litellm/tests/integration/providers/test_databricks_chat_wire.py
zoveki 508a98586e
fix(databricks): join plain text blocks for non-Claude json_object requests (#49385)
* fix(databricks): join plain text blocks for non-Claude json_object requests

* fix(databricks): join only the last message for json_object and drop cache_control under drop_params

Databricks checks for "json" only in the last message, so earlier turns now go out as sent and only the
last message, plus any system messages merged into it, is joined into a string. Under drop_params a
text block's cache_control is dropped so that message can be joined too, and without it the request
still goes out as a list.

* fix(databricks): skip dropped assistant turns and blank parts when joining for json_object

The json_object join picked the last message before the request transform drops bare assistant turns,
so a trailing thinking-only or reasoning-only turn (a Responses input ending in a reasoning item included)
left the real last user message as a list and Databricks still returned its 400. The pick now skips the
turns that transform drops.

The join also ran when only one part had text, which sent whitespace-only parts the existing empty block
filter used to drop on requests that already worked. It now joins only two or more non-blank parts, so a
request with one non-blank part goes out exactly as before. Without drop_params, a message with a
message-level cache_control now goes out as sent instead of being rewritten into one cached block.

* fix(databricks): join json_object text parts only on models Databricks hosts

Databricks checks for the word "json" only on the models it hosts
(databricks-* pay per token names and system.ai.* AI Gateway names). An
external model endpoint skips that check and takes a list of text parts
today, so its request now goes out as sent instead of joined.

The drop_params read now goes through drops_unsupported_params, and a
test pins that a text block with a truthy non-string text is kept.

* fix(databricks): reject a text part holding a non-string locally with a clear 400

* refactor(databricks): reject a non-string text part at the transform_request boundary

