<jupyter_start><jupyter_text>**These are all causes of hangover.  So in a hangover there is an increase of lactate.  The question that we want to answer then, is do we have a way to decrease lactate or lactates.  And the same for aldehydes etc...So what I would like you to do is to try to run either some chemical-(lactate) and chemical-gene-lactate queries through strider and aragorn and let's see if we can get results.  And also do it for aldehyes, and etc.**  1. Chemical to AldehydesDo we have a way to decrease Aldehydes<jupyter_code>with open('/Users/priyash/Documents/GitHub/robogallery/user_queries/json_queries/hangover_three.json', 'r') as myfile:
    query = make_message(json.loads(myfile.read()))
printjson(query)
query['message']['knowledge_graph'] = {'nodes':{}, 'edges':{}}
query['message']['results'] = []<jupyter_output><empty_output><jupyter_text>Strider Direct<jupyter_code>start = dt.now()
strider_result = strider(query)
end = dt.now()
print(f"Strider produced {len(strider_result['message']['results'])} results in {end-start}.")
prov = get_provenance(strider_result)
display(prov)
print_queried_sources(strider_result)
for logmessage in strider_result['logs']:
        if logmessage['level'] == 'ERROR':
            print(logmessage['message'])
for logmessage in strider_result['logs'][:2]:
    printjson(logmessage)
view = GammaViewer(props={"data":strider_result})
display(view)
pred = get_predicate(strider_result)
display(pred)
node =which_nodes(strider_result, 'biolink:overlaps')
display(node)<jupyter_output><empty_output><jupyter_text>Aragorn<jupyter_code>start = dt.now()
aragorn_result = aragorn(query)
end = dt.now()
if 'results' in aragorn_result['message']:
    print(f"ARAGORN produced {len(aragorn_result['message']['results'])} results in {end-start}.")
else:
    print('Error, no result field')
prov = get_provenance(strider_result)
display(prov)
for logmessage in strider_result['logs']:
        if logmessage['level'] == 'ERROR':
            print(logmessage['message'])
for logmessage in aragorn_result['logs']:
    printjson(logmessage)
view = GammaViewer(props={"data":aragorn_result})
display(view)
pred = get_predicate(aragorn_result)
display(pred)
node =which_nodes(aragorn_result, 'biolink:overlaps')
display(node)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13147583804962995, 'fraction_numerical': 0.0008707009142359599, 'mean_word_length': 6.66, 'pattern_counts': {'":': 2, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '338905', 'license': 'MIT', 'n_tokens_mistral': 779, 'n_tokens_neox': 759, 'n_words': 187, 'path': 'user_queries/notebooks/Hangover_2.ipynb', 'repo_name': 'ranking-agent/robogallery', 'size': '2297'}