devinx — Claude Code on Cognition SWE-2 via cliproxyapi (setup guide)

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devinx — Claude Code running on SWE-2

Use Anthropic's Claude Code CLI (its UI, agent loop, and native tools) with Cognition's SWE-2 models as the backend, instead of a Claude model.

claude --model swe-2-max                    # Claude Code: harness, tools, UI
  → cliproxyapi  127.0.0.1:8317             # translates Anthropic API → OpenAI
  → devin-shim   127.0.0.1:8321             # translates OpenAI → Cognition Connect-RPC
  → server.codeium.com  GetChatMessage      # the same RPC the Devin CLI itself uses
  → SWE-2

The model streams text, thinking, and native tool calls back; Claude Code executes its own tools (Bash, Read, Edit, ...) and returns the results upstream. The Devin CLI binary is not in the request path — devin -p/devin acp run Devin's own agent loop and can't hand tool calls back to Claude Code. The shim instead speaks the exact protocol the Devin CLI speaks, authenticated with your Devin login.

0. What you need installed

# Claude Code
curl -fsSL https://claude.ai/install.sh | bash        # or: npm i -g @anthropic-ai/claude-code

# Devin CLI (needed for the login/credential only)
curl -fsSL https://cli.devin.ai/install.sh | bash     # macOS: brew install --cask devin-cli

# then log in (browser flow; --force-manual-token-flow for headless)
devin auth login

# Go 1.24+ if building cliproxyapi (macOS: brew install go)

Log in to Devin before continuing — the shim reads the credential it writes (~/.local/share/devin/credentials.toml, key windsurf_api_key).

1. Install cliproxyapi (the local API proxy)

Upstream source: https://github.com/router-for-me/CLIProxyAPI

git clone https://github.com/router-for-me/CLIProxyAPI ~/projects/cliproxyapi
cd ~/projects/cliproxyapi
go build -o cli-proxy-api ./cmd/server

Create config.yaml next to the binary (or wherever you run it from):

port: 8317
host: "127.0.0.1"

# Tokens Claude Code must present. Invent your own.
api-keys:
  - "sk-pick-a-long-random-token"

openai-compatibility:
  - name: "devin"
    base-url: "http://127.0.0.1:8321/v1"
    api-key-entries:
      - api-key: "devin-local-shim"   # identifies this upstream; not a real secret
    models:
      - name: "swe-2-max"
        alias: "swe-2-max"
      - name: "swe-2-high"
        alias: "swe-2-high"
      - name: "swe-2-medium"
        alias: "swe-2-medium"

Run it:

./cli-proxy-api          # serves 127.0.0.1:8317; hot-reloads config.yaml

Keep it running — a background terminal, tmux, or a service manager.

2. Install devin-shim (the protocol translator)

Copy this directory (server.py, all *.fdp, devin-shim.service) to ~/devin-shim. The *.fdp files are the Cognition protobuf descriptors and must stay beside server.py — if you don't have them, generate them with the included extract-fdps.py (pulls them from the jeopi-catalog npm package, stdlib only):

python3 extract-fdps.py
cd ~/devin-shim
python3 -m venv .venv
.venv/bin/pip install requests protobuf
.venv/bin/python server.py        # listens on 127.0.0.1:8321

Credential lookup order: DEVIN_SHIM_API_KEY env → ~/devin-shim/data/devin/credentials.toml → ~/.local/share/devin/credentials.toml. On macOS, if the CLI stores credentials elsewhere, copy its credentials.toml into ~/devin-shim/data/devin/ or set DEVIN_SHIM_API_KEY to the devin-session-token$... value.

Separate login (optional): XDG_DATA_HOME=~/devin-shim/data devin auth login gives the proxy path its own Devin session, independent of the main CLI login. On macOS the CLI may ignore XDG_DATA_HOME — copy the credentials file instead.

Keep it running

Linux/WSL (systemd):

mkdir -p ~/.config/systemd/user
cp devin-shim.service ~/.config/systemd/user/
systemctl --user daemon-reload
systemctl --user enable --now devin-shim

WSL requires [boot] systemd=true in /etc/wsl.conf (then wsl --shutdown and reopen). If you'd rather not touch systemd, nohup .venv/bin/python server.py & works.

macOS (launchd): create ~/Library/LaunchAgents/devin-shim.plist:




  Labeldevin-shim
  ProgramArguments
    $HOME/devin-shim/.venv/bin/python
    $HOME/devin-shim/server.py
  
  RunAtLoad
  KeepAlive

then launchctl load ~/Library/LaunchAgents/devin-shim.plist.