* fix(databricks): read pydantic message objects in the non-string text check

---------

Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
2026-11-02 11:17:40 -08:00

2194 lines
90 KiB
Python

import itertools
import json
import uuid
from collections.abc import Mapping
from concurrent.futures import ThreadPoolExecutor
from dataclasses import dataclass
from pathlib import Path
from typing import Final, Literal, TypeAlias
import anthropic
import openai
import pytest
from integration._support.client import Gateway, eventually
from integration._support.database import read_rows
from integration._support.process import owned_proxy_process
from integration._support.wire import Reply, Request, wire_server
from integration.translation.chat_completions.cross_model.contracts import assert_completion
from integration.translation.response_contracts import responses_structure
from pydantic import BaseModel, ConfigDict, JsonValue, TypeAdapter
_BACKEND: Final = "databricks-glm-5-2"
_API_KEY: Final = "synthetic-databricks-key"
_PROMPT: Final = "Summarise the cached briefing in one sentence."
_JSON_SCHEMA_BACKEND: Final = "databricks-qwen35-122b-a10b"
_CLAUDE_BACKEND: Final = "databricks-claude-haiku-4-5"
_JSON_SCHEMA_PROMPT: Final = "Return the requested JSON."
_JSON_CONTENT: Final = '{"p":{"name":"Ada"}}'
_PROVIDER_USAGE: Final[Mapping[str, JsonValue]] = {
"prompt_tokens": 12011,
"completion_tokens": 8,
"total_tokens": 12019,
"cache_read_input_tokens": 12002,
"cache_creation_input_tokens": 0,
}
_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue])
_PERSON_SCHEMA: Final[Mapping[str, JsonValue]] = {
"$defs": {
"Person": {
"type": "object",
"properties": {"name": {"type": "string"}},
"required": ["name"],
}
},
"type": "object",
"properties": {"p": {"$ref": "#/$defs/Person"}},
"required": ["p"],
}
_JSON_SCHEMA_RESPONSE_FORMAT: Final[Mapping[str, JsonValue]] = {
"type": "json_schema",
"json_schema": {"name": "P", "strict": True, "schema": _PERSON_SCHEMA},
}
_MESSAGES_PERSON_SCHEMA: Final[Mapping[str, JsonValue]] = {
"$defs": {
"Person": {
"type": "object",
"properties": {"name": {"type": "string"}},
"required": ["name"],
"additionalProperties": False,
}
},
"type": "object",
"properties": {"p": {"$ref": "#/$defs/Person"}},
"required": ["p"],
"additionalProperties": False,
}
_MESSAGES_RESPONSE_FORMAT: Final[Mapping[str, JsonValue]] = {
"type": "json_schema",
"json_schema": {
"name": "structured_output",
"schema": _MESSAGES_PERSON_SCHEMA,
"strict": True,
},
}
_JSON_TOOL_CALL_MESSAGE: Final[dict[str, JsonValue]] = {
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": "json-tool-call",
"type": "function",
"function": {"name": "json_tool_call", "arguments": _JSON_CONTENT},
}
],
}
def test_databricks_responses_reasoning_summary_keeps_reasoning_effort_a_string(gateway: Gateway) -> None:
def respond(request: Request) -> Reply:
assert request.method == "POST" and request.target == "/chat/completions"
assert _JSON_OBJECT.validate_json(request.body) == {
"model": _BACKEND,
"messages": [{"role": "user", "content": "Say hello."}],
"max_tokens": 64,
"reasoning_effort": "low",
}
return Reply(body=_chat_completion_response(_BACKEND, {"role": "assistant", "content": "Hello."}, "stop"))
with wire_server(respond) as wire, gateway.scenario() as scenario:
alias: Final = scenario.model(model=f"databricks/{_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/responses",
{
"model": alias,
"input": "Say hello.",
"max_output_tokens": 64,
"reasoning": {"effort": "low", "summary": "auto"},
},
)
assert response.status_code == 200, response.text
body: Final = _JSON_OBJECT.validate_json(response.content)
responses_structure(body)
assert body["usage"] == {
"input_tokens": 1,
"output_tokens": 1,
"total_tokens": 2,
"input_tokens_details": None,
"output_tokens_details": None,
"cost": None,
}
assert len(wire.drain()) == 1
def _chat_completion_response(model: str, message: dict[str, JsonValue], finish_reason: str) -> bytes:
response: Final = {
"id": "databricks-json-schema-response",
"object": "chat.completion",
"created": 1,
"model": model,
"choices": [{"index": 0, "message": message, "finish_reason": finish_reason}],
"usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
}
return json.dumps(response).encode()
class _PromptTokensDetails(BaseModel):
model_config = ConfigDict(extra="ignore")
cached_tokens: int | None = None
class _Usage(BaseModel):
model_config = ConfigDict(extra="ignore")
prompt_tokens: int
completion_tokens: int
total_tokens: int
prompt_tokens_details: _PromptTokensDetails | None = None
class _Delta(BaseModel):
model_config = ConfigDict(extra="ignore")
content: str | None = None
class _Choice(BaseModel):
model_config = ConfigDict(extra="ignore")
delta: _Delta
class _Chunk(BaseModel):
model_config = ConfigDict(extra="ignore")
id: str
choices: tuple[_Choice, ...]
usage: _Usage | None = None
def _frame(
identity: str,
choices: list[Mapping[str, object]],
usage: Mapping[str, JsonValue] | None = None,
model: str = _BACKEND,
) -> bytes:
value: Final = {
"id": identity,
"object": "chat.completion.chunk",
"created": 1,
"model": model,
"choices": choices,
**({} if usage is None else {"usage": usage}),
}
return b"data: " + json.dumps(value).encode() + b"\n\n"
@pytest.mark.covers("other.provider_wire.databricks.stream_usage_and_cache_reads_reach_client_and_spend_log")
def test_databricks_stream_final_usage_chunk_reaches_client_and_spend_log(gateway: Gateway) -> None:
identity: Final = f"databricks-stream-{uuid.uuid4().hex}"
frames: Final = (
_frame(
identity, [{"index": 0, "delta": {"role": "assistant", "content": "The briefing "}, "finish_reason": None}]
),
_frame(identity, [{"index": 0, "delta": {"content": "is short."}, "finish_reason": None}]),
_frame(identity, [{"index": 0, "delta": {}, "finish_reason": "stop"}]),
_frame(identity, [], usage=_PROVIDER_USAGE),
b"data: [DONE]\n\n",
)
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/chat/completions"
assert request.headers["authorization"] == f"Bearer {_API_KEY}"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["model"] == _BACKEND
assert body["messages"] == [{"role": "user", "content": _PROMPT}]
assert body["stream"] is True
return Reply(content_type="text/event-stream", chunks=frames)
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_BACKEND}", api_base=wire.url, api_key=_API_KEY)
with gateway.client.stream(
"POST",
"/v1/chat/completions",
json={
"model": model,
"messages": [{"role": "user", "content": _PROMPT}],
"stream": True,
"stream_options": {"include_usage": True},
},
headers={"Authorization": f"Bearer {gateway.key}"},
) as response:
assert response.status_code == 200, response.read()
lines: Final = tuple(line for line in response.iter_lines() if line.startswith("data: "))
assert lines[-1] == "data: [DONE]", lines
chunks: Final = tuple(_Chunk.model_validate_json(line.removeprefix("data: ")) for line in lines[:-1])
assert {chunk.id for chunk in chunks} == {identity}
assert (
"".join(choice.delta.content or "" for chunk in chunks for choice in chunk.choices)
== "The briefing is short."
)
usages: Final = tuple(chunk.usage for chunk in chunks if chunk.usage is not None)
assert len(usages) == 1, lines
assert (
usages[0].prompt_tokens,
usages[0].completion_tokens,
usages[0].total_tokens,
usages[0].prompt_tokens_details.cached_tokens if usages[0].prompt_tokens_details is not None else None,
) == (12011, 8, 12019, 12002), lines
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/chat/completions")]
rows: Final = eventually(
lambda: read_rows(
'SELECT prompt_tokens, completion_tokens, total_tokens FROM "LiteLLM_SpendLogs" WHERE request_id=%s',
(identity,),
),
lambda values: len(values) == 1,
seconds=70,
)
assert (rows[0]["prompt_tokens"], rows[0]["completion_tokens"], rows[0]["total_tokens"]) == (12011, 8, 12019)
def _shape_reply(identity: str, stream: bool) -> Reply:
if stream:
chunks: Final = (
_frame(
identity,
[{"index": 0, "delta": {"role": "assistant", "content": "ok"}, "finish_reason": None}],
),
_frame(identity, [{"index": 0, "delta": {}, "finish_reason": "stop"}]),
b"data: [DONE]\n\n",
)
return Reply(content_type="text/event-stream", chunks=chunks)
body: Final = {
"id": identity,
"object": "chat.completion",
"created": 1,
"model": _BACKEND,
"choices": [
{
"index": 0,
"message": {"role": "assistant", "content": "ok"},
"finish_reason": "stop",
}
],
"usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
}
return Reply(body=json.dumps(body).encode())
@pytest.mark.parametrize(
"case,endpoint,provider_model,request_body,expected_messages,responses_mode,upstream_path",
[
pytest.param(
"chat_nonstream",
"/v1/chat/completions",
"databricks-gemma-3-12b",
{
"messages": [{"role": "user", "content": [{"type": "text", "text": "Reply in JSON"}]}],
"response_format": {"type": "json_object"},
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A1-chat-nonstream",
),
pytest.param(
"chat_stream",
"/v1/chat/completions",
"databricks-gemma-3-12b",
{
"messages": [{"role": "user", "content": [{"type": "text", "text": "Reply in JSON"}]}],
"response_format": {"type": "json_object"},
"stream": True,
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A2-chat-stream",
),
pytest.param(
"responses-mode-bridge",
"/v1/chat/completions",
"databricks-qwen3-next-80b-a3b-instruct",
{
"messages": [{"role": "user", "content": "Reply in JSON"}],
"response_format": {"type": "json_object"},
},
[{"role": "user", "content": "Reply in JSON"}],
True,
"/chat/completions",
id="A3-responses-mode",
),
pytest.param(
"responses-mode-bridge-unity-catalog",
"/v1/chat/completions",
"system.ai.deepseek-v4-1-flash",
{
"messages": [{"role": "user", "content": "Reply in JSON with key a. hi"}],
"response_format": {"type": "json_object"},
},
[{"role": "user", "content": "Reply in JSON with key a. hi"}],
True,
"/ai-gateway/mlflow/v1/chat/completions",
id="A3b-responses-mode-unity-catalog-model",
),
pytest.param(
"messages-endpoint",
"/v1/messages",
"databricks-gemma-3-12b",
{
"max_tokens": 32,
"messages": [{"role": "user", "content": [{"type": "text", "text": "Reply in JSON"}]}],
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A4-messages",
),
pytest.param(
"responses-endpoint",
"/v1/responses",
"databricks-gemma-3-12b",
