| import pytest |
| import requests |
| import time |
| import random |
|
|
| from openai import OpenAI |
| from utils import * |
|
|
| server = ServerPreset.tinyllama2() |
|
|
| JSON_MULTIMODAL_KEY = "multimodal_data" |
| JSON_PROMPT_STRING_KEY = "prompt_string" |
|
|
| @pytest.fixture(autouse=True) |
| def create_server(): |
| global server |
| server = ServerPreset.tinyllama2() |
|
|
| @pytest.mark.parametrize("prompt,n_predict,re_content,n_prompt,n_predicted,truncated,return_tokens", [ |
| ("I believe the meaning of life is", 8, "(going|bed)+", 18, 8, False, False), |
| ("Write a joke about AI from a very long prompt which will not be truncated", 64, "(princesses|everyone|kids|Anna|forest)+", 46, 64, False, True), |
| ]) |
| def test_completion(prompt: str, n_predict: int, re_content: str, n_prompt: int, n_predicted: int, truncated: bool, return_tokens: bool): |
| global server |
| server.start() |
| res = server.make_request("POST", "/completion", data={ |
| "n_predict": n_predict, |
| "prompt": prompt, |
| "return_tokens": return_tokens, |
| }) |
| assert res.status_code == 200 |
| assert res.body["timings"]["prompt_n"] == n_prompt |
| assert res.body["timings"]["predicted_n"] == n_predicted |
| assert res.body["truncated"] == truncated |
| assert type(res.body["has_new_line"]) == bool |
| assert match_regex(re_content, res.body["content"]) |
| if return_tokens: |
| assert len(res.body["tokens"]) > 0 |
| assert all(type(tok) == int for tok in res.body["tokens"]) |
| else: |
| assert res.body["tokens"] == [] |
|
|
|
|
| @pytest.mark.parametrize("prompt,n_predict,re_content,n_prompt,n_predicted,truncated", [ |
| ("I believe the meaning of life is", 8, "(going|bed)+", 18, 8, False), |
| ("Write a joke about AI from a very long prompt which will not be truncated", 64, "(princesses|everyone|kids|Anna|forest)+", 46, 64, False), |
| ]) |
| def test_completion_stream(prompt: str, n_predict: int, re_content: str, n_prompt: int, n_predicted: int, truncated: bool): |
| global server |
| server.start() |
| res = server.make_stream_request("POST", "/completion", data={ |
| "n_predict": n_predict, |
| "prompt": prompt, |
| "stream": True, |
| }) |
| content = "" |
| for data in res: |
| assert "stop" in data and type(data["stop"]) == bool |
| if data["stop"]: |
| assert data["timings"]["prompt_n"] == n_prompt |
| assert data["timings"]["predicted_n"] == n_predicted |
| assert data["truncated"] == truncated |
| assert data["stop_type"] == "limit" |
| assert type(data["has_new_line"]) == bool |
| assert "generation_settings" in data |
| assert server.n_predict is not None |
| assert data["generation_settings"]["n_predict"] == min(n_predict, server.n_predict) |
| assert data["generation_settings"]["seed"] == server.seed |
| assert match_regex(re_content, content) |
| else: |
| assert len(data["tokens"]) > 0 |
| assert all(type(tok) == int for tok in data["tokens"]) |
| content += data["content"] |
|
|
|
|
| def test_completion_stream_vs_non_stream(): |
| global server |
| server.start() |
| res_stream = server.make_stream_request("POST", "/completion", data={ |
| "n_predict": 8, |
| "prompt": "I believe the meaning of life is", |
| "stream": True, |
| }) |
| res_non_stream = server.make_request("POST", "/completion", data={ |
| "n_predict": 8, |
| "prompt": "I believe the meaning of life is", |
| }) |
| content_stream = "" |
| for data in res_stream: |
| content_stream += data["content"] |
| assert content_stream == res_non_stream.body["content"] |
|
|
|
|
| def test_completion_with_openai_library(): |
| global server |
| server.start() |
| client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}/v1") |
| res = client.completions.create( |
| model="davinci-002", |
| prompt="I believe the meaning of life is", |
| max_tokens=8, |
| ) |