3. The devinx alias

Add to ~/.bashrc (or ~/.zshrc on macOS), using the same sk-... you put in api-keys above:

alias devinx='ANTHROPIC_BASE_URL=http://127.0.0.1:8317 \
ANTHROPIC_AUTH_TOKEN=sk-pick-a-long-random-token \
CLAUDE_CODE_SUBAGENT_MODEL=swe-2-max \
CLAUDE_CODE_ALWAYS_ENABLE_EFFORT=1 \
CLAUDE_CODE_MAX_TOOL_USE_CONCURRENCY=3 \
ENABLE_TOOL_SEARCH=false \
CLAUDE_CODE_MAX_CONTEXT_TOKENS=262000 \
CLAUDE_CODE_AUTO_COMPACT_WINDOW=262000 \
CLAUDE_AUTOCOMPACT_PCT_OVERRIDE=92 \
claude --model swe-2-max'

What the knobs do:

  • SWE-2's real context window is 262k — the two *_CONTEXT/WINDOW vars tell Claude Code (it defaults unknown models to 200k).
  • Claude Code's auto-compact trigger is min(window − window×0.2, window − 13000) → ~209k by default. CLAUDE_AUTOCOMPACT_PCT_OVERRIDE=92 moves it to ~241k; the hard block stays at window−3000. (Verified in claude 2.1.268.)
  • CLAUDE_CODE_SUBAGENT_MODEL routes Agent-tool delegates through SWE-2 too.

4. Verify each layer

# shim
curl http://127.0.0.1:8321/v1/models
curl http://127.0.0.1:8321/v1/chat/completions -H 'content-type: application/json' \
  -d '{"model":"swe-2-max","messages":[{"role":"user","content":"Reply with exactly: PONG"}]}'

# proxy, Anthropic shape (what Claude Code sends)
curl http://127.0.0.1:8317/v1/messages -H "x-api-key: sk-pick-a-long-random-token" \
  -H 'anthropic-version: 2023-06-01' -H 'content-type: application/json' \
  -d '{"model":"swe-2-max","max_tokens":1024,"messages":[{"role":"user","content":"Reply with exactly: PONG"}]}'

# real harness
source ~/.bashrc && devinx
# inside: "Reply with exactly: PONG"
# then a tool call: "Use the Bash tool to run `hostname` and tell me the output"

Troubleshooting

Symptom Meaning Fix
permission_denied: ...content policy Cognition's input classifier rejected the payload — it is nondeterministic on borderline text Shim already scrubs known boilerplate and retries ≤3× before output. If it persists, set DEVIN_SHIM_DUMP=/tmp/dr on the shim, reproduce, and add the new trigger to _SYS_REWRITES/_TOOL_DESC_REWRITES
503 auth_unavailable cliproxyapi circuit-broke the provider after upstream errors restart cliproxyapi (or wait out cooldown); shim retries normally prevent this
update your editor precondition wrong request_type — must be CASCADE (5) already correct in server.py
[unrecognized_model] warning cosmetic; Claude Code doesn't know swe-2-max ignore

How it works (for maintainers)