{"input": [{"role": "user", "content": [{"type": "input_text", "text": "Reply in JSON"}]}]},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A5-responses-list-input",
),
pytest.param(
"json-object-two-blocks",
"/v1/chat/completions",
"databricks-meta-llama-3-3-70b-instruct",
{
"messages": [
{"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]}
],
"response_format": {"type": "json_object"},
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A6-chat-json-object-two-blocks-joined",
),
pytest.param(
"json-object-two-blocks-stream",
"/v1/chat/completions",
"databricks-qwen35-122b-a10b",
{
"messages": [
{"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]}
],
"response_format": {"type": "json_object"},
"stream": True,
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A7-chat-stream-json-object-two-blocks-joined",
),
pytest.param(
"json-object-history",
"/v1/chat/completions",
"databricks-meta-llama-3-3-70b-instruct",
{
"messages": [
{"role": "user", "content": [{"type": "text", "text": "Code: A"}, {"type": "text", "text": "BC"}]},
{"role": "assistant", "content": "Got it."},
{"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]},
],
"response_format": {"type": "json_object"},
},
[
{"role": "user", "content": [{"type": "text", "text": "Code: A"}, {"type": "text", "text": "BC"}]},
{"role": "assistant", "content": "Got it."},
{"role": "user", "content": "Reply in JSON"},
],
False,
"/chat/completions",
id="A8-chat-json-object-earlier-turns-kept",
),
pytest.param(
"json-object-trailing-system",
"/v1/chat/completions",
"databricks-meta-llama-3-3-70b-instruct",
{
"messages": [
{"role": "user", "content": "Say hi"},
{"role": "system", "content": [{"type": "text", "text": "Alpha"}, {"type": "text", "text": " rule."}]},
{"role": "system", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]},
],
"response_format": {"type": "json_object"},
},
[{"role": "user", "content": "Say hi"}, {"role": "system", "content": "Alpha rule.\n\nReply in JSON"}],
False,
"/chat/completions",
id="A8b-chat-json-object-trailing-system-keeps-break",
),
pytest.param(
"json-object-drop-params-cache-control",
"/v1/chat/completions",
"databricks-meta-llama-3-3-70b-instruct",
{
"messages": [
{
"role": "user",
"content": [
{"type": "text", "text": "Reply"},
{"type": "text", "text": " in JSON", "cache_control": {"type": "ephemeral"}},
],
}
],
"response_format": {"type": "json_object"},
"drop_params": True,
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A8c-chat-json-object-drop-params-drops-cache-control",
),
pytest.param(
"json-object-trailing-thinking-turn",
"/v1/chat/completions",
"databricks-meta-llama-3-3-70b-instruct",
{
"messages": [
{"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]},
{
"role": "assistant",
"content": "",
"thinking_blocks": [{"type": "thinking", "thinking": "Plan.", "signature": "sig"}],
},
],
"response_format": {"type": "json_object"},
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A8d-chat-json-object-trailing-thinking-turn-dropped",
),
pytest.param(
"json-object-external-endpoint",
"/v1/chat/completions",
"openai-gpt-external",
{
"messages": [
{"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]}
],
"response_format": {"type": "json_object"},
},
[{"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]}],
False,
"/chat/completions",
id="A8e-chat-json-object-external-endpoint-kept-as-sent",
),
pytest.param(
"json-object-responses-two-parts",
"/v1/responses",
"databricks-qwen35-122b-a10b",
{
"input": [
{
"role": "user",
"content": [{"type": "input_text", "text": "Reply"}, {"type": "input_text", "text": " in JSON"}],
}
],
"text": {"format": {"type": "json_object"}},
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A9-responses-json-object-two-parts-joined",
),
pytest.param(
"json-object-responses-trailing-reasoning",
"/v1/responses",
"databricks-qwen35-122b-a10b",
{
"input": [
{
"role": "user",
"content": [{"type": "input_text", "text": "Reply"}, {"type": "input_text", "text": " in JSON"}],
},
{"type": "reasoning", "id": "rs_1", "summary": [{"type": "summary_text", "text": "Plan."}]},
],
"text": {"format": {"type": "json_object"}},
},
[{"role": "user", "content": "Reply in JSON"}],
False,
"/chat/completions",
id="A9b-responses-json-object-trailing-reasoning-dropped",
),
],
)
def test_databricks_non_claude_plain_text_content_reaches_upstream_as_string(
gateway: Gateway,
case: str,
endpoint: str,
provider_model: str,
request_body: dict[str, JsonValue],
expected_messages: list[JsonValue],
responses_mode: bool,
upstream_path: str,
) -> None:
identity: Final = f"databricks-plain-text-{case}-{uuid.uuid4().hex}"
streaming: Final = request_body.get("stream") is True
def respond(request: Request) -> Reply:
assert request.method == "POST"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["messages"] == expected_messages, body["messages"]
return _shape_reply(identity, streaming)
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(
model=f"databricks/{provider_model}",
api_base=wire.url,
api_key=_API_KEY,
model_info={"mode": "responses"} if responses_mode else None,
)
headers: Final = {"anthropic-version": "2023-06-01"} if endpoint == "/v1/messages" else {}
body: Final = {"model": model, **request_body}
if streaming:
with gateway.client.stream(
"POST", endpoint, json=body, headers={"Authorization": f"Bearer {gateway.key}", **headers}
) as response:
assert response.status_code == 200, response.read()
lines: Final = tuple(line for line in response.iter_lines() if line.startswith("data: "))
assert lines[-1] == "data: [DONE]", lines
assert any('"content":"ok"' in line for line in lines), lines
else:
response: Final = gateway.request("POST", endpoint, body, headers=headers)
assert response.status_code == 200, response.text
assert _JSON_OBJECT.validate_json(response.content)["id"]
assert [(request.method, request.target) for request in wire.drain()] == [("POST", upstream_path)]
@pytest.mark.parametrize(
"case,provider_model,content,expected_content",
[
pytest.param(
"cache-control",
"databricks-gemma-3-12b",
[{"type": "text", "text": "Reply in JSON", "cache_control": {"type": "ephemeral"}}],
[{"type": "text", "text": "Reply in JSON", "cache_control": {"type": "ephemeral"}}],
id="B1-cache-control-stays-list",
),
pytest.param(
"two-text-blocks",
"databricks-gemma-3-12b",
[{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}],
[{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}],
id="B2-two-text-blocks-stays-list",
),
pytest.param(
"text-and-image",
"databricks-gemma-3-12b",
[
{"type": "text", "text": "Reply in JSON"},
{"type": "image_url", "image_url": {"url": "https://example.com/image.png"}},
],
[
{"type": "text", "text": "Reply in JSON"},
{"type": "image_url", "image_url": {"url": "https://example.com/image.png"}},
],
id="B3-text-and-image-stays-list",
),
pytest.param(
"claude",
"databricks-claude-opus-5-5",
[{"type": "text", "text": "Reply in JSON"}],
[{"type": "text", "text": "Reply in JSON"}],
id="B4-claude-stays-list",
),
],
)
def test_databricks_list_content_stays_list(
gateway: Gateway,
case: str,
provider_model: str,
content: list[JsonValue],
expected_content: list[JsonValue],
) -> None:
identity: Final = f"databricks-list-content-{case}-{uuid.uuid4().hex}"
expected_messages: Final = [{"role": "user", "content": expected_content}]
def respond(request: Request) -> Reply:
assert request.method == "POST"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["messages"] == expected_messages, body["messages"]
return _shape_reply(identity, False)
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{provider_model}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/chat/completions",
{"model": model, "messages": [{"role": "user", "content": content}]},
)
assert response.status_code == 200, response.text
assert _JSON_OBJECT.validate_json(response.content)["id"]
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/chat/completions")]
def test_databricks_json_schema_refs_are_preserved_in_chat_completions(gateway: Gateway) -> None:
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/chat/completions"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["model"] == _JSON_SCHEMA_BACKEND
assert body["messages"] == [{"role": "user", "content": _JSON_SCHEMA_PROMPT}]
assert body["stream"] is False
assert body["response_format"] == _JSON_SCHEMA_RESPONSE_FORMAT
return Reply(
body=_chat_completion_response(
_JSON_SCHEMA_BACKEND,
{"role": "assistant", "content": _JSON_CONTENT},
"stop",
)
)
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_JSON_SCHEMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/chat/completions",
{
"model": model,
"messages": [{"role": "user", "content": _JSON_SCHEMA_PROMPT}],
"response_format": _JSON_SCHEMA_RESPONSE_FORMAT,
},
)
assert response.status_code == 200, response.text
body: Final = _JSON_OBJECT.validate_json(response.content)
assert_completion(body)
assert body["choices"] == [
{
"index": 0,
"message": {"role": "assistant", "content": _JSON_CONTENT},
"finish_reason": "stop",
}
]
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/chat/completions")]
def test_databricks_streaming_json_schema_refs_are_preserved(gateway: Gateway) -> None:
identity: Final = f"databricks-json-schema-stream-{uuid.uuid4().hex}"
frames: Final = (
_frame(
identity,
[{"index": 0, "delta": {"role": "assistant", "content": '{"p":'}, "finish_reason": None}],
model=_JSON_SCHEMA_BACKEND,
),
_frame(
identity,
[{"index": 0, "delta": {"content": '{"name":"Ada"}}'}, "finish_reason": None}],
model=_JSON_SCHEMA_BACKEND,
),
_frame(identity, [{"index": 0, "delta": {}, "finish_reason": "stop"}], model=_JSON_SCHEMA_BACKEND),
b"data: [DONE]\n\n",
)
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/chat/completions"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["model"] == _JSON_SCHEMA_BACKEND
assert body["messages"] == [{"role": "user", "content": _JSON_SCHEMA_PROMPT}]
assert body["stream"] is True
assert body["response_format"] == _JSON_SCHEMA_RESPONSE_FORMAT
return Reply(content_type="text/event-stream", chunks=frames)
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_JSON_SCHEMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
with gateway.client.stream(
"POST",
"/v1/chat/completions",
json={
"model": model,
"messages": [{"role": "user", "content": _JSON_SCHEMA_PROMPT}],
"response_format": _JSON_SCHEMA_RESPONSE_FORMAT,
