dream

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import requests
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from time import time
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def main_test():
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    url = "http://0.0.0.0:8150/model"
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    batch_url = "http://0.0.0.0:8150/batch_model"
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    configs = [
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        {
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            "sentences": ["do you like porn"],
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            "task": "all",
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            "possible_answers": {
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                "cobot_topics": ["Sex_Profanity"],
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                "cobot_dialogact_topics": ["Inappropriate_Content"],
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            },
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        },
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        {
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            "sentences": ["let's talk about movies", "do you like porn"],
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            "task": "cobot_dialogact_topics",
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            "answers_bert": [["Entertainment_Movies"], ["Inappropriate_Content"]],
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        },
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        {
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            "sentences": ["let's talk about games", "do you like watching films"],
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            "task": "cobot_topics",
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            "answers_bert": [["Games"], ["Movies_TV"]],
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        },
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        {
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            "sentences_with_history": ["What is the capital of Great Britain [SEP] I don't know"],
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            "sentences": ["I don't know"],
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            "task": "cobot_dialogact_intents",
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            "answers_bert": [["Information_DeliveryIntent"]],
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        },
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        {
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            "sentences": ["how do I empty my DNS cache?", "which do you prefer?", "where is montreal"],
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            "task": "factoid_classification",
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            "answers_bert": [["is_factoid"], ["is_conversational"], ["is_factoid"]],
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        },
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        {
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            "sentences": ["i love you", "i hate you", "It is now"],
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            "task": "sentiment_classification",
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            "answers_bert": [["positive"], ["negative"], ["neutral"]],
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        },
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        {
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            "sentences": ["why you are such a fool"],
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            "task": "emotion_classification",
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            "answers_bert": [["anger"]],
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        },
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        {
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            "sentences_with_history": ["this is the best dog [SEP] so what you think"],
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            "sentences": ["so what you think"],
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            "task": "midas_classification",
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            "answers_bert": [["open_question_opinion"]],
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        },
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        {
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            "sentences": ["please talk about movies", "talk about games"],
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            "task": "deeppavlov_topics",
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            "answers_bert": [["Movies&Tv"], ["Videogames"]],
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        },
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        {
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            "sentences": ["you son of the bitch", "yes", "do you like porn"],
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            "task": "toxic_classification",
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            "answers_bert": [["obscene"], ["not_toxic"], ["sexual_explicit"]],
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        },
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    ]
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    t = time()
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    for config in configs:
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        if "sentences_with_history" in config:
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            config["utterances_with_histories"] = [[k] for k in config["sentences_with_history"]]
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        else:
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            config["utterances_with_histories"] = [[k] for k in config["sentences"]]
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        responses = requests.post(url, json=config).json()
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        batch_responses = requests.post(batch_url, json=config).json()
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        batch_error_msg = f"Batch responses {batch_responses} not match to responses {responses}"
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        assert (
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            batch_responses[0]["batch"][0]["toxic_classification"] == responses[0]["toxic_classification"]
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        ), batch_error_msg
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        if config["task"] == "all":
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            for i in range(len(responses)):
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                print(f"Checking that at least 1 annotator works for {config['sentences'][i]}")
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                predicted_cobot_topics = [
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                    class_
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                    for class_ in responses[i]["cobot_topics"]
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                    if responses[i]["cobot_topics"][class_] == max(responses[0]["cobot_topics"].values())
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                ]
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                predicted_cobot_da_topics = [
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                    class_
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                    for class_ in responses[i]["cobot_dialogact_topics"]
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                    if responses[i]["cobot_dialogact_topics"][class_]
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                    == max(responses[i]["cobot_dialogact_topics"].values())
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                ]
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                error_msg1 = (
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                    f"Predicted cobot topics {predicted_cobot_topics} and da topics {predicted_cobot_da_topics}"
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                    f"not match with sensitive cobot_topics {config['possible_answers']['cobot_topics']}"
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                    f"and sensitive cobot da topics {config['possible_answers']['cobot_dialogact_topics']}"
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                )
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                assert any(
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                    [
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                        set(predicted_cobot_topics) & set(config["possible_answers"]["cobot_topics"]),
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                        set(predicted_cobot_da_topics) & set(config["possible_answers"]["cobot_dialogact_topics"]),
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                    ]
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                ), error_msg1
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        else:
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            responses = [j[config["task"]] for j in responses]
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            for response, answer, sentence in zip(responses, config["answers_bert"], config["sentences"]):
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                #  print((response, answer, sentence))
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                predicted_classes = [class_ for class_ in response if response[class_] == max(response.values())]
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                assert sorted(answer) == sorted(predicted_classes), " * ".join(
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                    [str(j) for j in [sentence, config["task"], answer, predicted_classes, response]]
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                )
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    print("SUCCESS!")
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    print(time() - t)
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    return 0
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main_test()
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