  • server.py translates chat.completions → GetChatMessageRequest (protobuf + gzip + Connect-RPC framing) and streams delta_text, delta_thinking, delta_tool_calls back as OpenAI SSE, which cliproxyapi renders as Anthropic text/thinking/tool_use blocks.
  • Auth: windsurf_api_key → GetUserJwt → user_jwt in request Metadata (cached, refreshed ~50min). Client identity presents as Windsurf — the same metadata the Devin CLI sends.
  • Cognition runs an input classifier that rejects competitor-harness boilerplate and certain vocabulary. _SYS_REWRITES neutralizes the known Claude Code system-prompt blocks (identity line, security-policy paragraph, product marketing, the emoji line); _TOOL_DESC_REWRITES shortens the TaskOutput description. These are matched against current Claude Code text — a future version adding new boilerplate may need new rewrites.
[Unit]
Description=Devin Connect-RPC to OpenAI shim for CLIProxyAPI
After=network.target
[Service]
Type=simple
WorkingDirectory=%h/devin-shim
ExecStart=%h/devin-shim/.venv/bin/python %h/devin-shim/server.py
Restart=always
RestartSec=5
Environment=HOME=%h
[Install]
WantedBy=default.target
#!/usr/bin/env python3
"""Extract Cognition protobuf descriptors (*.fdp) from the jeopi-catalog npm
package for devin-shim's server.py. stdlib only — no node/npm/protobuf needed.
Usage: python3 extract-fdps.py [outdir] (default: current directory)
"""
import base64
import io
import json
import os
import re
import sys
import tarfile
import urllib.request
PKG_URL = "https://registry.npmjs.org/jeopi-catalog/latest"
def main():
outdir = sys.argv[1] if len(sys.argv) > 1 else "."
meta = json.loads(urllib.request.urlopen(PKG_URL, timeout=30).read())
tarball_url = meta["dist"]["tarball"]
print(f"jeopi-catalog {meta['version']} -> {tarball_url}")
blob = urllib.request.urlopen(tarball_url, timeout=60).read()
n = 0
with tarfile.open(fileobj=io.BytesIO(blob), mode="r:gz") as tf:
for member in tf.getmembers():
if not member.name.endswith(".ts"):
continue
src = tf.extractfile(member).read().decode("utf-8", "replace")
gen = re.search(r"@generated from file (\S+\.proto)", src)
desc = re.search(r'fileDesc\("([A-Za-z0-9+/=]+)"', src)
if not gen or not desc:
continue
proto_path = gen.group(1) # e.g. exa/auth_pb/auth.proto
name = os.path.basename(proto_path)[:-6] # auth.proto -> auth
if not name.endswith("_pb"):
name += "_pb" # keep *_pb.fdp style
name += ".fdp"
payload = desc.group(1)
payload += "=" * (-len(payload) % 4)
with open(os.path.join(outdir, name), "wb") as fh:
fh.write(base64.b64decode(payload))
n += 1
print(f" {proto_path} -> {name}")
print(f"wrote {n} .fdp files to {outdir}")
if n == 0:
sys.exit("no descriptors found — package layout may have changed")
if __name__ == "__main__":
main()
#!/usr/bin/env python3
"""OpenAI-compatible shim in front of Cognition's Connect-RPC GetChatMessage.
Serves POST /v1/chat/completions (stream + non-stream) and GET /v1/models by
translating to exa.api_server_pb.ApiServerService/GetChatMessage against
server.codeium.com, authenticated with the Devin CLI's stored credential.
Runs behind CLIProxyAPI as an openai-compatibility upstream.
"""
import glob
import gzip
import json
import os
import re
import struct
import threading
import time
import uuid
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
import requests
from google.protobuf import descriptor_pb2, descriptor_pool, message_factory
from google.protobuf import timestamp_pb2, duration_pb2, any_pb2, struct_pb2
from google.protobuf import wrappers_pb2, empty_pb2, field_mask_pb2, type_pb2
from google.protobuf import source_context_pb2, api_pb2
HERE = os.path.dirname(os.path.abspath(__file__))
UPSTREAM = "https://server.codeium.com"
AUTH_PATH = "/exa.auth_pb.AuthService/GetUserJwt"
CHAT_PATH = "/exa.api_server_pb.ApiServerService/GetChatMessage"
