phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-10-16 06:53:47 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

feat(tests): auto-merge all model list responses and unify recordings

Browse source
This commit is contained in:
Ashwin Bharambe 2025-09-03 10:27:44 -07:00
parent faf891b40c
commit 34f5da6cdc
121 changed files with 17457 additions and 16126 deletions
Download patch file Download diff file Expand all files Collapse all files

12
tests/integration/recordings/responses/140187e305dc.json
View file

@ -1,7 +1,7 @@
{
"request": {
"method": "POST",
"url": "http://localhost:11434/v1/v1/chat/completions",
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
"headers": {},
"body": {
"model": "llama3.2:3b-instruct-fp16",
@ -20,14 +20,14 @@
"body": {
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
"__data__": {
"id": "chatcmpl-876",
"id": "chatcmpl-974",
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"message": {
"content": "I'm afraid I don't have a built-in ability to directly interface with or \"test\" OpenAI models, including the original GPT-1 model. However, I can explain how you might approach this task:\n\nThe OpenAI GPT-1 is a large transformer-based language model that was trained on a massive dataset of text and achieved state-of-the-art results in various natural language processing tasks.\n\nTo test or evaluate the performance of a model like GPT-1, you would typically follow these steps:\n\n1. **Get access to the OpenAI API**: The OpenAI API provides a way for developers to interact with the GPT-1 model programmatically. You can sign up for an API key on the OpenAI website.\n2. **Choose a testing platform or environment**: You'll need a compute platform that supports the necessary algorithms and data structures to run inference on the GPT-1 model. Some popular options include AWS, Google Cloud, or Azure Compute Virtual Machines.\n3. **Prepare your test input data**: This will involve creating text inputs in the format expected by the OpenAI API (i.e., a JSON object containing the text to be processed).\n4. **Use the OpenAI Python library or SDK**: The OpenAI Python library provides an easy-to-use interface for interacting with the GPT-1 model through the API.\n\nHere's some example code that demonstrates how you might use the OpenAI Flask API to test a single input:\n\n```python\nfrom flask import Flask, request, jsonify\nimport json\n\napp = Flask(__name__)\n\n@ app . route ( '/ /gpt-en ', ' Text ', methods = ['POST'])\ndef gpt_en () -> Json :\n data = request . get_json ()\n if not data or \"message\" in ( data ):\n return None , 400 , { ' error' : \"Input must be a text string.\" }\n response = []\n while True:\n message = \"\"\n for token in data [\"input\"]:\n response_text = f\"{data['prompt']} {token}\"\n data[\"input\"] = [response_text]\n new_response = gpt_en()(data)\n if all([not item or not isinstance(item, dict) for item in new_response]):\n break\n\n message = json . dumps ({}\"text\": response_text})\n response.append(message)\n\n return jsonify ({\"output\": response}), 200 , {}\n\nif __name__ == \"__main__\":\n app.run(debug=True)\n```\n\n5. **Evaluate the output**: Once you have processed your test input data using the GPT-1 model, you can evaluate the accuracy of the generated responses.\n\nKeep in mind that this is just a basic example to illustrate how you might approach testing the OpenAI GPT-1 model.",
"content": "I'm happy to help you test the OpenAI API, however I can not access the API.\n\nInstead why don't we follow these steps:\n\n* Check documentation\n* Contact support\n* Reach out to their community forum. \n\nLet me know if I can be of any additional assistance",
"refusal": null,
"role": "assistant",
"annotations": null,
@ -37,15 +37,15 @@
}
}
],
"created": 1754510050,
"created": 1756921202,
"model": "llama3.2:3b-instruct-fp16",
"object": "chat.completion",
"service_tier": null,
"system_fingerprint": "fp_ollama",
"usage": {
"completion_tokens": 567,
"completion_tokens": 61,
"prompt_tokens": 31,
"total_tokens": 598,
"total_tokens": 92,
"completion_tokens_details": null,
"prompt_tokens_details": null
}