Add exo eval

https://platform.openai.com/docs/api-reference/chat/get

bench/exo_eval.py

@@ -0,0 +1,378 @@
+#!/usr/bin/env python3
+# pyright: reportAny=false, reportUnknownMemberType=false, reportUnknownVariableType=false, reportUnknownArgumentType=false, reportMissingTypeStubs=false
+"""
+exo-eval: Run SWE-bench evaluation against exo using OpenHands SDK (local, no Docker).
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import subprocess
+import tempfile
+import time
+from dataclasses import dataclass
+from enum import Enum
+from pathlib import Path
+from typing import Any
+
+from datasets import load_dataset
+from loguru import logger
+from openhands.sdk import LLM, Agent, Conversation, Tool
+from openhands.tools.file_editor import FileEditorTool
+from openhands.tools.terminal import TerminalTool
+
+
+class EvalStatus(str, Enum):
+    Resolved = "Resolved"
+    Failed = "Failed"
+    Error = "Error"
+    Timeout = "Timeout"
+
+
+@dataclass
+class EvalResult:
+    instance_id: str
+    repo: str
+    status: EvalStatus
+    elapsed_seconds: float
+    tests_passed: list[str]
+    tests_failed: list[str]
+    error_message: str | None = None
+
+
+def load_swe_bench(
+    split: str = "lite",
+    limit: int | None = None,
+    instance_ids: list[str] | None = None,
+) -> list[dict[str, Any]]:
+    """Load SWE-bench dataset from HuggingFace."""
+    # SWE-bench Lite is a curated 300-instance subset
+    dataset_name = (
+        "princeton-nlp/SWE-bench_Lite" if split == "lite" else "princeton-nlp/SWE-bench"
+    )
+    actual_split = "test" if split == "lite" else split
+
+    ds = load_dataset(dataset_name, split=actual_split)
+    instances = [dict(row) for row in ds]
+
+    if instance_ids:
+        instances = [i for i in instances if i["instance_id"] in instance_ids]
+
+    if limit:
+        instances = instances[:limit]
+
+    return instances
+
+
+def clone_repo_at_commit(repo: str, commit: str, dest: Path) -> None:
+    """Clone a repo at a specific commit."""
+    repo_url = f"https://github.com/{repo}.git"
+
+    subprocess.run(
+        ["git", "clone", "--depth", "1", repo_url, str(dest)],
+        check=True,
+        capture_output=True,
+    )
+
+    subprocess.run(
+        ["git", "fetch", "--depth", "1", "origin", commit],
+        cwd=dest,
+        check=True,
+        capture_output=True,
+    )
+
+    subprocess.run(
+        ["git", "checkout", commit],
+        cwd=dest,
+        check=True,
+        capture_output=True,
+    )
+
+
+def build_agent_prompt(instance: dict[str, Any]) -> str:
+    """Build the prompt for the agent."""
+    return f"""You are a software engineer fixing a bug in the {instance['repo']} repository.
+
+## Problem Statement
+{instance['problem_statement']}
+
+## Instructions
+1. Explore the codebase to understand the issue
+2. Identify the files that need to be modified
+3. Make the necessary changes to fix the issue
+4. The fix should be minimal and targeted
+
+You have access to:
+- terminal: Run shell commands (git, grep, python, etc.)
+- file_editor: View and edit files
+
+Start by exploring the repository structure to understand where the relevant code is.
+"""
+
+
+def parse_fail_to_pass(fail_to_pass_str: str) -> list[str]:
+    """Parse the FAIL_TO_PASS field into a list of test names."""
+    try:
+        return json.loads(fail_to_pass_str)
+    except json.JSONDecodeError:
+        return [t.strip() for t in fail_to_pass_str.split(",") if t.strip()]
+
+
+def run_tests(workspace: Path, tests: list[str]) -> tuple[list[str], list[str]]:
+    """Run tests and return (passed, failed) lists."""
+    passed = []
+    failed = []
+
+    for test in tests:
+        try:
+            result = subprocess.run(
+                ["python", "-m", "pytest", "-xvs", test],
+                cwd=workspace,
+                capture_output=True,
+                timeout=300,
+            )
+            if result.returncode == 0:
+                passed.append(test)
+            else:
+                failed.append(test)
+        except subprocess.TimeoutExpired:
+            failed.append(test)
+
+    return passed, failed
+
+
+def run_single_eval(
+    instance: dict[str, Any],
+    host: str,
+    port: int,
+    model: str,
+    max_turns: int = 30,
+    timeout: float = 600.0,
+) -> EvalResult:
+    """Evaluate a single SWE-bench instance."""
+    instance_id = instance["instance_id"]
+    repo = instance["repo"]
+    base_commit = instance["base_commit"]
+    fail_to_pass = parse_fail_to_pass(instance["FAIL_TO_PASS"])
+
+    start_time = time.perf_counter()
+
+    try:
+        with tempfile.TemporaryDirectory() as tmpdir:
+            workspace = Path(tmpdir) / "repo"
+
+            # Clone repo at base commit
+            logger.info(f"Cloning {repo} at {base_commit[:8]}...")
+            clone_repo_at_commit(repo, base_commit, workspace)
+
+            # Setup OpenHands agent
+            llm = LLM(
+                model=f"openai/{model}",
+                base_url=f"http://{host}:{port}/v1",
+                api_key="not-needed",
+            )
+
+            agent = Agent(
+                llm=llm,
+                tools=[
+                    Tool(name=TerminalTool.name),
+                    Tool(name=FileEditorTool.name),
+                ],
+            )
+
+            # Run agent
+            conversation = Conversation(
+                agent=agent,
+                workspace=str(workspace),
+            )
+
+            logger.info(f"Running agent on {instance_id}...")
+            conversation.send_message(build_agent_prompt(instance))
+
+            for _turn in range(max_turns):
+                if time.perf_counter() - start_time > timeout:
+                    return EvalResult(
+                        instance_id=instance_id,
+                        repo=repo,
+                        status=EvalStatus.Timeout,
+                        elapsed_seconds=time.perf_counter() - start_time,
+                        tests_passed=[],