IDE_NAME = "windsurf"
IDE_VERSION = "3.51.3"
EXT_VERSION = "1.48.2"
SESSION_PREFIX = "devin-session-token$"
STOP_PATTERNS = ["<|user|>", "<|bot|>", "<|context_request|>", "<|endoftext|>", "<|end_of_turn|>"]
MODELS = [
"swe-2-max", "swe-2-high", "swe-2-medium",
"swe-1-7", "swe-1-7-medium", "swe-1-7-lightning", "swe-1-7-lightning-medium",
"swe-1-6", "swe-1-6-fast",
]
SRC_USER, SRC_SYSTEM, SRC_TOOL = 1, 2, 4
REQ_CASCADE, PLANNER_DEFAULT = 5, 1
CACHE_EPHEMERAL = 1
STOP_MAX_TOKENS = 3
pool = descriptor_pool.DescriptorPool()
for _m in (timestamp_pb2, duration_pb2, any_pb2, struct_pb2, descriptor_pb2,
wrappers_pb2, empty_pb2, field_mask_pb2, type_pb2, source_context_pb2, api_pb2):
_fd = descriptor_pb2.FileDescriptorProto()
_fd.ParseFromString(_m.DESCRIPTOR.serialized_pb)
try:
pool.Add(_fd)
except Exception:
pass
_fdps = {}
for _p in glob.glob(os.path.join(HERE, "*.fdp")):
_fd = descriptor_pb2.FileDescriptorProto()
_fd.ParseFromString(open(_p, "rb").read())
_fdps[_fd.name] = _fd
_added = set()
for _ in range(40):
for _name, _fd in _fdps.items():
if _name in _added:
continue
try:
pool.Add(_fd)
_added.add(_name)
except Exception:
pass
def _msg(name):
return message_factory.GetMessageClass(pool.FindMessageTypeByName(name))
GetUserJwtRequest = _msg("exa.auth_pb.GetUserJwtRequest")
GetUserJwtResponse = _msg("exa.auth_pb.GetUserJwtResponse")
GetChatMessageRequest = _msg("exa.api_server_pb.GetChatMessageRequest")
GetChatMessageResponse = _msg("exa.api_server_pb.GetChatMessageResponse")
def _load_key():
if os.environ.get("DEVIN_SHIM_API_KEY"):
return os.environ["DEVIN_SHIM_API_KEY"]
# Prefer the shim's own login (created via `XDG_DATA_HOME=~/devin-shim/data
# devin auth login`); fall back to the Devin CLI's credential.
for cred in (os.path.expanduser("~/devin-shim/data/devin/credentials.toml"),
os.path.expanduser("~/.local/share/devin/credentials.toml")):
if not os.path.exists(cred):
continue
for line in open(cred):
if line.startswith("windsurf_api_key"):
return line.split('"')[1]
raise RuntimeError("no devin credential found")
API_KEY = _load_key()
if not API_KEY.startswith(SESSION_PREFIX):
API_KEY = SESSION_PREFIX + API_KEY
_jwt_lock = threading.Lock()
_jwt = {"token": None, "exp": 0.0, "base": None}
def _metadata(jwt=""):
return {
"api_key": API_KEY,
"user_jwt": jwt,
"ide_name": IDE_NAME,
"ide_version": IDE_VERSION,
"extension_name": "windsurf",
"extension_version": EXT_VERSION,
"locale": "en",
"session_id": str(uuid.uuid4()),
"request_id": uuid.uuid4().int & (2**63 - 1),
}
def _jwt_expiry(token):
try:
import base64
payload = token.split(".")[1]
payload += "=" * (-len(payload) % 4)
return json.loads(base64.urlsafe_b64decode(payload)).get("exp", 0)
except Exception:
return 0.0
def get_jwt(force=False):
with _jwt_lock:
now = time.time()
if not force and _jwt["token"] and _jwt["exp"] - 60 > now:
return _jwt["token"], _jwt["base"]
req = GetUserJwtRequest(metadata=_metadata())
r = requests.post(UPSTREAM + AUTH_PATH, data=req.SerializeToString(),
headers={"content-type": "application/proto",
"connect-protocol-version": "1"}, timeout=30)
r.raise_for_status()
resp = GetUserJwtResponse()
try:
resp.ParseFromString(r.content)
except Exception:
resp.ParseFromString(gzip.decompress(r.content))
if not resp.user_jwt:
raise RuntimeError("GetUserJwt returned empty jwt")
_jwt["token"] = resp.user_jwt
_jwt["exp"] = _jwt_expiry(resp.user_jwt) or now + 3300
_jwt["base"] = resp.custom_api_server_url.strip() or None
return _jwt["token"], _jwt["base"]
def _text_of(content):
if isinstance(content, str):
return content
out = []
for part in content or []:
if part.get("type") == "text":
out.append(part.get("text", ""))
return "".join(out)