"stream": True,
},
headers={"Authorization": f"Bearer {gateway.key}"},
) as response:
assert response.status_code == 200, response.read()
lines: Final = tuple(line for line in response.iter_lines() if line.startswith("data: "))
assert lines[-1] == "data: [DONE]", lines
chunks: Final = tuple(_Chunk.model_validate_json(line.removeprefix("data: ")) for line in lines[:-1])
choices: Final = tuple(itertools.chain.from_iterable(chunk.choices for chunk in chunks))
assert "".join(choice.delta.content or "" for choice in choices) == _JSON_CONTENT
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/chat/completions")]
def test_databricks_claude_json_schema_refs_are_preserved_in_tool_parameters(gateway: Gateway) -> None:
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/chat/completions"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["model"] == _CLAUDE_BACKEND
assert body["messages"] == [{"role": "user", "content": _JSON_SCHEMA_PROMPT}]
assert "response_format" not in body
assert body["tools"] == [
{
"type": "function",
"function": {"name": "json_tool_call", "parameters": _PERSON_SCHEMA},
}
]
assert body["tool_choice"] == {"type": "function", "function": {"name": "json_tool_call"}}
return Reply(body=_chat_completion_response(_CLAUDE_BACKEND, _JSON_TOOL_CALL_MESSAGE, "tool_calls"))
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_CLAUDE_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/chat/completions",
{
"model": model,
"messages": [{"role": "user", "content": _JSON_SCHEMA_PROMPT}],
"response_format": _JSON_SCHEMA_RESPONSE_FORMAT,
},
)
assert response.status_code == 200, response.text
body: Final = _JSON_OBJECT.validate_json(response.content)
assert body["choices"] == [
{
"index": 0,
"message": {"role": "assistant", "content": _JSON_CONTENT},
"finish_reason": "stop",
}
]
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/chat/completions")]
def test_databricks_responses_json_schema_refs_are_preserved_in_chat_bridge(gateway: Gateway) -> None:
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/chat/completions"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["model"] == _JSON_SCHEMA_BACKEND
assert body["messages"] == [{"role": "user", "content": _JSON_SCHEMA_PROMPT}]
assert body["response_format"] == {
"type": "json_schema",
"json_schema": {"name": "P", "schema": _PERSON_SCHEMA, "strict": True},
}
return Reply(
body=_chat_completion_response(
_JSON_SCHEMA_BACKEND,
{"role": "assistant", "content": _JSON_CONTENT},
"stop",
)
)
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_JSON_SCHEMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/responses",
{
"model": model,
"input": _JSON_SCHEMA_PROMPT,
"text": {
"format": {
"type": "json_schema",
"name": "P",
"strict": True,
"schema": _PERSON_SCHEMA,
}
},
},
)
assert response.status_code == 200, response.text
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/chat/completions")]
def test_databricks_messages_json_schema_refs_are_preserved_for_qwen(gateway: Gateway) -> None:
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/chat/completions"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["model"] == _JSON_SCHEMA_BACKEND
assert body["response_format"] == _MESSAGES_RESPONSE_FORMAT
return Reply(
body=_chat_completion_response(
_JSON_SCHEMA_BACKEND,
{"role": "assistant", "content": _JSON_CONTENT},
"stop",
)
)
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_JSON_SCHEMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/messages",
{
"model": model,
"max_tokens": 64,
"messages": [{"role": "user", "content": _JSON_SCHEMA_PROMPT}],
"output_format": {"type": "json_schema", "schema": _PERSON_SCHEMA},
},
)
assert response.status_code == 200, response.text
body: Final = _JSON_OBJECT.validate_json(response.content)
assert body["content"] == [{"type": "text", "text": _JSON_CONTENT}]
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/chat/completions")]
def test_databricks_messages_claude_json_schema_refs_are_preserved_in_tool_parameters(gateway: Gateway) -> None:
def respond(request: Request) -> Reply:
assert request.method == "POST"
assert request.target == "/chat/completions"
body: Final = _JSON_OBJECT.validate_json(request.body)
assert body["model"] == _CLAUDE_BACKEND
assert "response_format" not in body
assert body["tools"] == [
{
"type": "function",
"function": {"name": "json_tool_call", "parameters": _MESSAGES_PERSON_SCHEMA},
}
]
assert body["tool_choice"] == {"type": "function", "function": {"name": "json_tool_call"}}
return Reply(body=_chat_completion_response(_CLAUDE_BACKEND, _JSON_TOOL_CALL_MESSAGE, "tool_calls"))
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_CLAUDE_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/messages",
{
"model": model,
"max_tokens": 64,
"messages": [{"role": "user", "content": _JSON_SCHEMA_PROMPT}],
"output_format": {"type": "json_schema", "schema": _PERSON_SCHEMA},
},
)
assert response.status_code == 200, response.text
body: Final = _JSON_OBJECT.validate_json(response.content)
assert body["content"] == [{"type": "text", "text": _JSON_CONTENT}]
assert [(request.method, request.target) for request in wire.drain()] == [("POST", "/chat/completions")]
_Endpoint: TypeAlias = Literal["chat", "responses", "messages"]
_PATHS: Final[Mapping[_Endpoint, str]] = {
"chat": "/v1/chat/completions",
"responses": "/v1/responses",
"messages": "/v1/messages",
}
_OUTAGE: Final = "upstream-outage"
_OUTAGE_MESSAGE: Final = "The service is temporarily unavailable"
_EXPECTED_JSON: Final[JsonValue] = _JSON_OBJECT.validate_json(_JSON_CONTENT)
_CONTENT_DELTAS: Final[tuple[Mapping[str, JsonValue], ...]] = (
{"role": "assistant", "content": '{"p":'},
{"content": '{"name":"Ada"}}'},
)
_TOOL_CALL_DELTAS: Final[tuple[Mapping[str, JsonValue], ...]] = (
{
"role": "assistant",
"content": None,
"tool_calls": [
{
"index": 0,
"id": "json-tool-call",
"type": "function",
"function": {"name": "json_tool_call", "arguments": ""},
}
],
},
{"tool_calls": [{"index": 0, "function": {"arguments": _JSON_CONTENT}}]},
)
class _ChatMessage(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
content: str | None = None
class _ChatChoice(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
message: _ChatMessage
class _ChatCompletion(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
choices: tuple[_ChatChoice, ...]
class _OutputPart(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
text: str | None = None
class _OutputItem(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
content: tuple[_OutputPart, ...] = ()
class _ResponsesBody(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
output: tuple[_OutputItem, ...]
class _ResponsesEvent(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
response: _ResponsesBody | None = None
class _MessagesBlock(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
text: str | None = None
class _MessagesBody(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
content: tuple[_MessagesBlock, ...]
class _MessagesDelta(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str | None = None
text: str | None = None
class _MessagesEvent(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
delta: _MessagesDelta | None = None
class _StreamDelta(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
content: str | None = None
class _StreamChoice(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
delta: _StreamDelta
class _StreamChunk(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
choices: tuple[_StreamChoice, ...]
def _json_schema_format(schema: Mapping[str, JsonValue]) -> dict[str, JsonValue]:
return {"type": "json_schema", "json_schema": {"name": "P", "strict": True, "schema": dict(schema)}}
def _client_body(
endpoint: _Endpoint,
model: str,
stream: bool,
prompt: str = _JSON_SCHEMA_PROMPT,
) -> dict[str, JsonValue]:
match endpoint:
case "chat":
return {
"model": model,
"messages": [{"role": "user", "content": prompt}],
"response_format": _json_schema_format(_PERSON_SCHEMA),
"stream": stream,
}
case "responses":
return {
"model": model,
"input": prompt,
"text": {
"format": {"type": "json_schema", "name": "P", "strict": True, "schema": dict(_PERSON_SCHEMA)}
},
"stream": stream,
}
case "messages":
return {
"model": model,
"max_tokens": 64,
"messages": [{"role": "user", "content": prompt}],
"output_format": {"type": "json_schema", "schema": dict(_PERSON_SCHEMA)},
"stream": stream,
}
def _expected_outbound(endpoint: _Endpoint, backend: str) -> dict[str, JsonValue]:
schema: Final = dict(_MESSAGES_PERSON_SCHEMA if endpoint == "messages" else _PERSON_SCHEMA)
if "claude" in backend:
return _JSON_OBJECT.validate_python(
{
"tools": [{"type": "function", "function": {"name": "json_tool_call", "parameters": schema}}],
"tool_choice": {"type": "function", "function": {"name": "json_tool_call"}},
}
)
name: Final = "structured_output" if endpoint == "messages" else "P"
return _JSON_OBJECT.validate_python(
{"response_format": {"type": "json_schema", "json_schema": {"name": name, "schema": schema, "strict": True}}}
)
def _assert_outbound(request: Request, endpoint: _Endpoint, backend: str, stream: bool) -> None:
assert (request.method, request.target) == ("POST", "/chat/completions")
body: Final = _JSON_OBJECT.validate_json(request.body)
expected: Final = _expected_outbound(endpoint, backend)
assert {key: body.get(key) for key in expected} == expected
assert (body["model"], body.get("stream") is True) == (backend, stream)
assert "claude" not in backend or "response_format" not in body
def _upstream_reply(backend: str, stream: bool) -> Reply:
claude: Final = "claude" in backend
finish_reason: Final = "tool_calls" if claude else "stop"
if not stream:
message: Final[dict[str, JsonValue]] = (
_JSON_TOOL_CALL_MESSAGE if claude else {"role": "assistant", "content": _JSON_CONTENT}
)
return Reply(body=_chat_completion_response(backend, message, finish_reason))
identity: Final = f"databricks-json-schema-{uuid.uuid4().hex}"
deltas: Final = _TOOL_CALL_DELTAS if claude else _CONTENT_DELTAS
frames: Final = (
*(_frame(identity, [{"index": 0, "delta": delta, "finish_reason": None}], model=backend) for delta in deltas),
_frame(identity, [{"index": 0, "delta": {}, "finish_reason": finish_reason}], model=backend),
b"data: [DONE]\n\n",
)
