forked from kristjan/cjvt-valency
working on api changes
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ca942344d7
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@ -26,6 +26,7 @@ from email.mime.text import MIMEText
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from copy import deepcopy as DC
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from pathlib import Path
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from pymongo import MongoClient
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import pymongo
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import argparse
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# some db collections
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@ -55,7 +56,8 @@ CORS(app)
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@app.route("/api/dev")
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def api_dev():
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cur = valdb.kres.find({"sid": "F0015940.37.2"})
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print("DEV")
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cur = valdb.kres.find({"headwords": "nagovarjati"})
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frames = []
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for ent in cur:
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frames += frames_from_db_entry(ent)
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@ -236,20 +238,18 @@ def api_token():
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def prepare_frames(ret_frames):
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# append sentences
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for frame in ret_frames:
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frame.sentences = []
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unique_sids = {".".join(x.split(".")[:-1]): x for x in frame.tids}
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log.debug(str(unique_sids))
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frame.sentences = []
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# frame.sentences = []
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frame.aggr_sent = {}
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# sid, tid==hw
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for sid, tid in unique_sids.items():
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hwl = vallex.get_token(tid)["lemma"]
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# hwl = vallex.get_token(tid)["lemma"]
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hwl = "derp"
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tmp_idx = len(frame.sentences)
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if hwl not in frame.aggr_sent:
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frame.aggr_sent[hwl] = []
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frame.aggr_sent[hwl].append(tmp_idx)
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frame.sentences.append(
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vallex.get_tokenized_sentence(tid)
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)
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# return (n-frames, rendered template)
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# json frames
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json_ret = {"frames": []}
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@ -259,7 +259,7 @@ def prepare_frames(ret_frames):
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# input: hw, reduct_function
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@app.route("/api/hw-frames")
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@app.route("/api/frames")
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def api_get_frames():
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hw = request.args.get("hw")
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if hw is None:
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@ -267,8 +267,21 @@ def api_get_frames():
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rf_name = request.args.get("rf", "reduce_0") # 2nd is default
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RF = reduce_functions[rf_name]["f"]
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entry = vallex.entries[hw] # TODO hw -> [Frame,]
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ret_frames = RF(entry.raw_frames, vallex)
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# entry = vallex.entries[hw] # TODO hw -> [Frame,]
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cur = valdb.kres.find({"headwords": hw})
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frames = []
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for ent in cur:
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# TODO: maybe filter by hw?
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frames += frames_from_db_entry(ent)
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# return json.dumps([x.to_json() for x in frames])
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print("A")
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print(frames[0].to_json())
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ret_frames = RF(frames, None)
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print("B")
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print(ret_frames[0].to_json())
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return prepare_frames(ret_frames)
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@ -408,18 +421,22 @@ def prepare_db():
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for corpus in CORPORA:
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for e in valdb[corpus].find({}):
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if e["srl_links"] is None:
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continue
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e["headwords"] = []
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e["functors"] = []
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else:
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hw_tids = list(set([x["from"] for x in e["srl_links"]]))
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hw_tokens = [helper_tid_to_token(tid, e["tokens"]) for tid in hw_tids]
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headwords = [(t["lemma"] if t["msd"][0] == "G" else t["lemma"] + "_") for t in hw_tokens]
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e["headwords"] = headwords
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functors = list(set([x["afun"] for x in e["srl_links"]]))
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e["headwords"] = headwords
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e["functors"] = functors
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valdb[corpus].save(e)
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valdb[corpus].ensure_index([("headwords", pymongo.ASCENDING)])
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valdb[corpus].ensure_index([("functors", pymongo.ASCENDING)])
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# create app_index (used in frontend, left side word index)
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for corpus in CORPORA:
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res_hws = {}
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@ -6,6 +6,8 @@ def frames_from_db_entry(dbent):
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def _full_tid(tid):
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return ".".join([dbent["sid"], str(tid)])
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token_dict = {str(x["tid"]): x for x in dbent["tokens"]}
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frames = []
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if "srl_links" not in dbent:
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return []
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@ -18,19 +20,20 @@ def frames_from_db_entry(dbent):
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srldict[key] += [srl]
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for hwtid, srlarr in srldict.items():
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frames += [Frame(
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hw_lemma=_full_tid(hwtid),
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tids=[_full_tid(x["to"]) for x in srlarr],
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hw_lemma=token_dict[hwtid]["text"],
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tids=[_full_tid(hwtid)],
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slots=[
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Slot(
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functor=srl["afun"],
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tids=[_full_tid(srl["to"])]
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) for srl in srlarr
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]
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],
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sentences=[dbent["tokens"]],
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)]
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return frames
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class Frame():
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def __init__(self, tids, deep_links=None, slots=None, hw_lemma=None):
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def __init__(self, tids, deep_links=None, slots=None, hw_lemma=None, sentences=None):
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self.hw = hw_lemma
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self.tids = tids # list of tokens with the same hw_lemma
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# Each tid = "S123.t123";
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@ -41,7 +44,7 @@ class Frame():
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else:
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self.slots = slots
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self.sense_info = {}
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self.sentences = None # Used for passing to view in app.py, get_frames
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self.sentences = sentences
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self.aggr_sent = None # Dictionary { hw: self.sentences idx }
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def to_json(self):
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@ -56,11 +56,13 @@ def reduce_1(frames, vallex=None):
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break
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else:
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# Python for else -> fires if loop has ended.
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# init new frame set [set_of_functors, list_of_one_frame]
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frame_sets.append([functors, [frame]])
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ret_frames = []
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for fs in frame_sets:
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tids = []
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sentences = []
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slots = {}
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# All possible slots in this frame.
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for functor in fs[0]:
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@ -68,12 +70,13 @@ def reduce_1(frames, vallex=None):
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# Reduce slots from all frames. (Merge ACT from all frames, ...)
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for frame in fs[1]:
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tids += frame.tids
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sentences += frame.sentences
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for sl in frame.slots:
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slots[sl.functor].tids += sl.tids
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slots_list = []
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for k, e in slots.items():
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slots_list.append(e)
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rf = Frame(tids=tids, slots=slots_list)
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rf = Frame(tids=tids, slots=slots_list, sentences=sentences)
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rf.sort_slots()
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ret_frames.append(rf)
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return sorted_by_len_tids(ret_frames)
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