update sdk document (#2374)

### What problem does this PR solve?

_Briefly describe what this PR aims to solve. Include background context
that will help reviewers understand the purpose of the PR._

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

---------

Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>

api/apps/sdk/doc.py

+from io import BytesIO
+
+from flask import request,send_file
+from api.utils.api_utils import get_json_result, construct_json_result, server_error_response
+from api.utils.api_utils import get_json_result, token_required, get_data_error_result
+from api.db import FileType, ParserType, FileSource, TaskStatus
+from api.db.db_models import File
+from api.db.services.document_service import DocumentService
+from api.db.services.file2document_service import File2DocumentService
+from api.db.services.file_service import FileService
+from api.db.services.knowledgebase_service import KnowledgebaseService
+from api.db.services.user_service import TenantService, UserTenantService
+from api.settings import RetCode
+from api.utils.api_utils import construct_json_result, construct_error_response
+from rag.utils.storage_factory import STORAGE_IMPL
+
+
+@manager.route('/dataset/<dataset_id>/documents/upload', methods=['POST'])
+@token_required
+def upload(dataset_id, tenant_id):
+    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(dataset_id)
+    if not e:
+        raise LookupError(f"Can't find the knowledgebase with ID {dataset_id}!")
+    err, _ = FileService.upload_document(kb, file_objs, tenant_id)
+    if err:
+        return get_json_result(
+            data=False, retmsg="\n".join(err), retcode=RetCode.SERVER_ERROR)
+    return get_json_result(data=True)
+
+
+@manager.route('/infos', methods=['GET'])
+@token_required
+def docinfos(tenant_id):
+    req = request.args
+    if "id" in req:
+        doc_id = req["id"]
+        e, doc = DocumentService.get_by_id(doc_id)
+        return get_json_result(data=doc.to_json())
+    if "name" in req:
+        doc_name = req["name"]
+        doc_id = DocumentService.get_doc_id_by_doc_name(doc_name)
+        e, doc = DocumentService.get_by_id(doc_id)
+        return get_json_result(data=doc.to_json())
+
+
+@manager.route('/save', methods=['POST'])
+@token_required
+def save_doc(tenant_id):
+    req = request.json  # Expecting JSON input
+    if "id" in req:
+        doc_id = req["id"]
+    if "name" in req:
+        doc_name = req["name"]
+        doc_id = DocumentService.get_doc_id_by_doc_name(doc_name)
+    data = request.json
+    # Call the update method with the provided id and data
+    try:
+        num = DocumentService.update_by_id(doc_id, data)
+        if num > 0:
+            return get_json_result(retmsg="success", data={"updated_count": num})
+        else:
+            return get_json_result(retcode=404, retmsg="Document not found")
+    except Exception as e:
+        return get_json_result(retmsg=f"Error occurred: {str(e)}")
+
+
+@manager.route("/<dataset_id>/documents/<document_id>", methods=["GET"])
+@token_required
+def download_document(dataset_id, document_id):
+    try:
+        # Check whether there is this dataset
+        exist, _ = KnowledgebaseService.get_by_id(dataset_id)
+        if not exist:
+            return construct_json_result(code=RetCode.DATA_ERROR,
+                                         message=f"This dataset '{dataset_id}' cannot be found!")
+
+        # Check whether there is this document
+        exist, document = DocumentService.get_by_id(document_id)
+        if not exist:
+            return construct_json_result(message=f"This document '{document_id}' cannot be found!",
+                                         code=RetCode.ARGUMENT_ERROR)
+
+        # The process of downloading
+        doc_id, doc_location = File2DocumentService.get_minio_address(doc_id=document_id)  # minio address
+        file_stream = STORAGE_IMPL.get(doc_id, doc_location)
+        if not file_stream:
+            return construct_json_result(message="This file is empty.", code=RetCode.DATA_ERROR)
+
+        file = BytesIO(file_stream)
+
+        # Use send_file with a proper filename and MIME type
+        return send_file(
+            file,
+            as_attachment=True,
+            download_name=document.name,
+            mimetype='application/octet-stream'  # Set a default MIME type
+        )
+
+    # Error
+    except Exception as e:
+        return construct_error_response(e)
+
+@manager.route('/dataset/<dataset_id>/documents', methods=['GET'])
+@token_required
+def list_docs(dataset_id,tenant_id):
+    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)
+    tenants = UserTenantService.query(user_id=tenant_id)
+    for tenant in tenants:
+        if KnowledgebaseService.query(
+                tenant_id=tenant.tenant_id, id=kb_id):
+            break
+    else:
+        return get_json_result(
+            data=False, retmsg=f'Only owner of knowledgebase authorized for this operation.',
+            retcode=RetCode.OPERATING_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)
+
+
+@manager.route('/delete', methods=['DELETE'])
+@token_required
+def rm(tenant_id):
+    req = request.args
+    if "doc_id" not in req:
+        return get_data_error_result(
+            retmsg="doc_id is required")
+    doc_ids = req["doc_id"]
+    if isinstance(doc_ids, str): doc_ids = [doc_ids]
+    root_folder = FileService.get_root_folder(tenant_id)
+    pf_id = root_folder["id"]
+    FileService.init_knowledgebase_docs(pf_id, tenant_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)
+
+            STORAGE_IMPL.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,retmsg="success")

