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| # | |
| # Copyright 2024 The InfiniFlow Authors. All Rights Reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License | |
| # | |
| import datetime | |
| import hashlib | |
| import json | |
| import os | |
| import pathlib | |
| import re | |
| import traceback | |
| from concurrent.futures import ThreadPoolExecutor | |
| from copy import deepcopy | |
| from io import BytesIO | |
| import flask | |
| from elasticsearch_dsl import Q | |
| from flask import request | |
| from flask_login import login_required, current_user | |
| from api.db.db_models import Task, File | |
| from api.db.services.dialog_service import DialogService, ConversationService | |
| from api.db.services.file2document_service import File2DocumentService | |
| from api.db.services.file_service import FileService | |
| from api.db.services.llm_service import LLMBundle | |
| from api.db.services.task_service import TaskService, queue_tasks | |
| from api.db.services.user_service import TenantService | |
| from graphrag.mind_map_extractor import MindMapExtractor | |
| from rag.app import naive | |
| from rag.nlp import search | |
| from rag.utils.es_conn import ELASTICSEARCH | |
| from api.db.services import duplicate_name | |
| from api.db.services.knowledgebase_service import KnowledgebaseService | |
| from api.utils.api_utils import server_error_response, get_data_error_result, validate_request | |
| from api.utils import get_uuid | |
| from api.db import FileType, TaskStatus, ParserType, FileSource, LLMType | |
| from api.db.services.document_service import DocumentService | |
| from api.settings import RetCode, stat_logger | |
| from api.utils.api_utils import get_json_result | |
| from rag.utils.minio_conn import MINIO | |
| from api.utils.file_utils import filename_type, thumbnail, get_project_base_directory | |
| from api.utils.web_utils import html2pdf, is_valid_url | |
| def upload(): | |
| kb_id = request.form.get("kb_id") | |
| if not kb_id: | |
| return get_json_result( | |
| data=False, retmsg='Lack of "KB ID"', retcode=RetCode.ARGUMENT_ERROR) | |
| if 'file' not in request.files: | |
| return get_json_result( | |
| data=False, retmsg='No file part!', retcode=RetCode.ARGUMENT_ERROR) | |
| file_objs = request.files.getlist('file') | |
| for file_obj in file_objs: | |
| if file_obj.filename == '': | |
| return get_json_result( | |
| data=False, retmsg='No file selected!', retcode=RetCode.ARGUMENT_ERROR) | |
| e, kb = KnowledgebaseService.get_by_id(kb_id) | |
| if not e: | |
| raise LookupError("Can't find this knowledgebase!") | |
| err, _ = FileService.upload_document(kb, file_objs) | |
| if err: | |
| return get_json_result( | |
| data=False, retmsg="\n".join(err), retcode=RetCode.SERVER_ERROR) | |
| return get_json_result(data=True) | |
| def web_crawl(): | |
| kb_id = request.form.get("kb_id") | |
| if not kb_id: | |
| return get_json_result( | |
| data=False, retmsg='Lack of "KB ID"', retcode=RetCode.ARGUMENT_ERROR) | |
| name = request.form.get("name") | |
| url = request.form.get("url") | |
| if not is_valid_url(url): | |
| return get_json_result( | |
| data=False, retmsg='The URL format is invalid', retcode=RetCode.ARGUMENT_ERROR) | |
| e, kb = KnowledgebaseService.get_by_id(kb_id) | |
| if not e: | |
| raise LookupError("Can't find this knowledgebase!") | |
| blob = html2pdf(url) | |
| if not blob: return server_error_response(ValueError("Download failure.")) | |
| root_folder = FileService.get_root_folder(current_user.id) | |
| pf_id = root_folder["id"] | |
| FileService.init_knowledgebase_docs(pf_id, current_user.id) | |
| kb_root_folder = FileService.get_kb_folder(current_user.id) | |
| kb_folder = FileService.new_a_file_from_kb(kb.tenant_id, kb.name, kb_root_folder["id"]) | |
