fix: MD5 and 8‑hex Suffix Collision Risk

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

api/.env.example

@@ -156,7 +156,7 @@ WEB_API_CORS_ALLOW_ORIGINS=http://localhost:3000,*
 CONSOLE_CORS_ALLOW_ORIGINS=http://localhost:3000,*
 
 # Vector database configuration
-# Supported values are `weaviate`, `qdrant`, `milvus`, `myscale`, `relyt`, `pgvector`, `pgvecto-rs`, `chroma`, `opensearch`, `oracle`, `tencent`, `elasticsearch`, `elasticsearch-ja`, `analyticdb`, `couchbase`, `vikingdb`, `oceanbase`, `opengauss`, `tablestore`,`vastbase`,`tidb`,`tidb_on_qdrant`,`baidu`,`lindorm`,`huawei_cloud`,`upstash`, `matrixone`.
+# Supported values are `weaviate`, `qdrant`, `milvus`, `myscale`, `relyt`, `pgvector`, `pgvecto-rs`, `chroma`, `opensearch`, `oracle`, `tencent`, `elasticsearch`, `elasticsearch-ja`, `analyticdb`, `couchbase`, `vikingdb`, `oceanbase`, `opengauss`, `tablestore`,`vastbase`,`tidb`,`tidb_on_qdrant`,`baidu`,`lindorm`,`huawei_cloud`,`upstash`, `matrixone`, `pinecone`.
 VECTOR_STORE=weaviate
 # Prefix used to create collection name in vector database
 VECTOR_INDEX_NAME_PREFIX=Vector_index
@@ -361,6 +361,17 @@ PROMPT_GENERATION_MAX_TOKENS=512
 CODE_GENERATION_MAX_TOKENS=1024
 PLUGIN_BASED_TOKEN_COUNTING_ENABLED=false
 
+
+# Pinecone configuration, only available when VECTOR_STORE is `pinecone`
+PINECONE_API_KEY=your-pinecone-api-key
+PINECONE_ENVIRONMENT=your-pinecone-environment
+PINECONE_INDEX_NAME=dify-index
+PINECONE_CLIENT_TIMEOUT=30
+PINECONE_BATCH_SIZE=100
+PINECONE_METRIC=cosine
+PINECONE_PODS=1
+PINECONE_POD_TYPE=s1
+
 # Mail configuration, support: resend, smtp, sendgrid
 MAIL_TYPE=
 # If using SendGrid, use the 'from' field for authentication if necessary.

api/configs/middleware/__init__.py

@@ -35,6 +35,7 @@ from .vdb.opensearch_config import OpenSearchConfig
 from .vdb.oracle_config import OracleConfig
 from .vdb.pgvector_config import PGVectorConfig
 from .vdb.pgvectors_config import PGVectoRSConfig
+from .vdb.pinecone_config import PineconeConfig
 from .vdb.qdrant_config import QdrantConfig
 from .vdb.relyt_config import RelytConfig
 from .vdb.tablestore_config import TableStoreConfig
@@ -331,6 +332,7 @@ class MiddlewareConfig(
     PGVectorConfig,
     VastbaseVectorConfig,
     PGVectoRSConfig,
+    PineconeConfig,
     QdrantConfig,
     RelytConfig,
     TencentVectorDBConfig,

api/configs/middleware/vdb/pinecone_config.py

@@ -0,0 +1,41 @@
+from typing import Optional
+
+from pydantic import Field, PositiveInt
+from pydantic_settings import BaseSettings
+
+
+class PineconeConfig(BaseSettings):
+    """
+    Configuration settings for Pinecone vector database
+    """
+
+    PINECONE_API_KEY: Optional[str] = Field(
+        description="API key for authenticating with Pinecone service",
+        default=None,
+    )
+
+    PINECONE_ENVIRONMENT: Optional[str] = Field(
+        description="Pinecone environment (e.g., 'us-west1-gcp', 'us-east-1-aws')",
+        default=None,
+    )
+
+    PINECONE_INDEX_NAME: Optional[str] = Field(
+        description="Default Pinecone index name",
+        default=None,
+    )
+
+    PINECONE_CLIENT_TIMEOUT: PositiveInt = Field(
+        description="Timeout in seconds for Pinecone client operations (default is 30 seconds)",
+        default=30,
+    )
+
+    PINECONE_BATCH_SIZE: PositiveInt = Field(
+        description="Batch size for Pinecone operations (default is 100)",
+        default=100,
+    )
+
+    PINECONE_METRIC: str = Field(
+        description="Distance metric for Pinecone index (cosine, euclidean, dotproduct)",
+        default="cosine",
+    )
+

api/controllers/console/auth/oauth_server.py

@@ -44,22 +44,19 @@ def oauth_server_access_token_required(view):
         if not oauth_provider_app or not isinstance(oauth_provider_app, OAuthProviderApp):
             raise BadRequest("Invalid oauth_provider_app")
 
-        if not request.headers.get("Authorization"):
-            raise BadRequest("Authorization is required")
-
         authorization_header = request.headers.get("Authorization")
         if not authorization_header:
             raise BadRequest("Authorization header is required")
 
-        parts = authorization_header.split(" ")
+        parts = authorization_header.strip().split(" ")
         if len(parts) != 2:
             raise BadRequest("Invalid Authorization header format")
 
-        token_type = parts[0]
-        if token_type != "Bearer":
+        token_type = parts[0].strip()
+        if token_type.lower() != "bearer":
             raise BadRequest("token_type is invalid")
 
-        access_token = parts[1]
+        access_token = parts[1].strip()
         if not access_token:
             raise BadRequest("access_token is required")
 
@@ -125,7 +122,10 @@ class OAuthServerUserTokenApi(Resource):
         parser.add_argument("refresh_token", type=str, required=False, location="json")
         parsed_args = parser.parse_args()
 
-        grant_type = OAuthGrantType(parsed_args["grant_type"])
+        try:
+            grant_type = OAuthGrantType(parsed_args["grant_type"])
+        except ValueError:
+            raise BadRequest("invalid grant_type")
 
         if grant_type == OAuthGrantType.AUTHORIZATION_CODE:
             if not parsed_args["code"]:
@@ -163,8 +163,6 @@ class OAuthServerUserTokenApi(Resource):
                     "refresh_token": refresh_token,
                 }
             )
-        else:
-            raise BadRequest("invalid grant_type")
 
 
 class OAuthServerUserAccountApi(Resource):

api/controllers/console/datasets/datasets.py

@@ -660,6 +660,7 @@ class DatasetRetrievalSettingApi(Resource):
                 | VectorType.BAIDU
                 | VectorType.VIKINGDB
                 | VectorType.UPSTASH
+                | VectorType.PINECONE
             ):
                 return {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH.value]}
             case (
@@ -711,6 +712,7 @@ class DatasetRetrievalSettingMockApi(Resource):
                 | VectorType.BAIDU
                 | VectorType.VIKINGDB
                 | VectorType.UPSTASH
+                | VectorType.PINECONE
             ):
                 return {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH.value]}
             case (

api/controllers/inner_api/wraps.py

@@ -1,8 +1,12 @@
 from base64 import b64encode
+from collections.abc import Callable
 from functools import wraps
 from hashlib import sha1
 from hmac import new as hmac_new
+from typing import ParamSpec, TypeVar
 
+P = ParamSpec("P")
+R = TypeVar("R")
 from flask import abort, request
 
 from configs import dify_config
@@ -10,9 +14,9 @@ from extensions.ext_database import db
 from models.model import EndUser
 