+                        tests_failed=fail_to_pass,
+                    )
+
+                result = conversation.run(max_turns=1)
+                if result.done:
+                    break
+
+            # Run tests to verify
+            logger.info(f"Running tests for {instance_id}...")
+            passed, failed = run_tests(workspace, fail_to_pass)
+
+            elapsed = time.perf_counter() - start_time
+            status = EvalStatus.Resolved if not failed else EvalStatus.Failed
+
+            return EvalResult(
+                instance_id=instance_id,
+                repo=repo,
+                status=status,
+                elapsed_seconds=elapsed,
+                tests_passed=passed,
+                tests_failed=failed,
+            )
+
+    except Exception as e:
+        return EvalResult(
+            instance_id=instance_id,
+            repo=repo,
+            status=EvalStatus.Error,
+            elapsed_seconds=time.perf_counter() - start_time,
+            tests_passed=[],
+            tests_failed=[],
+            error_message=str(e),
+        )
+
+
+def verify_exo_running(host: str, port: int, model: str) -> str:
+    """Verify exo is running and return full model ID."""
+    import http.client
+
+    conn = http.client.HTTPConnection(host, port, timeout=10)
+    conn.request("GET", "/models")
+    resp = conn.getresponse()
+
+    if resp.status != 200:
+        raise RuntimeError(f"exo not responding at {host}:{port}")
+
+    data = json.loads(resp.read())
+    for m in data.get("data", []):
+        if m.get("id") == model or m.get("hugging_face_id") == model:
+            return m.get("hugging_face_id") or m.get("id")
+
+    raise ValueError(f"Model '{model}' not found in exo")
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser(
+        prog="exo-eval",
+        description="Run SWE-bench evaluation against exo (local, no Docker).",
+    )
+
+    ap.add_argument("--host", default=os.environ.get("EXO_HOST", "localhost"))
+    ap.add_argument(
+        "--port", type=int, default=int(os.environ.get("EXO_PORT", "52415"))
+    )
+    ap.add_argument("--model", required=True, help="exo model ID")
+    ap.add_argument(
+        "--split", default="lite", choices=["lite", "dev", "test", "train"]
+    )
+    ap.add_argument("--limit", type=int, default=10, help="Max instances")
+    ap.add_argument("--instance-ids", nargs="+", help="Specific instance IDs")
+    ap.add_argument("--max-turns", type=int, default=30)
+    ap.add_argument("--timeout", type=float, default=600.0)
+    ap.add_argument("--json-out", default="bench/eval_results.json")
+    ap.add_argument("-v", "--verbose", action="store_true")
+    ap.add_argument("--dry-run", action="store_true")
+
+    args = ap.parse_args()
+
+    # Load dataset first (doesn't require exo to be running)
+    logger.info(f"Loading SWE-bench {args.split} dataset...")
+    instances = load_swe_bench(
+        split=args.split,
+        limit=args.limit,
+        instance_ids=args.instance_ids,
+    )
+    logger.info(f"Loaded {len(instances)} instances")
+
+    if args.dry_run:
+        print(f"\nSWE-bench {args.split} instances ({len(instances)}):")
+        for inst in instances:
+            print(f"  {inst['instance_id']} ({inst['repo']})")
+        return 0
+
+    # Verify exo is running
+    model_id = verify_exo_running(args.host, args.port, args.model)
+    logger.info(f"Using model: {model_id}")
+
+    # Run evaluation
+    results: list[EvalResult] = []
+    for i, instance in enumerate(instances):
+        logger.info(f"[{i+1}/{len(instances)}] {instance['instance_id']}")
+
+        result = run_single_eval(
+            instance=instance,
+            host=args.host,
+            port=args.port,
+            model=model_id,
+            max_turns=args.max_turns,
+            timeout=args.timeout,
+        )
+        results.append(result)
+
+        logger.info(f"  Status: {result.status.value}")
+        if result.tests_passed:
+            logger.info(f"  Passed: {len(result.tests_passed)} tests")
+        if result.tests_failed:
+            logger.info(f"  Failed: {len(result.tests_failed)} tests")
+        if result.error_message:
+            logger.error(f"  Error: {result.error_message}")
+
+    # Compute summary
+    total = len(results)
+    resolved = sum(1 for r in results if r.status == EvalStatus.Resolved)
+    failed = sum(1 for r in results if r.status == EvalStatus.Failed)
+    errors = sum(1 for r in results if r.status == EvalStatus.Error)
+    timeouts = sum(1 for r in results if r.status == EvalStatus.Timeout)
+
+    summary = {
+        "model": model_id,
+        "split": args.split,
+        "total": total,
+        "resolved": resolved,
+        "resolved_rate": resolved / total if total else 0,
+        "failed": failed,
+        "errors": errors,
+        "timeouts": timeouts,
+    }
+
+    output = {
+        "summary": summary,
+        "results": [
+            {
+                "instance_id": r.instance_id,
+                "repo": r.repo,
+                "status": r.status.value,
+                "elapsed_seconds": r.elapsed_seconds,
+                "tests_passed": r.tests_passed,
+                "tests_failed": r.tests_failed,
+                "error_message": r.error_message,
+            }
+            for r in results
+        ],
+    }
+
+    Path(args.json_out).write_text(json.dumps(output, indent=2))
+    logger.info(f"Results written to {args.json_out}")
+
+    # Print summary
+    print("\n" + "=" * 60)
+    print("SWE-bench Evaluation Results")
+    print("=" * 60)
+    print(f"Model:    {model_id}")
+    print(f"Split:    {args.split}")
+    print(f"Total:    {total}")
+    if total:
+        print(f"Resolved: {resolved} ({resolved/total*100:.1f}%)")
+    else:
+        print("Resolved: 0")
+    print(f"Failed:   {failed}")
+    print(f"Errors:   {errors}")
+    print(f"Timeouts: {timeouts}")
+    print("=" * 60)
+
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