| try: | |
| filename = duplicate_name( | |
| DocumentService.query, | |
| name=name + ".pdf", | |
| kb_id=kb.id) | |
| filetype = filename_type(filename) | |
| if filetype == FileType.OTHER.value: | |
| raise RuntimeError("This type of file has not been supported yet!") | |
| location = filename | |
| while MINIO.obj_exist(kb_id, location): | |
| location += "_" | |
| MINIO.put(kb_id, location, blob) | |
| doc = { | |
| "id": get_uuid(), | |
| "kb_id": kb.id, | |
| "parser_id": kb.parser_id, | |
| "parser_config": kb.parser_config, | |
| "created_by": current_user.id, | |
| "type": filetype, | |
| "name": filename, | |
| "location": location, | |
| "size": len(blob), | |
| "thumbnail": thumbnail(filename, blob) | |
| } | |
| if doc["type"] == FileType.VISUAL: | |
| doc["parser_id"] = ParserType.PICTURE.value | |
| if doc["type"] == FileType.AURAL: | |
| doc["parser_id"] = ParserType.AUDIO.value | |
| if re.search(r"\.(ppt|pptx|pages)$", filename): | |
| doc["parser_id"] = ParserType.PRESENTATION.value | |
| DocumentService.insert(doc) | |
| FileService.add_file_from_kb(doc, kb_folder["id"], kb.tenant_id) | |
| except Exception as e: | |
| return server_error_response(e) | |
| return get_json_result(data=True) | |
| def create(): | |
| req = request.json | |
| kb_id = req["kb_id"] | |
| if not kb_id: | |
| return get_json_result( | |
| data=False, retmsg='Lack of "KB ID"', retcode=RetCode.ARGUMENT_ERROR) | |
| try: | |
| e, kb = KnowledgebaseService.get_by_id(kb_id) | |
| if not e: | |
| return get_data_error_result( | |
| retmsg="Can't find this knowledgebase!") | |
| if DocumentService.query(name=req["name"], kb_id=kb_id): | |
| return get_data_error_result( | |
| retmsg="Duplicated document name in the same knowledgebase.") | |
| doc = DocumentService.insert({ | |
| "id": get_uuid(), | |
| "kb_id": kb.id, | |
| "parser_id": kb.parser_id, | |
| "parser_config": kb.parser_config, | |
| "created_by": current_user.id, | |
| "type": FileType.VIRTUAL, | |
| "name": req["name"], | |
| "location": "", | |
| "size": 0 | |
| }) | |
| return get_json_result(data=doc.to_json()) | |
| except Exception as e: | |
| return server_error_response(e) | |
| def list_docs(): | |
| kb_id = request.args.get("kb_id") | |
| if not kb_id: | |
| return get_json_result( | |
| data=False, retmsg='Lack of "KB ID"', retcode=RetCode.ARGUMENT_ERROR) | |
| keywords = request.args.get("keywords", "") | |
| page_number = int(request.args.get("page", 1)) | |
| items_per_page = int(request.args.get("page_size", 15)) | |
| orderby = request.args.get("orderby", "create_time") | |
| desc = request.args.get("desc", True) | |
| try: | |
| docs, tol = DocumentService.get_by_kb_id( | |
| kb_id, page_number, items_per_page, orderby, desc, keywords) | |
| return get_json_result(data={"total": tol, "docs": docs}) | |
| except Exception as e: | |
| return server_error_response(e) | |
| def thumbnails(): | |
| doc_ids = request.args.get("doc_ids").split(",") | |
| if not doc_ids: | |
| return get_json_result( | |
| data=False, retmsg='Lack of "Document ID"', retcode=RetCode.ARGUMENT_ERROR) | |
| try: | |
| docs = DocumentService.get_thumbnails(doc_ids) | |
| return get_json_result(data={d["id"]: d["thumbnail"] for d in docs}) | |
| except Exception as e: | |
| return server_error_response(e) | |
| def change_status(): | |
| req = request.json | |
| if str(req["status"]) not in ["0", "1"]: | |
| get_json_result( | |
| data=False, | |
| retmsg='"Status" must be either 0 or 1!', | |
| retcode=RetCode.ARGUMENT_ERROR) | |
| try: | |
| e, doc = DocumentService.get_by_id(req["doc_id"]) | |
| if not e: | |
| return get_data_error_result(retmsg="Document not found!") | |
