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import json
from huggingface_hub import hf_hub_download
from llama_cpp import Llama
from llama_cpp_agent import LlamaCppAgent, MessagesFormatterType
from llama_cpp_agent.providers import LlamaCppPythonProvider
class ModelRunner:
def __init__(self, repo_id: str, filename: str):
model_path = hf_hub_download(
repo_id=repo_id,
filename=filename,
local_dir="./models"
)
self.llm = Llama(
model_path=model_path,
n_gpu_layers=0, # ⛔ No GPU
n_batch=512, # safe default for CPU
n_ctx=4096 # lower context for CPU environments
)
self.provider = LlamaCppPythonProvider(self.llm)
self.agent = LlamaCppAgent(
self.provider,
system_prompt="You are an AI developer. Given a codegen output, return a JSON mapping of filenames to file contents.",
predefined_messages_formatter_type=MessagesFormatterType.GEMMA_2,
debug_output=False
)
def interpret_code_description(self, pasted_text: str) -> str:
user_prompt = (
"Here is an AI output that includes multiple code files. "
"Please convert it into a JSON object like {\"file1.py\": \"...code...\", \"file2.txt\": \"...\"}\n\n"
f"{pasted_text}"
)
output = ""
for chunk in self.agent.get_chat_response(user_prompt, returns_streaming_generator=True):
output += chunk
return output
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