# Cognition's input classifier rejects these Claude Code system-prompt blocks
# (competitor identity, security-policy vocabulary, product marketing + URLs).
# Rewrite them to neutral equivalents; behavior instructions are unchanged.
_SYS_REWRITES = [
(re.compile(r"You are (?:a )?Claude[^.]*\."), "You are a coding agent."),
(re.compile(r"IMPORTANT: Assist with authorized security testing.*?(?=\n\s*\n|\Z)", re.S),
"Assist with authorized security testing and defensive security work; refuse harmful or destructive requests."),
(re.compile(r"\n?\s*-?\s*Claude Code is available[^\n]*"), ""),
(re.compile(r"- For clear communication with the user the assistant MUST avoid using emojis\."),
"- For clear communication with the user, avoid emojis."),
]
def _scrub_system(text):
for rx, rep in _SYS_REWRITES:
text = rx.sub(rep, text)
return text
# TaskOutput's shipped description trips the same classifier in combination
# (per-line fragments pass). It is deprecated upstream; send a short equivalent.
_TOOL_DESC_REWRITES = {
"TaskOutput": "Get the output of a running or completed background task (shell, agent, or remote session) by task_id.",
}
def _images_of(content):
if isinstance(content, str) or not content:
return []
out = []
for part in content or []:
if part.get("type") == "image_url":
url = part.get("image_url", {}).get("url", "")
if url.startswith("data:"):
mime, _, b64 = url[5:].partition(";base64,")
out.append({"base64_data": b64, "mime_type": mime or "image/png"})
return out
def build_request(body):
system_parts, prompts = [], []
cascade_id = str(uuid.uuid4())
for i, m in enumerate(body.get("messages", [])):
role = m.get("role")
mid = str(uuid.uuid5(uuid.NAMESPACE_URL, f"{cascade_id}\0{i}\0{role}"))
if role in ("system", "developer"):
system_parts.append(_scrub_system(_text_of(m.get("content"))))
elif role == "user":
prompts.append({"message_id": mid, "source": SRC_USER,
"prompt": _text_of(m.get("content")),
"images": _images_of(m.get("content"))})
elif role == "assistant":
tcs = [{"id": tc.get("id", ""), "name": tc.get("function", {}).get("name", ""),
"arguments_json": tc.get("function", {}).get("arguments", "")}
for tc in m.get("tool_calls") or []]
text = _text_of(m.get("content"))
thinking = m.get("reasoning_content") or ""
prompts.append({"message_id": mid, "source": SRC_SYSTEM, "prompt": text,
"thinking": thinking, "tool_calls": tcs})
elif role == "tool":
prompts.append({"message_id": mid, "source": SRC_TOOL,
"tool_call_id": m.get("tool_call_id", ""),
"prompt": _text_of(m.get("content")),
"images": _images_of(m.get("content"))})
tools = [{"name": t["function"]["name"],
"description": _TOOL_DESC_REWRITES.get(t["function"]["name"],
t["function"].get("description", "")),
"json_schema_string": json.dumps(t["function"].get("parameters") or {}),
"strict": bool(t["function"].get("strict"))}
for t in body.get("tools") or [] if t.get("type") == "function"]
tc = body.get("tool_choice")
tool_choice = {"option_name": "auto"}
if isinstance(tc, str) and tc in ("auto", "required", "none"):
tool_choice = {"option_name": tc}
elif isinstance(tc, dict):
fn = (tc.get("function") or {}).get("name")
if fn:
tool_choice = {"tool_name": fn}
stops = list(STOP_PATTERNS)
stop = body.get("stop")
stops += [stop] if isinstance(stop, str) else list(stop or [])
conf = {"num_completions": 1, "max_newlines": 200, "top_k": 50,
"stop_patterns": stops, "fim_eot_prob_threshold": 1}
conf["max_tokens"] = int(body.get("max_completion_tokens") or body.get("max_tokens") or 64000)
if body.get("temperature") is not None:
conf["temperature"] = conf["first_temperature"] = float(body["temperature"])
else:
conf["temperature"] = conf["first_temperature"] = 0.4
if body.get("top_p") is not None:
conf["top_p"] = float(body["top_p"])
else:
conf["top_p"] = 1
model = body.get("model", "swe-2-max")
if "/" in model:
model = model.rsplit("/", 1)[-1]
return GetChatMessageRequest(