| e, kb = KnowledgebaseService.get_by_id(doc.kb_id) | |
| if not e: | |
| return get_data_error_result( | |
| retmsg="Can't find this knowledgebase!") | |
| if not DocumentService.update_by_id( | |
| req["doc_id"], {"status": str(req["status"])}): | |
| return get_data_error_result( | |
| retmsg="Database error (Document update)!") | |
| if str(req["status"]) == "0": | |
| ELASTICSEARCH.updateScriptByQuery(Q("term", doc_id=req["doc_id"]), | |
| scripts="ctx._source.available_int=0;", | |
| idxnm=search.index_name( | |
| kb.tenant_id) | |
| ) | |
| else: | |
| ELASTICSEARCH.updateScriptByQuery(Q("term", doc_id=req["doc_id"]), | |
| scripts="ctx._source.available_int=1;", | |
| idxnm=search.index_name( | |
| kb.tenant_id) | |
| ) | |
| return get_json_result(data=True) | |
| except Exception as e: | |
| return server_error_response(e) | |
| def rm(): | |
| req = request.json | |
| doc_ids = req["doc_id"] | |
| if isinstance(doc_ids, str): doc_ids = [doc_ids] | |
| root_folder = FileService.get_root_folder(current_user.id) | |
| pf_id = root_folder["id"] | |
| FileService.init_knowledgebase_docs(pf_id, current_user.id) | |
| errors = "" | |
| for doc_id in doc_ids: | |
| try: | |
| e, doc = DocumentService.get_by_id(doc_id) | |
| if not e: | |
| return get_data_error_result(retmsg="Document not found!") | |
| tenant_id = DocumentService.get_tenant_id(doc_id) | |
| if not tenant_id: | |
| return get_data_error_result(retmsg="Tenant not found!") | |
| b, n = File2DocumentService.get_minio_address(doc_id=doc_id) | |
| if not DocumentService.remove_document(doc, tenant_id): | |
| return get_data_error_result( | |
| retmsg="Database error (Document removal)!") | |
| f2d = File2DocumentService.get_by_document_id(doc_id) | |
| FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.id == f2d[0].file_id]) | |
| File2DocumentService.delete_by_document_id(doc_id) | |
| MINIO.rm(b, n) | |
| except Exception as e: | |
| errors += str(e) | |
| if errors: | |
| return get_json_result(data=False, retmsg=errors, retcode=RetCode.SERVER_ERROR) | |
| return get_json_result(data=True) | |
| def run(): | |
| req = request.json | |
| try: | |
| for id in req["doc_ids"]: | |
| info = {"run": str(req["run"]), "progress": 0} | |
| if str(req["run"]) == TaskStatus.RUNNING.value: | |
| info["progress_msg"] = "" | |
| info["chunk_num"] = 0 | |
| info["token_num"] = 0 | |
| DocumentService.update_by_id(id, info) | |
| # if str(req["run"]) == TaskStatus.CANCEL.value: | |
| tenant_id = DocumentService.get_tenant_id(id) | |
| if not tenant_id: | |
| return get_data_error_result(retmsg="Tenant not found!") | |
| ELASTICSEARCH.deleteByQuery( | |
| Q("match", doc_id=id), idxnm=search.index_name(tenant_id)) | |
| if str(req["run"]) == TaskStatus.RUNNING.value: | |
| TaskService.filter_delete([Task.doc_id == id]) | |
| e, doc = DocumentService.get_by_id(id) | |
| doc = doc.to_dict() | |
| doc["tenant_id"] = tenant_id | |
| bucket, name = File2DocumentService.get_minio_address(doc_id=doc["id"]) | |
| queue_tasks(doc, bucket, name) | |
| return get_json_result(data=True) | |
| except Exception as e: | |
| return server_error_response(e) | |
| def rename(): | |
| req = request.json | |
| try: | |
| e, doc = DocumentService.get_by_id(req["doc_id"]) | |
| if not e: | |
| return get_data_error_result(retmsg="Document not found!") | |
| if pathlib.Path(req["name"].lower()).suffix != pathlib.Path( | |
| doc.name.lower()).suffix: | |
| return get_json_result( | |
| data=False, | |
| retmsg="The extension of file can't be changed", | |
| retcode=RetCode.ARGUMENT_ERROR) | |
| for d in DocumentService.query(name=req["name"], kb_id=doc.kb_id): | |
| if d.name == req["name"]: | |
| return get_data_error_result( | |
| retmsg="Duplicated document name in the same knowledgebase.") | |