return Reply(content_type="text/event-stream", chunks=frames)
def _outage_or_reply(request: Request) -> Reply:
if _OUTAGE.encode() in request.body:
error: Final = {"error_code": "TEMPORARILY_UNAVAILABLE", "message": _OUTAGE_MESSAGE}
return Reply(status=503, body=json.dumps(error).encode())
body: Final = _JSON_OBJECT.validate_json(request.body)
return _upstream_reply(str(body["model"]), body.get("stream") is True)
def _item_text(item: _OutputItem) -> str:
return "".join(part.text or "" for part in item.content) if item.type == "message" else ""
def _responses_text(body: _ResponsesBody) -> str:
return "".join(_item_text(item) for item in body.output)
def _messages_delta_text(delta: _MessagesDelta) -> str:
return delta.text or "" if delta.type == "text_delta" else ""
def _final_text(endpoint: _Endpoint, content: bytes) -> str:
match endpoint:
case "chat":
return _ChatCompletion.model_validate_json(content).choices[0].message.content or ""
case "responses":
return _responses_text(_ResponsesBody.model_validate_json(content))
case "messages":
return "".join(block.text or "" for block in _MessagesBody.model_validate_json(content).content)
def _streamed_text(endpoint: _Endpoint, data: tuple[str, ...]) -> str:
match endpoint:
case "chat":
assert data[-1] == "[DONE]", data
chunks: Final = tuple(_StreamChunk.model_validate_json(line) for line in data[:-1])
choices: Final = tuple(itertools.chain.from_iterable(chunk.choices for chunk in chunks))
return "".join(choice.delta.content or "" for choice in choices)
case "responses":
events: Final = tuple(_ResponsesEvent.model_validate_json(line) for line in data if line != "[DONE]")
completed: Final = tuple(event.response for event in events if event.type == "response.completed")
assert len(completed) == 1 and completed[0] is not None, data
return _responses_text(completed[0])
case "messages":
message_events: Final = tuple(_MessagesEvent.model_validate_json(line) for line in data)
assert message_events[-1].type == "message_stop", data
deltas: Final = tuple(event.delta for event in message_events if event.delta is not None)
return "".join(_messages_delta_text(delta) for delta in deltas)
def _outcome(status: int, text: str) -> tuple[int, JsonValue]:
if status == 200:
return status, _JSON_OBJECT.validate_json(text)
return status, _OUTAGE_MESSAGE if _OUTAGE_MESSAGE in text else text
def _call(gateway: Gateway, endpoint: _Endpoint, body: Mapping[str, JsonValue]) -> tuple[int, str]:
if body["stream"] is not True:
response: Final = gateway.request("POST", _PATHS[endpoint], body)
return response.status_code, _final_text(endpoint, response.content) if response.is_success else response.text
with gateway.client.stream(
"POST", _PATHS[endpoint], json=dict(body), headers={"Authorization": f"Bearer {gateway.key}"}
) as streamed:
if not streamed.is_success:
return streamed.status_code, streamed.read().decode()
data: Final = tuple(line.removeprefix("data: ") for line in streamed.iter_lines() if line.startswith("data: "))
return 200, _streamed_text(endpoint, data)
@pytest.mark.parametrize(
("endpoint", "backend", "stream"),
[
pytest.param("chat", _CLAUDE_BACKEND, True, id="chat-stream-claude"),
pytest.param("responses", _CLAUDE_BACKEND, False, id="responses-claude"),
pytest.param("responses", _JSON_SCHEMA_BACKEND, True, id="responses-stream-qwen"),
pytest.param("responses", _CLAUDE_BACKEND, True, id="responses-stream-claude"),
pytest.param("messages", _JSON_SCHEMA_BACKEND, True, id="messages-stream-qwen"),
pytest.param("messages", _CLAUDE_BACKEND, True, id="messages-stream-claude"),
],
)
def test_databricks_json_schema_refs_are_preserved_on_every_endpoint(
gateway: Gateway, endpoint: _Endpoint, backend: str, stream: bool
) -> None:
with wire_server(lambda _request: _upstream_reply(backend, stream)) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{backend}", api_base=wire.url, api_key=_API_KEY)
status, text = _call(gateway, endpoint, _client_body(endpoint, model, stream))
received: Final = wire.drain()
assert len(received) == 1, received
_assert_outbound(received[0], endpoint, backend, stream)
assert _outcome(status, text) == (200, _EXPECTED_JSON), text
@pytest.mark.parametrize(
"response_format",
[
pytest.param(
_json_schema_format(
{
"definitions": {
"Person": {"type": "object", "properties": {"name": {"type": "string"}}, "required": ["name"]}
},
"type": "object",
"properties": {"p": {"$ref": "#/definitions/Person"}},
"required": ["p"],
}
),
id="definitions-ref",
),
pytest.param(
_json_schema_format(
{
"type": "object",
"properties": {
"name": {"type": "string"},
"children": {"type": "array", "items": {"$ref": "#"}},
},
"required": ["name", "children"],
}
),
id="recursive-root-ref",
),
pytest.param(
_json_schema_format({"type": "object", "properties": {"$ref": {"type": "string"}}, "required": ["$ref"]}),
id="property-named-ref",
),
pytest.param(
_json_schema_format({"type": "object", "properties": {"name": {"type": "string"}}, "required": ["name"]}),
id="flat-schema",
),
pytest.param({"type": "json_object"}, id="json-object"),
],
)
def test_databricks_response_format_reaches_upstream_as_sent(
gateway: Gateway, response_format: dict[str, JsonValue]
) -> None:
with (
wire_server(lambda _request: _upstream_reply(_JSON_SCHEMA_BACKEND, False)) as wire,
gateway.scenario() as scenario,
):
model: Final = scenario.model(model=f"databricks/{_JSON_SCHEMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/chat/completions",
{
"model": model,
"messages": [{"role": "user", "content": _JSON_SCHEMA_PROMPT}],
"response_format": response_format,
},
)
received: Final = wire.drain()
assert response.status_code == 200, response.text
assert _final_text("chat", response.content) == _JSON_CONTENT
assert [(request.method, request.target) for request in received] == [("POST", "/chat/completions")]
assert _JSON_OBJECT.validate_json(received[0].body)["response_format"] == response_format
def test_databricks_json_schema_without_schema_returns_the_upstream_error(gateway: Gateway) -> None:
response_format: Final[dict[str, JsonValue]] = {"type": "json_schema", "json_schema": {"name": "P", "strict": True}}
upstream_error: Final = {"error_code": "INVALID_PARAMETER_VALUE", "message": "json_schema.schema is required"}
def respond(_request: Request) -> Reply:
return Reply(status=400, body=json.dumps(upstream_error).encode())
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_JSON_SCHEMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/chat/completions",
{
"model": model,
"messages": [{"role": "user", "content": _JSON_SCHEMA_PROMPT}],
"response_format": response_format,
},
)
received: Final = wire.drain()
assert (response.status_code, "json_schema.schema is required" in response.text) == (400, True), response.text
assert [(request.method, request.target) for request in received] == [("POST", "/chat/completions")]
assert _JSON_OBJECT.validate_json(received[0].body)["response_format"] == response_format
def _assert_burst_outbound(request: Request) -> None:
body: Final = _JSON_OBJECT.validate_json(request.body)
endpoint: Final[_Endpoint] = "messages" if body["response_format"] == _MESSAGES_RESPONSE_FORMAT else "chat"
_assert_outbound(request, endpoint, _JSON_SCHEMA_BACKEND, body.get("stream") is True)
def _burst_request(index: int) -> tuple[_Endpoint, bool, bool]:
endpoints: Final[tuple[_Endpoint, ...]] = ("chat", "responses", "messages")
return endpoints[index % 3], index % 2 == 1, index % 5 == 2
def test_databricks_json_schema_burst_through_an_upstream_outage_keeps_every_ref(gateway: Gateway) -> None:
plan: Final = tuple(_burst_request(index) for index in range(24))
recovery: Final[tuple[_Endpoint, ...]] = ("chat", "responses", "messages")
with wire_server(_outage_or_reply) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_JSON_SCHEMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
endpoints: Final = tuple(endpoint for endpoint, _stream, _down in plan)
bodies: Final = tuple(
_client_body(endpoint, model, stream, f"{_JSON_SCHEMA_PROMPT} {index} {_OUTAGE if down else ''}")
for index, (endpoint, stream, down) in enumerate(plan)
)
with ThreadPoolExecutor(max_workers=12) as pool:
results: Final = tuple(pool.map(_call, itertools.repeat(gateway), endpoints, bodies))
recovered: Final = tuple(
_call(gateway, endpoint, _client_body(endpoint, model, False)) for endpoint in recovery
)
received: Final = wire.drain()
assert len(received) == len(plan) + len(recovery), received
for request in received:
_assert_burst_outbound(request)
expected: Final = tuple(
(503, _OUTAGE_MESSAGE) if down else (200, _EXPECTED_JSON) for _endpoint, _stream, down in plan
)
assert tuple(_outcome(*result) for result in results) == expected
assert tuple(_outcome(*result) for result in recovered) == ((200, _EXPECTED_JSON),) * len(recovery)
_GEMMA_BACKEND: Final = "databricks-gemma-3-12b"
_NO_CACHE: Final[dict[str, JsonValue]] = {"no-cache": True}
def _one_block(text: str) -> list[JsonValue]:
return [{"type": "text", "text": text}]
def _plain_reply(_request: Request) -> Reply:
return _shape_reply(f"databricks-plain-{uuid.uuid4().hex}", False)
def _sent_messages(request: Request) -> JsonValue:
return _JSON_OBJECT.validate_json(request.body)["messages"]
def _tool_call(identity: str, city: str) -> dict[str, JsonValue]:
return {
"id": identity,
"type": "function",
"function": {"name": "get_weather", "arguments": json.dumps({"city": city})},
}
@pytest.mark.parametrize(
"messages,expected_messages",
[
pytest.param(
[
{"role": "system", "content": _one_block("Alpha rule.")},
{"role": "system", "content": _one_block("Bravo rule.")},
{"role": "user", "content": _one_block("Reply in JSON")},
],
[
{"role": "system", "content": "Alpha rule.\n\nBravo rule."},
{"role": "user", "content": "Reply in JSON"},
],
id="C1-two-one-block-system-messages",
),
pytest.param(
[
{"role": "system", "content": _one_block("Alpha rule.")},
{"role": "developer", "content": _one_block("Bravo rule.")},
{"role": "user", "content": "Reply in JSON"},
],
[
{"role": "system", "content": "Alpha rule.\n\nBravo rule."},
{"role": "user", "content": "Reply in JSON"},
],
id="C2-system-then-developer-one-block",
),
pytest.param(
[
{"role": "system", "content": _one_block("Alpha rule.")},
{"role": "system", "content": "Bravo rule."},
{"role": "user", "content": "Reply in JSON"},
],
[
