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import json
from unittest import mock # python 3.3 and above
import httpx
import pytest
from cohere import ChatMessage, Client
from httpx import Client as HTTPXClient
import sentry_sdk
from sentry_sdk import start_transaction
from sentry_sdk.consts import SPANDATA
from sentry_sdk.integrations.cohere import CohereIntegration
@pytest.mark.parametrize("span_streaming", [True, False])
@pytest.mark.parametrize(
"send_default_pii, include_prompts",
[(True, True), (True, False), (False, True), (False, False)],
)
def test_nonstreaming_chat(
sentry_init,
capture_events,
capture_items,
send_default_pii,
include_prompts,
span_streaming,
):
sentry_init(
integrations=[CohereIntegration(include_prompts=include_prompts)],
traces_sample_rate=1.0,
send_default_pii=send_default_pii,
_experiments={"trace_lifecycle": "stream" if span_streaming else "static"},
)
client = Client(api_key="z")
HTTPXClient.request = mock.Mock(
return_value=httpx.Response(
200,
json={
"text": "the model response",
"meta": {
"billed_units": {
"output_tokens": 10,
"input_tokens": 20,
}
},
},
)
)
if span_streaming:
items = capture_items("span")
with start_transaction(name="cohere tx"):
response = client.chat(
model="some-model",
chat_history=[ChatMessage(role="SYSTEM", message="some context")],
message="hello",
).text
assert response == "the model response"
sentry_sdk.flush()
assert len(items) == 1
span = items[0].payload
assert span["attributes"]["sentry.op"] == "ai.chat_completions.create.cohere"
assert span["attributes"][SPANDATA.AI_MODEL_ID] == "some-model"
if send_default_pii and include_prompts:
assert (
'{"role": "system", "content": "some context"}'
in span["attributes"][SPANDATA.AI_INPUT_MESSAGES]
)
assert (
'{"role": "user", "content": "hello"}'
in span["attributes"][SPANDATA.AI_INPUT_MESSAGES]
)
assert "the model response" in span["attributes"][SPANDATA.AI_RESPONSES]
else:
assert SPANDATA.AI_INPUT_MESSAGES not in span["attributes"]
assert SPANDATA.AI_RESPONSES not in span["attributes"]
assert span["attributes"]["gen_ai.usage.output_tokens"] == 10
assert span["attributes"]["gen_ai.usage.input_tokens"] == 20
assert span["attributes"]["gen_ai.usage.total_tokens"] == 30
else:
events = capture_events()
with start_transaction(name="cohere tx"):
response = client.chat(
model="some-model",
chat_history=[ChatMessage(role="SYSTEM", message="some context")],
message="hello",
).text
assert response == "the model response"
tx = events[0]
assert tx["type"] == "transaction"
assert len(tx["spans"]) == 1
span = tx["spans"][0]
assert span["op"] == "ai.chat_completions.create.cohere"
assert span["data"][SPANDATA.AI_MODEL_ID] == "some-model"
if send_default_pii and include_prompts:
assert (
'{"role": "system", "content": "some context"}'
in span["data"][SPANDATA.AI_INPUT_MESSAGES]
)
assert (
'{"role": "user", "content": "hello"}'
in span["data"][SPANDATA.AI_INPUT_MESSAGES]
)
assert "the model response" in span["data"][SPANDATA.AI_RESPONSES]
else:
assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
assert SPANDATA.AI_RESPONSES not in span["data"]
assert span["data"]["gen_ai.usage.output_tokens"] == 10
assert span["data"]["gen_ai.usage.input_tokens"] == 20
assert span["data"]["gen_ai.usage.total_tokens"] == 30
# noinspection PyTypeChecker
@pytest.mark.parametrize("span_streaming", [True, False])
@pytest.mark.parametrize(
"send_default_pii, include_prompts",
[(True, True), (True, False), (False, True), (False, False)],
)
def test_streaming_chat(
sentry_init,
capture_events,
capture_items,
send_default_pii,
include_prompts,
span_streaming,
):
sentry_init(
integrations=[CohereIntegration(include_prompts=include_prompts)],
traces_sample_rate=1.0,
send_default_pii=send_default_pii,
_experiments={"trace_lifecycle": "stream" if span_streaming else "static"},
)
client = Client(api_key="z")
