mirror of
https://github.com/meta-llama/llama-stack.git
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59 lines
2 KiB
JSON
Generated
59 lines
2 KiB
JSON
Generated
{
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"test_id": "tests/integration/telemetry/test_completions.py::test_telemetry_format_completeness[txt=ollama/llama3.2:3b-instruct-fp16]",
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"request": {
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"method": "POST",
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"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
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"headers": {},
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"body": {
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"model": "llama3.2:3b-instruct-fp16",
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"messages": [
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{
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"role": "user",
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"content": "Test trace openai with temperature 0.7"
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}
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],
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"max_tokens": 100,
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"stream": false,
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"temperature": 0.7
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},
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"endpoint": "/v1/chat/completions",
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"model": "llama3.2:3b-instruct-fp16"
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},
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"response": {
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"body": {
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"__type__": "openai.types.chat.chat_completion.ChatCompletion",
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"__data__": {
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"id": "rec-1fcfd86d8111",
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"choices": [
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{
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"finish_reason": "length",
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"index": 0,
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"logprobs": null,
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"message": {
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"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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"refusal": null,
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"role": "assistant",
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"annotations": null,
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"audio": null,
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"function_call": null,
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"tool_calls": null
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}
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}
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],
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"created": 0,
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"model": "llama3.2:3b-instruct-fp16",
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"object": "chat.completion",
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"service_tier": null,
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"system_fingerprint": "fp_ollama",
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"usage": {
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"completion_tokens": 100,
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"prompt_tokens": 35,
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"total_tokens": 135,
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"completion_tokens_details": null,
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"prompt_tokens_details": null
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}
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}
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},
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"is_streaming": false
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}
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}
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