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cloooooo — personal LLM client, prompt/context/thinking interface over local Ollama

Project description

clovis

Client Python personnel pour un LLM local via Ollama. Interface ultra-simple : prompt, negative_prompt, thinking, context.

Install

pip install clovis

Usage

from clovis import cloooooo

ai = cloooooo()

# Appel direct
print(ai("Explique les trous noirs"))

# Avec options
print(ai(
    "Génère un poème sur la mer",
    negative_prompt="pas de rimes",
    thinking=True,
    context="Tu es un poète du 19e siècle.",
))

# Streaming token par token
for token in ai.stream("Raconte une histoire courte"):
    print(token, end="", flush=True)

# Conversation avec mémoire
conv = ai.conversation(context="Tu es un expert en finance.")
conv("Explique le CAPM")
conv("Et ses limites ?")  # se souvient de la réponse précédente

CLI

clovis "Explique les trous noirs"           # question directe
clovis "Génère un poème" --no "sans rimes"  # avec negative prompt
clovis "Résous ce problème" --think          # mode réflexion
clovis repl                                  # conversation interactive
clovis serve --port 8000                     # démarre le serveur API

API server

clovis serve --port 8000 --key sk-montoken

Requête :

curl -X POST http://localhost:8000/ia \
  -H "Authorization: Bearer sk-montoken" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Bonjour !", "thinking": false}'

Réponse : {"response": "Bonjour ! Comment puis-je t'aider ?"}

Streaming : ajouter "stream": true → réponse en text/plain token par token.

Config

export CLOVIS_MODEL="qwen3-72b-q5km"        # modèle Ollama
export CLOVIS_OLLAMA_URL="http://localhost:11434"
export CLOVIS_API_KEY="sk-..."              # clé API pour le serveur

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