| if not DocumentService.update_by_id( | |
| req["doc_id"], {"name": req["name"]}): | |
| return get_data_error_result( | |
| retmsg="Database error (Document rename)!") | |
| informs = File2DocumentService.get_by_document_id(req["doc_id"]) | |
| if informs: | |
| e, file = FileService.get_by_id(informs[0].file_id) | |
| FileService.update_by_id(file.id, {"name": req["name"]}) | |
| return get_json_result(data=True) | |
| except Exception as e: | |
| return server_error_response(e) | |
| # @login_required | |
| def get(doc_id): | |
| try: | |
| e, doc = DocumentService.get_by_id(doc_id) | |
| if not e: | |
| return get_data_error_result(retmsg="Document not found!") | |
| b, n = File2DocumentService.get_minio_address(doc_id=doc_id) | |
| response = flask.make_response(MINIO.get(b, n)) | |
| ext = re.search(r"\.([^.]+)$", doc.name) | |
| if ext: | |
| if doc.type == FileType.VISUAL.value: | |
| response.headers.set('Content-Type', 'image/%s' % ext.group(1)) | |
| else: | |
| response.headers.set( | |
| 'Content-Type', | |
| 'application/%s' % | |
| ext.group(1)) | |
| return response | |
| except Exception as e: | |
| return server_error_response(e) | |
| def change_parser(): | |
| req = request.json | |
| try: | |
| e, doc = DocumentService.get_by_id(req["doc_id"]) | |
| if not e: | |
| return get_data_error_result(retmsg="Document not found!") | |
| if doc.parser_id.lower() == req["parser_id"].lower(): | |
| if "parser_config" in req: | |
| if req["parser_config"] == doc.parser_config: | |
| return get_json_result(data=True) | |
| else: | |
| return get_json_result(data=True) | |
| if doc.type == FileType.VISUAL or re.search( | |
| r"\.(ppt|pptx|pages)$", doc.name): | |
| return get_data_error_result(retmsg="Not supported yet!") | |
| e = DocumentService.update_by_id(doc.id, | |
| {"parser_id": req["parser_id"], "progress": 0, "progress_msg": "", | |
| "run": TaskStatus.UNSTART.value}) | |
| if not e: | |
| return get_data_error_result(retmsg="Document not found!") | |
| if "parser_config" in req: | |
| DocumentService.update_parser_config(doc.id, req["parser_config"]) | |
| if doc.token_num > 0: | |
| e = DocumentService.increment_chunk_num(doc.id, doc.kb_id, doc.token_num * -1, doc.chunk_num * -1, | |
| doc.process_duation * -1) | |
| if not e: | |
| return get_data_error_result(retmsg="Document not found!") | |
| tenant_id = DocumentService.get_tenant_id(req["doc_id"]) | |
| if not tenant_id: | |
| return get_data_error_result(retmsg="Tenant not found!") | |
| ELASTICSEARCH.deleteByQuery( | |
| Q("match", doc_id=doc.id), idxnm=search.index_name(tenant_id)) | |
| return get_json_result(data=True) | |
| except Exception as e: | |
| return server_error_response(e) | |
| # @login_required | |
| def get_image(image_id): | |
| try: | |
| bkt, nm = image_id.split("-") | |
| response = flask.make_response(MINIO.get(bkt, nm)) | |
| response.headers.set('Content-Type', 'image/JPEG') | |
| return response | |
| except Exception as e: | |
| return server_error_response(e) | |
| def upload_and_parse(): | |
| req = request.json | |
| if 'file' not in request.files: | |
| return get_json_result( | |
| data=False, retmsg='No file part!', retcode=RetCode.ARGUMENT_ERROR) | |
| file_objs = request.files.getlist('file') | |
| for file_obj in file_objs: | |
| if file_obj.filename == '': | |
| return get_json_result( | |
| data=False, retmsg='No file selected!', retcode=RetCode.ARGUMENT_ERROR) | |
| e, conv = ConversationService.get_by_id(req["conversation_id"]) | |
| if not e: | |
| return get_data_error_result(retmsg="Conversation not found!") | |
| e, dia = DialogService.get_by_id(conv.dialog_id) | |
| kb_id = dia.kb_ids[0] | |
| e, kb = KnowledgebaseService.get_by_id(kb_id) | |