pyproject.toml

@@ -23,6 +23,9 @@ dependencies = [
     "tiktoken>=0.12.0", # required for kimi k2 tokenizer
     "hypercorn>=0.18.0",
     "openai-harmony>=0.0.8",
+    "openhands-sdk>=0.1.0", # for exo-eval SWE-bench evaluation
+    "openhands-tools>=0.1.0", # tools for openhands agents
+    "datasets>=3.0.0", # for loading SWE-bench from HuggingFace
 ]
 
 [project.scripts]

src/exo/master/api.py

@@ -1,6 +1,6 @@
 import time
 from collections.abc import AsyncGenerator
-from typing import cast
+from typing import Any, cast
 
 import anyio
 from anyio import create_task_group
@@ -72,7 +72,13 @@ def chunk_to_response(
         choices=[
             StreamingChoiceResponse(
                 index=0,
-                delta=ChatCompletionMessage(role="assistant", content=chunk.text),
+                delta=ChatCompletionMessage(
+                    role="assistant",
+                    content=chunk.text if chunk.text else None,
+                    tool_calls=[tc.model_dump() for tc in chunk.tool_calls]
+                    if chunk.tool_calls
+                    else None,
+                ),
                 finish_reason=chunk.finish_reason,
             )
         ],
@@ -424,6 +430,7 @@ class API:
         text_parts: list[str] = []
         model: str | None = None
         finish_reason: FinishReason | None = None
+        all_tool_calls: list[dict[str, Any]] = []
 
         async for chunk in self._chat_chunk_stream(command_id):
             if model is None:
@@ -431,6 +438,20 @@ class API:
 
             text_parts.append(chunk.text)
 