| assert res.system_fingerprint is not None and res.system_fingerprint.startswith("b") |
| assert res.choices[0].finish_reason == "length" |
| assert res.choices[0].text is not None |
| assert match_regex("(going|bed)+", res.choices[0].text) |
|
|
|
|
| def test_completion_stream_with_openai_library(): |
| global server |
| server.start() |
| client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}/v1") |
| res = client.completions.create( |
| model="davinci-002", |
| prompt="I believe the meaning of life is", |
| max_tokens=8, |
| stream=True, |
| ) |
| output_text = '' |
| for data in res: |
| choice = data.choices[0] |
| if choice.finish_reason is None: |
| assert choice.text is not None |
| output_text += choice.text |
| assert match_regex("(going|bed)+", output_text) |
|
|
|
|
| |
| @pytest.mark.slow |
| def test_completion_stream_with_openai_library_stops(): |
| global server |
| server.model_hf_repo = "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M" |
| server.model_hf_file = None |
| server.start() |
| client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}/v1") |
| res = client.completions.create( |
| model="davinci-002", |
| prompt="System: You are helpfull assistant.\nAssistant:\nHey! How could I help?\nUser:\nTell me a joke.\nAssistant:\n", |
| stop=["User:\n", "Assistant:\n"], |
| max_tokens=200, |
| stream=True, |
| ) |
| output_text = '' |
| for data in res: |
| choice = data.choices[0] |
| if choice.finish_reason is None: |
| assert choice.text is not None |
| output_text += choice.text |
| assert match_regex("Sure, here's one for[\\s\\S]*", output_text), f'Unexpected output: {output_text}' |
|
|
|
|
| @pytest.mark.parametrize("n_slots", [1, 2]) |
| def test_consistent_result_same_seed(n_slots: int): |
| global server |
| server.n_slots = n_slots |
| server.start() |
| last_res = None |
| for _ in range(4): |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| "seed": 42, |
| "temperature": 0.0, |
| "cache_prompt": False, |
| }) |
| if last_res is not None: |
| assert res.body["content"] == last_res.body["content"] |
| last_res = res |
|
|
|
|
| @pytest.mark.parametrize("n_slots", [1, 2]) |
| def test_different_result_different_seed(n_slots: int): |
| global server |
| server.n_slots = n_slots |
| server.start() |
| last_res = None |
| for seed in range(4): |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| "seed": seed, |
| "temperature": 1.0, |
| "cache_prompt": False, |
| }) |
| if last_res is not None: |
| assert res.body["content"] != last_res.body["content"] |
| last_res = res |
|
|
| |
| |
| @pytest.mark.parametrize("n_batch", [16, 32]) |
| @pytest.mark.parametrize("temperature", [0.0]) |
| def test_consistent_result_different_batch_size(n_batch: int, temperature: float): |
| global server |
| server.n_batch = n_batch |
| server.start() |
| last_res = None |
| for _ in range(4): |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| "seed": 42, |
| "temperature": temperature, |
| "cache_prompt": False, |
| }) |
| if last_res is not None: |
| assert res.body["content"] == last_res.body["content"] |
| last_res = res |
|
|
|
|
| @pytest.mark.skip(reason="This test fails on linux, need to be fixed") |
| def test_cache_vs_nocache_prompt(): |
| global server |
| server.start() |
| res_cache = server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| "seed": 42, |
| "temperature": 1.0, |
| "cache_prompt": True, |
| }) |
| res_no_cache = server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| "seed": 42, |
| "temperature": 1.0, |
| "cache_prompt": False, |
| }) |
| assert res_cache.body["content"] == res_no_cache.body["content"] |
|
|
|
|
| def test_nocache_long_input_prompt(): |
| global server |
| server.start() |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is"*32, |
| "seed": 42, |
| "temperature": 1.0, |