| if not e: | |
| raise LookupError("Can't find this knowledgebase!") | |
| idxnm = search.index_name(kb.tenant_id) | |
| if not ELASTICSEARCH.indexExist(idxnm): | |
| ELASTICSEARCH.createIdx(idxnm, json.load( | |
| open(os.path.join(get_project_base_directory(), "conf", "mapping.json"), "r"))) | |
| embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING, llm_name=kb.embd_id, lang=kb.language) | |
| err, files = FileService.upload_document(kb, file_objs) | |
| if err: | |
| return get_json_result( | |
| data=False, retmsg="\n".join(err), retcode=RetCode.SERVER_ERROR) | |
| def dummy(prog=None, msg=""): | |
| pass | |
| parser_config = {"chunk_token_num": 4096, "delimiter": "\n!?。;!?", "layout_recognize": False} | |
| exe = ThreadPoolExecutor(max_workers=12) | |
| threads = [] | |
| for d, blob in files: | |
| kwargs = { | |
| "callback": dummy, | |
| "parser_config": parser_config, | |
| "from_page": 0, | |
| "to_page": 100000 | |
| } | |
| threads.append(exe.submit(naive.chunk, d["name"], blob, **kwargs)) | |
| for (docinfo,_), th in zip(files, threads): | |
| docs = [] | |
| doc = { | |
| "doc_id": docinfo["id"], | |
| "kb_id": [kb.id] | |
| } | |
| for ck in th.result(): | |
| d = deepcopy(doc) | |
| d.update(ck) | |
| md5 = hashlib.md5() | |
| md5.update((ck["content_with_weight"] + | |
| str(d["doc_id"])).encode("utf-8")) | |
| d["_id"] = md5.hexdigest() | |
| d["create_time"] = str(datetime.datetime.now()).replace("T", " ")[:19] | |
| d["create_timestamp_flt"] = datetime.datetime.now().timestamp() | |
| if not d.get("image"): | |
| docs.append(d) | |
| continue | |
| output_buffer = BytesIO() | |
| if isinstance(d["image"], bytes): | |
| output_buffer = BytesIO(d["image"]) | |
| else: | |
| d["image"].save(output_buffer, format='JPEG') | |
| MINIO.put(kb.id, d["_id"], output_buffer.getvalue()) | |
| d["img_id"] = "{}-{}".format(kb.id, d["_id"]) | |
| del d["image"] | |
| docs.append(d) | |
| parser_ids = {d["id"]: d["parser_id"] for d, _ in files} | |
| docids = [d["id"] for d, _ in files] | |
| chunk_counts = {id: 0 for id in docids} | |
| token_counts = {id: 0 for id in docids} | |
| es_bulk_size = 64 | |
| def embedding(doc_id, cnts, batch_size=16): | |
| nonlocal embd_mdl, chunk_counts, token_counts | |
| vects = [] | |
| for i in range(0, len(cnts), batch_size): | |
| vts, c = embd_mdl.encode(cnts[i: i + batch_size]) | |
| vects.extend(vts.tolist()) | |
| chunk_counts[doc_id] += len(cnts[i:i + batch_size]) | |
| token_counts[doc_id] += c | |
| return vects | |
| _, tenant = TenantService.get_by_id(kb.tenant_id) | |
| llm_bdl = LLMBundle(kb.tenant_id, LLMType.CHAT, tenant.llm_id) | |
| for doc_id in docids: | |
| cks = [c for c in docs if c["doc_id"] == doc_id] | |
| if parser_ids[doc_id] != ParserType.PICTURE.value: | |
| mindmap = MindMapExtractor(llm_bdl) | |
| try: | |
| mind_map = json.dumps(mindmap([c["content_with_weight"] for c in docs if c["doc_id"] == doc_id]).output, ensure_ascii=False, indent=2) | |
| if len(mind_map) < 32: raise Exception("Few content: "+mind_map) | |
| cks.append({ | |
| "doc_id": doc_id, | |
| "kb_id": [kb.id], | |
| "content_with_weight": mind_map, | |
| "knowledge_graph_kwd": "mind_map" | |
| }) | |
| except Exception as e: | |
| stat_logger.error("Mind map generation error:", traceback.format_exc()) | |
| vects = embedding(doc_id, cks) | |
| assert len(cks) == len(vects) | |
| for i, d in enumerate(cks): | |
| v = vects[i] | |
| d["q_%d_vec" % len(v)] = v | |
| for b in range(0, len(cks), es_bulk_size): | |
| ELASTICSEARCH.bulk(cks[b:b + es_bulk_size], idxnm) | |
| DocumentService.increment_chunk_num( | |
| doc_id, kb.id, token_counts[doc_id], chunk_counts[doc_id], 0) | |
| return get_json_result(data=[d["id"] for d in files]) | |