sdk/python/ragflow/__init__.py

 from .ragflow import RAGFlow
 from .modules.dataset import DataSet
 from .modules.assistant import Assistant
-from .modules.session import Session
+from .modules.session import Session
+from .modules.document import Document

sdk/python/ragflow/modules/dataset.py

+from typing import Optional, List
+
+from .document import Document
+
 from .base import Base
 
 
         res = res.json()
         if res.get("retmsg") == "success": return True
         raise Exception(res["retmsg"])
+
+    def list_docs(self, keywords: Optional[str] = None, offset: int = 0, limit: int = -1) -> List[Document]:
+        """
+        List the documents in the dataset, optionally filtering by keywords, with pagination support.
+
+        Args:
+            keywords (Optional[str]): A string of keywords to filter the documents. Defaults to None.
+            offset (int): The starting point for pagination. Defaults to 0.
+            limit (int): The maximum number of documents to return. Defaults to -1 (no limit).
+
+        Returns:
+            List[Document]: A list of Document objects.
+        """
+        # Construct the request payload for listing documents
+        payload = {
+            "kb_id": self.id,
+            "keywords": keywords,
+            "offset": offset,
+            "limit": limit
+        }
+
+        # Send the request to the server to list documents
+        res = self.get(f'/doc/dataset/{self.id}/documents', payload)
+        res_json = res.json()
+
+        # Handle response and error checking
+        if res_json.get("retmsg") != "success":
+            raise Exception(res_json.get("retmsg"))
+
+        # Parse the document data from the response
+        documents = []
+        for doc_data in res_json["data"].get("docs", []):
+            doc = Document(self.rag, doc_data)
+            documents.append(doc)
+
+        return documents