{"role": "system", "content": "Alpha rule.\n\nBravo rule."},
{"role": "user", "content": "Reply in JSON"},
],
id="C3-one-block-then-string-system",
),
pytest.param(
[
{"role": "system", "content": _one_block("Alpha rule.")},
{
"role": "system",
"content": [{"type": "text", "text": "Bravo", "cache_control": {"type": "ephemeral"}}],
},
{"role": "user", "content": "Reply in JSON"},
],
[
{
"role": "system",
"content": [
{"type": "text", "text": "Alpha rule."},
{"type": "text", "text": "Bravo", "cache_control": {"type": "ephemeral"}},
],
},
{"role": "user", "content": "Reply in JSON"},
],
id="C4-one-block-then-cache-marked-system-stays-parts",
),
pytest.param(
[
{"role": "user", "content": _one_block("Weather in Paris and Rome?")},
{
"role": "assistant",
"content": _one_block("Checking both."),
"tool_calls": [_tool_call("call-paris", "Paris"), _tool_call("call-rome", "Rome")],
},
{"role": "tool", "tool_call_id": "call-paris", "content": _one_block("18C")},
{"role": "tool", "tool_call_id": "call-rome", "content": _one_block("22C")},
],
[
{"role": "user", "content": "Weather in Paris and Rome?"},
{"role": "assistant", "content": "Checking both.", "tool_calls": [_tool_call("call-paris", "Paris")]},
{"role": "tool", "tool_call_id": "call-paris", "content": "18C"},
{"role": "assistant", "tool_calls": [_tool_call("call-rome", "Rome")]},
{"role": "tool", "tool_call_id": "call-rome", "content": "22C"},
],
id="C5-parallel-tool-results-split-and-collapsed",
),
pytest.param(
[
{"role": "user", "content": [{"type": "text", "text": "Reply in JSON", "cache_control": None}]},
{"role": "assistant", "content": [{"type": "text", "text": "ok", "annotations": []}]},
{"role": "user", "content": _one_block(" ")},
{"role": "user", "content": _one_block("x" * 5120)},
],
[
{"role": "user", "content": [{"type": "text", "text": "Reply in JSON", "cache_control": None}]},
{"role": "assistant", "content": [{"type": "text", "text": "ok", "annotations": []}]},
{"role": "user"},
{"role": "user", "content": "x" * 5120},
],
id="F1-extra-keys-stay-list-blank-dropped-5kb-collapsed",
),
],
)
def test_databricks_non_claude_message_shapes_reach_upstream(
gateway: Gateway, messages: list[JsonValue], expected_messages: list[JsonValue]
) -> None:
with wire_server(_plain_reply) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_GEMMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/chat/completions",
{"model": model, "messages": messages, "cache": _NO_CACHE},
)
received: Final = wire.drain()
assert response.status_code == 200, response.text
assert [(request.method, request.target) for request in received] == [("POST", "/chat/completions")]
assert _sent_messages(received[0]) == expected_messages
def test_databricks_responses_instructions_and_one_block_developer_reach_upstream_joined(gateway: Gateway) -> None:
with wire_server(_plain_reply) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_GEMMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/responses",
{
"model": model,
"instructions": "Alpha rule.",
"input": [
{"role": "developer", "content": [{"type": "input_text", "text": "Bravo rule."}]},
{"role": "user", "content": [{"type": "input_text", "text": "Reply in JSON"}]},
],
},
)
received: Final = wire.drain()
assert response.status_code == 200, response.text
assert [(request.method, request.target) for request in received] == [("POST", "/chat/completions")]
assert _sent_messages(received[0]) == [
{"role": "system", "content": "Alpha rule.\n\nBravo rule."},
{"role": "user", "content": "Reply in JSON"},
]
def test_databricks_fallback_sends_the_collapsed_string_to_both_deployments(gateway: Gateway) -> None:
marker: Final = uuid.uuid4().hex
fallback_backend: Final = "databricks-qwen3-next-80b-a3b-instruct"
def respond(request: Request) -> Reply:
if _JSON_OBJECT.validate_json(request.body)["model"] == _GEMMA_BACKEND:
return Reply(status=500, body=b'{"error_code": "INTERNAL_ERROR", "message": "primary deployment is down"}')
return _shape_reply(f"databricks-fallback-{marker}", False)
with wire_server(respond) as wire, gateway.scenario() as scenario:
primary: Final = scenario.model(model=f"databricks/{_GEMMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
fallback: Final = scenario.model(model=f"databricks/{fallback_backend}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/chat/completions",
{
"model": primary,
"messages": [{"role": "user", "content": _one_block(f"Reply in JSON {marker}")}],
"response_format": {"type": "json_object"},
"fallbacks": [fallback],
"num_retries": 0,
"cache": _NO_CACHE,
},
)
received: Final = wire.drain()
assert response.status_code == 200, response.text
assert _JSON_OBJECT.validate_json(response.content)["id"] == f"databricks-fallback-{marker}"
assert [_JSON_OBJECT.validate_json(request.body)["model"] for request in received] == [
_GEMMA_BACKEND,
fallback_backend,
]
assert [_sent_messages(request) for request in received] == [
[{"role": "user", "content": f"Reply in JSON {marker}"}],
] * 2
def _proxy_root(gateway: Gateway) -> str:
return str(gateway.client.base_url).rstrip("/")
def test_databricks_openai_sdk_sync_one_block_reaches_upstream_as_string_and_logs_spend(gateway: Gateway) -> None:
identity: Final = f"databricks-openai-sdk-{uuid.uuid4().hex}"
with (
wire_server(lambda _request: _shape_reply(identity, False)) as wire,
gateway.scenario() as scenario,
openai.OpenAI(base_url=f"{_proxy_root(gateway)}/v1", api_key=gateway.key, max_retries=0) as client,
):
model: Final = scenario.model(model=f"databricks/{_GEMMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
completion: Final = client.chat.completions.create(
model=model,
messages=[{"role": "user", "content": [{"type": "text", "text": "Reply in JSON"}]}],
response_format={"type": "json_object"},
extra_body={"cache": _NO_CACHE},
)
received: Final = wire.drain()
assert (completion.id, completion.choices[0].message.content) == (identity, "ok")
assert [_sent_messages(request) for request in received] == [[{"role": "user", "content": "Reply in JSON"}]]
rows: Final = eventually(
lambda: read_rows('SELECT status, call_type FROM "LiteLLM_SpendLogs" WHERE request_id=%s', (identity,)),
lambda values: len(values) == 1,
seconds=70,
)
assert (rows[0]["status"], rows[0]["call_type"]) == ("success", "acompletion")
async def test_databricks_openai_sdk_async_stream_one_block_reaches_upstream_as_string(gateway: Gateway) -> None:
identity: Final = f"databricks-openai-async-{uuid.uuid4().hex}"
with wire_server(lambda _request: _shape_reply(identity, True)) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_GEMMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
async with openai.AsyncOpenAI(
base_url=f"{_proxy_root(gateway)}/v1", api_key=gateway.key, max_retries=0
) as client:
stream: Final = await client.chat.completions.create(
model=model,
messages=[{"role": "user", "content": [{"type": "text", "text": "Reply in JSON"}]}],
response_format={"type": "json_object"},
stream=True,
extra_body={"cache": _NO_CACHE},
)
chunks: Final = [chunk async for chunk in stream]
received: Final = wire.drain()
assert {chunk.id for chunk in chunks} == {identity}
assert "".join(chunk.choices[0].delta.content or "" for chunk in chunks if chunk.choices) == "ok"
assert [_sent_messages(request) for request in received] == [[{"role": "user", "content": "Reply in JSON"}]]
async def test_databricks_anthropic_sdk_async_stream_one_block_system_and_user_reach_upstream_as_strings(
gateway: Gateway,
) -> None:
identity: Final = f"databricks-anthropic-async-{uuid.uuid4().hex}"
with wire_server(lambda _request: _shape_reply(identity, True)) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_GEMMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
async with anthropic.AsyncAnthropic(
base_url=_proxy_root(gateway), api_key=gateway.key, max_retries=0
) as client:
async with client.messages.stream(
model=model,
max_tokens=32,
system=[{"type": "text", "text": "Reply in JSON."}],
messages=[{"role": "user", "content": [{"type": "text", "text": "What is 2+2?"}]}],
) as stream:
final: Final = await stream.get_final_message()
received: Final = wire.drain()
assert [block.text for block in final.content if block.type == "text"] == ["ok"]
assert [_sent_messages(request) for request in received] == [
[{"role": "system", "content": "Reply in JSON."}, {"role": "user", "content": "What is 2+2?"}]
]
def test_databricks_one_block_burst_through_an_upstream_outage_reaches_upstream_as_strings(gateway: Gateway) -> None:
plan: Final = tuple(_burst_request(index) for index in range(24))
def respond(request: Request) -> Reply:
if _OUTAGE.encode() in request.body:
error: Final = {"error_code": "TEMPORARILY_UNAVAILABLE", "message": _OUTAGE_MESSAGE}
return Reply(status=503, body=json.dumps(error).encode())
body: Final = _JSON_OBJECT.validate_json(request.body)
return _upstream_reply(_JSON_SCHEMA_BACKEND, body.get("stream") is True)
def one_block_body(endpoint: _Endpoint, model: str, stream: bool, prompt: str) -> dict[str, JsonValue]:
body: Final = _client_body(endpoint, model, stream, prompt)
match endpoint:
case "responses":
return {**body, "input": [{"role": "user", "content": [{"type": "input_text", "text": prompt}]}]}
case "chat" | "messages":
return {**body, "messages": [{"role": "user", "content": _one_block(prompt)}]}
with wire_server(respond) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_JSON_SCHEMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
prompts: Final = tuple(
f"{_JSON_SCHEMA_PROMPT} {index} {_OUTAGE if down else ''}".strip()
for index, (_e, _s, down) in enumerate(plan)
)
bodies: Final = tuple(
one_block_body(endpoint, model, stream, prompt) for (endpoint, stream, _down), prompt in zip(plan, prompts)
)
with ThreadPoolExecutor(max_workers=12) as pool:
results: Final = tuple(pool.map(_call, itertools.repeat(gateway), (e for e, _s, _d in plan), bodies))
received: Final = wire.drain()
assert sorted(json.dumps(_sent_messages(request)) for request in received) == sorted(
json.dumps([{"role": "user", "content": prompt}]) for prompt in prompts
)
expected: Final = tuple(
(503, _OUTAGE_MESSAGE) if down else (200, _EXPECTED_JSON) for _endpoint, _stream, down in plan
)
assert tuple(_outcome(*result) for result in results) == expected