HTTPXClient.send = mock.Mock(
return_value=httpx.Response(
200,
content="\n".join(
[
json.dumps({"event_type": "text-generation", "text": "the model "}),
json.dumps({"event_type": "text-generation", "text": "response"}),
json.dumps(
{
"event_type": "stream-end",
"finish_reason": "COMPLETE",
"response": {
"text": "the model response",
"meta": {
"billed_units": {
"output_tokens": 10,
"input_tokens": 20,
}
},
},
}
),
]
),
)
)
if span_streaming:
items = capture_items("span")
with start_transaction(name="cohere tx"):
responses = list(
client.chat_stream(
model="some-model",
chat_history=[ChatMessage(role="SYSTEM", message="some context")],
message="hello",
)
)
response_string = responses[-1].response.text
assert response_string == "the model response"
sentry_sdk.flush()
assert len(items) == 1
span = items[0].payload
assert span["attributes"]["sentry.op"] == "ai.chat_completions.create.cohere"
assert span["attributes"][SPANDATA.AI_MODEL_ID] == "some-model"
if send_default_pii and include_prompts:
assert (
'{"role": "system", "content": "some context"}'
in span["attributes"][SPANDATA.AI_INPUT_MESSAGES]
)
assert (
'{"role": "user", "content": "hello"}'
in span["attributes"][SPANDATA.AI_INPUT_MESSAGES]
)
assert "the model response" in span["attributes"][SPANDATA.AI_RESPONSES]
else:
assert SPANDATA.AI_INPUT_MESSAGES not in span["attributes"]
assert SPANDATA.AI_RESPONSES not in span["attributes"]
assert span["attributes"]["gen_ai.usage.output_tokens"] == 10
assert span["attributes"]["gen_ai.usage.input_tokens"] == 20
assert span["attributes"]["gen_ai.usage.total_tokens"] == 30
else:
events = capture_events()
with start_transaction(name="cohere tx"):
responses = list(
client.chat_stream(
model="some-model",
chat_history=[ChatMessage(role="SYSTEM", message="some context")],
message="hello",
)
)
response_string = responses[-1].response.text
assert response_string == "the model response"
tx = events[0]
assert tx["type"] == "transaction"
assert len(tx["spans"]) == 1
span = tx["spans"][0]
assert span["op"] == "ai.chat_completions.create.cohere"
assert span["data"][SPANDATA.AI_MODEL_ID] == "some-model"
if send_default_pii and include_prompts:
assert (
'{"role": "system", "content": "some context"}'
in span["data"][SPANDATA.AI_INPUT_MESSAGES]
)
assert (
'{"role": "user", "content": "hello"}'
in span["data"][SPANDATA.AI_INPUT_MESSAGES]
)
assert "the model response" in span["data"][SPANDATA.AI_RESPONSES]
else:
assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
assert SPANDATA.AI_RESPONSES not in span["data"]
assert span["data"]["gen_ai.usage.output_tokens"] == 10
assert span["data"]["gen_ai.usage.input_tokens"] == 20
assert span["data"]["gen_ai.usage.total_tokens"] == 30
def test_bad_chat(sentry_init, capture_events):
sentry_init(integrations=[CohereIntegration()], traces_sample_rate=1.0)
events = capture_events()
client = Client(api_key="z")
HTTPXClient.request = mock.Mock(
side_effect=httpx.HTTPError("API rate limit reached")
)
with pytest.raises(httpx.HTTPError):
client.chat(model="some-model", message="hello")
(event, transaction) = events
assert event["level"] == "error"
assert transaction["contexts"]["trace"]["status"] == "internal_error"
def test_span_status_error(sentry_init, capture_events):
sentry_init(integrations=[CohereIntegration()], traces_sample_rate=1.0)
events = capture_events()
with start_transaction(name="test"):
client = Client(api_key="z")
HTTPXClient.request = mock.Mock(
side_effect=httpx.HTTPError("API rate limit reached")
)
with pytest.raises(httpx.HTTPError):
client.chat(model="some-model", message="hello")
(error, transaction) = events
assert error["level"] == "error"
assert transaction["spans"][0]["status"] == "internal_error"
assert transaction["spans"][0]["tags"]["status"] == "internal_error"
def test_span_status_error_streaming(sentry_init, capture_events, capture_items):