+            # Collect tool calls
+            if chunk.tool_calls:
+                for tc in chunk.tool_calls:
+                    all_tool_calls.append(
+                        {
+                            "id": tc.id,
+                            "type": tc.type,
+                            "function": {
+                                "name": tc.function.name,
+                                "arguments": tc.function.arguments,
+                            },
+                        }
+                    )
+
             if chunk.finish_reason is not None:
                 finish_reason = chunk.finish_reason
 
@@ -446,7 +467,8 @@ class API:
                     index=0,
                     message=ChatCompletionMessage(
                         role="assistant",
-                        content=combined_text,
+                        content=combined_text if combined_text else None,
+                        tool_calls=all_tool_calls if all_tool_calls else None,
                     ),
                     finish_reason=finish_reason,
                 )
@@ -459,6 +481,7 @@ class API:
         text_parts: list[str] = []
         model: str | None = None
         finish_reason: FinishReason | None = None
+        all_tool_calls: list[dict[str, Any]] = []
 
         stats: GenerationStats | None = None
 
@@ -469,6 +492,20 @@ class API:
             text_parts.append(chunk.text)
             stats = chunk.stats or stats
 
+            # Collect tool calls
+            if chunk.tool_calls:
+                for tc in chunk.tool_calls:
+                    all_tool_calls.append(
+                        {
+                            "id": tc.id,
+                            "type": tc.type,
+                            "function": {
+                                "name": tc.function.name,
+                                "arguments": tc.function.arguments,
+                            },
+                        }
+                    )
+
             if chunk.finish_reason is not None:
                 finish_reason = chunk.finish_reason
 
@@ -483,7 +520,9 @@ class API:
                 ChatCompletionChoice(
                     index=0,
                     message=ChatCompletionMessage(
-                        role="assistant", content=combined_text
+                        role="assistant",
+                        content=combined_text if combined_text else None,
+                        tool_calls=all_tool_calls if all_tool_calls else None,
                     ),
                     finish_reason=finish_reason,
                 )

src/exo/shared/types/chunks.py

@@ -1,4 +1,7 @@
 from enum import Enum
+from typing import Literal
+
+from pydantic import BaseModel
 
 from exo.shared.types.api import GenerationStats
 from exo.utils.pydantic_ext import TaggedModel
@@ -12,6 +15,17 @@ class ChunkType(str, Enum):
     Image = "Image"
 
 
+class ToolCallFunction(BaseModel, frozen=True):
+    name: str
+    arguments: str
+
+
+class ToolCall(BaseModel, frozen=True):
+    id: str
+    type: Literal["function"] = "function"
+    function: ToolCallFunction
+
+
 class BaseChunk(TaggedModel):
     idx: int
     model: ModelId
@@ -22,6 +36,7 @@ class TokenChunk(BaseChunk):
     token_id: int
     finish_reason: FinishReason | None = None
     stats: GenerationStats | None = None
+    tool_calls: list[ToolCall] | None = None
 
 
 class ImageChunk(BaseChunk):

src/exo/shared/types/worker/runner_response.py

@@ -1,4 +1,5 @@
 from exo.shared.types.api import FinishReason, GenerationStats
+from exo.shared.types.chunks import ToolCall
 from exo.utils.pydantic_ext import TaggedModel
 
 
@@ -16,6 +17,7 @@ class GenerationResponse(BaseRunnerResponse):
     # logprobs: list[float] | None = None # too big. we can change to be top-k
     finish_reason: FinishReason | None = None
     stats: GenerationStats | None = None
+    tool_calls: list[ToolCall] | None = None
 
 
 class FinishedResponse(BaseRunnerResponse):

src/exo/worker/runner/runner.py

@@ -1,9 +1,13 @@
+import json
 import time
 from collections.abc import Generator
 from functools import cache
+from typing import Any
+from uuid import uuid4
 