 
-def billing_inner_api_only(view):
+def billing_inner_api_only(view: Callable[P, R]):
     @wraps(view)
-    def decorated(*args, **kwargs):
+    def decorated(*args: P.args, **kwargs: P.kwargs):
         if not dify_config.INNER_API:
             abort(404)
 
@@ -26,9 +30,9 @@ def billing_inner_api_only(view):
     return decorated
 
 
-def enterprise_inner_api_only(view):
+def enterprise_inner_api_only(view: Callable[P, R]):
     @wraps(view)
-    def decorated(*args, **kwargs):
+    def decorated(*args: P.args, **kwargs: P.kwargs):
         if not dify_config.INNER_API:
             abort(404)
 
@@ -78,9 +82,9 @@ def enterprise_inner_api_user_auth(view):
     return decorated
 
 
-def plugin_inner_api_only(view):
+def plugin_inner_api_only(view: Callable[P, R]):
     @wraps(view)
-    def decorated(*args, **kwargs):
+    def decorated(*args: P.args, **kwargs: P.kwargs):
         if not dify_config.PLUGIN_DAEMON_KEY:
             abort(404)
 

api/core/rag/datasource/retrieval_service.py

@@ -24,7 +24,7 @@ default_retrieval_model = {
     "search_method": RetrievalMethod.SEMANTIC_SEARCH.value,
     "reranking_enable": False,
     "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
-    "top_k": 2,
+    "top_k": 4,
     "score_threshold_enabled": False,
 }
 

api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py

@@ -256,7 +256,7 @@ class AnalyticdbVectorOpenAPI:
         response = self._client.query_collection_data(request)
         documents = []
         for match in response.body.matches.match:
-            if match.score > score_threshold:
+            if match.score >= score_threshold:
                 metadata = json.loads(match.metadata.get("metadata_"))
                 metadata["score"] = match.score
                 doc = Document(
@@ -293,7 +293,7 @@ class AnalyticdbVectorOpenAPI:
         response = self._client.query_collection_data(request)
         documents = []
         for match in response.body.matches.match:
-            if match.score > score_threshold:
+            if match.score >= score_threshold:
                 metadata = json.loads(match.metadata.get("metadata_"))
                 metadata["score"] = match.score
                 doc = Document(

api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py

@@ -229,7 +229,7 @@ class AnalyticdbVectorBySql:
             documents = []
             for record in cur:
                 id, vector, score, page_content, metadata = record
-                if score > score_threshold:
+                if score >= score_threshold:
                     metadata["score"] = score
                     doc = Document(
                         page_content=page_content,

api/core/rag/datasource/vdb/baidu/baidu_vector.py

@@ -157,7 +157,7 @@ class BaiduVector(BaseVector):
             if meta is not None:
                 meta = json.loads(meta)
             score = row.get("score", 0.0)
-            if score > score_threshold:
+            if score >= score_threshold:
                 meta["score"] = score
                 doc = Document(page_content=row_data.get(self.field_text), metadata=meta)
                 docs.append(doc)

api/core/rag/datasource/vdb/chroma/chroma_vector.py

@@ -120,7 +120,7 @@ class ChromaVector(BaseVector):
             distance = distances[index]
             metadata = dict(metadatas[index])
             score = 1 - distance
-            if score > score_threshold:
+            if score >= score_threshold:
                 metadata["score"] = score
                 doc = Document(
                     page_content=documents[index],

api/core/rag/datasource/vdb/couchbase/couchbase_vector.py

@@ -304,7 +304,7 @@ class CouchbaseVector(BaseVector):
         return docs
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
-        top_k = kwargs.get("top_k", 2)
+        top_k = kwargs.get("top_k", 4)
         try:
             CBrequest = search.SearchRequest.create(search.QueryStringQuery("text:" + query))
             search_iter = self._scope.search(

api/core/rag/datasource/vdb/elasticsearch/elasticsearch_vector.py

@@ -216,7 +216,7 @@ class ElasticSearchVector(BaseVector):
         docs = []
         for doc, score in docs_and_scores:
             score_threshold = float(kwargs.get("score_threshold") or 0.0)
-            if score > score_threshold:
+            if score >= score_threshold:
                 if doc.metadata is not None:
                     doc.metadata["score"] = score
                     docs.append(doc)

api/core/rag/datasource/vdb/huawei/huawei_cloud_vector.py

@@ -127,7 +127,7 @@ class HuaweiCloudVector(BaseVector):
         docs = []
         for doc, score in docs_and_scores:
             score_threshold = float(kwargs.get("score_threshold") or 0.0)
-            if score > score_threshold:
+            if score >= score_threshold:
                 if doc.metadata is not None:
                     doc.metadata["score"] = score
             docs.append(doc)

api/core/rag/datasource/vdb/lindorm/lindorm_vector.py

@@ -275,7 +275,7 @@ class LindormVectorStore(BaseVector):
         docs = []
         for doc, score in docs_and_scores:
             score_threshold = kwargs.get("score_threshold", 0.0) or 0.0
-            if score > score_threshold:
+            if score >= score_threshold:
                 if doc.metadata is not None:
                     doc.metadata["score"] = score
                 docs.append(doc)

api/core/rag/datasource/vdb/opengauss/opengauss.py

@@ -194,7 +194,7 @@ class OpenGauss(BaseVector):
                 metadata, text, distance = record
                 score = 1 - distance
                 metadata["score"] = score
-                if score > score_threshold:
+                if score >= score_threshold:
                     docs.append(Document(page_content=text, metadata=metadata))
         return docs
 

api/core/rag/datasource/vdb/opensearch/opensearch_vector.py

@@ -211,7 +211,7 @@ class OpenSearchVector(BaseVector):
 
             metadata["score"] = hit["_score"]
             score_threshold = float(kwargs.get("score_threshold") or 0.0)
-            if hit["_score"] > score_threshold:
+            if hit["_score"] >= score_threshold:
                 doc = Document(page_content=hit["_source"].get(Field.CONTENT_KEY.value), metadata=metadata)
                 docs.append(doc)
 

api/core/rag/datasource/vdb/oracle/oraclevector.py

@@ -261,7 +261,7 @@ class OracleVector(BaseVector):
                     metadata, text, distance = record
                     score = 1 - distance
                     metadata["score"] = score
-                    if score > score_threshold:
+                    if score >= score_threshold:
                         docs.append(Document(page_content=text, metadata=metadata))
             conn.close()
         return docs

api/core/rag/datasource/vdb/pgvecto_rs/pgvecto_rs.py

@@ -202,7 +202,7 @@ class PGVectoRS(BaseVector):
             score = 1 - dis
             metadata["score"] = score
             score_threshold = float(kwargs.get("score_threshold") or 0.0)
-            if score > score_threshold:
+            if score >= score_threshold:
                 doc = Document(page_content=record.text, metadata=metadata)
                 docs.append(doc)
         return docs

api/core/rag/datasource/vdb/pgvector/pgvector.py

@@ -195,7 +195,7 @@ class PGVector(BaseVector):
                 metadata, text, distance = record
                 score = 1 - distance
                 metadata["score"] = score
-                if score > score_threshold:
+                if score >= score_threshold:
                     docs.append(Document(page_content=text, metadata=metadata))
         return docs
 

