mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-10-20 05:15:31 +00:00
Removing old patches
This commit is contained in:
Sam Herring
parent
e46d5b2c13
commit
e3123be445
1 changed files with 6 additions and 98 deletions
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@ -27,6 +27,7 @@ from pathlib import Path
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from typing import Any, Dict, List, Optional, Tuple
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from pydantic import Field
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from datasets import load_dataset
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# Ensure hermes-agent root is on path
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_repo_root = Path(__file__).resolve().parent.parent.parent
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@ -36,64 +37,16 @@ if str(_repo_root) not in sys.path:
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from atroposlib.envs.base import ScoredDataGroup, ScoredDataItem
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from atroposlib.type_definitions import Item
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# Monkey-patch atroposlib's ManagedServer to forward chat_template_kwargs from
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# extra_body into apply_chat_template. Should be upstreamed to atroposlib.
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# Monkey-patch ManagedServer to normalize out Qwen3's empty think prefill
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# before prefix matching. The model echoes the prefill (<think>\n\n</think>\n\n)
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# in its completion, but the chat template strips it when re-rendering prior
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# turns, causing the prefix match to fail every turn.
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def _patch_managed_server():
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import inspect
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from atroposlib.envs.server_handling import managed_server as _ms
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_ManagedServer = _ms.ManagedServer
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# Patch 1: add extra_template_kwargs + chat_template_kwargs forwarding
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# Only apply if not already in the installed version
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_needs_patch1 = "extra_template_kwargs" not in inspect.signature(_ManagedServer._convert_messages_to_prompt).parameters
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if _needs_patch1:
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def _convert_messages_to_prompt(self, messages, tools=None, extra_template_kwargs=None):
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if tools and self._get_translator():
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messages = self._get_translator().convert_messages_for_template(messages)
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if self.tokenizer is None:
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return "\n".join([f"{m['role']}: {m.get('content', '')}" for m in messages])
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if hasattr(self.tokenizer, "apply_chat_template"):
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add_generation_prompt = len(messages) == 0 or messages[-1].get("role") != "assistant"
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if not self._preserve_think_blocks:
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messages = self._protect_think_blocks(messages)
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template_kwargs = {"tokenize": False, "add_generation_prompt": add_generation_prompt}
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if tools:
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template_kwargs["tools"] = tools
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if extra_template_kwargs:
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template_kwargs.update(extra_template_kwargs)
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prompt = self.tokenizer.apply_chat_template(messages, **template_kwargs)
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prompt = prompt.replace(self._THINK_OPEN, "<think>")
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prompt = prompt.replace(self._THINK_CLOSE, "</think>")
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return prompt
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return "\n".join([f"{m['role']}: {m.get('content', '')}" for m in messages])
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_orig_chat_completion = _ManagedServer.chat_completion
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async def chat_completion(self, **kwargs):
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extra_body = kwargs.get("extra_body", {}) or {}
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chat_template_kwargs = extra_body.get("chat_template_kwargs", None)
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self._pending_chat_template_kwargs = chat_template_kwargs
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try:
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return await _orig_chat_completion(self, **kwargs)
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finally:
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self._pending_chat_template_kwargs = None
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def _convert_messages_to_prompt_with_stash(self, messages, tools=None, extra_template_kwargs=None):
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if extra_template_kwargs is None:
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extra_template_kwargs = getattr(self, "_pending_chat_template_kwargs", None)
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return _convert_messages_to_prompt(self, messages, tools=tools, extra_template_kwargs=extra_template_kwargs)
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_ManagedServer._convert_messages_to_prompt = _convert_messages_to_prompt_with_stash
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_ManagedServer.chat_completion = chat_completion
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print("[patch] ManagedServer: support chat_template_kwargs in extra_body")
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# Patch 2: fix _find_extending_node and _compute_input_ids to normalize out
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# Qwen3's empty think prefill before prefix matching. The model echoes the
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# prefill (<think>\n\n</think>\n\n or <think>\n</think>\n\n) in its completion,
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# but the chat template strips it when re-rendering prior turns, causing the
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# prefix match to fail every turn.
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# Normalize out Qwen3's empty think prefill before prefix matching.
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import re as _re
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_EMPTY_THINK_RE = _re.compile(r"<think>\n*</think>\n\n")
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@ -332,12 +285,9 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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self._split_dataset()
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return
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# Otherwise, load from HuggingFace
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logger.info(f"Loading dataset from HuggingFace: {self.config.dataset_name}")
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try:
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from datasets import load_dataset
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self._dataset = await asyncio.get_event_loop().run_in_executor(
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None,
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lambda: load_dataset(
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@ -381,7 +331,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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random.shuffle(self._dataset_indices)
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self._current_index = 0
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# Fix eval indices with a fixed seed so the same 20 tasks are used across runs
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num_eval = min(self.config.num_eval_tasks, len(self._eval_dataset))
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rng = random.Random(42)
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self._eval_indices = rng.sample(range(len(self._eval_dataset)), num_eval)
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@ -745,15 +694,12 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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task_id = str(uuid.uuid4())
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task_name = item.get("task_name", "unknown")
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# Build task-specific Docker image (cached across runs)
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docker_image = await asyncio.get_event_loop().run_in_executor(
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None, self._build_task_docker_image, item
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)
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logger.debug(f"collect_trajectory START for {task_name}")
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# Register image override for this task_id (set both docker_image and
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# modal_image so the correct one is used regardless of backend)
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logger.debug(f"Registering Docker image: {docker_image}")
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register_task_env_overrides(task_id, {
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"docker_image": docker_image,
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@ -765,7 +711,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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logger.debug("Docker image registered")
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try:
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# Get group-level tools (resolved once in collect_trajectories)
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logger.debug("Resolving tools...")
