From f871294a6fddd2064b8fa2ac0a15870c97f7b68d Mon Sep 17 00:00:00 2001 From: ngupta10 Date: Mon, 6 May 2024 15:21:29 +0530 Subject: [PATCH] final fixes --- ..._llm_bert_ner_or_fixed_entities_set_ner.py | 6 -- .../relationship_extraction_llm.py | 1 - .../ner_llm_transformer.py | 2 +- .../llm/predicate_checker/image+predicate.pdf | Bin 0 -> 84194 bytes .../data/llm/{predicate_checker => }/test.pdf | Bin ...test_fixed_entities_predicates_workflow.py | 54 +++++++++--------- ...test_fixed_entities_predicates_workflow.py | 6 +- 7 files changed, 31 insertions(+), 38 deletions(-) create mode 100644 tests/data/llm/predicate_checker/image+predicate.pdf rename tests/data/llm/{predicate_checker => }/test.pdf (100%) diff --git a/querent/core/transformers/gpt_llm_bert_ner_or_fixed_entities_set_ner.py b/querent/core/transformers/gpt_llm_bert_ner_or_fixed_entities_set_ner.py index 48a768a4..8be671cb 100644 --- a/querent/core/transformers/gpt_llm_bert_ner_or_fixed_entities_set_ner.py +++ b/querent/core/transformers/gpt_llm_bert_ner_or_fixed_entities_set_ner.py @@ -335,7 +335,6 @@ async def process_tokens(self, data: IngestedTokens): else: filtered_triples, file = result modified_data = GPTLLM.remove_items_from_tuples(filtered_triples) - print("Data in GPT------------------------", modified_data[:1]) for entity1, context_json, entity2 in modified_data: context_data = json.loads(context_json) context = context_data.get("context", "") @@ -352,15 +351,12 @@ async def process_tokens(self, data: IngestedTokens): relationships.append(output_tuple) if len(relationships) > 0: if self.fixed_relationships and self.sample_relationships: - print("Both are settttttttttttttttttttt-----") embedding_triples = self.create_emb.generate_embeddings(relationships, relationship_finder=True, generate_embeddings_with_fixed_relationship = True) elif self.sample_relationships: - print("Only Sample Relationships are settttttttttttttttttttttttt-----") embedding_triples = self.create_emb.generate_embeddings(relationships, relationship_finder=True) else: embedding_triples = self.create_emb.generate_embeddings(relationships) if self.sample_relationships: - print("Going to compute scores------------------------------") embedding_triples = self.predicate_context_extractor.update_embedding_triples_with_similarity(self.predicate_json_emb, embedding_triples) for triple in embedding_triples: if not self.termination_event.is_set(): @@ -377,9 +373,7 @@ async def process_tokens(self, data: IngestedTokens): else: return except Exception as e: - print("Exception in GPT-----------------------", e) self.logger.error(f"Invalid {self.__class__.__name__} configuration. Unable to extract predicates using GPT. {e}") - raise Exception(f"An error occurred while extracting predicates using GPT: {e}") async def process_messages(self, data: IngestedMessages): raise NotImplementedError \ No newline at end of file diff --git a/querent/core/transformers/relationship_extraction_llm.py b/querent/core/transformers/relationship_extraction_llm.py index 6f2ab4fa..6bb61da0 100644 --- a/querent/core/transformers/relationship_extraction_llm.py +++ b/querent/core/transformers/relationship_extraction_llm.py @@ -197,7 +197,6 @@ def extract_relationships(self, triples, fixed_entities = False): entity2=predicate.get('entity2_nn_chunk', ''), entity1_label=predicate.get('entity1_label', ''), entity2_label=predicate.get('entity2_label', '')) - print("This is the prompt -----------------",query ) answer_relation = self.qa_system.ask_question(prompt=query, llm=self.qa_system.llm, grammar=self.grammar) try: choices_text = answer_relation['choices'][0]['text'] diff --git a/querent/kg/ner_helperfunctions/ner_llm_transformer.py b/querent/kg/ner_helperfunctions/ner_llm_transformer.py index ca1afa18..46808d82 100644 --- a/querent/kg/ner_helperfunctions/ner_llm_transformer.py +++ b/querent/kg/ner_helperfunctions/ner_llm_transformer.py @@ -382,7 +382,7 @@ def final_ingested_images_tuples(self, filtered_triples, create_embeddings): info['predicate_type'] = "has image" info['context_embeddings'] = create_embeddings.get_embeddings([info['context']])[0] updated_json = json.dumps(info) - updated_tuple = (entity, updated_json, second_entity) + updated_tuple = (info['entity1_nn_chunk'], updated_json, info['entity2_nn_chunk']) return updated_tuple def remove_duplicates(self, data): diff --git a/tests/data/llm/predicate_checker/image+predicate.pdf b/tests/data/llm/predicate_checker/image+predicate.pdf new file mode 100644 index 0000000000000000000000000000000000000000..d406f837ce32b2ee5ea702d3895e0885ccd8647c GIT binary patch literal 84194 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