api/core/rag/datasource/vdb/pinecone/pinecone_vector.py

@@ -0,0 +1,341 @@
+import json
+import time
+from typing import Any, Optional
+
+from pinecone import Pinecone, ServerlessSpec
+from pydantic import BaseModel
+
+from configs import dify_config
+from core.rag.datasource.vdb.field import Field
+from core.rag.datasource.vdb.vector_base import BaseVector
+from core.rag.datasource.vdb.vector_factory import AbstractVectorFactory
+from core.rag.datasource.vdb.vector_type import VectorType
+from core.rag.embedding.embedding_base import Embeddings
+from core.rag.models.document import Document
+from extensions.ext_database import db
+from extensions.ext_redis import redis_client
+from models.dataset import Dataset, DatasetCollectionBinding
+
+
+class PineconeConfig(BaseModel):
+    """Pinecone configuration class"""
+    api_key: str
+    environment: str
+    index_name: Optional[str] = None
+    timeout: float = 30
+    batch_size: int = 100
+    metric: str = "cosine"
+
+
+class PineconeVector(BaseVector):
+    """Pinecone vector database concrete implementation class"""
+
+    def __init__(self, collection_name: str, group_id: str, config: PineconeConfig):
+        super().__init__(collection_name)
+        self._client_config = config
+        self._group_id = group_id
+
+        # Initialize Pinecone client with SSL configuration
+        try:
+            self._pc = Pinecone(
+                api_key=config.api_key,
+                # Configure SSL to handle connection issues
+                ssl_ca_certs=None,  # Use system default CA certificates
+            )
+        except Exception as e:
+            # Fallback to basic initialization if SSL config fails
+            self._pc = Pinecone(api_key=config.api_key)
+
+        # Normalize index name: lowercase, only a-z0-9- and <=45 chars
+        import re, hashlib
+        base_name = collection_name.lower()
+        base_name = re.sub(r'[^a-z0-9-]+', '-', base_name)  # replace invalid chars with '-'
+        base_name = re.sub(r'-+', '-', base_name).strip('-')
+        # Use longer secure suffix to reduce collision risk
+        suffix_len = 24  # 24 hex digits (96-bit entropy)
+        if len(base_name) > 45:
+            hash_suffix = hashlib.sha256(base_name.encode()).hexdigest()[:suffix_len]
+            truncated_name = base_name[:45-(suffix_len+1)].rstrip('-')
+            self._index_name = f"{truncated_name}-{hash_suffix}"
+        else:
+            self._index_name = base_name
+        # Guard empty name
+        if not self._index_name:
+            self._index_name = f"index-{hashlib.sha256(collection_name.encode()).hexdigest()[:suffix_len]}"
+        self._index = None
+        
+    def get_type(self) -> str:
+        """Return vector database type identifier"""
+        return "pinecone"
+
+    def _ensure_index_initialized(self) -> None:
+        """Ensure that self._index is attached to an existing Pinecone index."""
+        if self._index is not None:
+            return
+        try:
+            existing_indexes = self._pc.list_indexes().names()
+            if self._index_name in existing_indexes:
+                self._index = self._pc.Index(self._index_name)
+            else:
+                raise ValueError("Index not initialized. Please ingest documents to create index.")
+        except Exception:
+            raise 
+
+    def to_index_struct(self) -> dict:
+        """Generate index structure dictionary"""
+        return {
+            "type": self.get_type(),
+            "vector_store": {"class_prefix": self._collection_name}
+        }
+
+    def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs):
+        """Create vector index"""
+        if texts:
+            # Get vector dimension
+            vector_size = len(embeddings[0])
+
+            # Create Pinecone index
+            self.create_index(vector_size)
+
+            # Add vector data
+            self.add_texts(texts, embeddings, **kwargs)
+
+    def create_index(self, dimension: int):
+        """Create Pinecone index"""
+        lock_name = f"vector_indexing_lock_{self._index_name}"
+
+        with redis_client.lock(lock_name, timeout=30):
+            # Check Redis cache
+            index_exist_cache_key = f"vector_indexing_{self._index_name}"
+            if redis_client.get(index_exist_cache_key):
+                self._index = self._pc.Index(self._index_name)
+                return
+
+            # Check if index already exists
+            existing_indexes = self._pc.list_indexes().names()
+
+            if self._index_name not in existing_indexes:
+                # Create new index using ServerlessSpec
+                self._pc.create_index(
+                    name=self._index_name,
+                    dimension=dimension,
+                    metric=self._client_config.metric,
+                    spec=ServerlessSpec(
+                        cloud='aws',
+                        region=self._client_config.environment
+                    )
+                )
+
+                # Wait for index creation to complete
+                while not self._pc.describe_index(self._index_name).status['ready']:
+                    time.sleep(1)
+            else:
+                # Get index instance
+                self._index = self._pc.Index(self._index_name)
+
+            # Set cache
+            redis_client.set(index_exist_cache_key, 1, ex=3600)
+    
+    def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
+        """Batch add document vectors"""
+        if not self._index:
+            raise ValueError("Index not initialized. Call create() first.")
+
+        total_docs = len(documents)
+
+        uuids = self._get_uuids(documents)
+        batch_size = self._client_config.batch_size
+        added_ids = []
+
+        # Batch processing
+        total_batches = (total_docs + batch_size - 1) // batch_size  # Ceiling division
+        for batch_idx, i in enumerate(range(0, len(documents), batch_size), 1):
+            batch_documents = documents[i:i + batch_size]
+            batch_embeddings = embeddings[i:i + batch_size]
+            batch_uuids = uuids[i:i + batch_size]
+            batch_size_actual = len(batch_documents)
+
+            # Build Pinecone vector data (metadata must be primitives or list[str])
+            vectors_to_upsert = []
+            for doc, embedding, doc_id in zip(batch_documents, batch_embeddings, batch_uuids):
+                raw_meta = doc.metadata or {}
+                safe_meta: dict[str, Any] = {}
+                # lift common identifiers to top-level fields for filtering
+                for k, v in raw_meta.items():
+                    if isinstance(v, (str, int, float, bool)):
+                        safe_meta[k] = v
+                    elif isinstance(v, list) and all(isinstance(x, str) for x in v):
+                        safe_meta[k] = v
+                    else:
+                        safe_meta[k] = json.dumps(v, ensure_ascii=False)
+
+                # keep content as string metadata if needed
+                safe_meta[Field.CONTENT_KEY.value] = doc.page_content
+                # group id as string
+                safe_meta[Field.GROUP_KEY.value] = str(self._group_id)
+
+                vectors_to_upsert.append({
+                    "id": doc_id,
+                    "values": embedding,
+                    "metadata": safe_meta
+                })
+
+            # Batch insert to Pinecone
+            try:
+                self._index.upsert(vectors=vectors_to_upsert)
+                added_ids.extend(batch_uuids)
+            except Exception as e:
+                raise
+
+        return added_ids
+    
+    def search_by_vector(self, query_vector: list[float], **kwargs) -> list[Document]:
+        """Vector similarity search"""
+        # Lazily attach to an existing index if needed
+        self._ensure_index_initialized()
+
+        top_k = kwargs.get("top_k", 4)
+        score_threshold = float(kwargs.get("score_threshold", 0.0))
+
+        # Build filter conditions
+        filter_dict = {Field.GROUP_KEY.value: {"$eq": str(self._group_id)}}
+
+        # Document scope filtering
+        document_ids_filter = kwargs.get("document_ids_filter")
+        if document_ids_filter:
+            filter_dict["document_id"] = {"$in": document_ids_filter}
+
+        # Execute search
+        try:
+            response = self._index.query(
+                vector=query_vector,
+                top_k=top_k,
+                include_metadata=True,
+                filter=filter_dict
+            )
+        except Exception as e:
+            raise
+
+        # Convert results
+        docs = []
+        filtered_count = 0
+        for match in response.matches:
+            if match.score >= score_threshold:
+                page_content = match.metadata.get(Field.CONTENT_KEY.value, "")
+                metadata = dict(match.metadata or {})
+                metadata.pop(Field.CONTENT_KEY.value, None)
+                metadata.pop(Field.GROUP_KEY.value, None)
+                metadata["score"] = match.score
+
+                doc = Document(page_content=page_content, metadata=metadata)
+                docs.append(doc)
+            else:
+                filtered_count += 1
+
+        # Sort by similarity score in descending order
+        docs.sort(key=lambda x: x.metadata.get("score", 0), reverse=True)
+
+        return docs
+    
+    def search_by_full_text(self, query: str, **kwargs) -> list[Document]:
+        """Full-text search - Pinecone does not natively support it, returns empty list"""
+        return []
+    
+    def delete_by_metadata_field(self, key: str, value: str):
+        """Delete by metadata field"""
+        self._ensure_index_initialized()
+
+        try:
+            # Build filter conditions
+            filter_dict = {
+                Field.GROUP_KEY.value: {"$eq": self._group_id},
+                f"{Field.METADATA_KEY.value}.{key}": {"$eq": value}
+            }
+
+            # Pinecone delete operation
+            self._index.delete(filter=filter_dict)
+        except Exception as e:
+            # Ignore delete errors
+            pass
+    
+    def delete_by_ids(self, ids: list[str]) -> None:
+        """Batch delete by ID list"""
+        self._ensure_index_initialized()
+
+        try:
+            # Pinecone delete by ID
+            self._index.delete(ids=ids)
+        except Exception as e:
+            raise
+    
+    def delete(self) -> None:
+        """Delete all vector data for the entire dataset"""
+        self._ensure_index_initialized()
+
+        try:
+            # Delete all vectors by group_id
+            filter_dict = {Field.GROUP_KEY.value: {"$eq": self._group_id}}
+            self._index.delete(filter=filter_dict)
+        except Exception as e:
+            raise
+    
+    def text_exists(self, id: str) -> bool:
+        """Check if document exists"""
+        try:
+            self._ensure_index_initialized()
+        except Exception:
+            return False
+
+        try:
+            # Check if vector exists through query
+            response = self._index.fetch(ids=[id])
+            exists = id in response.vectors
+            return exists
+        except Exception as e:
+            return False
+
+
+class PineconeVectorFactory(AbstractVectorFactory):
+    """Pinecone vector database factory class"""
+    
+    def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> PineconeVector:
+        """Create PineconeVector instance"""
+        
+        # Determine index name
+        if dataset.collection_binding_id:
+            dataset_collection_binding = (
+                db.session.query(DatasetCollectionBinding)
+                .where(DatasetCollectionBinding.id == dataset.collection_binding_id)
+                .one_or_none()
+            )
+            if dataset_collection_binding:
+                collection_name = dataset_collection_binding.collection_name
+            else:
+                raise ValueError("Dataset Collection Bindings does not exist!")
+        else:
+            if dataset.index_struct_dict:
+                class_prefix: str = dataset.index_struct_dict["vector_store"]["class_prefix"]
+                collection_name = class_prefix
+            else:
+                dataset_id = dataset.id
+                collection_name = Dataset.gen_collection_name_by_id(dataset_id)
+        
+        # Set index structure
+        if not dataset.index_struct_dict:
+            dataset.index_struct = json.dumps(
+                self.gen_index_struct_dict("pinecone", collection_name)
+            )
+        
+        # Create PineconeVector instance
+        return PineconeVector(
+            collection_name=collection_name,
+            group_id=dataset.id,
+            config=PineconeConfig(
+                api_key=dify_config.PINECONE_API_KEY or "",
+                environment=dify_config.PINECONE_ENVIRONMENT or "",
+                index_name=dify_config.PINECONE_INDEX_NAME,
+                timeout=dify_config.PINECONE_CLIENT_TIMEOUT,
+                batch_size=dify_config.PINECONE_BATCH_SIZE,
+                metric=dify_config.PINECONE_METRIC,
+            ),
+        )

