From 7781a6e8b98684a06231e19aed8987e3e64e81cb Mon Sep 17 00:00:00 2001 From: Manxin Xu Date: Mon, 25 Mar 2024 15:08:32 +0800 Subject: [PATCH 01/12] enable table and table summary for rag pdf Signed-off-by: Manxin Xu --- .../unitTest/run_unit_test_neuralchat.sh | 2 + .../neural_chat/assets/docs/LLAMA2_page6.pdf | Bin 0 -> 373280 bytes .../neural_chat/chatbot.py | 32 +++++-- .../plugins/retrieval/parser/context_utils.py | 80 +++++++++++++++-- .../plugins/retrieval/parser/parser.py | 12 ++- .../neural_chat/prompts/prompt.py | 11 +++ .../ci/plugins/retrieval/test_parameters.py | 81 ++++++++++++++++++ .../neural_chat/tests/requirements.txt | 2 +- 8 files changed, 204 insertions(+), 16 deletions(-) create mode 100644 intel_extension_for_transformers/neural_chat/assets/docs/LLAMA2_page6.pdf diff --git a/.github/workflows/script/unitTest/run_unit_test_neuralchat.sh b/.github/workflows/script/unitTest/run_unit_test_neuralchat.sh index 07e601a5e69..ebaead97cfd 100644 --- a/.github/workflows/script/unitTest/run_unit_test_neuralchat.sh +++ b/.github/workflows/script/unitTest/run_unit_test_neuralchat.sh @@ -87,6 +87,8 @@ function main() { apt-get install -y libgl1-mesa-glx apt-get install -y libgl1-mesa-dev apt-get install libsm6 libxext6 -y + brew install tesseract + brew install poppler wget http://nz2.archive.ubuntu.com/ubuntu/pool/main/o/openssl/libssl1.1_1.1.1f-1ubuntu2.19_amd64.deb dpkg -i libssl1.1_1.1.1f-1ubuntu2.19_amd64.deb python -m pip install --upgrade --force-reinstall torch==2.2.0 diff --git a/intel_extension_for_transformers/neural_chat/assets/docs/LLAMA2_page6.pdf b/intel_extension_for_transformers/neural_chat/assets/docs/LLAMA2_page6.pdf new file mode 100644 index 0000000000000000000000000000000000000000..e741ee1993ebfb2e49521aa643a45933d67feabb GIT binary patch literal 373280 zcmb5U1z1$u_s5N*0@5Mf-7s_`-3`*s(49jo-JyUq0wUer-AZ?dl;qIOJKXgCulId_ zFV8c~nRE86wf1*?_S$>S*%XSR;tT*r4n&Hz_2F^Emn`fo9K_7Tc1D(ne0)se7S_%{ 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z{@Lg2MLV(!mz%RT?%A=_JD^UFK>Di(Y!%g`ho_9Gv$Neh|Cqx)%y08N*M5M$uJgBx tUBA3%^1g939=L7q?KK`vUO*$iAC8t`TmN386)&|}?rq&Vzp%@_{|}FqIjH~u literal 0 HcmV?d00001 diff --git a/intel_extension_for_transformers/neural_chat/chatbot.py b/intel_extension_for_transformers/neural_chat/chatbot.py index f523f092a16..2ef2b70bae4 100644 --- a/intel_extension_for_transformers/neural_chat/chatbot.py +++ b/intel_extension_for_transformers/neural_chat/chatbot.py @@ -178,7 +178,8 @@ def build_chatbot(config: PipelineConfig=None): return from .models.base_model import register_model_adapter register_model_adapter(adapter) - # register plugin instance in model adaptor + # register plugin instance in model adapter + use_retrieval_plugin = False if config.plugins: for plugin_name, plugin_value in config.plugins.items(): enable_plugin = plugin_value.get('enable', False) @@ -243,6 +244,10 @@ def build_chatbot(config: PipelineConfig=None): elif plugin_name == "retrieval": from .pipeline.plugins.retrieval.retrieval_agent import Agent_QA plugins[plugin_name]['class'] = Agent_QA + use_retrieval_plugin = True + retrieval_plugin_value = plugin_value + retrieval_plugin_value['args']['table_summary_model_name_or_path'] = config.model_name_or_path + continue elif plugin_name == "cache": from .pipeline.plugins.caching.cache import ChatCache plugins[plugin_name]['class'] = ChatCache @@ -267,15 +272,12 @@ def build_chatbot(config: PipelineConfig=None): try: plugins[plugin_name]["instance"] = plugins[plugin_name]['class'](**plugin_value['args']) except Exception as e: - if "[Rereieval ERROR] Document format not supported" in str(e): - set_latest_error(ErrorCodes.ERROR_RETRIEVAL_DOC_FORMAT_NOT_SUPPORTED) - logger.error("build_chatbot: retrieval plugin init failed") - elif "[SafetyChecker ERROR] Sensitive check file not found" in str(e): + if "[SafetyChecker ERROR] Sensitive check file not found" in str(e): set_latest_error(ErrorCodes.ERROR_SENSITIVE_CHECK_FILE_NOT_FOUND) - logger.error("build_chatbot: safety checker plugin init failed") + logging.error("build_chatbot: safety checker plugin init failed") else: set_latest_error(ErrorCodes.ERROR_GENERIC) - logger.error("build_chatbot: plugin init failed") + logging.error("build_chatbot: plugin init failed") return adapter.register_plugin_instance(plugin_name, plugins[plugin_name]["instance"]) @@ -306,6 +308,22 @@ def build_chatbot(config: PipelineConfig=None): if config.hf_endpoint_url: return adapter adapter.load_model(parameters) + + if use_retrieval_plugin: + print(f"create retrieval plugin instance...") + print(f"plugin parameters: ", retrieval_plugin_value['args']) + try: + plugins["retrieval"]["instance"] = plugins["retrieval"]['class'](**retrieval_plugin_value['args']) + except Exception as e: + if "[Rereieval ERROR] Document format not supported" in str(e): + set_latest_error(ErrorCodes.ERROR_RETRIEVAL_DOC_FORMAT_NOT_SUPPORTED) + logging.error("build_chatbot: retrieval plugin init failed") + else: + set_latest_error(ErrorCodes.ERROR_GENERIC) + logging.error("build_chatbot: plugin init failed") + return + adapter.register_plugin_instance(plugin_name, plugins[plugin_name]["instance"]) + if get_latest_error(): return else: diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py index bac5b0d2396..5468739200d 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py @@ -48,8 +48,13 @@ def uni_pro(text): return filtered_text -def read_pdf(pdf_path): +def read_pdf(pdf_path, table_summary_mode, table_summary_model_name_or_path): """Read the pdf file.""" + from unstructured.partition.pdf import partition_pdf + from unstructured.documents.elements import FigureCaption + from intel_extension_for_transformers.neural_chat.models.model_utils import predict + from intel_extension_for_transformers.neural_chat.prompts.prompt import TABLESUMMARY_PROMPT + doc = fitz.open(pdf_path) reader = easyocr.Reader(['en']) result ='' @@ -77,7 +82,71 @@ def read_pdf(pdf_path): else: pageimg=pageimg+'.' result=result+pageimg - return result + + tables_result = [] + def get_relation(table_coords, caption_coords, table_page_number, caption_page_number, threshold=100): + same_page = table_page_number == caption_page_number + x_overlap = (min(table_coords[2][0], caption_coords[2][0]) - max(table_coords[0][0], caption_coords[0][0])) > 0 + if table_coords[0][1] - caption_coords[1][1] >= 0: + y_distance = table_coords[0][1] - caption_coords[1][1] + elif caption_coords[0][1] - table_coords[1][1] >= 0: + y_distance = caption_coords[0][1] - table_coords[1][1] + else: + y_distance = 0 + y_close = y_distance < threshold + return same_page and x_overlap and y_close, y_distance + + raw_pdf_elements = partition_pdf( + filename=pdf_path, + infer_table_structure=True, + ) + + tables = [el for el in raw_pdf_elements if el.category == "Table"] + for table in tables: + table_coords = table.metadata.coordinates.points + content = table.metadata.text_as_html + table_page_number = table.metadata.page_number + min_distance = float('inf') + table_summary = None + if table_summary_mode == 'title': + for element in raw_pdf_elements: + if isinstance(element, FigureCaption) or element.text.startswith('Tab'): + caption_page_number = element.metadata.page_number + caption_coords = element.metadata.coordinates.points + related, y_distance = get_relation(table_coords, caption_coords, table_page_number, caption_page_number) + if related: + if y_distance < min_distance: + min_distance = y_distance + table_summary = element.text + if table_summary is None: + parent_id = table.metadata.parent_id + for element in raw_pdf_elements: + if element.id == parent_id: + table_summary = element.text + break + elif table_summary_mode == 'llm': + prompt = TABLESUMMARY_PROMPT.format(table_content=content) + params = {} + params["model_name"] = table_summary_model_name_or_path + params["prompt"] = prompt + params["temperature"] = 0.8 + params["top_p"] = 0.9 + params["top_k"] = 40 + params["max_new_tokens"] = 1000 + params["num_beams"] = 2 + params["num_return_sequences"] = 2 + params["use_cache"] = True + table_summary = predict(**params) + table_summary = table_summary[table_summary.find('### Generated Summary:\n'):] + table_summary = re.sub('### Generated Summary:\n', '', table_summary) + elif table_summary_mode == 'none': + table_summary = None + if table_summary is None: + text = f'[Table: {content}]' + else: + text = f'|Table: [Summary: {table_summary}], [Content: {content}]|' + tables_result.append([text, pdf_path]) + return result, tables_result def read_html(html_path): @@ -214,10 +283,11 @@ def load_structured_data(input, process, max_length, min_length): content = load_csv(input) return content -def load_unstructured_data(input): +def load_unstructured_data(input, table_summary_mode, table_summary_model_name_or_path): """Load unstructured context.""" + tables = None if input.endswith("pdf"): - text = read_pdf(input) + text, tables = read_pdf(input, table_summary_mode, table_summary_model_name_or_path) elif input.endswith("docx"): text = read_docx(input) elif input.endswith("html"): @@ -231,7 +301,7 @@ def load_unstructured_data(input): text = text.replace('\n\n', ' ') text = uni_pro(text) text = re.sub(r'\s+', ' ', text) - return text + return text, tables def get_chuck_data(content, max_length, min_length, input): """Process the context to make it maintain a suitable length for the generation.""" diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py index 3337470f430..72529a5099a 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py @@ -49,7 +49,9 @@ def load(self, input, **kwargs): self.min_chuck_size = kwargs['min_chuck_size'] if 'process' in kwargs: self.process = kwargs['process'] - + self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] + self.table_summary_mode = kwargs['table_summary_mode'] if 'table_summary_mode' in kwargs else 'none' + if isinstance(input, str): if os.path.isfile(input): data_collection = self.parse_document(input) @@ -74,11 +76,13 @@ def parse_document(self, input): """ if input.endswith("pdf") or input.endswith("docx") or input.endswith("html") \ or input.endswith("txt") or input.endswith("md"): - content = load_unstructured_data(input) + content, tables = load_unstructured_data(input, self.table_summary_mode, self.table_summary_model_name_or_path) if self.process: chuck = get_chuck_data(content, self.max_chuck_size, self.min_chuck_size, input) else: chuck = [[content.strip(),input]] + if tables is not None: + chuck = chuck + tables elif input.endswith("jsonl") or input.endswith("xlsx") or input.endswith("csv") or \ input.endswith("json"): chuck = load_structured_data(input, self.process, \ @@ -118,11 +122,13 @@ def batch_parse_document(self, input): for filename in filenames: if filename.endswith("pdf") or filename.endswith("docx") or filename.endswith("html") \ or filename.endswith("txt") or filename.endswith("md"): - content = load_unstructured_data(os.path.join(dirpath, filename)) + content, tables = load_unstructured_data(os.path.join(dirpath, filename), self.table_summary_mode, self.table_summary_model_name_or_path) if self.process: chuck = get_chuck_data(content, self.max_chuck_size, self.min_chuck_size, input) else: chuck = [[content.strip(),input]] + if tables is not None: + chuck = chuck + tables paragraphs += chuck elif filename.endswith("jsonl") or filename.endswith("xlsx") or filename.endswith("csv") or \ filename.endswith("json"): diff --git a/intel_extension_for_transformers/neural_chat/prompts/prompt.py b/intel_extension_for_transformers/neural_chat/prompts/prompt.py index 6a1da02af39..a0a9c095845 100644 --- a/intel_extension_for_transformers/neural_chat/prompts/prompt.py +++ b/intel_extension_for_transformers/neural_chat/prompts/prompt.py @@ -321,3 +321,14 @@ def generate_sqlcoder_prompt(qurey, metadata_file): qurey=qurey, table_metadata_string=table_metadata_string ) return prompt + +TABLESUMMARY_PROMPT = """ +Task: Your task is to give a concise summary of the table. \ +The summary should cover the overall table structure and all detailed information of the table. \ +The table will be given in html format. Summarize the table below. +--- +### Table: +{table_content} +--- +### Generated Summary: +""" \ No newline at end of file diff --git a/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py b/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py index 3de0f5a6567..6e013289aa1 100644 --- a/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py +++ b/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py @@ -714,5 +714,86 @@ def test_embedding_precision_fp32(self): plugins.retrieval.args = {} plugins.retrieval.enable = False +class TestTableSummaryTitleMode(unittest.TestCase): + def setUp(self): + if os.path.exists("./table_summary_title_mode"): + shutil.rmtree("./table_summary_title_mode", ignore_errors=True) + return super().setUp() + + def tearDown(self) -> None: + if os.path.exists("./table_summary_title_mode"): + shutil.rmtree("./table_summary_title_mode", ignore_errors=True) + return super().tearDown() + + def test_table_summary_title_mode(self): + plugins.retrieval.args = {} + plugins.retrieval.enable = True + plugins.retrieval.args["input_path"] = "../assets/docs/LLAMA2_short.pdf" + plugins.retrieval.args["persist_directory"] = "./table_summary_title_mode" + plugins.retrieval.args["retrieval_type"] = 