sdk/python/ragflow/modules/document.py

+
+from .base import Base
+
+
+
+class Document(Base):
+    def __init__(self, rag, res_dict):
+        self.id = ""
+        self.name = ""
+        self.thumbnail = None
+        self.kb_id = None
+        self.parser_method = ""
+        self.parser_config = {"pages": [[1, 1000000]]}
+        self.source_type = "local"
+        self.type = ""
+        self.created_by = ""
+        self.size = 0
+        self.token_num = 0
+        self.chunk_num = 0
+        self.progress = 0.0
+        self.progress_msg = ""
+        self.process_begin_at = None
+        self.process_duration = 0.0
+        for k in list(res_dict.keys()):
+            if k not in self.__dict__:
+                res_dict.pop(k)
+        super().__init__(rag, res_dict)
+
+    def save(self) -> bool:
+        """
+        Save the document details to the server.
+        """
+        res = self.post('/doc/save',
+                        {"id": self.id, "name": self.name, "thumbnail": self.thumbnail, "kb_id": self.kb_id,
+                         "parser_id": self.parser_method, "parser_config": self.parser_config.to_json(),
+                         "source_type": self.source_type, "type": self.type, "created_by": self.created_by,
+                         "size": self.size, "token_num": self.token_num, "chunk_num": self.chunk_num,
+                         "progress": self.progress, "progress_msg": self.progress_msg,
+                         "process_begin_at": self.process_begin_at, "process_duation": self.process_duration
+                         })
+        res = res.json()
+        if res.get("retmsg") == "success":
+            return True
+        raise Exception(res["retmsg"])
+
+    def delete(self) -> bool:
+        """
+        Delete the document from the server.
+        """
+        res = self.rm('/doc/delete',
+                      {"doc_id": self.id})
+        res = res.json()
+        if res.get("retmsg") == "success":
+            return True
+        raise Exception(res["retmsg"])
+
+    def download(self) -> bytes:
+        """
+        Download the document content from the server using the Flask API.
+
+        :return: The downloaded document content in bytes.
+        """
+        # Construct the URL for the API request using the document ID and knowledge base ID
+        res = self.get(f"/doc/{self.kb_id}/documents/{self.id}",
+                       {"headers": self.rag.authorization_header, "id": self.id, "name": self.name, "stream": True})
+
+        # Check the response status code to ensure the request was successful
+        if res.status_code == 200:
+            # Return the document content as bytes
+            return res.content
+        else:
+            # Handle the error and raise an exception
+            raise Exception(
+                f"Failed to download document. Server responded with: {res.status_code}, {res.text}"
+            )

sdk/python/ragflow/ragflow.py

 
 from .modules.assistant import Assistant
 from .modules.dataset import DataSet
-
+from .modules.document import Document
 
 class RAGFlow:
     def __init__(self, user_key, base_url, version='v1'):
                 result_list.append(Assistant(self, data))
             return result_list
         raise Exception(res["retmsg"])
+
+    def create_document(self, ds:DataSet, name: str, blob: bytes) -> bool:
+        url = f"/doc/dataset/{ds.id}/documents/upload"
+        files = {
+            'file': (name, blob)
+        }
+        data = {
+            'kb_id': ds.id
+        }
+        headers = {
+            'Authorization': f"Bearer {ds.rag.user_key}"
+        }
+
+        response = requests.post(self.api_url + url, data=data, files=files,
+                                 headers=headers)
+
+        if response.status_code == 200 and response.json().get('retmsg') == 'success':
+            return True
+        else:
+            raise Exception(f"Upload failed: {response.json().get('retmsg')}")
+
+        return False
+    def get_document(self, id: str = None, name: str = None) -> Document:
+        res = self.get("/doc/infos", {"id": id, "name": name})
+        res = res.json()
+        if res.get("retmsg") == "success":
+            return Document(self, res['data'])
+        raise Exception(res["retmsg"])
+

sdk/python/test/ragflow.txt

+{"data":null,"retcode":100,"retmsg":"TypeError(\"download_document() got an unexpected keyword argument 'tenant_id'\")"}