api/core/rag/datasource/vdb/pyvastbase/vastbase_vector.py

@@ -170,7 +170,7 @@ class VastbaseVector(BaseVector):
                 metadata, text, distance = record
                 score = 1 - distance
                 metadata["score"] = score
-                if score > score_threshold:
+                if score >= score_threshold:
                     docs.append(Document(page_content=text, metadata=metadata))
         return docs
 

api/core/rag/datasource/vdb/qdrant/qdrant_vector.py

@@ -369,7 +369,7 @@ class QdrantVector(BaseVector):
                 continue
             metadata = result.payload.get(Field.METADATA_KEY.value) or {}
             # duplicate check score threshold
-            if result.score > score_threshold:
+            if result.score >= score_threshold:
                 metadata["score"] = result.score
                 doc = Document(
                     page_content=result.payload.get(Field.CONTENT_KEY.value, ""),

api/core/rag/datasource/vdb/relyt/relyt_vector.py

@@ -233,7 +233,7 @@ class RelytVector(BaseVector):
         docs = []
         for document, score in results:
             score_threshold = float(kwargs.get("score_threshold") or 0.0)
-            if 1 - score > score_threshold:
+            if 1 - score >= score_threshold:
                 docs.append(document)
         return docs
 

api/core/rag/datasource/vdb/tablestore/tablestore_vector.py

@@ -300,7 +300,7 @@ class TableStoreVector(BaseVector):
         )
         documents = []
         for search_hit in search_response.search_hits:
-            if search_hit.score > score_threshold:
+            if search_hit.score >= score_threshold:
                 ots_column_map = {}
                 for col in search_hit.row[1]:
                     ots_column_map[col[0]] = col[1]

api/core/rag/datasource/vdb/tencent/tencent_vector.py

@@ -291,7 +291,7 @@ class TencentVector(BaseVector):
                 score = 1 - result.get("score", 0.0)
             else:
                 score = result.get("score", 0.0)
-            if score > score_threshold:
+            if score >= score_threshold:
                 meta["score"] = score
                 doc = Document(page_content=result.get(self.field_text), metadata=meta)
                 docs.append(doc)

api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_on_qdrant_vector.py

@@ -351,7 +351,7 @@ class TidbOnQdrantVector(BaseVector):
             metadata = result.payload.get(Field.METADATA_KEY.value) or {}
             # duplicate check score threshold
             score_threshold = kwargs.get("score_threshold") or 0.0
-            if result.score > score_threshold:
+            if result.score >= score_threshold:
                 metadata["score"] = result.score
                 doc = Document(
                     page_content=result.payload.get(Field.CONTENT_KEY.value, ""),

api/core/rag/datasource/vdb/upstash/upstash_vector.py

@@ -110,7 +110,7 @@ class UpstashVector(BaseVector):
             score = record.score
             if metadata is not None and text is not None:
                 metadata["score"] = score
-                if score > score_threshold:
+                if score >= score_threshold:
                     docs.append(Document(page_content=text, metadata=metadata))
         return docs
 

api/core/rag/datasource/vdb/vector_factory.py

@@ -86,6 +86,10 @@ class Vector:
                 from core.rag.datasource.vdb.pgvecto_rs.pgvecto_rs import PGVectoRSFactory
 
                 return PGVectoRSFactory
+            case VectorType.PINECONE:
+                from core.rag.datasource.vdb.pinecone.pinecone_vector import PineconeVectorFactory
+
+                return PineconeVectorFactory
             case VectorType.QDRANT:
                 from core.rag.datasource.vdb.qdrant.qdrant_vector import QdrantVectorFactory
 