def test_databricks_transform_request_shows_the_collapsed_string(gateway: Gateway, tmp_path: Path) -> None:
environment: Final = {
"DATABRICKS_API_BASE": "https://databricks.invalid/serving-endpoints",
"DATABRICKS_API_KEY": _API_KEY,
}
with owned_proxy_process(gateway, tmp_path, environment) as owned:
response: Final = owned.gateway.request(
"POST",
"/utils/transform_request",
{
"call_type": "completion",
"request_body": {
"model": f"databricks/{_GEMMA_BACKEND}",
"messages": [{"role": "user", "content": _one_block("Reply in JSON")}],
},
},
)
assert response.status_code == 200, response.text
body: Final = _JSON_OBJECT.validate_json(response.content)
assert body["error"] is None, body
assert body["raw_request_api_base"] == "https://databricks.invalid/serving-endpoints/chat/completions"
sent: Final = body["raw_request_body"]
assert isinstance(sent, dict), body
assert sent["messages"] == [{"role": "user", "content": "Reply in JSON"}]
def test_databricks_non_string_text_block_is_rejected_before_reaching_upstream(gateway: Gateway) -> None:
with wire_server(_plain_reply) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_GEMMA_BACKEND}", api_base=wire.url, api_key=_API_KEY)
response: Final = gateway.request(
"POST",
"/v1/chat/completions",
{
"model": model,
"messages": [{"role": "user", "content": [{"type": "text", "text": 42}]}],
"cache": _NO_CACHE,
},
)
received: Final = wire.drain()
assert response.status_code == 400, response.text
assert "A text content block needs a string 'text', got int" in response.text
assert received == ()
_JSON_ANSWER_FRAGMENTS: Final = ('{"p":', '{"name":"Ada"}', "}")
_PROSE_FRAGMENTS: Final = ("I will check ", "the weather first.")
_WEATHER_FRAGMENTS: Final = ('{"city": ', '"Paris"}')
_WEATHER_PARAMETERS: Final[Mapping[str, JsonValue]] = {
"type": "object",
"properties": {"city": {"type": "string"}},
"required": ["city"],
}
_FORCED_JSON_TOOL_CHOICE: Final[Mapping[str, JsonValue]] = {"type": "function", "function": {"name": "json_tool_call"}}
_JSON_VALUE: Final[TypeAdapter[JsonValue]] = TypeAdapter(JsonValue)
@dataclass(frozen=True, slots=True)
class _Reasoning:
text: str
@dataclass(frozen=True, slots=True)
class _Text:
fragments: tuple[str, ...]
@dataclass(frozen=True, slots=True)
class _ToolUse:
index: int
name: str
fragments: tuple[str, ...]
_Part: TypeAlias = _Reasoning | _Text | _ToolUse
@dataclass(frozen=True, slots=True)
class _Answer:
text: str
tools: tuple[tuple[str, JsonValue], ...]
finish: str
thought: bool
@dataclass(frozen=True, slots=True)
class _Shape:
parts: tuple[_Part, ...]
upstream_finish: str
thinking: bool
user_tools: bool
json_schema: bool
expected: _Answer
_THINKING: Final = _Reasoning("The caller wants Ada.")
_PROSE: Final = _Text(_PROSE_FRAGMENTS)
_WEATHER: Final = ("get_weather", _JSON_VALUE.validate_json("".join(_WEATHER_FRAGMENTS)))
_JSON_ONLY: Final = _Answer(_JSON_CONTENT, (), "stop", True)
_JSON_AND_WEATHER: Final = _Answer(_JSON_CONTENT, (_WEATHER,), "tool_calls", True)
_PROSE_AND_WEATHER: Final = _Answer("".join(_PROSE_FRAGMENTS), (_WEATHER,), "tool_calls", True)
def _json_tool(index: int) -> _ToolUse:
return _ToolUse(index, "json_tool_call", _JSON_ANSWER_FRAGMENTS)
def _weather_tool(index: int) -> _ToolUse:
return _ToolUse(index, "get_weather", _WEATHER_FRAGMENTS)
_SHAPES: Final[Mapping[str, _Shape]] = {
"json-only": _Shape((_json_tool(0),), "tool_calls", False, False, True, _Answer(_JSON_CONTENT, (), "stop", False)),
"prose-then-json": _Shape((_THINKING, _PROSE, _json_tool(0)), "tool_calls", True, False, True, _JSON_ONLY),
"json-then-user-tool": _Shape(
(_THINKING, _json_tool(0), _weather_tool(1)), "tool_calls", True, True, True, _JSON_AND_WEATHER
),
"user-tool-then-json": _Shape(
(_THINKING, _weather_tool(0), _json_tool(1)), "tool_calls", True, True, True, _JSON_AND_WEATHER
),
"prose-user-tool-json": _Shape(
(_THINKING, _PROSE, _weather_tool(0), _json_tool(1)), "tool_calls", True, True, True, _JSON_AND_WEATHER
),
"text-answer": _Shape((_THINKING, _Text(_JSON_ANSWER_FRAGMENTS)), "stop", True, False, True, _JSON_ONLY),
"prose-then-user-tool": _Shape(
(_THINKING, _PROSE, _weather_tool(0)), "tool_calls", True, True, True, _PROSE_AND_WEATHER
),
"no-json-schema-prose-then-user-tool": _Shape(
(_THINKING, _PROSE, _weather_tool(0)), "tool_calls", True, True, False, _PROSE_AND_WEATHER
),
}
def _reasoning_block(text: str) -> JsonValue:
return {"type": "reasoning", "summary": [{"type": "summary_text", "text": text, "signature": "signature"}]}
def _text_delta(fragment: str) -> Mapping[str, JsonValue]:
return {"content": fragment}
def _part_deltas(part: _Part) -> tuple[Mapping[str, JsonValue], ...]:
match part:
case _Reasoning(text=text):
return ({"content": [_reasoning_block(text)]},)
case _Text(fragments=fragments):
return tuple(_text_delta(fragment) for fragment in fragments)
case _ToolUse(index=index, name=name, fragments=fragments):
opening: Final[Mapping[str, JsonValue]] = {
"tool_calls": [
{
"index": index,
"id": f"toolu_{name}",
"type": "function",
"function": {"name": name, "arguments": ""},
}
]
}
arguments: Final[tuple[Mapping[str, JsonValue], ...]] = tuple(
{"tool_calls": [{"index": index, "function": {"arguments": fragment}}]} for fragment in fragments
)
return (opening, *arguments)
def _answer_message(parts: tuple[_Part, ...]) -> JsonValue:
reasoning: Final = tuple(_reasoning_block(part.text) for part in parts if isinstance(part, _Reasoning))
texts: Final[tuple[JsonValue, ...]] = tuple(
{"type": "text", "text": "".join(part.fragments)} for part in parts if isinstance(part, _Text)
)
tool_calls: Final[tuple[JsonValue, ...]] = tuple(
{
"id": f"toolu_{part.name}",
"type": "function",
"function": {"name": part.name, "arguments": "".join(part.fragments)},
}
for part in parts
if isinstance(part, _ToolUse)
)
return {"role": "assistant", "content": [*reasoning, *texts], "tool_calls": list(tool_calls)}
def _answer_reply(shape: _Shape, stream: bool) -> Reply:
identity: Final = f"databricks-json-answer-{uuid.uuid4().hex}"
if not stream:
completion: Final = {
"id": identity,
"object": "chat.completion",
"created": 1,
"model": _CLAUDE_BACKEND,
"choices": [{"index": 0, "message": _answer_message(shape.parts), "finish_reason": shape.upstream_finish}],
"usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
}
return Reply(body=json.dumps(completion).encode())
deltas: Final = ({"role": "assistant"}, *itertools.chain.from_iterable(_part_deltas(part) for part in shape.parts))
frames: Final = (
*(
_frame(identity, [{"index": 0, "delta": delta, "finish_reason": None}], model=_CLAUDE_BACKEND)
for delta in deltas
),
_frame(identity, [{"index": 0, "delta": {}, "finish_reason": shape.upstream_finish}], model=_CLAUDE_BACKEND),
b"data: [DONE]\n\n",
)
return Reply(content_type="text/event-stream", chunks=frames)
def _answer_request(
endpoint: _Endpoint, model: str, stream: bool, shape: _Shape, marker: str
) -> Mapping[str, JsonValue]:
prompt: Final = f"{_JSON_SCHEMA_PROMPT} {marker}"
match endpoint:
case "chat":
return {
"model": model,
"messages": [{"role": "user", "content": prompt}],
"max_tokens": 2048,
"stream": stream,
**({"response_format": _json_schema_format(_PERSON_SCHEMA)} if shape.json_schema else {}),
**(
{
"tools": [
{
"type": "function",
"function": {"name": "get_weather", "parameters": dict(_WEATHER_PARAMETERS)},
}
]
}
if shape.user_tools
else {}
),
**({"reasoning_effort": "low"} if shape.thinking else {}),
}
case "responses":
return {
"model": model,
"input": prompt,
"max_output_tokens": 2048,
"stream": stream,
**(
{
"text": {
"format": {
"type": "json_schema",
"name": "P",
"strict": True,
"schema": dict(_PERSON_SCHEMA),
}
}
}
if shape.json_schema
else {}
),
**(
{"tools": [{"type": "function", "name": "get_weather", "parameters": dict(_WEATHER_PARAMETERS)}]}
if shape.user_tools
else {}
),
**({"reasoning": {"effort": "low"}} if shape.thinking else {}),
}
case "messages":
return {
"model": model,
"max_tokens": 2048,
"messages": [{"role": "user", "content": prompt}],
"stream": stream,
**(
{"output_format": {"type": "json_schema", "schema": dict(_PERSON_SCHEMA)}}
if shape.json_schema
else {}
),
**(
{"tools": [{"name": "get_weather", "input_schema": dict(_WEATHER_PARAMETERS)}]}
if shape.user_tools
else {}
),
**({"thinking": {"type": "enabled", "budget_tokens": 1024}} if shape.thinking else {}),
}
class _OutboundFunction(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
name: str
class _OutboundTool(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
function: _OutboundFunction
class _OutboundBody(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
model: str
stream: bool | None = None
tools: tuple[_OutboundTool, ...] = ()
tool_choice: JsonValue = None
def _assert_answer_outbound(request: Request, shape: _Shape, stream: bool, marker: str) -> None:
assert (request.method, request.target) == ("POST", "/chat/completions")
assert marker.encode() in request.body
body: Final = _OutboundBody.model_validate_json(request.body)
tool_names: Final = (
*(("get_weather",) if shape.user_tools else ()),
*(("json_tool_call",) if shape.json_schema else ()),
)
assert (body.model, body.stream is True, sorted(tool.function.name for tool in body.tools)) == (
_CLAUDE_BACKEND,
stream,
sorted(tool_names),
)
assert (body.tool_choice == _FORCED_JSON_TOOL_CHOICE) == (shape.json_schema and not shape.thinking), body
class _ChatToolFunction(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
name: str | None = None
arguments: str | None = None
class _ChatToolCallDelta(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
index: int
function: _ChatToolFunction | None = None
class _ChatAnswerDelta(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
content: str | None = None
reasoning_content: str | None = None
tool_calls: tuple[_ChatToolCallDelta, ...] | None = None
class _ChatAnswerStreamChoice(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
delta: _ChatAnswerDelta
finish_reason: str | None = None
class _ChatAnswerChunk(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
choices: tuple[_ChatAnswerStreamChoice, ...]
class _ChatToolCall(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
function: _ChatToolFunction
class _ChatAnswerMessage(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
content: str | None = None
reasoning_content: str | None = None
tool_calls: tuple[_ChatToolCall, ...] | None = None
