diff --git a/miles/rollout/miles_router_generate.py b/miles/rollout/miles_router_generate.py
deleted file mode 100644
index ab100574b17..00000000000
--- a/miles/rollout/miles_router_generate.py
+++ /dev/null
@@ -1,117 +0,0 @@
-from miles.utils.http_utils import post
-from miles.utils.types import Sample
-
-
-async def generate_with_miles_router(args, sample: Sample, sampling_params) -> Sample:
-    """Generate using MilesRouter with text-based workflow"""
-
-    assert (
-        sample.status == Sample.Status.PENDING or sample.status == Sample.Status.ABORTED
-    ), f"Sample status is {sample.status}"
-
-    url = f"http://{args.sglang_router_ip}:{args.sglang_router_port}/generate"
-
-    # Build full text (prompt + existing response)
-    if isinstance(sample.prompt, str):
-        full_text = sample.prompt + sample.response
-    else:
-        # Handle list of dicts format (chat format)
-        # For now, just convert to simple string - this might need refinement
-        full_text = str(sample.prompt) + sample.response
-
-    # Adjust max_new_tokens based on existing response length
-    if len(sample.response) > 0:
-        sampling_params["max_new_tokens"] -= sample.response_length
-
-    assert (
-        sampling_params["max_new_tokens"] >= 0
-    ), f"max_new_tokens: {sampling_params['max_new_tokens']} should not be less than 0"
-    if sampling_params["max_new_tokens"] == 0:
-        sample.status = Sample.Status.TRUNCATED
-        return sample
-
-    # Prepare payload for MilesRouter (text-based)
-    payload = {
-        "text": full_text,
-        "sampling_params": sampling_params,
-        "return_logprob": True,
-    }
-
-    # Call MilesRouter /generate endpoint
-    output = await post(url, payload)
-
-    # Extract generated text and update sample
-    generated_text = output.get("text", "")
-    sample.response += generated_text
-    # Don't update response_length here - it will be calculated from actual tokens later
-
-    # Get token IDs and logprobs using MilesRouter's /retrieve_from_text
-    retrieve_url = f"http://{args.sglang_router_ip}:{args.sglang_router_port}/retrieve_from_text"
-    retrieve_payload = {"text": sample.prompt + sample.response, "return_logp": True}
-
-    retrieve_output = await post(retrieve_url, retrieve_payload)
-
-    # Update sample with retrieved token information
-    if "tokens" in retrieve_output:
-        sample.tokens = retrieve_output["tokens"]
-
-        # Calculate response_length from actual tokens
-        # Get prompt tokens to determine response length
-        if hasattr(sample, "prompt_tokens") and sample.prompt_tokens:
-            prompt_token_count = len(sample.prompt_tokens)
-        else:
-            # Fallback: tokenize prompt to get prompt token count
-            from transformers import AutoTokenizer
-
-            tokenizer = AutoTokenizer.from_pretrained(args.hf_checkpoint, trust_remote_code=True)
-            prompt_tokens = tokenizer(sample.prompt, add_special_tokens=False)["input_ids"]
-            prompt_token_count = len(prompt_tokens)
-
-        # Calculate response_length as the difference between total and prompt tokens
-        sample.response_length = len(sample.tokens) - prompt_token_count
-
-    if "logp" in retrieve_output:
-        # For MilesRouter, we get the full logprobs - need to extract only response ones
-        full_logprobs = retrieve_output["logp"]
-        if sample.rollout_log_probs is None:
-            sample.rollout_log_probs = []
-
-        # Get the full token sequence to determine prompt vs response split
-        full_tokens = retrieve_output.get("tokens", [])
-
-        # Calculate prompt token count (this should match the original prompt)
-        if hasattr(sample, "prompt_tokens") and sample.prompt_tokens:
-            prompt_token_count = len(sample.prompt_tokens)
-        else:
-            # Fallback: tokenize prompt to get prompt token count
-            from transformers import AutoTokenizer
-
-            tokenizer = AutoTokenizer.from_pretrained(args.hf_checkpoint, trust_remote_code=True)
-            prompt_tokens = tokenizer(sample.prompt, add_special_tokens=False)["input_ids"]
-            prompt_token_count = len(prompt_tokens)
-
-        # Extract only the response log_probs (skip prompt part)
-        response_logprobs = full_logprobs[prompt_token_count:] if len(full_logprobs) > prompt_token_count else []
-
-        # Ensure we only add logprobs for the actual response tokens
-        if len(response_logprobs) > 0:
-            sample.rollout_log_probs.extend(response_logprobs)
-
-    # Handle weight version if available
-    if "meta_info" in output and "weight_version" in output["meta_info"]:
-        sample.weight_versions.append(output["meta_info"]["weight_version"])
-
-    # Set finish reason based on output
-    if "meta_info" in output and "finish_reason" in output["meta_info"]:
-        match output["meta_info"]["finish_reason"]["type"]:
-            case "length":
-                sample.status = Sample.Status.TRUNCATED
-            case "abort":
-                sample.status = Sample.Status.ABORTED
-            case "stop":
-                sample.status = Sample.Status.COMPLETED
-    else:
-        # Default to completed if no finish_reason provided
-        sample.status = Sample.Status.COMPLETED
-
-    return sample