api/core/rag/datasource/vdb/vector_type.py

@@ -31,3 +31,4 @@ class VectorType(StrEnum):
     HUAWEI_CLOUD = "huawei_cloud"
     MATRIXONE = "matrixone"
     CLICKZETTA = "clickzetta"
+    PINECONE = "pinecone"

api/core/rag/datasource/vdb/vikingdb/vikingdb_vector.py

@@ -192,7 +192,7 @@ class VikingDBVector(BaseVector):
             metadata = result.fields.get(vdb_Field.METADATA_KEY.value)
             if metadata is not None:
                 metadata = json.loads(metadata)
-            if result.score > score_threshold:
+            if result.score >= score_threshold:
                 metadata["score"] = result.score
                 doc = Document(page_content=result.fields.get(vdb_Field.CONTENT_KEY.value), metadata=metadata)
                 docs.append(doc)

api/core/rag/datasource/vdb/weaviate/weaviate_vector.py

@@ -220,7 +220,7 @@ class WeaviateVector(BaseVector):
         for doc, score in docs_and_scores:
             score_threshold = float(kwargs.get("score_threshold") or 0.0)
             # check score threshold
-            if score > score_threshold:
+            if score >= score_threshold:
                 if doc.metadata is not None:
                     doc.metadata["score"] = score
                     docs.append(doc)

api/core/rag/extractor/excel_extractor.py

@@ -10,6 +10,23 @@ from core.rag.extractor.extractor_base import BaseExtractor
 from core.rag.models.document import Document
 
 
+def _format_cell_value(value) -> str:
+    if pd.isna(value):
+        return ""
+    
+    if isinstance(value, (int, float)):
+        if isinstance(value, float):
+            if value.is_integer():
+                return str(int(value))
+            else:
+                formatted = f"{value:f}"
+                return formatted.rstrip('0').rstrip('.')
+        else:
+            return str(value)
+    
+    return str(value)
+
+
 class ExcelExtractor(BaseExtractor):
     """Load Excel files.
 
@@ -49,10 +66,12 @@ class ExcelExtractor(BaseExtractor):
                                 row=cast(int, index) + 2, column=col_index + 1
                             )  # +2 to account for header and 1-based index
                             if cell.hyperlink:
-                                value = f"[{v}]({cell.hyperlink.target})"
+                                formatted_v = _format_cell_value(v)
+                                value = f"[{formatted_v}]({cell.hyperlink.target})"
                                 page_content.append(f'"{k}":"{value}"')
                             else:
-                                page_content.append(f'"{k}":"{v}"')
+                                formatted_v = _format_cell_value(v)
+                                page_content.append(f'"{k}":"{formatted_v}"')
                     documents.append(
                         Document(page_content=";".join(page_content), metadata={"source": self._file_path})
                     )
@@ -67,7 +86,8 @@ class ExcelExtractor(BaseExtractor):
                     page_content = []
                     for k, v in row.items():
                         if pd.notna(v):
-                            page_content.append(f'"{k}":"{v}"')
+                            formatted_v = _format_cell_value(v)
+                            page_content.append(f'"{k}":"{formatted_v}"')
                     documents.append(
                         Document(page_content=";".join(page_content), metadata={"source": self._file_path})
                     )

api/core/rag/index_processor/processor/paragraph_index_processor.py

@@ -123,7 +123,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor):
         for result in results:
             metadata = result.metadata
             metadata["score"] = result.score
-            if result.score > score_threshold:
+            if result.score >= score_threshold:
                 doc = Document(page_content=result.page_content, metadata=metadata)
                 docs.append(doc)
         return docs

api/core/rag/index_processor/processor/parent_child_index_processor.py

@@ -162,7 +162,7 @@ class ParentChildIndexProcessor(BaseIndexProcessor):
         for result in results:
             metadata = result.metadata
             metadata["score"] = result.score
-            if result.score > score_threshold:
+            if result.score >= score_threshold:
                 doc = Document(page_content=result.page_content, metadata=metadata)
                 docs.append(doc)
         return docs

api/core/rag/index_processor/processor/qa_index_processor.py

@@ -158,7 +158,7 @@ class QAIndexProcessor(BaseIndexProcessor):
         for result in results:
             metadata = result.metadata
             metadata["score"] = result.score
-            if result.score > score_threshold:
+            if result.score >= score_threshold:
                 doc = Document(page_content=result.page_content, metadata=metadata)
                 docs.append(doc)
         return docs

api/core/rag/retrieval/dataset_retrieval.py

@@ -65,7 +65,7 @@ default_retrieval_model: dict[str, Any] = {
     "search_method": RetrievalMethod.SEMANTIC_SEARCH.value,
     "reranking_enable": False,
     "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
-    "top_k": 2,
+    "top_k": 4,
     "score_threshold_enabled": False,
 }
 
@@ -647,7 +647,7 @@ class DatasetRetrieval:
                             retrieval_method=retrieval_model["search_method"],
                             dataset_id=dataset.id,
                             query=query,
-                            top_k=retrieval_model.get("top_k") or 2,
+                            top_k=retrieval_model.get("top_k") or 4,
                             score_threshold=retrieval_model.get("score_threshold", 0.0)
                             if retrieval_model["score_threshold_enabled"]
                             else 0.0,
@@ -743,7 +743,7 @@ class DatasetRetrieval:
             tool = DatasetMultiRetrieverTool.from_dataset(
                 dataset_ids=[dataset.id for dataset in available_datasets],
                 tenant_id=tenant_id,
-                top_k=retrieve_config.top_k or 2,
+                top_k=retrieve_config.top_k or 4,
                 score_threshold=retrieve_config.score_threshold,
                 hit_callbacks=[hit_callback],
                 return_resource=return_resource,

api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py

@@ -181,7 +181,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
                     retrieval_method="keyword_search",
                     dataset_id=dataset.id,
                     query=query,
-                    top_k=retrieval_model.get("top_k") or 2,
+                    top_k=retrieval_model.get("top_k") or 4,
                 )
                 if documents:
                     all_documents.extend(documents)
@@ -192,7 +192,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
                         retrieval_method=retrieval_model["search_method"],
                         dataset_id=dataset.id,
                         query=query,
-                        top_k=retrieval_model.get("top_k") or 2,
+                        top_k=retrieval_model.get("top_k") or 4,
                         score_threshold=retrieval_model.get("score_threshold", 0.0)
                         if retrieval_model["score_threshold_enabled"]
                         else 0.0,

api/core/tools/utils/dataset_retriever/dataset_retriever_base_tool.py

@@ -13,7 +13,7 @@ class DatasetRetrieverBaseTool(BaseModel, ABC):
     name: str = "dataset"
     description: str = "use this to retrieve a dataset. "
     tenant_id: str
-    top_k: int = 2
+    top_k: int = 4
     score_threshold: Optional[float] = None
     hit_callbacks: list[DatasetIndexToolCallbackHandler] = []
     return_resource: bool

api/core/workflow/nodes/document_extractor/node.py

@@ -485,6 +485,24 @@ def _extract_text_from_csv(file_content: bytes) -> str:
         raise TextExtractionError(f"Failed to extract text from CSV: {str(e)}") from e
 
 
+def _format_cell_value_for_markdown(value) -> str:
+    """格式化单元格值，避免科学计数法"""
+    if pd.isna(value):
+        return ""
+    
+    if isinstance(value, (int, float)):
+        if isinstance(value, float):
+            if value.is_integer():
+                return str(int(value))
+            else:
+                formatted = f"{value:f}"
+                return formatted.rstrip('0').rstrip('.')
+        else:
+            return str(value)
+    
+    return str(value)
+
+
 def _extract_text_from_excel(file_content: bytes) -> str:
     """Extract text from an Excel file using pandas."""
 