'default' + plugins.retrieval.args["table_summary_mode"] = 'title' + config = PipelineConfig(model_name_or_path="facebook/opt-125m", + plugins=plugins) + chatbot = build_chatbot(config) + response = chatbot.predict("What is the number of training tokens for LLaMA2?") + print(response) + self.assertIsNotNone(response) + plugins.retrieval.args = {} + plugins.retrieval.enable = False + +class TestTableSummaryLLMMode(unittest.TestCase): + def setUp(self): + if os.path.exists("./table_summary_llm_mode"): + shutil.rmtree("./table_summary_llm_mode", ignore_errors=True) + return super().setUp() + + def tearDown(self) -> None: + if os.path.exists("./table_summary_llm_mode"): + shutil.rmtree("./table_summary_llm_mode", ignore_errors=True) + return super().tearDown() + + def test_table_summary_llm_mode(self): + plugins.retrieval.args = {} + plugins.retrieval.enable = True + plugins.retrieval.args["input_path"] = "../assets/docs/LLAMA2_short.pdf" + plugins.retrieval.args["persist_directory"] = "./table_summary_llm_mode" + plugins.retrieval.args["retrieval_type"] = 'default' + plugins.retrieval.args["table_summary_mode"] = 'llm' + config = PipelineConfig(model_name_or_path="facebook/opt-125m", + plugins=plugins) + chatbot = build_chatbot(config) + response = chatbot.predict("What is the number of training tokens for LLaMA2?") + print(response) + self.assertIsNotNone(response) + plugins.retrieval.args = {} + plugins.retrieval.enable = False + +class TestTableSummaryNoneMode(unittest.TestCase): + def setUp(self): + if os.path.exists("./table_summary_none_mode"): + shutil.rmtree("./table_summary_none_mode", ignore_errors=True) + return super().setUp() + + def tearDown(self) -> None: + if os.path.exists("./table_summary_none_mode"): + shutil.rmtree("./table_summary_none_mode", ignore_errors=True) + return super().tearDown() + + def test_table_summary_none_mode(self): + plugins.retrieval.args = {} + plugins.retrieval.enable = True + plugins.retrieval.args["input_path"] = "../assets/docs/LLAMA2_short.pdf" + plugins.retrieval.args["persist_directory"] = "./table_summary_none_mode" + plugins.retrieval.args["retrieval_type"] = 'default' + plugins.retrieval.args["table_summary_mode"] = 'none' + config = PipelineConfig(model_name_or_path="facebook/opt-125m", + plugins=plugins) + chatbot = build_chatbot(config) + response = chatbot.predict("What is the number of training tokens for LLaMA2?") + print(response) + self.assertIsNotNone(response) + plugins.retrieval.args = {} + plugins.retrieval.enable = False + if __name__ == '__main__': unittest.main() diff --git a/intel_extension_for_transformers/neural_chat/tests/requirements.txt b/intel_extension_for_transformers/neural_chat/tests/requirements.txt index 8d79ecdd5d5..c1e8414351f 100644 --- a/intel_extension_for_transformers/neural_chat/tests/requirements.txt +++ b/intel_extension_for_transformers/neural_chat/tests/requirements.txt @@ -84,7 +84,7 @@ torchvision==0.17.0 tqdm transformers==4.36.2 transformers_stream_generator -unstructured +unstructured[all-docs] urllib3 uvicorn vector_quantize_pytorch From 222ee8170a17f7b36daea3c560e9a165dba569f9 Mon Sep 17 00:00:00 2001 From: Manxin Xu Date: Mon, 25 Mar 2024 16:09:14 +0800 Subject: [PATCH 02/12] fix code format Signed-off-by: Manxin Xu --- .../neural_chat/chatbot.py | 20 +++++++++---------- .../plugins/retrieval/parser/context_utils.py | 3 ++- .../plugins/retrieval/parser/parser.py | 7 +++++-- 3 files changed, 17 insertions(+), 13 deletions(-) diff --git a/intel_extension_for_transformers/neural_chat/chatbot.py b/intel_extension_for_transformers/neural_chat/chatbot.py index 2ef2b70bae4..6ed798b96a7 100644 --- a/intel_extension_for_transformers/neural_chat/chatbot.py +++ b/intel_extension_for_transformers/neural_chat/chatbot.py @@ -312,16 +312,16 @@ def build_chatbot(config: PipelineConfig=None): if use_retrieval_plugin: print(f"create retrieval plugin instance...") print(f"plugin parameters: ", retrieval_plugin_value['args']) - try: - plugins["retrieval"]["instance"] = plugins["retrieval"]['class'](**retrieval_plugin_value['args']) - except Exception as e: - if "[Rereieval ERROR] Document format not supported" in str(e): - set_latest_error(ErrorCodes.ERROR_RETRIEVAL_DOC_FORMAT_NOT_SUPPORTED) - logging.error("build_chatbot: retrieval plugin init failed") - else: - set_latest_error(ErrorCodes.ERROR_GENERIC) - logging.error("build_chatbot: plugin init failed") - return + # try: + plugins["retrieval"]["instance"] = plugins["retrieval"]['class'](**retrieval_plugin_value['args']) + # except Exception as e: + # if "[Rereieval ERROR] Document format not supported" in str(e): + # set_latest_error(ErrorCodes.ERROR_RETRIEVAL_DOC_FORMAT_NOT_SUPPORTED) + # logging.error("build_chatbot: retrieval plugin init failed") + # else: + # set_latest_error(ErrorCodes.ERROR_GENERIC) + # logging.error("build_chatbot: plugin init failed") + # return adapter.register_plugin_instance(plugin_name, plugins[plugin_name]["instance"]) if get_latest_error(): diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py index 5468739200d..7e4d0401724 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py @@ -113,7 +113,8 @@ def get_relation(table_coords, caption_coords, table_page_number, caption_page_n if isinstance(element, FigureCaption) or element.text.startswith('Tab'): caption_page_number = element.metadata.page_number caption_coords = element.metadata.coordinates.points - related, y_distance = get_relation(table_coords, caption_coords, table_page_number, caption_page_number) + related, y_distance = get_relation(table_coords, caption_coords, \ + table_page_number, caption_page_number) if related: if y_distance < min_distance: min_distance = y_distance diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py index 72529a5099a..55bff291d41 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py @@ -76,7 +76,8 @@ def parse_document(self, input): """ if input.endswith("pdf") or input.endswith("docx") or input.endswith("html") \ or input.endswith("txt") or input.endswith("md"): - content, tables = load_unstructured_data(input, self.table_summary_mode, self.table_summary_model_name_or_path) + content, tables = load_unstructured_data(input, self.table_summary_mode, \ + self.table_summary_model_name_or_path) if self.process: chuck = get_chuck_data(content, self.max_chuck_size, self.min_chuck_size, input) else: @@ -122,7 +123,9 @@ def batch_parse_document(self, input): for filename in filenames: if filename.endswith("pdf") or filename.endswith("docx") or filename.endswith("html") \ or filename.endswith("txt") or filename.endswith("md"): - content, tables = load_unstructured_data(os.path.join(dirpath, filename), self.table_summary_mode, self.table_summary_model_name_or_path) + content, tables = load_unstructured_data(os.path.join(dirpath, filename), \ + self.table_summary_mode, \ + self.table_summary_model_name_or_path) if self.process: chuck = get_chuck_data(content, self.max_chuck_size, self.min_chuck_size, input) else: From dc0faf8e51379d065de073db0d504efd9404d6ca Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 25 Mar 2024 07:19:47 +0000 Subject: [PATCH 03/12] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Signed-off-by: Manxin Xu --- intel_extension_for_transformers/neural_chat/chatbot.py | 2 +- .../pipeline/plugins/retrieval/parser/context_utils.py | 2 +- .../neural_chat/pipeline/plugins/retrieval/parser/parser.py | 2 +- intel_extension_for_transformers/neural_chat/prompts/prompt.py | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/intel_extension_for_transformers/neural_chat/chatbot.py b/intel_extension_for_transformers/neural_chat/chatbot.py index 6ed798b96a7..2fdb7302a1e 100644 --- a/intel_extension_for_transformers/neural_chat/chatbot.py +++ b/intel_extension_for_transformers/neural_chat/chatbot.py @@ -323,7 +323,7 @@ def build_chatbot(config: PipelineConfig=None): # logging.error("build_chatbot: plugin init failed") # return adapter.register_plugin_instance(plugin_name, plugins[plugin_name]["instance"]) - + if get_latest_error(): return else: diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py index 7e4d0401724..519d255ceeb 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py @@ -95,7 +95,7 @@ def get_relation(table_coords, caption_coords, table_page_number, caption_page_n y_distance = 0 y_close = y_distance < threshold return same_page and x_overlap and y_close, y_distance - + raw_pdf_elements = partition_pdf( filename=pdf_path, infer_table_structure=True, diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py index 55bff291d41..40648a45cc3 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py @@ -51,7 +51,7 @@ def load(self, input, **kwargs): self.process = kwargs['process'] self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] self.table_summary_mode = kwargs['table_summary_mode'] if 'table_summary_mode' in kwargs else 'none' - + if isinstance(input, str): if os.path.isfile(input): data_collection = self.parse_document(input) diff --git a/intel_extension_for_transformers/neural_chat/prompts/prompt.py b/intel_extension_for_transformers/neural_chat/prompts/prompt.py index a0a9c095845..f1f2b6fb0f1 100644 --- a/intel_extension_for_transformers/neural_chat/prompts/prompt.py +++ b/intel_extension_for_transformers/neural_chat/prompts/prompt.py @@ -331,4 +331,4 @@ def generate_sqlcoder_prompt(qurey, metadata_file): {table_content} --- ### Generated Summary: -""" \ No newline at end of file +""" From d5b93dd8743015829c9519dd5034c20cc93c7f41 Mon Sep 17 00:00:00 2001 From: Manxin Xu Date: Tue, 26 Mar 2024 10:10:42 +0800 Subject: [PATCH 04/12] fix environment issue Signed-off-by: Manxin Xu --- .../workflows/script/unitTest/run_unit_test_neuralchat.sh | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/script/unitTest/run_unit_test_neuralchat.sh b/.github/workflows/script/unitTest/run_unit_test_neuralchat.sh index ebaead97cfd..c47c0aa147d 100644 --- a/.github/workflows/script/unitTest/run_unit_test_neuralchat.sh +++ b/.github/workflows/script/unitTest/run_unit_test_neuralchat.sh @@ -87,8 +87,9 @@ function main() { apt-get install -y libgl1-mesa-glx apt-get install -y libgl1-mesa-dev apt-get install libsm6 libxext6 -y - brew install tesseract - brew install poppler + apt-get install tesseract-ocr -y + apt-get install libtesseract-dev -y + apt-get install poppler-utils -y wget http://nz2.archive.ubuntu.com/ubuntu/pool/main/o/openssl/libssl1.1_1.1.1f-1ubuntu2.19_amd64.deb dpkg -i libssl1.1_1.1.1f-1ubuntu2.19_amd64.deb python -m pip install --upgrade --force-reinstall torch==2.2.0 From d8687ef4a914da97d48342cc2a186189e3c521e7 Mon Sep 17 00:00:00 2001 From: Manxin Xu Date: Tue, 26 Mar 2024 11:24:42 +0800 Subject: [PATCH 05/12] fix key error Signed-off-by: Manxin Xu --- .../neural_chat/chatbot.py | 20 +++++++++---------- .../plugins/retrieval/parser/parser.py | 3 ++- 2 files changed, 12 insertions(+), 11 deletions(-) diff --git a/intel_extension_for_transformers/neural_chat/chatbot.py b/intel_extension_for_transformers/neural_chat/chatbot.py index 2fdb7302a1e..a7f0c3cc5d7 100644 --- a/intel_extension_for_transformers/neural_chat/chatbot.py +++ b/intel_extension_for_transformers/neural_chat/chatbot.py @@ -312,16 +312,16 @@ def build_chatbot(config: PipelineConfig=None): if use_retrieval_plugin: print(f"create retrieval plugin instance...") print(f"plugin parameters: ", retrieval_plugin_value['args']) - # try: - plugins["retrieval"]["instance"] = plugins["retrieval"]['class'](**retrieval_plugin_value['args']) - # except Exception as e: - # if "[Rereieval ERROR] Document format not supported" in str(e): - # set_latest_error(ErrorCodes.ERROR_RETRIEVAL_DOC_FORMAT_NOT_SUPPORTED) - # logging.error("build_chatbot: retrieval plugin init failed") - # else: - # set_latest_error(ErrorCodes.ERROR_GENERIC) - # logging.error("build_chatbot: plugin init failed") - # return + try: + plugins["retrieval"]["instance"] = plugins["retrieval"]['class'](**retrieval_plugin_value['args']) + except Exception as e: + if "[Rereieval ERROR] Document format not supported" in str(e): + set_latest_error(ErrorCodes.ERROR_RETRIEVAL_DOC_FORMAT_NOT_SUPPORTED) + logging.error("build_chatbot: retrieval plugin init failed") + else: + set_latest_error(ErrorCodes.ERROR_GENERIC) + logging.error("build_chatbot: plugin init failed") + return adapter.register_plugin_instance(plugin_name, plugins[plugin_name]["instance"]) if get_latest_error(): diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py index 40648a45cc3..ecdae5a2309 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py @@ -49,7 +49,8 @@ def load(self, input, **kwargs): self.min_chuck_size = kwargs['min_chuck_size'] if 'process' in kwargs: self.process = kwargs['process'] - self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] + if 'table_summary_model_name_or_path' in kwargs: + self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] self.table_summary_mode = kwargs['table_summary_mode'] if 'table_summary_mode' in kwargs else 'none' if isinstance(input, str): From 824c48eac6dcd889ba0fef64374544842dff041c Mon Sep 17 00:00:00 2001 From: Manxin Xu Date: Tue, 26 Mar 2024 13:25:15 +0800 Subject: [PATCH 06/12] fix two parameters Signed-off-by: Manxin Xu --- .../pipeline/plugins/retrieval/parser/context_utils.py | 2 +- .../neural_chat/pipeline/plugins/retrieval/parser/parser.py | 5 ++--- .../tests/ci/plugins/retrieval/test_parameters.py | 1 - 3 files changed, 3 insertions(+), 5 deletions(-) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py index 519d255ceeb..4bab85903f8 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py @@ -140,7 +140,7 @@ def get_relation(table_coords, caption_coords, table_page_number, caption_page_n table_summary = predict(**params) table_summary = table_summary[table_summary.find('### Generated Summary:\n'):] table_summary = re.sub('### Generated Summary:\n', '', table_summary) - elif table_summary_mode == 'none': + elif table_summary_mode == None: table_summary = None if table_summary is None: text = f'[Table: {content}]' diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py index ecdae5a2309..7c2750bc4d1 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py @@ -49,9 +49,8 @@ def load(self, input, **kwargs): self.min_chuck_size = kwargs['min_chuck_size'] if 'process' in kwargs: self.process = kwargs['process'] - if 'table_summary_model_name_or_path' in kwargs: - self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] - self.table_summary_mode = kwargs['table_summary_mode'] if 'table_summary_mode' in kwargs else 'none' + self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] if 'table_summary_model_name_or_path' in kwargs else None + self.table_summary_mode = kwargs['table_summary_mode'] if 'table_summary_mode' in kwargs else None if isinstance(input, str): if os.path.isfile(input): diff --git a/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py b/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py index 6e013289aa1..c94441835fa 100644 --- a/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py +++ b/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py @@ -785,7 +785,6 @@ def test_table_summary_none_mode(self): plugins.retrieval.args["input_path"] = "../assets/docs/LLAMA2_short.pdf" plugins.retrieval.args["persist_directory"] = "./table_summary_none_mode" plugins.retrieval.args["retrieval_type"] = 'default' - plugins.retrieval.args["table_summary_mode"] = 'none' config = PipelineConfig(model_name_or_path="facebook/opt-125m", plugins=plugins) chatbot = build_chatbot(config) From 81ca43d1882b60fb64d0969df9efa19c7a9625a4 Mon Sep 17 00:00:00 2001 From: Manxin Xu Date: Tue, 26 Mar 2024 13:47:13 +0800 Subject: [PATCH 07/12] fix line too long Signed-off-by: Manxin Xu --- .../neural_chat/pipeline/plugins/retrieval/parser/parser.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py index 7c2750bc4d1..31ef0c3d3e9 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py @@ -49,7 +49,8 @@ def load(self, input, **kwargs): self.min_chuck_size = kwargs['min_chuck_size'] if 'process' in kwargs: self.process = kwargs['process'] - self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] if 'table_summary_model_name_or_path' in kwargs else None + self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] \ + if 'table_summary_model_name_or_path' in kwargs else None self.table_summary_mode = kwargs['table_summary_mode'] if 'table_summary_mode' in kwargs else None if isinstance(input, str): From e7e5331dee6a5fb940bbf2efa5664d5013157298 Mon Sep 17 00:00:00 2001 From: Manxin Xu Date: Thu, 28 Mar 2024 11:09:11 +0800 Subject: [PATCH 08/12] clear code, update README Signed-off-by: Manxin Xu --- .../pipeline/plugins/retrieval/README.md | 3 +- .../plugins/retrieval/parser/context_utils.py | 146 +++++++++--------- 2 files changed, 78 insertions(+), 71 deletions(-) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md index 87f9e984cc3..a0dc6c945c3 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md @@ -42,7 +42,7 @@ To ensure a smooth experience, we've made sure this plugin is compatible with co | pdf | No format required | # Usage -Before using RAG in NeuralChat, please install the necessary dependencies in [requirements.txt](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/requirements.txt) to avoid the import errors. The most convenient way to use is this plugin is via our `build_chatbot` api as introduced in the [example code](https://github.com/intel/intel-extension-for-transformers/tree/main/intel_extension_for_transformers/neural_chat/examples/plugins/retrieval). The user could refer to it for a simple test. +Before using RAG in NeuralChat, please install the necessary dependencies in [requirements.txt](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/requirements.txt) to avoid the import errors. Additionally, for users who take pdf format file as input, the installation of [tesseract](https://tesseract-ocr.github.io/tessdoc/Installation.html) and [poppler](https://poppler.freedesktop.org/) is also required. The most convenient way to use is this plugin is via our `build_chatbot` api as introduced in the [example code](https://github.com/intel/intel-extension-for-transformers/tree/main/intel_extension_for_transformers/neural_chat/examples/plugins/retrieval). The user could refer to it for a simple test. We support multiple file formats for retrieval, including unstructured file formats such as pdf, docx, html, txt, and markdown, as well as structured file formats like jsonl/json, csv, xlsx. For structured file formats, they must adhere to predefined structures. We also support to upload the knowledge base via a http web link. @@ -92,6 +92,7 @@ Below are the description for the available parameters in `agent_QA`, | enable_rerank | bool | Whether to enable retrieval then rerank pipeline |True, False| | reranker_model | str | The name of the reranker model from the Huggingface or a local path |-| | top_n | int | The return number of the reranker model |-| +| table_summary_mode | str | Utilize the table's title as its summarization or employ a LLM for table summarization, so that achieve better table retrieval performance|"title","llm"| More retriever- and vectorstore-related parameters please check [here](#langchain-extension) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py index 4bab85903f8..a4ceea1cd79 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py @@ -50,11 +50,6 @@ def uni_pro(text): def read_pdf(pdf_path, table_summary_mode, table_summary_model_name_or_path): """Read the pdf file.""" - from unstructured.partition.pdf import partition_pdf - from unstructured.documents.elements import FigureCaption - from intel_extension_for_transformers.neural_chat.models.model_utils import predict - from intel_extension_for_transformers.neural_chat.prompts.prompt import TABLESUMMARY_PROMPT - doc = fitz.open(pdf_path) reader = easyocr.Reader(['en']) result ='' @@ -82,71 +77,7 @@ def read_pdf(pdf_path, table_summary_mode, table_summary_model_name_or_path): else: pageimg=pageimg+'.' result=result+pageimg - - tables_result = [] - def get_relation(table_coords, caption_coords, table_page_number, caption_page_number, threshold=100): - same_page = table_page_number == caption_page_number - x_overlap = (min(table_coords[2][0], caption_coords[2][0]) - max(table_coords[0][0], caption_coords[0][0])) > 0 - if table_coords[0][1] - caption_coords[1][1] >= 0: - y_distance = table_coords[0][1] - caption_coords[1][1] - elif caption_coords[0][1] - table_coords[1][1] >= 0: - y_distance = caption_coords[0][1] - table_coords[1][1] - else: - y_distance = 0 - y_close = y_distance < threshold - return same_page and x_overlap and y_close, y_distance - - raw_pdf_elements = partition_pdf( - filename=pdf_path, - infer_table_structure=True, - ) - - tables = [el for el in raw_pdf_elements if el.category == "Table"] - for table in tables: - table_coords = table.metadata.coordinates.points - content = table.metadata.text_as_html - table_page_number = table.metadata.page_number - min_distance = float('inf') - table_summary = None - if table_summary_mode == 'title': - for element in raw_pdf_elements: - if isinstance(element, FigureCaption) or element.text.startswith('Tab'): - caption_page_number = element.metadata.page_number - caption_coords = element.metadata.coordinates.points - related, y_distance = get_relation(table_coords, caption_coords, \ - table_page_number, caption_page_number) - if related: - if y_distance < min_distance: - min_distance = y_distance - table_summary = element.text - if table_summary is None: - parent_id = table.metadata.parent_id - for element in raw_pdf_elements: - if element.id == parent_id: - table_summary = element.text - break - elif table_summary_mode == 'llm': - prompt = TABLESUMMARY_PROMPT.format(table_content=content) - params = {} - params["model_name"] = table_summary_model_name_or_path - params["prompt"] = prompt - params["temperature"] = 0.8 - params["top_p"] = 0.9 - params["top_k"] = 40 - params["max_new_tokens"] = 1000 - params["num_beams"] = 2 - params["num_return_sequences"] = 2 - params["use_cache"] = True - table_summary = predict(**params) - table_summary = table_summary[table_summary.find('### Generated Summary:\n'):] - table_summary = re.sub('### Generated Summary:\n', '', table_summary) - elif table_summary_mode == None: - table_summary = None - if table_summary is None: - text = f'[Table: {content}]' - else: - text = f'|Table: [Summary: {table_summary}], [Content: {content}]|' - tables_result.append([text, pdf_path]) + tables_result = get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_path) return result, tables_result @@ -326,3 +257,78 @@ def get_chuck_data(content, max_length, min_length, input): current_length = sentence_length return paragraphs + + +def get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_path): + """Extract tables information from pdf file.""" + from unstructured.partition.pdf import partition_pdf + from unstructured.documents.elements import FigureCaption + from intel_extension_for_transformers.neural_chat.models.model_utils import predict + from intel_extension_for_transformers.neural_chat.prompts.prompt import TABLESUMMARY_PROMPT + + tables_result = [] + raw_pdf_elements = partition_pdf( + filename=pdf_path, + infer_table_structure=True, + ) + tables = [el for el in raw_pdf_elements if el.category == "Table"] + for table in tables: + table_coords = table.metadata.coordinates.points + content = table.metadata.text_as_html + table_page_number = table.metadata.page_number + min_distance = float('inf') + table_summary = None + if table_summary_mode == 'title': + for element in raw_pdf_elements: + if isinstance(element, FigureCaption) or element.text.startswith('Tab'): + caption_page_number = element.metadata.page_number + caption_coords = element.metadata.coordinates.points + related, y_distance = get_relation(table_coords, caption_coords, \ + table_page_number, caption_page_number) + if related: + if y_distance < min_distance: + min_distance = y_distance + table_summary = element.text + if table_summary is None: + parent_id = table.metadata.parent_id + for element in raw_pdf_elements: + if element.id == parent_id: + table_summary = element.text + break + elif table_summary_mode == 'llm': + prompt = TABLESUMMARY_PROMPT.format(table_content=content) + params = {} + params["model_name"] = table_summary_model_name_or_path + params["prompt"] = prompt + params["temperature"] = 0.8 + params["top_p"] = 0.9 + params["top_k"] = 40 + params["max_new_tokens"] = 1000 + params["num_beams"] = 2 + params["num_return_sequences"] = 2 + params["use_cache"] = True + table_summary = predict(**params) + table_summary = table_summary[table_summary.find('### Generated Summary:\n'):] + table_summary = re.sub('### Generated Summary:\n', '', table_summary) + elif table_summary_mode == None: + table_summary = None + if table_summary is None: + text = f'[Table: {content}]' + else: + text = f'|Table: [Summary: {table_summary}], [Content: {content}]|' + tables_result.append([text, pdf_path]) + return tables_result + + +def get_relation(table_coords, caption_coords, table_page_number, caption_page_number, threshold=100): + """Get the relation of a pair of table and caption""" + same_page = table_page_number == caption_page_number + x_overlap = (min(table_coords[2][0], caption_coords[2][0]) - max(table_coords[0][0], caption_coords[0][0])) > 0 + if table_coords[0][1] - caption_coords[1][1] >= 0: + y_distance = table_coords[0][1] - caption_coords[1][1] + elif caption_coords[0][1] - table_coords[1][1] >= 0: + y_distance = caption_coords[0][1] - table_coords[1][1] + else: + y_distance = 0 + y_close = y_distance < threshold + return same_page and x_overlap and y_close, y_distance \ No newline at end of file From f71b6021f3349a371f1f61c0313e68f5c16731e2 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 28 Mar 2024 03:09:41 +0000 Subject: [PATCH 09/12] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- .../pipeline/plugins/retrieval/parser/context_utils.