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_mock_external_openai_server.py
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# Copyright 2010 New Relic, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
from testing_support.mock_external_http_server import MockExternalHTTPServer
# This defines an external server test apps can make requests to instead of
# the real OpenAI backend. This provides 3 features:
#
# 1) This removes dependencies on external websites.
# 2) Provides a better mechanism for making an external call in a test app than
# simple calling another endpoint the test app makes available because this
# server will not be instrumented meaning we don't have to sort through
# transactions to separate the ones created in the test app and the ones
# created by an external call.
# 3) This app runs on a separate thread meaning it won't block the test app.
RESPONSES = {
"Invalid API key.": (
{"Content-Type": "application/json; charset=utf-8", "x-request-id": "4f8f61a7d0401e42a6760ea2ca2049f6"},
401,
{
"error": {
"message": "Incorrect API key provided: invalid. You can find your API key at https://platform.openai.com/account/api-keys.",
"type": "invalid_request_error",
"param": "null",
"code": "invalid_api_key",
}
},
),
"Embedded: Invalid API key.": (
{"Content-Type": "application/json; charset=utf-8", "x-request-id": "4f8f61a7d0401e42a6760ea2ca2049f6"},
401,
{
"error": {
"message": "Incorrect API key provided: DEADBEEF. You can find your API key at https://platform.openai.com/account/api-keys.",
"type": "invalid_request_error",
"param": "null",
"code": "invalid_api_key",
}
},
),
"Model does not exist.": (
{
"Content-Type": "application/json",
"x-request-id": "cfdf51fb795362ae578c12a21796262c",
},
404,
{
"error": {
"message": "The model `does-not-exist` does not exist",
"type": "invalid_request_error",
"param": "null",
"code": "model_not_found",
}
},
),
"This is an embedding test.": (
{
"Content-Type": "application/json",
"openai-organization": "new-relic-nkmd8b",
"openai-processing-ms": "54",
"openai-version": "2020-10-01",
"x-ratelimit-limit-requests": "200",
"x-ratelimit-limit-tokens": "150000",
"x-ratelimit-remaining-requests": "197",
"x-ratelimit-remaining-tokens": "149994",
"x-ratelimit-reset-requests": "19m45.394s",
"x-ratelimit-reset-tokens": "2ms",
"x-request-id": "c70828b2293314366a76a2b1dcb20688",
},
200,
{
"data": [
{
"embedding": "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",
"index": 0,
"object": "embedding",
}
],
"model": "text-embedding-ada-002-v2",
"object": "list",
"usage": {"prompt_tokens": 6, "total_tokens": 6},
},
),
"You are a scientist.": (
{
"Content-Type": "application/json",
"openai-model": "gpt-3.5-turbo-0613",
"openai-organization": "new-relic-nkmd8b",
"openai-processing-ms": "1469",
"openai-version": "2020-10-01",
"x-ratelimit-limit-requests": "200",
"x-ratelimit-limit-tokens": "40000",
"x-ratelimit-remaining-requests": "199",
"x-ratelimit-remaining-tokens": "39940",
"x-ratelimit-reset-requests": "7m12s",
"x-ratelimit-reset-tokens": "90ms",
"x-request-id": "49dbbffbd3c3f4612aa48def69059ccd",
},
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"You are a mathematician.": (
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def simple_get(self):
content_len = int(self.headers.get("content-length"))
content = json.loads(self.rfile.read(content_len).decode("utf-8"))
prompt = extract_shortened_prompt(content)
if not prompt:
self.send_response(500)
self.end_headers()
self.wfile.write("Could not parse prompt.".encode("utf-8"))
return
headers, response = ({}, "")
for k, v in RESPONSES.items():
if prompt.startswith(k):
headers, status_code, response = v
break
else: # If no matches found
self.send_response(500)
self.end_headers()
self.wfile.write(("Unknown Prompt:\n%s" % prompt).encode("utf-8"))
return
# Send response code
self.send_response(status_code)
# Send headers
for k, v in headers.items():
self.send_header(k, v)
self.end_headers()
# Send response body
self.wfile.write(json.dumps(response).encode("utf-8"))
return
def extract_shortened_prompt(content):
prompt = (
content.get("prompt", None)
or content.get("input", None)
or "\n".join(m["content"] for m in content.get("messages"))
)
return prompt.lstrip().split("\n")[0]
class MockExternalOpenAIServer(MockExternalHTTPServer):
# To use this class in a test one needs to start and stop this server
# before and after making requests to the test app that makes the external
# calls.
def __init__(self, handler=simple_get, port=None, *args, **kwargs):
super(MockExternalOpenAIServer, self).__init__(handler=handler, port=port, *args, **kwargs)
if __name__ == "__main__":
with MockExternalOpenAIServer() as server:
print("MockExternalOpenAIServer serving on port %s" % str(server.port))
while True:
pass # Serve forever