| "cache_prompt": False, |
| }) |
| assert res.status_code == 400 |
|
|
| def test_json_prompt_no_mtmd(): |
| global server |
| server.start() |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": { JSON_PROMPT_STRING_KEY: "I believe the meaning of life is" }, |
| "seed": 42, |
| "temperature": 1.0, |
| "cache_prompt": False, |
| }) |
| assert res.status_code == 200 |
|
|
| def test_json_prompt_mtm_error_when_not_supported(): |
| global server |
| server.start() |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": { JSON_PROMPT_STRING_KEY: "I believe the meaning of life is <__media__>", JSON_MULTIMODAL_KEY: "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=" }, |
| "seed": 42, |
| "temperature": 1.0, |
| "cache_prompt": False, |
| }) |
| |
| assert res.status_code != 200 |
|
|
| def test_completion_with_tokens_input(): |
| global server |
| server.temperature = 0.0 |
| server.start() |
| prompt_str = "I believe the meaning of life is" |
| res = server.make_request("POST", "/tokenize", data={ |
| "content": prompt_str, |
| "add_special": True, |
| }) |
| assert res.status_code == 200 |
| tokens = res.body["tokens"] |
|
|
| |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": tokens, |
| }) |
| assert res.status_code == 200 |
| assert type(res.body["content"]) == str |
|
|
| |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": [tokens, tokens], |
| }) |
| assert res.status_code == 200 |
| assert type(res.body) == list |
| assert len(res.body) == 2 |
| assert res.body[0]["content"] == res.body[1]["content"] |
|
|
| |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": [tokens, prompt_str], |
| }) |
| assert res.status_code == 200 |
| assert type(res.body) == list |
| assert len(res.body) == 2 |
| assert res.body[0]["content"] == res.body[1]["content"] |
|
|
| |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": [ |
| tokens, |
| { |
| JSON_PROMPT_STRING_KEY: "I believe the meaning of life is", |
| }, |
| ], |
| }) |
| assert res.status_code == 200 |
| assert type(res.body) == list |
| assert len(res.body) == 2 |
| assert res.body[0]["content"] == res.body[1]["content"] |
|
|
| |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": [1, 2, 3, 4, 5, 6, prompt_str, 7, 8, 9, 10, prompt_str], |
| }) |
| assert res.status_code == 200 |
| assert type(res.body["content"]) == str |
|
|
|
|
| @pytest.mark.parametrize("n_slots,n_requests", [ |
| (1, 3), |
| (2, 2), |
| (2, 4), |
| (4, 2), |
| (4, 6), |
| ]) |
| def test_completion_parallel_slots(n_slots: int, n_requests: int): |
| global server |
| server.n_slots = n_slots |
| server.temperature = 0.0 |
| server.start() |
|
|
| PROMPTS = [ |
| ("Write a very long book.", "(very|special|big)+"), |
| ("Write another a poem.", "(small|house)+"), |
| ("What is LLM?", "(Dad|said)+"), |
| ("The sky is blue and I love it.", "(climb|leaf)+"), |
| ("Write another very long music lyrics.", "(friends|step|sky)+"), |
| ("Write a very long joke.", "(cat|Whiskers)+"), |
| ] |
| def check_slots_status(): |
| should_all_slots_busy = n_requests >= n_slots |
| time.sleep(0.1) |
| res = server.make_request("GET", "/slots") |
| n_busy = sum([1 for slot in res.body if slot["is_processing"]]) |
| if should_all_slots_busy: |
| assert n_busy == n_slots |
| else: |
| assert n_busy <= n_slots |
|
|
| tasks = [] |
| for i in range(n_requests): |
| prompt, re_content = PROMPTS[i % len(PROMPTS)] |
| tasks.append((server.make_request, ("POST", "/completion", { |
| "prompt": prompt, |
| "seed": 42, |
| "temperature": 1.0, |
| }))) |
| tasks.append((check_slots_status, ())) |
| results = parallel_function_calls(tasks) |
|
|
| |
| for i in range(n_requests): |
| prompt, re_content = PROMPTS[i % len(PROMPTS)] |
| res = results[i] |
| assert res.status_code == 200 |
| assert type(res.body["content"]) == str |