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if self._current_group_tools is None:
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tools, valid_names = self._resolve_tools_for_group()
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@ -787,10 +732,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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async with self._container_sem:
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if self._use_managed_server():
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try:
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# No tool_call_parser — let the chat template render tool calls
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# natively so full_text is consistent across turns (enabling
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# multi-turn sequence extension). agent_loop has a fallback
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# to parse raw <tool_call> content.
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managed_ctx = self.server.managed_server(
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tokenizer=self.tokenizer,
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preserve_think_blocks=True,
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@ -824,7 +765,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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)
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result = await agent.run(messages)
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else:
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# Phase 1: OpenAI server
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agent = HermesAgentLoop(
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server=self.server,
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tool_schemas=tools,
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@ -837,7 +777,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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)
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result = await agent.run(messages)
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# Skip reward computation if agent produced no output
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only_system_and_user = all(
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msg.get("role") in ("system", "user") for msg in result.messages
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)
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@ -846,10 +785,8 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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"Agent loop produced no output (turns=%d). Skipping trajectory.",
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result.turns_used,
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)
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# Return None to skip this trajectory (likely an API failure)
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return None, []
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else:
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# Compute reward using ToolContext
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ctx = ToolContext(task_id)
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try:
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reward = await self.compute_reward(item, result, ctx)
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@ -883,23 +820,9 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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self._metrics_buffer.append(task_metrics)
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# ============================================================================
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# Build ScoredDataItem from result
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# ============================================================================
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# Phase 2: Extract tokens/masks/logprobs from first SequenceNode
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# Phase 1: Create placeholder tokens for OpenAI-style servers
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# ============================================================================
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# Build return value.
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# The base collect_trajectories() calls this group_size times and
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# aggregates using .append(), so we must return a ScoredDataItem
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# (scalar scores, single token list, etc.) -- NOT a ScoredDataGroup
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# with list-valued fields, which would cause double-wrapping and
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# "unhashable type: list" errors in handle_send_to_api.
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nodes = (managed_state or {}).get("nodes", []) if managed_state else []
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if nodes:
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# Phase 2: Use last node — ManagedServer extends the sequence each turn,
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# carrying forward masked_tokens so all assistant turns are unmasked.
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node = nodes[-1]
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tokens = node.tokens
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masks = node.masked_tokens
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@ -911,7 +834,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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inference_logprobs = [1.0] * len(tokens)
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logger.warning(f"Phase 2: node has no logprobs! Falling back to placeholders.")
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else:
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# Phase 1: placeholder tokens
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logger.warning(f"Phase 1 fallback: managed_state empty, using placeholder logprobs. IS loss will be zero!")
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full_text = "\n".join(
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msg.get("content", "") for msg in result.messages if msg.get("content")
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@ -939,7 +861,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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return scored_item, []
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finally:
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# Clean up task overrides and sandbox
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clear_task_env_overrides(task_id)
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try:
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cleanup_vm(task_id)
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@ -971,7 +892,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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logger.info(f"Task {task_name}: running tests in sandbox...")
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try:
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# Run tests in a thread to avoid blocking the event loop
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loop = asyncio.get_event_loop()
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reward = await loop.run_in_executor(
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None,
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@ -1018,15 +938,12 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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Float between 0.0 and 1.0 based on test pass ratio
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"""
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try:
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# Upload test file to a writable temp directory
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# (Using /workspace fails on macOS local backend because / is read-only)
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test_content = test_file_path.read_text()
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test_dir = f"/tmp/_hermes_test_{os.getpid()}"
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test_path = f"{test_dir}/test_final_state.py"
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ctx.write_file(test_path, test_content)
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logger.debug(f"Task {task_name}: uploaded test file to {test_path}")
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# Run pytest -v for per-test pass/fail details
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result = ctx.terminal(
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f"cd {test_dir} && python3 -m pytest -v test_final_state.py 2>&1",
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timeout=self.config.test_timeout_s,
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@ -1039,16 +956,12 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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logger.debug(f"Task {task_name}: all tests passed")
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return 1.0
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# Parse pytest -v output for granular scoring
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# Lines like: "test_final_state.py::test_name PASSED"
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# or: "test_final_state.py::test_name FAILED"
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passed = len(re.findall(r" PASSED", output))
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failed = len(re.findall(r" FAILED", output))
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errored = len(re.findall(r" ERROR", output))
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total = passed + failed + errored
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if total > 0:
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# Score is fraction of tests passed
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reward = passed / total
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logger.info(
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f"Task {task_name}: {passed}/{total} tests passed "
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@ -1056,8 +969,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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)
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return reward
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else:
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# Couldn't parse output — fall back to binary
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# Also try the summary line: "X passed, Y failed"
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summary_match = re.search(
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r"(\d+) passed(?:.*?(\d+) failed)?", output
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)
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@ -1100,7 +1011,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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logger.warning("Eval dataset is empty")
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return {}
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# Use min of num_eval_tasks and actual eval set size
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print(f"[evaluate] running {len(self._eval_indices)} eval tasks at step {self.curr_step}")
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logger.info(f"Starting evaluation on {len(self._eval_indices)} held-out tasks...")
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@ -1111,8 +1021,6 @@ class EndlessTerminalsEnv(HermesAgentBaseEnv):
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"natural_finishes": [],
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}
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# Sample from eval set (holdout)
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import random
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eval_items = [self._build_item_from_dataset(self._eval_dataset[idx]) for idx in self._eval_indices]
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eval_items = [item for item in eval_items if item is not None]
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print(f"[evaluate] built {len(eval_items)} items from {len(self._eval_indices)} indices")
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