message(
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content=f"Résultat workflow :\n```json\n{json.dumps(new_state, indent=2, ensure_ascii=False)}\n```"
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).send() |