@@ -499,7 +517,8 @@ def _extract_text_from_excel(file_content: bytes) -> str:
         # Construct the data rows
         data_rows = []
         for _, row in df.iterrows():
-            data_row = "| " + " | ".join(map(str, row)) + " |"
+            formatted_row = [_format_cell_value_for_markdown(cell) for cell in row]
+            data_row = "| " + " | ".join(formatted_row) + " |"
             data_rows.append(data_row)
 
         # Combine all rows into a single string

api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py

@@ -78,7 +78,7 @@ default_retrieval_model = {
     "search_method": RetrievalMethod.SEMANTIC_SEARCH.value,
     "reranking_enable": False,
     "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
-    "top_k": 2,
+    "top_k": 4,
     "score_threshold_enabled": False,
 }
 

api/pyproject.toml

@@ -88,6 +88,7 @@ dependencies = [
     "httpx-sse>=0.4.0",
     "sendgrid~=6.12.3",
     "flask-restx>=1.3.0",
+    "pinecone>=7.3.0",
 ]
 # Before adding new dependency, consider place it in
 # alphabet order (a-z) and suitable group.

api/services/dataset_service.py

@@ -1149,7 +1149,7 @@ class DocumentService:
                         "search_method": RetrievalMethod.SEMANTIC_SEARCH.value,
                         "reranking_enable": False,
                         "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
-                        "top_k": 2,
+                        "top_k": 4,
                         "score_threshold_enabled": False,
                     }
 
@@ -1612,7 +1612,7 @@ class DocumentService:
                 search_method=RetrievalMethod.SEMANTIC_SEARCH.value,
                 reranking_enable=False,
                 reranking_model=RerankingModel(reranking_provider_name="", reranking_model_name=""),
-                top_k=2,
+                top_k=4,
                 score_threshold_enabled=False,
             )
         # save dataset

api/services/hit_testing_service.py

@@ -18,7 +18,7 @@ default_retrieval_model = {
     "search_method": RetrievalMethod.SEMANTIC_SEARCH.value,
     "reranking_enable": False,
     "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
-    "top_k": 2,
+    "top_k": 4,
     "score_threshold_enabled": False,
 }
 
@@ -66,7 +66,7 @@ class HitTestingService:
             retrieval_method=retrieval_model.get("search_method", "semantic_search"),
             dataset_id=dataset.id,
             query=query,
-            top_k=retrieval_model.get("top_k", 2),
+            top_k=retrieval_model.get("top_k", 4),
             score_threshold=retrieval_model.get("score_threshold", 0.0)
             if retrieval_model["score_threshold_enabled"]
             else 0.0,

api/tests/integration_tests/vdb/pinecone/test_pinecone.py

@@ -0,0 +1,30 @@
+from core.rag.datasource.vdb.pinecone.pinecone_vector import PineconeConfig, PineconeVector
+from core.rag.models.document import Document
+from tests.integration_tests.vdb.test_vector_store import (
+    AbstractVectorTest,
+    setup_mock_redis,
+)
+
+
+class PineconeVectorTest(AbstractVectorTest):
+    def __init__(self):
+        super().__init__()
+        self.attributes = ["doc_id", "dataset_id", "document_id", "doc_hash"]
+        self.vector = PineconeVector(
+            collection_name=self.collection_name,
+            group_id=self.dataset_id,
+            config=PineconeConfig(
+                api_key="test_api_key",
+                environment="test_environment",
+                index_name="test_index",
+            ),
+        )
+
+    def search_by_vector(self):
+        super().search_by_vector()
+
+
+def test_pinecone_vector(setup_mock_redis):
+
+
+    PineconeVectorTest().run_all_tests()

docker/docker-compose.middleware.yaml

@@ -20,7 +20,17 @@ services:
     ports:
       - "${EXPOSE_POSTGRES_PORT:-5432}:5432"
     healthcheck:
-      test: [ 'CMD', 'pg_isready', '-h', 'db', '-U', '${PGUSER:-postgres}', '-d', '${POSTGRES_DB:-dify}' ]
+      test:
+        [
+          "CMD",
+          "pg_isready",
+          "-h",
+          "db",
+          "-U",
+          "${PGUSER:-postgres}",
+          "-d",
+          "${POSTGRES_DB:-dify}",
+        ]
       interval: 1s
       timeout: 3s
       retries: 30
@@ -41,7 +51,11 @@ services:
     ports:
       - "${EXPOSE_REDIS_PORT:-6379}:6379"
     healthcheck:
-      test: [ 'CMD-SHELL', 'redis-cli -a ${REDIS_PASSWORD:-difyai123456} ping | grep -q PONG' ]
+      test:
+        [
+          "CMD-SHELL",
+          "redis-cli -a ${REDIS_PASSWORD:-difyai123456} ping | grep -q PONG",
+        ]
 
   # The DifySandbox
   sandbox:
@@ -65,13 +79,13 @@ services:
       - ./volumes/sandbox/dependencies:/dependencies
       - ./volumes/sandbox/conf:/conf
     healthcheck:
-      test: [ "CMD", "curl", "-f", "http://localhost:8194/health" ]
+      test: ["CMD", "curl", "-f", "http://localhost:8194/health"]
     networks:
       - ssrf_proxy_network
 
   # plugin daemon
   plugin_daemon:
-    image: langgenius/dify-plugin-daemon:0.2.0-local
+    image: langgenius/dify-plugin-daemon:0.3.0-local
     restart: always
     env_file:
       - ./middleware.env
@@ -94,7 +108,6 @@ services:
       PLUGIN_REMOTE_INSTALLING_HOST: ${PLUGIN_DEBUGGING_HOST:-0.0.0.0}
       PLUGIN_REMOTE_INSTALLING_PORT: ${PLUGIN_DEBUGGING_PORT:-5003}
       PLUGIN_WORKING_PATH: ${PLUGIN_WORKING_PATH:-/app/storage/cwd}
-      FORCE_VERIFYING_SIGNATURE: ${FORCE_VERIFYING_SIGNATURE:-true}
       PYTHON_ENV_INIT_TIMEOUT: ${PLUGIN_PYTHON_ENV_INIT_TIMEOUT:-120}
       PLUGIN_MAX_EXECUTION_TIMEOUT: ${PLUGIN_MAX_EXECUTION_TIMEOUT:-600}
       PIP_MIRROR_URL: ${PIP_MIRROR_URL:-}
@@ -126,6 +139,9 @@ services:
       VOLCENGINE_TOS_ACCESS_KEY: ${PLUGIN_VOLCENGINE_TOS_ACCESS_KEY:-}
       VOLCENGINE_TOS_SECRET_KEY: ${PLUGIN_VOLCENGINE_TOS_SECRET_KEY:-}
       VOLCENGINE_TOS_REGION: ${PLUGIN_VOLCENGINE_TOS_REGION:-}
+      THIRD_PARTY_SIGNATURE_VERIFICATION_ENABLED: true
+      THIRD_PARTY_SIGNATURE_VERIFICATION_PUBLIC_KEYS: /app/keys/publickey.pem
+      FORCE_VERIFYING_SIGNATURE: false
     ports:
       - "${EXPOSE_PLUGIN_DAEMON_PORT:-5002}:${PLUGIN_DAEMON_PORT:-5002}"
       - "${EXPOSE_PLUGIN_DEBUGGING_PORT:-5003}:${PLUGIN_DEBUGGING_PORT:-5003}"
@@ -141,7 +157,12 @@ services:
     volumes:
       - ./ssrf_proxy/squid.conf.template:/etc/squid/squid.conf.template
       - ./ssrf_proxy/docker-entrypoint.sh:/docker-entrypoint-mount.sh
-    entrypoint: [ "sh", "-c", "cp /docker-entrypoint-mount.sh /docker-entrypoint.sh && sed -i 's/\r$$//' /docker-entrypoint.sh && chmod +x /docker-entrypoint.sh && /docker-entrypoint.sh" ]
+    entrypoint:
+      [
+        "sh",
+        "-c",
+        "cp /docker-entrypoint-mount.sh /docker-entrypoint.sh && sed -i 's/\r$$//' /docker-entrypoint.sh && chmod +x /docker-entrypoint.sh && /docker-entrypoint.sh",
+      ]
     env_file:
       - ./middleware.env
     environment:

docker/docker-compose.yaml

@@ -10,7 +10,7 @@ x-shared-env: &shared-api-worker-env
   SERVICE_API_URL: ${SERVICE_API_URL:-}
   APP_API_URL: ${APP_API_URL:-}
   APP_WEB_URL: ${APP_WEB_URL:-}
-  FILES_URL: ${FILES_URL:-}
+  FILES_URL: ${FILES_URL:-http://api:5001}
   INTERNAL_FILES_URL: ${INTERNAL_FILES_URL:-}
   LANG: ${LANG:-en_US.UTF-8}
   LC_ALL: ${LC_ALL:-en_US.UTF-8}
@@ -62,6 +62,7 @@ x-shared-env: &shared-api-worker-env
   SQLALCHEMY_ECHO: ${SQLALCHEMY_ECHO:-false}
   SQLALCHEMY_POOL_PRE_PING: ${SQLALCHEMY_POOL_PRE_PING:-false}
   SQLALCHEMY_POOL_USE_LIFO: ${SQLALCHEMY_POOL_USE_LIFO:-false}
+  SQLALCHEMY_POOL_TIMEOUT: ${SQLALCHEMY_POOL_TIMEOUT:-30}
   POSTGRES_MAX_CONNECTIONS: ${POSTGRES_MAX_CONNECTIONS:-100}
   POSTGRES_SHARED_BUFFERS: ${POSTGRES_SHARED_BUFFERS:-128MB}
   POSTGRES_WORK_MEM: ${POSTGRES_WORK_MEM:-4MB}
@@ -285,6 +286,8 @@ x-shared-env: &shared-api-worker-env
   BAIDU_VECTOR_DB_DATABASE: ${BAIDU_VECTOR_DB_DATABASE:-dify}
   BAIDU_VECTOR_DB_SHARD: ${BAIDU_VECTOR_DB_SHARD:-1}
   BAIDU_VECTOR_DB_REPLICAS: ${BAIDU_VECTOR_DB_REPLICAS:-3}
+  BAIDU_VECTOR_DB_INVERTED_INDEX_ANALYZER: ${BAIDU_VECTOR_DB_INVERTED_INDEX_ANALYZER:-DEFAULT_ANALYZER}
+  BAIDU_VECTOR_DB_INVERTED_INDEX_PARSER_MODE: ${BAIDU_VECTOR_DB_INVERTED_INDEX_PARSER_MODE:-COARSE_MODE}
   VIKINGDB_ACCESS_KEY: ${VIKINGDB_ACCESS_KEY:-your-ak}
   VIKINGDB_SECRET_KEY: ${VIKINGDB_SECRET_KEY:-your-sk}
   VIKINGDB_REGION: ${VIKINGDB_REGION:-cn-shanghai}
@@ -292,9 +295,10 @@ x-shared-env: &shared-api-worker-env
   VIKINGDB_SCHEMA: ${VIKINGDB_SCHEMA:-http}
   VIKINGDB_CONNECTION_TIMEOUT: ${VIKINGDB_CONNECTION_TIMEOUT:-30}
   VIKINGDB_SOCKET_TIMEOUT: ${VIKINGDB_SOCKET_TIMEOUT:-30}
-  LINDORM_URL: ${LINDORM_URL:-http://lindorm:30070}
-  LINDORM_USERNAME: ${LINDORM_USERNAME:-lindorm}
-  LINDORM_PASSWORD: ${LINDORM_PASSWORD:-lindorm}
+  LINDORM_URL: ${LINDORM_URL:-http://localhost:30070}
+  LINDORM_USERNAME: ${LINDORM_USERNAME:-admin}
+  LINDORM_PASSWORD: ${LINDORM_PASSWORD:-admin}
+  LINDORM_USING_UGC: ${LINDORM_USING_UGC:-True}
   LINDORM_QUERY_TIMEOUT: ${LINDORM_QUERY_TIMEOUT:-1}
   OCEANBASE_VECTOR_HOST: ${OCEANBASE_VECTOR_HOST:-oceanbase}
   OCEANBASE_VECTOR_PORT: ${OCEANBASE_VECTOR_PORT:-2881}
@@ -304,6 +308,7 @@ x-shared-env: &shared-api-worker-env
   OCEANBASE_CLUSTER_NAME: ${OCEANBASE_CLUSTER_NAME:-difyai}
   OCEANBASE_MEMORY_LIMIT: ${OCEANBASE_MEMORY_LIMIT:-6G}
   OCEANBASE_ENABLE_HYBRID_SEARCH: ${OCEANBASE_ENABLE_HYBRID_SEARCH:-false}
+  OCEANBASE_FULLTEXT_PARSER: ${OCEANBASE_FULLTEXT_PARSER:-ik}
   OPENGAUSS_HOST: ${OPENGAUSS_HOST:-opengauss}
   OPENGAUSS_PORT: ${OPENGAUSS_PORT:-6600}
   OPENGAUSS_USER: ${OPENGAUSS_USER:-postgres}
@@ -372,6 +377,7 @@ x-shared-env: &shared-api-worker-env
   INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH: ${INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH:-4000}
   INVITE_EXPIRY_HOURS: ${INVITE_EXPIRY_HOURS:-72}
   RESET_PASSWORD_TOKEN_EXPIRY_MINUTES: ${RESET_PASSWORD_TOKEN_EXPIRY_MINUTES:-5}
+  EMAIL_REGISTER_TOKEN_EXPIRY_MINUTES: ${EMAIL_REGISTER_TOKEN_EXPIRY_MINUTES:-5}
   CHANGE_EMAIL_TOKEN_EXPIRY_MINUTES: ${CHANGE_EMAIL_TOKEN_EXPIRY_MINUTES:-5}
   OWNER_TRANSFER_TOKEN_EXPIRY_MINUTES: ${OWNER_TRANSFER_TOKEN_EXPIRY_MINUTES:-5}
   CODE_EXECUTION_ENDPOINT: ${CODE_EXECUTION_ENDPOINT:-http://sandbox:8194}
@@ -394,6 +400,10 @@ x-shared-env: &shared-api-worker-env
   MAX_VARIABLE_SIZE: ${MAX_VARIABLE_SIZE:-204800}
   WORKFLOW_PARALLEL_DEPTH_LIMIT: ${WORKFLOW_PARALLEL_DEPTH_LIMIT:-3}
   WORKFLOW_FILE_UPLOAD_LIMIT: ${WORKFLOW_FILE_UPLOAD_LIMIT:-10}
+  GRAPH_ENGINE_MIN_WORKERS: ${GRAPH_ENGINE_MIN_WORKERS:-1}
+  GRAPH_ENGINE_MAX_WORKERS: ${GRAPH_ENGINE_MAX_WORKERS:-10}
+  GRAPH_ENGINE_SCALE_UP_THRESHOLD: ${GRAPH_ENGINE_SCALE_UP_THRESHOLD:-3}
+  GRAPH_ENGINE_SCALE_DOWN_IDLE_TIME: ${GRAPH_ENGINE_SCALE_DOWN_IDLE_TIME:-5.0}
   WORKFLOW_NODE_EXECUTION_STORAGE: ${WORKFLOW_NODE_EXECUTION_STORAGE:-rdbms}
   CORE_WORKFLOW_EXECUTION_REPOSITORY: ${CORE_WORKFLOW_EXECUTION_REPOSITORY:-core.repositories.sqlalchemy_workflow_execution_repository.SQLAlchemyWorkflowExecutionRepository}
   CORE_WORKFLOW_NODE_EXECUTION_REPOSITORY: ${CORE_WORKFLOW_NODE_EXECUTION_REPOSITORY:-core.repositories.sqlalchemy_workflow_node_execution_repository.SQLAlchemyWorkflowNodeExecutionRepository}
@@ -570,6 +580,7 @@ x-shared-env: &shared-api-worker-env
   QUEUE_MONITOR_INTERVAL: ${QUEUE_MONITOR_INTERVAL:-30}
   SWAGGER_UI_ENABLED: ${SWAGGER_UI_ENABLED:-true}
   SWAGGER_UI_PATH: ${SWAGGER_UI_PATH:-/swagger-ui.html}
+  DSL_EXPORT_ENCRYPT_DATASET_ID: ${DSL_EXPORT_ENCRYPT_DATASET_ID:-true}
   ENABLE_CLEAN_EMBEDDING_CACHE_TASK: ${ENABLE_CLEAN_EMBEDDING_CACHE_TASK:-false}
   ENABLE_CLEAN_UNUSED_DATASETS_TASK: ${ENABLE_CLEAN_UNUSED_DATASETS_TASK:-false}
   ENABLE_CREATE_TIDB_SERVERLESS_TASK: ${ENABLE_CREATE_TIDB_SERVERLESS_TASK:-false}
@@ -582,7 +593,7 @@ x-shared-env: &shared-api-worker-env
 services:
   # API service
   api:
-    image: langgenius/dify-api:1.8.0
+    image: langgenius/dify-api:1.9.0
     restart: always
     environment:
       # Use the shared environment variables.
@@ -611,7 +622,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:1.8.0
+    image: langgenius/dify-api:1.9.0
     restart: always
     environment:
       # Use the shared environment variables.
@@ -638,7 +649,7 @@ services:
   # worker_beat service
   # Celery beat for scheduling periodic tasks.
   worker_beat:
-    image: langgenius/dify-api:1.8.0
+    image: langgenius/dify-api:1.9.0
     restart: always
     environment:
       # Use the shared environment variables.
@@ -656,7 +667,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:1.8.0
+    image: langgenius/dify-web:1.9.0
     restart: always
     environment:
       CONSOLE_API_URL: ${CONSOLE_API_URL:-}
@@ -698,7 +709,17 @@ services:
     volumes:
       - ./volumes/db/data:/var/lib/postgresql/data
     healthcheck:
-      test: [ 'CMD', 'pg_isready', '-h', 'db', '-U', '${PGUSER:-postgres}', '-d', '${POSTGRES_DB:-dify}' ]
+      test:
+        [
+          "CMD",
+          "pg_isready",
+          "-h",
+          "db",
+          "-U",
+          "${PGUSER:-postgres}",
+          "-d",
+          "${POSTGRES_DB:-dify}",
+        ]
       interval: 1s
       timeout: 3s
       retries: 60
@@ -715,7 +736,11 @@ services:
     # Set the redis password when startup redis server.
     command: redis-server --requirepass ${REDIS_PASSWORD:-difyai123456}
     healthcheck:
-      test: [ 'CMD-SHELL', 'redis-cli -a ${REDIS_PASSWORD:-difyai123456} ping | grep -q PONG' ]
+      test:
+        [
+          "CMD-SHELL",
+          "redis-cli -a ${REDIS_PASSWORD:-difyai123456} ping | grep -q PONG",
+        ]
 