| assert len(res.body["content"]) > 10 |
| |
| |
|
|
|
|
| @pytest.mark.parametrize( |
| "n_ctx,n_slots,n_predict_vals,expected_success", |
| [ |
| (256, 4, [80, 40, 80, 80], [True, True, True, True]), |
| (256, 4, [70, 70, 70, 70], [False, False, False, False]), |
| (256, 4, [90, 90, 40, 90], [False, False, True, False]), |
| (256, 4, [90, 90, 40, 75], [True, True, True, True]), |
| ], |
| ) |
| def test_completion_unified(n_ctx, n_slots, n_predict_vals, expected_success): |
| global server |
| server.n_slots = n_slots |
| server.kv_unified = True |
| server.n_ctx = n_ctx |
| server.start() |
| prompt = "A" |
| tasks = [] |
| for n_predict in n_predict_vals: |
| tasks.append((server.make_request, ("POST", "/completion", {"prompt": prompt, "n_predict": n_predict}))) |
| results = parallel_function_calls(tasks) |
| for res, n_predict, expect_ok in zip(results, n_predict_vals, expected_success): |
| if expect_ok: |
| assert res.status_code == 200 |
|
|
| |
| if res.status_code == 200: |
| assert "content" in res.body |
| if "timings" in res.body: |
| assert res.body["timings"]["predicted_n"] == n_predict |
|
|
|
|
| @pytest.mark.parametrize( |
| "prompt,n_predict,response_fields", |
| [ |
| ("I believe the meaning of life is", 8, []), |
| ("I believe the meaning of life is", 32, ["content", "generation_settings/n_predict", "prompt"]), |
| ], |
| ) |
| def test_completion_response_fields( |
| prompt: str, n_predict: int, response_fields: list[str] |
| ): |
| global server |
| server.start() |
| res = server.make_request( |
| "POST", |
| "/completion", |
| data={ |
| "n_predict": n_predict, |
| "prompt": prompt, |
| "response_fields": response_fields, |
| }, |
| ) |
| assert res.status_code == 200 |
| assert "content" in res.body |
| assert len(res.body["content"]) |
| if len(response_fields): |
| assert res.body["generation_settings/n_predict"] == n_predict |
| assert res.body["prompt"] == "<s> " + prompt |
| assert isinstance(res.body["content"], str) |
| assert len(res.body) == len(response_fields) |
| else: |
| assert len(res.body) |
| assert "generation_settings" in res.body |
|
|
|
|
| def test_n_probs(): |
| global server |
| server.start() |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| "n_probs": 10, |
| "temperature": 0.0, |
| "n_predict": 5, |
| }) |
| assert res.status_code == 200 |
| assert "completion_probabilities" in res.body |
| assert len(res.body["completion_probabilities"]) == 5 |
| for tok in res.body["completion_probabilities"]: |
| assert "id" in tok and tok["id"] > 0 |
| assert "token" in tok and type(tok["token"]) == str |
| assert "logprob" in tok and tok["logprob"] <= 0.0 |
| assert "bytes" in tok and type(tok["bytes"]) == list |
| assert len(tok["top_logprobs"]) == 10 |
| for prob in tok["top_logprobs"]: |
| assert "id" in prob and prob["id"] > 0 |
| assert "token" in prob and type(prob["token"]) == str |
| assert "logprob" in prob and prob["logprob"] <= 0.0 |
| assert "bytes" in prob and type(prob["bytes"]) == list |
|
|
|
|
| def test_n_probs_stream(): |
| global server |
| server.start() |
| res = server.make_stream_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| "n_probs": 10, |
| "temperature": 0.0, |
| "n_predict": 5, |
| "stream": True, |
| }) |
| for data in res: |
| if data["stop"] == False: |
| assert "completion_probabilities" in data |
| assert len(data["completion_probabilities"]) == 1 |
| for tok in data["completion_probabilities"]: |
| assert "id" in tok and tok["id"] > 0 |
| assert "token" in tok and type(tok["token"]) == str |
| assert "logprob" in tok and tok["logprob"] <= 0.0 |
| assert "bytes" in tok and type(tok["bytes"]) == list |
| assert len(tok["top_logprobs"]) == 10 |
| for prob in tok["top_logprobs"]: |
| assert "id" in prob and prob["id"] > 0 |
| assert "token" in prob and type(prob["token"]) == str |