sdk/python/test/t_document.py

+from ragflow import RAGFlow, DataSet, Document
+
+from common import API_KEY, HOST_ADDRESS
+from test_sdkbase import TestSdk
+
+
+class TestDocument(TestSdk):
+    def test_upload_document_with_success(self):
+        """
+        Test ingesting a document into a dataset with success.
+        """
+        # Initialize RAGFlow instance
+        rag = RAGFlow(API_KEY, HOST_ADDRESS)
+
+        # Step 1: Create a new dataset
+        ds = rag.create_dataset(name="God")
+
+        # Ensure dataset creation was successful
+        assert isinstance(ds, DataSet), f"Failed to create dataset, error: {ds}"
+        assert ds.name == "God", "Dataset name does not match."
+
+        # Step 2: Create a new document
+        # The blob is the actual file content or a placeholder in this case
+        name = "TestDocument.txt"
+        blob = b"Sample document content for ingestion test."
+
+        res = rag.create_document(ds, name=name, blob=blob)
+
+        # Ensure document ingestion was successful
+        assert res is True, f"Failed to create document, error: {res}"
+
+    def test_get_detail_document_with_success(self):
+        """
+        Test getting a document's detail with success
+        """
+        rag = RAGFlow(API_KEY, HOST_ADDRESS)
+        doc = rag.get_document(name="TestDocument.txt")
+        assert isinstance(doc, Document), f"Failed to get dataset, error: {doc}."
+        assert doc.name == "TestDocument.txt", "Name does not match"
+
+    def test_update_document_with_success(self):
+        """
+        Test updating a document with success.
+        """
+        rag = RAGFlow(API_KEY, HOST_ADDRESS)
+        doc = rag.get_document(name="TestDocument.txt")
+        if isinstance(doc, Document):
+            doc.parser_method = "manual"
+            res = doc.save()
+            assert res is True, f"Failed to update document, error: {res}"
+        else:
+            assert False, f"Failed to get document, error: {doc}"
+
+    def test_download_document_with_success(self):
+        """
+        Test downloading a document with success.
+        """
+        # Initialize RAGFlow instance
+        rag = RAGFlow(API_KEY, HOST_ADDRESS)
+
+        # Retrieve a document
+        doc = rag.get_document(name="TestDocument.txt")
+
+        # Check if the retrieved document is of type Document
+        if isinstance(doc, Document):
+            # Download the document content and save it to a file
+            try:
+                with open("ragflow.txt", "wb+") as file:
+                    file.write(doc.download())
+                    # Print the document object for debugging
+                print(doc)
+
+                # Assert that the download was successful
+                assert True, "Document downloaded successfully."
+            except Exception as e:
+                # If an error occurs, raise an assertion error
+                assert False, f"Failed to download document, error: {str(e)}"
+        else:
+            # If the document retrieval fails, assert failure
+            assert False, f"Failed to get document, error: {doc}"
+
+    def test_list_all_documents_in_dataset_with_success(self):
+        """
+        Test list all documents into a dataset with success.
+        """
+        # Initialize RAGFlow instance
+        rag = RAGFlow(API_KEY, HOST_ADDRESS)
+
+        # Step 1: Create a new dataset
+        ds = rag.create_dataset(name="God2")
+
+        # Ensure dataset creation was successful
+        assert isinstance(ds, DataSet), f"Failed to create dataset, error: {ds}"
+        assert ds.name == "God2", "Dataset name does not match."
+
+        # Step 2: Create a new document
+        # The blob is the actual file content or a placeholder in this case
+        name1 = "Test Document111.txt"
+        blob1 = b"Sample document content for ingestion test111."
+        name2 = "Test Document222.txt"
+        blob2 = b"Sample document content for ingestion test222."
+
+        rag.create_document(ds, name=name1, blob=blob1)
+        rag.create_document(ds, name=name2, blob=blob2)
+        for d in ds.list_docs(keywords="test", offset=0, limit=12):
+            assert isinstance(d, Document)
+            print(d)
+
+    def test_delete_documents_in_dataset_with_success(self):
+        """
+        Test list all documents into a dataset with success.
+        """
+        # Initialize RAGFlow instance
+        rag = RAGFlow(API_KEY, HOST_ADDRESS)
+
+        # Step 1: Create a new dataset
+        ds = rag.create_dataset(name="God3")
+
+        # Ensure dataset creation was successful
+        assert isinstance(ds, DataSet), f"Failed to create dataset, error: {ds}"
+        assert ds.name == "God3", "Dataset name does not match."
+
+        # Step 2: Create a new document
+        # The blob is the actual file content or a placeholder in this case
+        name1 = "Test Document333.txt"
+        blob1 = b"Sample document content for ingestion test333."
+        name2 = "Test Document444.txt"
+        blob2 = b"Sample document content for ingestion test444."
+        name3='test.txt'
+        path='test_data/test.txt'
+        rag.create_document(ds, name=name3, blob=open(path, "rb").read())
+        rag.create_document(ds, name=name1, blob=blob1)
+        rag.create_document(ds, name=name2, blob=blob2)
+        for d in ds.list_docs(keywords="document", offset=0, limit=12):
+            assert isinstance(d, Document)
+            d.delete()
+            print(d)
+        remaining_docs = ds.list_docs(keywords="rag", offset=0, limit=12)
+        assert len(remaining_docs) == 0, "Documents were not properly deleted."
+
+
+
+
+