support prime sandboxes

Author: 13point5

examples/prime_repl_example.py

@@ -0,0 +1,48 @@
+"""
+Example script to test Prime Intellect Sandboxes.
+
+Requirements:
+1. Install the Prime SDK:
+   pip install prime
+   # or for lightweight SDK only:
+   pip install prime-sandboxes
+
+2. Authenticate with Prime:
+   prime login
+   # or set environment variable:
+   export PRIME_API_KEY="your-api-key"
+
+3. Set your LLM API key (OpenAI in this example):
+   export OPENAI_API_KEY="your-api-key"
+"""
+
+import os
+
+from dotenv import load_dotenv
+
+from rlm import RLM
+from rlm.logger import RLMLogger
+
+load_dotenv()
+
+logger = RLMLogger(log_dir="./logs")
+
+rlm = RLM(
+    backend="openai",
+    backend_kwargs={
+        "api_key": os.getenv("OPENAI_API_KEY"),
+        "model_name": "gpt-5-nano",
+    },
+    environment="prime",
+    environment_kwargs={
+        "name": "rlm-prime-demo",
+        "docker_image": "python:3.11-slim",
+        "timeout_minutes": 30,
+    },
+    max_depth=1,
+    logger=logger,
+    verbose=True,
+)
+
+result = rlm.completion("Using your code, solve 2^(2^(2^(2))). Show your work in Python.")
+print(result.response)

examples/rlm_example.py

@@ -9,10 +9,10 @@
 
 logger = RLMLogger(log_dir="./logs")
 rlm = RLM(
-    backend="portkey",
+    backend="openai",
     backend_kwargs={
-        "api_key": os.getenv("PORTKEY_API_KEY"),
-        "model_name": "@openai/gpt-5-nano",
+        "api_key": os.getenv("OPENAI_API_KEY"),
+        "model_name": "gpt-5-nano",
     },
     environment="local",
     environment_kwargs={},

pyproject.toml

@@ -17,6 +17,7 @@ dependencies = [
 
 [project.optional-dependencies]
 modal = ["modal>=0.73.0", "dill>=0.3.7"]
+prime = ["prime-sandboxes>=0.2.0", "dill>=0.3.7"]
 
 [build-system]
 requires = ["setuptools>=61.0"]

rlm/core/types.py

@@ -3,7 +3,7 @@
 from typing import Any, Literal
 
 ClientBackend = Literal["openai", "portkey", "openrouter", "vllm", "litellm", "anthropic"]
-EnvironmentType = Literal["local", "prime", "modal"]
+EnvironmentType = Literal["local", "docker", "modal", "prime"]
 
 
 def _serialize_value(value: Any) -> Any:

rlm/environments/__init__.py

@@ -5,12 +5,12 @@
 
 
 def get_environment(
-    environment: Literal["local", "modal", "docker"],
+    environment: Literal["local", "modal", "docker", "prime"],
     environment_kwargs: dict[str, Any],
 ) -> BaseEnv:
     """
     Routes a specific environment and the args (as a dict) to the appropriate environment if supported.
-    Currently supported environments: ['local', 'modal', 'docker']
+    Currently supported environments: ['local', 'modal', 'docker', 'prime']
     """
     if environment == "local":
         return LocalREPL(**environment_kwargs)
@@ -22,7 +22,11 @@ def get_environment(
         from rlm.environments.docker_repl import DockerREPL
 
         return DockerREPL(**environment_kwargs)
+    elif environment == "prime":
+        from rlm.environments.prime_repl import PrimeREPL
+
+        return PrimeREPL(**environment_kwargs)
     else:
         raise ValueError(
-            f"Unknown environment: {environment}. Supported: ['local', 'modal', 'docker']"
+            f"Unknown environment: {environment}. Supported: ['local', 'modal', 'docker', 'prime']"
         )