{
  "test_id": "tests/integration/telemetry/test_completions.py::test_telemetry_format_completeness[txt=ollama/llama3.2:3b-instruct-fp16]",
  "request": {
    "method": "POST",
    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
    "headers": {},
    "body": {
      "model": "llama3.2:3b-instruct-fp16",
      "messages": [
        {
          "role": "user",
          "content": "Test trace openai with temperature 0.7"
        }
      ],
      "max_tokens": 100,
      "stream": false,
      "temperature": 0.7
    },
    "endpoint": "/v1/chat/completions",
    "model": "llama3.2:3b-instruct-fp16"
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  "response": {
    "body": {
      "__type__": "openai.types.chat.chat_completion.ChatCompletion",
      "__data__": {
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        "choices": [
          {
            "finish_reason": "length",
            "index": 0,
            "logprobs": null,
            "message": {
              "content": "import torch\nfrom transformers import AutoModelForCausalLM, AutoTokenizer\n\n# Load the pre-trained model and tokenizer\nmodel_name = \"CompVis/transformers-base-uncased\"\nmodel = AutoModelForCausalLM.from_pretrained(model_name)\ntokenizer = AutoTokenizer.from_pretrained(model_name)\n\n# Set the temperature to 0.7\ntemperature = 0.7\n\n# Define a function to generate text\ndef generate_text(prompt, max_length=100):\n    input",
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