metadata=_metadata(get_jwt()[0]),
prompt="\n\n".join(p for p in system_parts if p),
chat_message_prompts=prompts,
chat_model_uid=model,
request_type=REQ_CASCADE,
planner_mode=PLANNER_DEFAULT,
tool_choice=tool_choice,
system_prompt_cache_options={"type": CACHE_EPHEMERAL},
disable_parallel_tool_calls=False,
cascade_id=cascade_id,
execution_id=str(uuid.uuid4()),
configuration=conf,
tools=tools,
), model
def chat_stream(req):
"""Yield (GetChatMessageResponse, None) per frame or (None, error_str) on trailer error."""
jwt, base = get_jwt()
req.metadata.user_jwt = jwt
body = req.SerializeToString()
for attempt in range(2):
gz = gzip.compress(body)
frame = bytes([1]) + struct.pack(">I", len(gz)) + gz
r = requests.post((base or UPSTREAM) + CHAT_PATH, data=frame,
headers={"content-type": "application/connect+proto",
"connect-protocol-version": "1",
"connect-content-encoding": "gzip",
"connect-accept-encoding": "gzip",
"user-agent": "connect-go/1.18.1 (go1.26.3)"},
timeout=600, stream=True)
if r.status_code == 200:
break
if r.status_code in (401, 403) and attempt == 0:
jwt, base = get_jwt(force=True)
req.metadata.user_jwt = jwt
body = req.SerializeToString()
continue
yield None, f"upstream {r.status_code}: {r.text[:400]}"
return
buf = b""
for chunk in r.iter_content(65536):
buf += chunk
while len(buf) >= 5:
flag = buf[0]
ln = struct.unpack(">I", buf[1:5])[0]
if len(buf) < 5 + ln:
break
payload = buf[5:5 + ln]
buf = buf[5 + ln:]
if flag & 2:
trailer = gzip.decompress(payload) if flag & 1 else payload
try:
err = json.loads(trailer).get("error") or {}
except Exception:
err = {}
if err.get("message"):
yield None, f"{err.get('code', 'error')}: {err['message']}"
continue
raw = gzip.decompress(payload) if flag & 1 else payload
msg = GetChatMessageResponse()
msg.ParseFromString(raw)
yield msg, None
def openai_chunk(model, delta=None, finish=None, usage=None):
ch = {"index": 0}
if delta is not None:
ch["delta"] = delta
if finish:
ch["finish_reason"] = finish
out = {"id": "chatcmpl-devin", "object": "chat.completion.chunk",
"created": int(time.time()), "model": model, "choices": [ch]}
if usage:
out["usage"] = usage
return out
def sse(obj):
return f"data: {json.dumps(obj)}\n\n".encode()
def run_chat(body, wfile):
"""Translate one OpenAI chat.completions call; returns (final_msg_dict, usage, error)."""
try:
req, model = build_request(body)
except Exception as e:
return None, None, f"request build: {e}"
stream = bool(body.get("stream"))
w = wfile if stream else None
headers_sent = False
# Cognition's input classifier denies borderline payloads nondeterministically
# (same body observed pass/fail). Retry while nothing reached the client.
for attempt in range(3):
if attempt:
req, model = build_request(body)
if w and not headers_sent:
w.write(b"HTTP/1.1 200 OK\r\ncontent-type: text/event-stream\r\n"
b"cache-control: no-cache\r\nconnection: close\r\n\r\n")
w.flush()
w.write(sse(openai_chunk(model, delta={"role": "assistant"})))
w.flush()
headers_sent = True
text, thinking = [], []
tool_blocks = {} # id -> {"name":..., "json":...}
tool_order = []
usage = {}
stop = 0
err = None
emitted = False
for msg, e in chat_stream(req):
if e:
err = e
break
if msg.delta_text:
text.append(msg.delta_text)
if w:
emitted = True
w.write(sse(openai_chunk(model, delta={"content": msg.delta_text})))
w.flush()
if msg.delta_thinking:
thinking.append(msg.delta_thinking)
if w:
emitted = True
w.write(sse(openai_chunk(model, delta={"reasoning_content": msg.delta_thinking})))
w.flush()
for tc in msg.delta_tool_calls:
tid = tc.id or (tool_order[-1] if tool_order else "")
if not tid:
continue
if tid not in tool_blocks:
tool_blocks[tid] = {"name": tc.name, "json": ""}
tool_order.append(tid)
if w:
emitted = True
idx = tool_order.index(tid)
w.write(sse(openai_chunk(model, delta={"tool_calls": [