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py index a4ceea1cd79..03f2c08e8b1 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py @@ -265,7 +265,7 @@ def get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_ from unstructured.documents.elements import FigureCaption from intel_extension_for_transformers.neural_chat.models.model_utils import predict from intel_extension_for_transformers.neural_chat.prompts.prompt import TABLESUMMARY_PROMPT - + tables_result = [] raw_pdf_elements = partition_pdf( filename=pdf_path, @@ -318,8 +318,8 @@ def get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_ text = f'|Table: [Summary: {table_summary}], [Content: {content}]|' tables_result.append([text, pdf_path]) return tables_result - - + + def get_relation(table_coords, caption_coords, table_page_number, caption_page_number, threshold=100): """Get the relation of a pair of table and caption""" same_page = table_page_number == caption_page_number @@ -331,4 +331,4 @@ def get_relation(table_coords, caption_coords, table_page_number, caption_page_n else: y_distance = 0 y_close = y_distance < threshold - return same_page and x_overlap and y_close, y_distance \ No newline at end of file + return same_page and x_overlap and y_close, y_distance From 39bd8d70772a4f58a0925b3ce23fdec161f70c81 Mon Sep 17 00:00:00 2001 From: Chen Xi Date: Fri, 29 Mar 2024 16:46:16 +0800 Subject: [PATCH 10/12] polish pr Signed-off-by: Chen Xi --- .../pipeline/plugins/retrieval/README.md | 2 +- .../plugins/retrieval/parser/context_utils.py | 19 ++++---- .../plugins/retrieval/parser/parser.py | 6 +-- .../ci/plugins/retrieval/test_parameters.py | 45 ++++++++++--------- 4 files changed, 38 insertions(+), 34 deletions(-) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md index a0dc6c945c3..8bec2cec2ea 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md @@ -92,7 +92,7 @@ Below are the description for the available parameters in `agent_QA`, | enable_rerank | bool | Whether to enable retrieval then rerank pipeline |True, False| | reranker_model | str | The name of the reranker model from the Huggingface or a local path |-| | top_n | int | The return number of the reranker model |-| -| table_summary_mode | str | Utilize the table's title as its summarization or employ a LLM for table summarization, so that achieve better table retrieval performance|"title","llm"| +| table_strategy | str | The strategies to understand tables for table retrieval. As the setting progresses from "fast" to "hq" to "llm," the focus shifts towards deeper table understanding at the expense of processing speed |"fast", "hq", "llm"| More retriever- and vectorstore-related parameters please check [here](#langchain-extension) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py index 03f2c08e8b1..3d305e49011 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py @@ -48,7 +48,7 @@ def uni_pro(text): return filtered_text -def read_pdf(pdf_path, table_summary_mode, table_summary_model_name_or_path): +def read_pdf(pdf_path, table_strategy, table_summary_model_name_or_path): """Read the pdf file.""" doc = fitz.open(pdf_path) reader = easyocr.Reader(['en']) @@ -77,7 +77,7 @@ def read_pdf(pdf_path, table_summary_mode, table_summary_model_name_or_path): else: pageimg=pageimg+'.' result=result+pageimg - tables_result = get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_path) + tables_result = get_tables_result(pdf_path, table_strategy, table_summary_model_name_or_path) return result, tables_result @@ -215,11 +215,11 @@ def load_structured_data(input, process, max_length, min_length): content = load_csv(input) return content -def load_unstructured_data(input, table_summary_mode, table_summary_model_name_or_path): +def load_unstructured_data(input, table_strategy, table_summary_model_name_or_path): """Load unstructured context.""" tables = None if input.endswith("pdf"): - text, tables = read_pdf(input, table_summary_mode, table_summary_model_name_or_path) + text, tables = read_pdf(input, table_strategy, table_summary_model_name_or_path) elif input.endswith("docx"): text = read_docx(input) elif input.endswith("html"): @@ -259,8 +259,11 @@ def get_chuck_data(content, max_length, min_length, input): return paragraphs -def get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_path): +def get_tables_result(pdf_path, table_strategy, table_summary_model_name_or_path): """Extract tables information from pdf file.""" + if table_strategy == 'fast': + return None + from unstructured.partition.pdf import partition_pdf from unstructured.documents.elements import FigureCaption from intel_extension_for_transformers.neural_chat.models.model_utils import predict @@ -278,7 +281,7 @@ def get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_ table_page_number = table.metadata.page_number min_distance = float('inf') table_summary = None - if table_summary_mode == 'title': + if table_strategy == 'hq': for element in raw_pdf_elements: if isinstance(element, FigureCaption) or element.text.startswith('Tab'): caption_page_number = element.metadata.page_number @@ -295,7 +298,7 @@ def get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_ if element.id == parent_id: table_summary = element.text break - elif table_summary_mode == 'llm': + elif table_strategy == 'llm': prompt = TABLESUMMARY_PROMPT.format(table_content=content) params = {} params["model_name"] = table_summary_model_name_or_path @@ -310,7 +313,7 @@ def get_tables_result(pdf_path, table_summary_mode, table_summary_model_name_or_ table_summary = predict(**params) table_summary = table_summary[table_summary.find('### Generated Summary:\n'):] table_summary = re.sub('### Generated Summary:\n', '', table_summary) - elif table_summary_mode == None: + elif table_strategy == None: table_summary = None if table_summary is None: text = f'[Table: {content}]' diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py index 31ef0c3d3e9..810869b492f 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/parser.py @@ -51,7 +51,7 @@ def load(self, input, **kwargs): self.process = kwargs['process'] self.table_summary_model_name_or_path = kwargs['table_summary_model_name_or_path'] \ if 'table_summary_model_name_or_path' in kwargs else None - self.table_summary_mode = kwargs['table_summary_mode'] if 'table_summary_mode' in kwargs else None + self.table_strategy = kwargs['table_strategy'] if 'table_strategy' in kwargs else 'fast' if isinstance(input, str): if os.path.isfile(input): @@ -77,7 +77,7 @@ def parse_document(self, input): """ if input.endswith("pdf") or input.endswith("docx") or input.endswith("html") \ or input.endswith("txt") or input.endswith("md"): - content, tables = load_unstructured_data(input, self.table_summary_mode, \ + content, tables = load_unstructured_data(input, self.table_strategy, \ self.table_summary_model_name_or_path) if self.process: chuck = get_chuck_data(content, self.max_chuck_size, self.min_chuck_size, input) @@ -125,7 +125,7 @@ def batch_parse_document(self, input): if filename.endswith("pdf") or filename.endswith("docx") or filename.endswith("html") \ or filename.endswith("txt") or filename.endswith("md"): content, tables = load_unstructured_data(os.path.join(dirpath, filename), \ - self.table_summary_mode, \ + self.table_strategy, \ self.table_summary_model_name_or_path) if self.process: chuck = get_chuck_data(content, self.max_chuck_size, self.min_chuck_size, input) diff --git a/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py b/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py index c94441835fa..6f0034e10ae 100644 --- a/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py +++ b/intel_extension_for_transformers/neural_chat/tests/ci/plugins/retrieval/test_parameters.py @@ -714,24 +714,24 @@ def test_embedding_precision_fp32(self): plugins.retrieval.args = {} plugins.retrieval.enable = False -class TestTableSummaryTitleMode(unittest.TestCase): +class TestHQTableStrategy(unittest.TestCase): def setUp(self): - if os.path.exists("./table_summary_title_mode"): - shutil.rmtree("./table_summary_title_mode", ignore_errors=True) + if os.path.exists("./hq_table_strategy"): + shutil.rmtree("./hq_table_strategy", ignore_errors=True) return super().setUp() def tearDown(self) -> None: - if os.path.exists("./table_summary_title_mode"): - shutil.rmtree("./table_summary_title_mode", ignore_errors=True) + if os.path.exists("./hq_table_strategy"): + shutil.rmtree("./hq_table_strategy", ignore_errors=True) return super().tearDown() - def test_table_summary_title_mode(self): + def test_hq_table_strategy(self): plugins.retrieval.args = {} plugins.retrieval.enable = True plugins.retrieval.args["input_path"] = "../assets/docs/LLAMA2_short.pdf" - plugins.retrieval.args["persist_directory"] = "./table_summary_title_mode" + plugins.retrieval.args["persist_directory"] = "./hq_table_strategy" plugins.retrieval.args["retrieval_type"] = 'default' - plugins.retrieval.args["table_summary_mode"] = 'title' + plugins.retrieval.args["table_strategy"] = 'hq' config = PipelineConfig(model_name_or_path="facebook/opt-125m", plugins=plugins) chatbot = build_chatbot(config) @@ -741,24 +741,24 @@ def test_table_summary_title_mode(self): plugins.retrieval.args = {} plugins.retrieval.enable = False -class TestTableSummaryLLMMode(unittest.TestCase): +class TestLLMTableStrategy(unittest.TestCase): def setUp(self): - if os.path.exists("./table_summary_llm_mode"): - shutil.rmtree("./table_summary_llm_mode", ignore_errors=True) + if os.path.exists("./llm_table_strategy"): + shutil.rmtree("./llm_table_strategy", ignore_errors=True) return super().setUp() def tearDown(self) -> None: - if os.path.exists("./table_summary_llm_mode"): - shutil.rmtree("./table_summary_llm_mode", ignore_errors=True) + if os.path.exists("./llm_table_strategy"): + shutil.rmtree("./llm_table_strategy", ignore_errors=True) return super().tearDown() - def test_table_summary_llm_mode(self): + def test_llm_table_strategy(self): plugins.retrieval.args = {} plugins.retrieval.enable = True plugins.retrieval.args["input_path"] = "../assets/docs/LLAMA2_short.pdf" - plugins.retrieval.args["persist_directory"] = "./table_summary_llm_mode" + plugins.retrieval.args["persist_directory"] = "./llm_table_strategy" plugins.retrieval.args["retrieval_type"] = 'default' - plugins.retrieval.args["table_summary_mode"] = 'llm' + plugins.retrieval.args["table_strategy"] = 'llm' config = PipelineConfig(model_name_or_path="facebook/opt-125m", plugins=plugins) chatbot = build_chatbot(config) @@ -770,21 +770,22 @@ def test_table_summary_llm_mode(self): class TestTableSummaryNoneMode(unittest.TestCase): def setUp(self): - if os.path.exists("./table_summary_none_mode"): - shutil.rmtree("./table_summary_none_mode", ignore_errors=True) + if os.path.exists("./fast_table_strategy"): + shutil.rmtree("./fast_table_strategy", ignore_errors=True) return super().setUp() def tearDown(self) -> None: - if os.path.exists("./table_summary_none_mode"): - shutil.rmtree("./table_summary_none_mode", ignore_errors=True) + if os.path.exists("./fast_table_strategy"): + shutil.rmtree("./fast_table_strategy", ignore_errors=True) return super().tearDown() - def test_table_summary_none_mode(self): + def test_fast_table_strategy(self): plugins.retrieval.args = {} plugins.retrieval.enable = True plugins.retrieval.args["input_path"] = "../assets/docs/LLAMA2_short.pdf" - plugins.retrieval.args["persist_directory"] = "./table_summary_none_mode" + plugins.retrieval.args["persist_directory"] = "./fast_table_strategy" plugins.retrieval.args["retrieval_type"] = 'default' + plugins.retrieval.args["table_strategy"] = 'fast' config = PipelineConfig(model_name_or_path="facebook/opt-125m", plugins=plugins) chatbot = build_chatbot(config) From 460110aa70d2d43d666894b56bb6cce8a9072a97 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 29 Mar 2024 08:51:00 +0000 Subject: [PATCH 11/12] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- .../pipeline/plugins/retrieval/parser/context_utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py index 3ebace9ac51..ebdb8421002 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/parser/context_utils.py @@ -264,7 +264,7 @@ def get_tables_result(pdf_path, table_strategy, table_summary_model_name_or_path """Extract tables information from pdf file.""" if table_strategy == 'fast': return None - + from unstructured.partition.pdf import partition_pdf from unstructured.documents.elements import FigureCaption from intel_extension_for_transformers.neural_chat.models.model_utils import predict From ee601db1d4cf49de3cbacfb9c152df8f1096d46e Mon Sep 17 00:00:00 2001 From: Chen Xi Date: Mon, 1 Apr 2024 14:42:58 +0800 Subject: [PATCH 12/12] polish readme Signed-off-by: Chen Xi --- .../neural_chat/pipeline/plugins/retrieval/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md index 8bec2cec2ea..11f3d15c580 100644 --- a/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md +++ b/intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md @@ -92,7 +92,7 @@ Below are the description for the available parameters in `agent_QA`, | enable_rerank | bool | Whether to enable retrieval then rerank pipeline |True, False| | reranker_model | str | The name of the reranker model from the Huggingface or a local path |-| | top_n | int | The return number of the reranker model |-| -| table_strategy | str | The strategies to understand tables for table retrieval. As the setting progresses from "fast" to "hq" to "llm," the focus shifts towards deeper table understanding at the expense of processing speed |"fast", "hq", "llm"| +| table_strategy | str | The strategies to understand tables for table retrieval. As the setting progresses from "fast" to "hq" to "llm," the focus shifts towards deeper table understanding at the expense of processing speed. The default strategy is "fast" |"fast", "hq", "llm"| More retriever- and vectorstore-related parameters please check [here](#langchain-extension)