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inference.py

@@ -5,10 +5,10 @@ Runs all 3 scenarios (easy/medium/hard) end-to-end against a containerised env,
 calling an LLM via the OpenAI client against a Hugging Face Router endpoint.
 
 Environment variables (all read via os.getenv):
-    HF_TOKEN         -- HuggingFace token used as the OpenAI API key.
+    HF_TOKEN         -- HuggingFace token used as the OpenAI API key (no default).
     API_BASE_URL     -- LLM base URL (default: HF Router).
     MODEL_NAME       -- LLM model id (default: Qwen/Qwen2.5-72B-Instruct).
-    IMAGE_NAME       -- local Docker image tag for the env container.
+    LOCAL_IMAGE_NAME -- optional; local Docker image tag when using from_docker_image().
 
 Strict stdout format enforced by the grader:
     [START] task=<id> env=<benchmark> model=<model>
@@ -40,11 +40,17 @@ except ModuleNotFoundError:
 
 
 # ---------- Config ----------
+# Follows hackathon pre-submission checklist:
+#   - Defaults are set only for API_BASE_URL and MODEL_NAME (not HF_TOKEN).
+#   - LOCAL_IMAGE_NAME is optional, used when calling from_docker_image().
+
+API_BASE_URL = os.getenv("API_BASE_URL", "https://router.huggingface.co/v1")
+MODEL_NAME = os.getenv("MODEL_NAME", "Qwen/Qwen2.5-72B-Instruct")
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+# Optional — used only when launching the env from a local Docker image.
+LOCAL_IMAGE_NAME = os.getenv("LOCAL_IMAGE_NAME", "postmortem_env-env:latest")
 
-API_KEY = os.getenv("HF_TOKEN") or os.getenv("API_KEY")
-API_BASE_URL = os.getenv("API_BASE_URL") or "https://router.huggingface.co/v1"
-MODEL_NAME = os.getenv("MODEL_NAME") or "Qwen/Qwen2.5-72B-Instruct"
-IMAGE_NAME = os.getenv("IMAGE_NAME") or "postmortem_env-env:latest"
 BENCHMARK = "postmortem_env"
 
 MAX_STEPS = 12
@@ -260,11 +266,11 @@ async def run_one_task(client: OpenAI, env: PostmortemEnv) -> None:
 
 
 async def main() -> None:
-    client = OpenAI(base_url=API_BASE_URL, api_key=API_KEY)
+    client = OpenAI(base_url=API_BASE_URL, api_key=HF_TOKEN)
 
     # Spin up one containerised env; run the 3 scenarios back-to-back
     # by issuing 3 resets (the env rotates scenarios on each reset).
-    env = await PostmortemEnv.from_docker_image(IMAGE_NAME)
+    env = await PostmortemEnv.from_docker_image(LOCAL_IMAGE_NAME)
     try:
         for _ in range(3):
             await run_one_task(client, env)