{"index": idx, "id": tid, "type": "function",
"function": {"name": tc.name, "arguments": ""}}]})))
w.flush()
if tc.name:
tool_blocks[tid]["name"] = tc.name
if tc.arguments_json:
prev = tool_blocks[tid]["json"]
acc = tc.arguments_json if tc.arguments_json.startswith(prev) else prev + tc.arguments_json
delta = acc[len(prev):]
tool_blocks[tid]["json"] = acc
if w and delta:
emitted = True
idx = tool_order.index(tid)
w.write(sse(openai_chunk(model, delta={"tool_calls": [
{"index": idx, "function": {"arguments": delta}}]})))
w.flush()
if msg.usage.input_tokens:
usage = {"prompt_tokens": int(msg.usage.input_tokens),
"completion_tokens": int(msg.usage.output_tokens),
"total_tokens": int(msg.usage.input_tokens + msg.usage.output_tokens)}
stop = msg.stop_reason
if err and not emitted and attempt < 2 and "permission_denied" in err:
print(f"upstream permission_denied, retrying (attempt {attempt + 2}/3)", flush=True)
continue
break
if err:
if w:
w.write(sse({"error": {"message": err, "type": "upstream_error"}}))
w.write(b"data: [DONE]\n\n")
w.flush()
return None, None, err
finish = "tool_calls" if tool_blocks else "stop"
if not tool_blocks and stop == STOP_MAX_TOKENS:
finish = "length"
if w:
final = openai_chunk(model, delta={}, finish=finish,
usage=usage if (body.get("stream_options") or {}).get("include_usage") else None)
w.write(sse(final))
w.write(b"data: [DONE]\n\n")
w.flush()
return None, None, None
msg_out = {"role": "assistant", "content": "".join(text)}
if thinking:
msg_out["reasoning_content"] = "".join(thinking)
if tool_blocks:
msg_out["tool_calls"] = [
{"id": tid, "type": "function",
"function": {"name": b["name"], "arguments": b["json"]}}
for tid, b in ((tid, tool_blocks[tid]) for tid in tool_order)]
msg_out["content"] = msg_out["content"] or None
resp = {"id": "chatcmpl-devin", "object": "chat.completion",
"created": int(time.time()), "model": model,
"choices": [{"index": 0, "message": msg_out, "finish_reason": finish}]}
if usage:
resp["usage"] = usage
return resp, usage, None
class Handler(BaseHTTPRequestHandler):
protocol_version = "HTTP/1.1"
def log_message(self, fmt, *args):
print(f"{self.address_string()} {fmt % args}", flush=True)
def _json(self, code, obj):
data = json.dumps(obj).encode()
self.send_response(code)
self.send_header("content-type", "application/json")
self.send_header("content-length", str(len(data)))
self.end_headers()
self.wfile.write(data)
def do_GET(self):
if self.path.split("?")[0] in ("/v1/models", "/models"):
self._json(200, {"object": "list", "data": [
{"id": m, "object": "model", "created": 0, "owned_by": "devin"} for m in MODELS]})
else:
self._json(404, {"error": {"message": "not found", "type": "invalid_request_error"}})
def do_POST(self):
path = self.path.split("?")[0]
if path not in ("/v1/chat/completions", "/chat/completions"):
self._json(404, {"error": {"message": "not found", "type": "invalid_request_error"}})
return
try:
raw = self.rfile.read(int(self.headers.get("content-length", 0)))
if os.environ.get("DEVIN_SHIM_DUMP"):
with open(os.environ["DEVIN_SHIM_DUMP"] + f".{time.time_ns()}.json", "wb") as fh:
fh.write(raw)
body = json.loads(raw)
except Exception as e:
self._json(400, {"error": {"message": f"bad json: {e}", "type": "invalid_request_error"}})
return
if body.get("stream"):
# run_chat owns the raw socket from here
resp, _, err = run_chat(body, self.wfile)
if err:
return
return
resp, _, err = run_chat(body, None)
if err:
self._json(502, {"error": {"message": err, "type": "upstream_error"}})
else:
self._json(200, resp)
if __name__ == "__main__":
port = int(os.environ.get("DEVIN_SHIM_PORT", "8321"))
print(f"devin-shim listening on 127.0.0.1:{port}", flush=True)
ThreadingHTTPServer(("127.0.0.1", port), Handler).serve_forever()
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