sentry_init(
integrations=[CohereIntegration()],
traces_sample_rate=1.0,
_experiments={"trace_lifecycle": "stream"},
)
items = capture_items("span")
client = Client(api_key="z")
HTTPXClient.request = mock.Mock(
side_effect=httpx.HTTPError("API rate limit reached")
)
with start_transaction(name="test"):
with pytest.raises(httpx.HTTPError):
client.chat(model="some-model", message="hello")
sentry_sdk.flush()
assert len(items) == 1
span = items[0].payload
assert span["status"] == "error"
@pytest.mark.parametrize("span_streaming", [True, False])
@pytest.mark.parametrize(
"send_default_pii, include_prompts",
[(True, True), (True, False), (False, True), (False, False)],
)
def test_embed(
sentry_init,
capture_events,
capture_items,
send_default_pii,
include_prompts,
span_streaming,
):
sentry_init(
integrations=[CohereIntegration(include_prompts=include_prompts)],
traces_sample_rate=1.0,
send_default_pii=send_default_pii,
_experiments={"trace_lifecycle": "stream" if span_streaming else "static"},
)
client = Client(api_key="z")
HTTPXClient.request = mock.Mock(
return_value=httpx.Response(
200,
json={
"response_type": "embeddings_floats",
"id": "1",
"texts": ["hello"],
"embeddings": [[1.0, 2.0, 3.0]],
"meta": {
"billed_units": {
"input_tokens": 10,
}
},
},
)
)
if span_streaming:
items = capture_items("span")
with start_transaction(name="cohere tx"):
response = client.embed(texts=["hello"], model="text-embedding-3-large")
assert len(response.embeddings[0]) == 3
sentry_sdk.flush()
assert len(items) == 1
span = items[0].payload
assert span["attributes"]["sentry.op"] == "ai.embeddings.create.cohere"
if send_default_pii and include_prompts:
assert "hello" in span["attributes"][SPANDATA.AI_INPUT_MESSAGES]
else:
assert SPANDATA.AI_INPUT_MESSAGES not in span["attributes"]
assert span["attributes"]["gen_ai.usage.input_tokens"] == 10
assert span["attributes"]["gen_ai.usage.total_tokens"] == 10
else:
events = capture_events()
with start_transaction(name="cohere tx"):
response = client.embed(texts=["hello"], model="text-embedding-3-large")
assert len(response.embeddings[0]) == 3
tx = events[0]
assert tx["type"] == "transaction"
assert len(tx["spans"]) == 1
span = tx["spans"][0]
assert span["op"] == "ai.embeddings.create.cohere"
if send_default_pii and include_prompts:
assert "hello" in span["data"][SPANDATA.AI_INPUT_MESSAGES]
else:
assert SPANDATA.AI_INPUT_MESSAGES not in span["data"]
assert span["data"]["gen_ai.usage.input_tokens"] == 10
assert span["data"]["gen_ai.usage.total_tokens"] == 10
def test_span_origin_chat(sentry_init, capture_events):
sentry_init(
integrations=[CohereIntegration()],
traces_sample_rate=1.0,
)
events = capture_events()
client = Client(api_key="z")
HTTPXClient.request = mock.Mock(
return_value=httpx.Response(
200,
json={
"text": "the model response",
"meta": {
"billed_units": {
"output_tokens": 10,
"input_tokens": 20,
}
},
},
)
)
with start_transaction(name="cohere tx"):
client.chat(
model="some-model",
chat_history=[ChatMessage(role="SYSTEM", message="some context")],
message="hello",
).text
(event,) = events
assert event["contexts"]["trace"]["origin"] == "manual"
assert event["spans"][0]["origin"] == "auto.ai.cohere"
def test_span_origin_embed(sentry_init, capture_events):
sentry_init(
integrations=[CohereIntegration()],
traces_sample_rate=1.0,
)
events = capture_events()
client = Client(api_key="z")
HTTPXClient.request = mock.Mock(
return_value=httpx.Response(
200,
json={
"response_type": "embeddings_floats",
"id": "1",
"texts": ["hello"],
"embeddings": [[1.0, 2.0, 3.0]],
"meta": {
"billed_units": {
"input_tokens": 10,
}
},
},
)
)
with start_transaction(name="cohere tx"):
client.embed(texts=["hello"], model="text-embedding-3-large")
(event,) = events
assert event["contexts"]["trace"]["origin"] == "manual"
assert event["spans"][0]["origin"] == "auto.ai.cohere"