 import mlx.core as mx
 from mlx_lm.models.gpt_oss import Model as GptOssModel
+from mlx_lm.tokenizer_utils import TokenizerWrapper
 from openai_harmony import (  # pyright: ignore[reportMissingTypeStubs]
     HarmonyEncodingName,
     Role,
@@ -12,7 +16,7 @@ from openai_harmony import (  # pyright: ignore[reportMissingTypeStubs]
 )
 
 from exo.shared.types.api import ChatCompletionMessageText
-from exo.shared.types.chunks import TokenChunk
+from exo.shared.types.chunks import TokenChunk, ToolCall, ToolCallFunction
 from exo.shared.types.events import (
     ChunkGenerated,
     Event,
@@ -172,7 +176,10 @@ def main(
                     if isinstance(model, GptOssModel):
                         mlx_generator = parse_gpt_oss(mlx_generator)
 
-                    # TODO: Add tool call parser here
+                    # Parse tool calls to place them in the tool calls section
+                    mlx_generator = parse_tool_calls(
+                        mlx_generator, tokenizer, task_params.tools
+                    )
 
                     for response in mlx_generator:
                         match response:
@@ -188,6 +195,7 @@ def main(
                                                 token_id=response.token,
                                                 finish_reason=response.finish_reason,
                                                 stats=response.stats,
+                                                tool_calls=response.tool_calls,
                                             ),
                                         )
                                     )
@@ -261,6 +269,98 @@ def parse_gpt_oss(
             break
 
 
+def _generate_tool_call_id() -> str:
+    return f"call_{uuid4().hex[:24]}"
+
+
+def _parse_tool_call_content(
+    content: str,
+    tokenizer: TokenizerWrapper,
+    tools: list[dict[str, Any]] | None,
+) -> ToolCall | None:
+    content = content.strip()
+    if not content:
+        return None
+
+    tool_parser: Any = getattr(tokenizer, "tool_parser", None)
+    if tool_parser is None:
+        logger.warning("No tool_parser available for tokenizer")
+        return None
+
+    try:
+        parsed: dict[str, Any] = tool_parser(content, tools)  # pyright: ignore[reportAny]
+        if parsed and "name" in parsed:
+            arguments: Any = parsed.get("arguments", {})  # pyright: ignore[reportAny]
+            arguments_str: str = (
+                json.dumps(arguments)
+                if not isinstance(arguments, str)
+                else arguments
+            )
+            return ToolCall(
+                id=_generate_tool_call_id(),
+                type="function",
+                function=ToolCallFunction(
+                    name=str(parsed["name"]),  # pyright: ignore[reportAny]
+                    arguments=arguments_str,
+                ),
+            )
+    except Exception as e:
+        logger.warning(f"tool_parser failed: {e}")
+
+    return None
+
+
+def parse_tool_calls(
+    responses: Generator[GenerationResponse],
+    tokenizer: TokenizerWrapper,
+    tools: list[dict[str, Any]] | None,
+) -> Generator[GenerationResponse]:
+    has_tool_calling = getattr(tokenizer, "has_tool_calling", False)
+    if not has_tool_calling or tools is None:
+        yield from responses
+        return
+
+    tool_call_start: str | None = getattr(tokenizer, "tool_call_start", None)
+    tool_call_end: str | None = getattr(tokenizer, "tool_call_end", None)
+
+    if tool_call_start is None or tool_call_end is None:
+        yield from responses
+        return
+
+    in_tool_call = False
+    tool_call_buffer: list[str] = []
+    pending_tool_calls: list[ToolCall] = []
+
+    for response in responses:
+        if response.text == tool_call_start:
+            in_tool_call = True
+            tool_call_buffer = []
+            continue
+
+        if response.text == tool_call_end:
+            in_tool_call = False
+            parsed = _parse_tool_call_content(
+                "".join(tool_call_buffer), tokenizer, tools
+            )
+            if parsed is not None:
+                pending_tool_calls.append(parsed)
+            continue
+
+        if in_tool_call:
+            tool_call_buffer.append(response.text)
+            continue
+
+        if response.finish_reason is None or not pending_tool_calls:
+            yield response
+        else:
+            yield response.model_copy(
+                update={
+                    "finish_reason": "tool_calls",
+                    "tool_calls": pending_tool_calls if pending_tool_calls else None,
+                }
+            )
+
+
 EXO_RUNNER_MUST_FAIL = "EXO RUNNER MUST FAIL"
 EXO_RUNNER_MUST_OOM = "EXO RUNNER MUST OOM"
 EXO_RUNNER_MUST_TIMEOUT = "EXO RUNNER MUST TIMEOUT"