class _ChatAnswerChoice(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
message: _ChatAnswerMessage
finish_reason: str | None = None
class _ChatAnswer(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
choices: tuple[_ChatAnswerChoice, ...]
class _ResponsesAnswerPart(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str | None = None
text: str | None = None
class _ResponsesAnswerItem(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
name: str | None = None
arguments: str | None = None
content: tuple[_ResponsesAnswerPart, ...] | None = None
class _ResponsesAnswer(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
status: str | None = None
output: tuple[_ResponsesAnswerItem, ...]
class _ResponsesAnswerEvent(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
response: _ResponsesAnswer | None = None
class _MessagesAnswerBlock(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
text: str | None = None
name: str | None = None
input: JsonValue = None
class _MessagesAnswer(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
content: tuple[_MessagesAnswerBlock, ...]
stop_reason: str | None = None
class _MessagesAnswerDelta(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str | None = None
text: str | None = None
partial_json: str | None = None
stop_reason: str | None = None
class _MessagesAnswerEvent(BaseModel):
model_config = ConfigDict(extra="ignore", frozen=True)
type: str
index: int | None = None
content_block: _MessagesAnswerBlock | None = None
delta: _MessagesAnswerDelta | None = None
def _only(values: tuple[str, ...]) -> str:
assert len(values) == 1, values
return values[0]
def _arguments(arguments: str | None) -> JsonValue:
return _JSON_VALUE.validate_json(arguments or "{}")
def _chat_answer(body: _ChatAnswer) -> _Answer:
assert len(body.choices) == 1, body
message: Final = body.choices[0].message
return _Answer(
text=message.content or "",
tools=tuple(
(call.function.name or "", _arguments(call.function.arguments)) for call in message.tool_calls or ()
),
finish=body.choices[0].finish_reason or "",
thought=bool(message.reasoning_content),
)
def _chat_stream_tool(fragments: tuple[_ChatToolCallDelta, ...]) -> tuple[str, JsonValue]:
functions: Final = tuple(fragment.function for fragment in fragments if fragment.function is not None)
names: Final = tuple(function.name for function in functions if function.name)
return _only(names), _arguments("".join(function.arguments or "" for function in functions))
def _chat_stream_answer(data: tuple[str, ...]) -> _Answer:
assert data[-1] == "[DONE]", data
choices: Final = tuple(
itertools.chain.from_iterable(_ChatAnswerChunk.model_validate_json(line).choices for line in data[:-1])
)
deltas: Final = tuple(choice.delta for choice in choices)
tool_deltas: Final = tuple(itertools.chain.from_iterable(delta.tool_calls or () for delta in deltas))
indexes: Final = tuple(dict.fromkeys(tool_delta.index for tool_delta in tool_deltas))
assert indexes == tuple(range(len(indexes))), indexes
return _Answer(
text="".join(delta.content or "" for delta in deltas),
tools=tuple(
_chat_stream_tool(tuple(tool_delta for tool_delta in tool_deltas if tool_delta.index == index))
for index in indexes
),
finish=_only(tuple(choice.finish_reason for choice in choices if choice.finish_reason)),
thought=any(delta.reasoning_content for delta in deltas),
)
def _responses_item_text(item: _ResponsesAnswerItem) -> str:
return "".join(part.text or "" for part in item.content or ()) if item.type == "message" else ""
def _responses_answer(body: _ResponsesAnswer) -> _Answer:
return _Answer(
text="".join(_responses_item_text(item) for item in body.output),
tools=tuple(
(item.name or "", _arguments(item.arguments)) for item in body.output if item.type == "function_call"
),
finish=body.status or "",
thought=any(item.type == "reasoning" for item in body.output),
)
def _responses_stream_answer(data: tuple[str, ...]) -> _Answer:
events: Final = tuple(_ResponsesAnswerEvent.model_validate_json(line) for line in data if line != "[DONE]")
completed: Final = tuple(event.response for event in events if event.type == "response.completed")
assert len(completed) == 1 and completed[0] is not None, data
return _responses_answer(completed[0])
def _messages_answer(body: _MessagesAnswer) -> _Answer:
return _Answer(
text="".join(block.text or "" for block in body.content if block.type == "text"),
tools=tuple((block.name or "", block.input) for block in body.content if block.type == "tool_use"),
finish=body.stop_reason or "",
thought=any(block.type == "thinking" for block in body.content),
)
def _messages_streamed_block(
start: _MessagesAnswerEvent, events: tuple[_MessagesAnswerEvent, ...]
) -> _MessagesAnswerBlock:
assert start.content_block is not None, start
block_events: Final = tuple(
event for event in events if event.type == "content_block_delta" and event.index == start.index
)
deltas: Final = tuple(event.delta for event in block_events if event.delta is not None)
partial_json: Final = "".join(delta.partial_json or "" for delta in deltas)
return start.content_block.model_copy(
update={
"text": "".join(delta.text or "" for delta in deltas),
"input": _JSON_VALUE.validate_json(partial_json) if partial_json else start.content_block.input,
}
)
def _messages_stream_answer(data: tuple[str, ...]) -> _Answer:
events: Final = tuple(_MessagesAnswerEvent.model_validate_json(line) for line in data)
assert events[-1].type == "message_stop", data
starts: Final = tuple(event for event in events if event.type == "content_block_start")
stop_reasons: Final = tuple(
event.delta.stop_reason for event in events if event.type == "message_delta" and event.delta is not None
)
return _messages_answer(
_MessagesAnswer(
content=tuple(_messages_streamed_block(start, events) for start in starts),
stop_reason=_only(tuple(reason for reason in stop_reasons if reason)),
)
)
def _final_answer(endpoint: _Endpoint, payload: bytes) -> _Answer:
match endpoint:
case "chat":
return _chat_answer(_ChatAnswer.model_validate_json(payload))
case "responses":
return _responses_answer(_ResponsesAnswer.model_validate_json(payload))
case "messages":
return _messages_answer(_MessagesAnswer.model_validate_json(payload))
def _streamed_answer(endpoint: _Endpoint, data: tuple[str, ...]) -> _Answer:
match endpoint:
case "chat":
return _chat_stream_answer(data)
case "responses":
return _responses_stream_answer(data)
case "messages":
return _messages_stream_answer(data)
def _call_for_answer(gateway: Gateway, endpoint: _Endpoint, body: Mapping[str, JsonValue]) -> _Answer:
stream: Final = body["stream"] is True
if not stream:
response: Final = gateway.request("POST", _PATHS[endpoint], body)
assert response.status_code == 200, response.text
return _final_answer(endpoint, response.content)
with gateway.client.stream(
"POST", _PATHS[endpoint], json=dict(body), headers={"Authorization": f"Bearer {gateway.key}"}
) as streamed:
assert streamed.status_code == 200, streamed.read()
data: Final = tuple(line.removeprefix("data: ") for line in streamed.iter_lines() if line.startswith("data: "))
return _streamed_answer(endpoint, data)
_ANTHROPIC_STOP_REASONS: Final[Mapping[str, str]] = {"stop": "end_turn", "tool_calls": "tool_use"}
def _endpoint_answer(endpoint: _Endpoint, answer: _Answer) -> _Answer:
match endpoint:
case "chat":
return answer
case "responses":
return _Answer(answer.text, answer.tools, "completed", answer.thought)
case "messages":
return _Answer(answer.text, answer.tools, _ANTHROPIC_STOP_REASONS[answer.finish], answer.thought)
@pytest.mark.parametrize(
("endpoint", "stream", "shape"),
[
pytest.param("chat", True, "json-only", id="chat-stream-json-only"),
pytest.param("chat", True, "prose-then-json", id="chat-stream-prose-then-json"),
pytest.param("chat", True, "json-then-user-tool", id="chat-stream-json-then-user-tool"),
pytest.param("chat", True, "user-tool-then-json", id="chat-stream-user-tool-then-json"),
pytest.param("chat", True, "prose-user-tool-json", id="chat-stream-prose-user-tool-json"),
pytest.param("chat", True, "text-answer", id="chat-stream-text-answer"),
pytest.param("chat", True, "prose-then-user-tool", id="chat-stream-prose-then-user-tool"),
pytest.param("chat", True, "no-json-schema-prose-then-user-tool", id="chat-stream-no-json-schema"),
pytest.param("responses", True, "prose-then-json", id="responses-stream-prose-then-json"),
pytest.param("responses", True, "json-then-user-tool", id="responses-stream-json-then-user-tool"),
pytest.param("responses", True, "prose-user-tool-json", id="responses-stream-prose-user-tool-json"),
pytest.param("responses", True, "prose-then-user-tool", id="responses-stream-prose-then-user-tool"),
pytest.param("messages", True, "json-only", id="messages-stream-json-only"),
pytest.param("messages", True, "prose-then-json", id="messages-stream-prose-then-json"),
pytest.param("messages", True, "json-then-user-tool", id="messages-stream-json-then-user-tool"),
pytest.param("messages", True, "prose-user-tool-json", id="messages-stream-prose-user-tool-json"),
pytest.param("messages", True, "prose-then-user-tool", id="messages-stream-prose-then-user-tool"),
pytest.param("messages", True, "no-json-schema-prose-then-user-tool", id="messages-stream-no-json-schema"),
pytest.param("chat", False, "prose-user-tool-json", id="chat-prose-user-tool-json"),
pytest.param("responses", False, "prose-user-tool-json", id="responses-prose-user-tool-json"),
pytest.param("messages", False, "prose-user-tool-json", id="messages-prose-user-tool-json"),
],
)
def test_databricks_claude_json_schema_answer_reaches_every_endpoint_as_text(
gateway: Gateway, endpoint: _Endpoint, stream: bool, shape: str
) -> None:
scripted: Final = _SHAPES[shape]
marker: Final = uuid.uuid4().hex
with wire_server(lambda _request: _answer_reply(scripted, stream)) as wire, gateway.scenario() as scenario:
model: Final = scenario.model(model=f"databricks/{_CLAUDE_BACKEND}", api_base=wire.url, api_key=_API_KEY)
answer: Final = _call_for_answer(gateway, endpoint, _answer_request(endpoint, model, stream, scripted, marker))
received: Final = wire.drain()
assert len(received) == 1, received
_assert_answer_outbound(received[0], scripted, stream, marker)
assert answer == _endpoint_answer(endpoint, scripted.expected)