| assert "logprob" in prob and prob["logprob"] <= 0.0 |
| assert "bytes" in prob and type(prob["bytes"]) == list |
|
|
|
|
| def test_n_probs_post_sampling(): |
| global server |
| server.start() |
| res = server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| "n_probs": 10, |
| "temperature": 0.0, |
| "n_predict": 5, |
| "post_sampling_probs": True, |
| }) |
| assert res.status_code == 200 |
| assert "completion_probabilities" in res.body |
| assert len(res.body["completion_probabilities"]) == 5 |
| for tok in res.body["completion_probabilities"]: |
| assert "id" in tok and tok["id"] > 0 |
| assert "token" in tok and type(tok["token"]) == str |
| assert "prob" in tok and 0.0 < tok["prob"] <= 1.0 |
| assert "bytes" in tok and type(tok["bytes"]) == list |
| assert len(tok["top_probs"]) == 10 |
| for prob in tok["top_probs"]: |
| assert "id" in prob and prob["id"] > 0 |
| assert "token" in prob and type(prob["token"]) == str |
| assert "prob" in prob and 0.0 <= prob["prob"] <= 1.0 |
| assert "bytes" in prob and type(prob["bytes"]) == list |
| |
| assert any(prob["prob"] == 1.0 for prob in tok["top_probs"]) |
|
|
|
|
| @pytest.mark.parametrize("tokenize,openai_style", [(False, False), (False, True), (True, False), (True, True)]) |
| def test_logit_bias(tokenize, openai_style): |
| global server |
| server.start() |
|
|
| exclude = ["i", "I", "the", "The", "to", "a", "an", "be", "is", "was", "but", "But", "and", "And", "so", "So", "you", "You", "he", "He", "she", "She", "we", "We", "they", "They", "it", "It", "his", "His", "her", "Her", "book", "Book"] |
|
|
| logit_bias = [] |
| if tokenize: |
| res = server.make_request("POST", "/tokenize", data={ |
| "content": " " + " ".join(exclude) + " ", |
| }) |
| assert res.status_code == 200 |
| tokens = res.body["tokens"] |
| logit_bias = [[tok, -100] for tok in tokens] |
|
|
| else: |
| logit_bias = [[" " + tok + " ", -100] for tok in exclude] |
|
|
| if openai_style: |
| logit_bias = {el[0]: -100 for el in logit_bias} |
|
|
| res = server.make_request("POST", "/completion", data={ |
| "n_predict": 64, |
| "prompt": "What is the best book", |
| "logit_bias": logit_bias, |
| "temperature": 0.0 |
| }) |
| assert res.status_code == 200 |
| output_text = res.body["content"] |
| assert all(output_text.find(" " + tok + " ") == -1 for tok in exclude) |
|
|
|
|
| def test_cancel_request(): |
| global server |
| server.n_ctx = 4096 |
| server.n_predict = -1 |
| server.n_slots = 1 |
| server.server_slots = True |
| server.start() |
| |
| try: |
| server.make_request("POST", "/completion", data={ |
| "prompt": "I believe the meaning of life is", |
| }, timeout=0.1) |
| except requests.exceptions.ReadTimeout: |
| pass |
| |
| time.sleep(2) |
| res = server.make_request("GET", "/slots") |
| assert res.body[0]["is_processing"] == False |
|
|
|
|
| |
| |
| |
| def test_completion_prompt_cache(): |
| global server |
| server.n_slots = 2 |
| server.kv_unified = True |
| server.start() |
|
|
| for _ in range(16): |
| |
| r = random.randint(0, 4) |
| prompt = (" Hello " + str(r)) * (40 + r) |
| n_prompt = (40 + r)*5 + 2 |
| n_predict = random.randint(1, 8) |
|
|
| res = server.make_request( |
| "POST", |
| "/completion", |
| data={ |
| "prompt": prompt, |
| "n_predict": n_predict, |
| }, |
| ) |
|
|
| assert res.status_code == 200 |
| assert "content" in res.body |
| content = res.body["content"] |
| assert isinstance(content, str) |
| assert len(content) > 0 |
|
|
| assert type(res.body["has_new_line"]) == bool |
| assert "timings" in res.body |
| timings = res.body["timings"] |
|
|
| assert "prompt_n" in timings and timings["prompt_n"] + timings["cache_n"] == n_prompt |
| assert "predicted_n" in timings and timings["predicted_n"] == n_predict |
| assert "tokens" in res.body and isinstance(res.body["tokens"], list) |
|
|