   # The DifySandbox
   sandbox:
@@ -737,13 +762,13 @@ services:
       - ./volumes/sandbox/dependencies:/dependencies
       - ./volumes/sandbox/conf:/conf
     healthcheck:
-      test: [ 'CMD', 'curl', '-f', 'http://localhost:8194/health' ]
+      test: ["CMD", "curl", "-f", "http://localhost:8194/health"]
     networks:
       - ssrf_proxy_network
 
   # plugin daemon
   plugin_daemon:
-    image: langgenius/dify-plugin-daemon:0.2.0-local
+    image: langgenius/dify-plugin-daemon:0.3.0-local
     restart: always
     environment:
       # Use the shared environment variables.
@@ -811,7 +836,12 @@ services:
     volumes:
       - ./ssrf_proxy/squid.conf.template:/etc/squid/squid.conf.template
       - ./ssrf_proxy/docker-entrypoint.sh:/docker-entrypoint-mount.sh
-    entrypoint: [ 'sh', '-c', "cp /docker-entrypoint-mount.sh /docker-entrypoint.sh && sed -i 's/\r$$//' /docker-entrypoint.sh && chmod +x /docker-entrypoint.sh && /docker-entrypoint.sh" ]
+    entrypoint:
+      [
+        "sh",
+        "-c",
+        "cp /docker-entrypoint-mount.sh /docker-entrypoint.sh && sed -i 's/\r$$//' /docker-entrypoint.sh && chmod +x /docker-entrypoint.sh && /docker-entrypoint.sh",
+      ]
     environment:
       # pls clearly modify the squid env vars to fit your network environment.
       HTTP_PORT: ${SSRF_HTTP_PORT:-3128}
@@ -840,8 +870,8 @@ services:
       - CERTBOT_EMAIL=${CERTBOT_EMAIL}
       - CERTBOT_DOMAIN=${CERTBOT_DOMAIN}
       - CERTBOT_OPTIONS=${CERTBOT_OPTIONS:-}
-    entrypoint: [ '/docker-entrypoint.sh' ]
-    command: [ 'tail', '-f', '/dev/null' ]
+    entrypoint: ["/docker-entrypoint.sh"]
+    command: ["tail", "-f", "/dev/null"]
 
   # The nginx reverse proxy.
   # used for reverse proxying the API service and Web service.
@@ -858,7 +888,12 @@ services:
       - ./volumes/certbot/conf/live:/etc/letsencrypt/live # cert dir (with certbot container)
       - ./volumes/certbot/conf:/etc/letsencrypt
       - ./volumes/certbot/www:/var/www/html
-    entrypoint: [ 'sh', '-c', "cp /docker-entrypoint-mount.sh /docker-entrypoint.sh && sed -i 's/\r$$//' /docker-entrypoint.sh && chmod +x /docker-entrypoint.sh && /docker-entrypoint.sh" ]
+    entrypoint:
+      [
+        "sh",
+        "-c",
+        "cp /docker-entrypoint-mount.sh /docker-entrypoint.sh && sed -i 's/\r$$//' /docker-entrypoint.sh && chmod +x /docker-entrypoint.sh && /docker-entrypoint.sh",
+      ]
     environment:
       NGINX_SERVER_NAME: ${NGINX_SERVER_NAME:-_}
       NGINX_HTTPS_ENABLED: ${NGINX_HTTPS_ENABLED:-false}
@@ -880,14 +915,14 @@ services:
       - api
       - web
     ports:
-      - '${EXPOSE_NGINX_PORT:-80}:${NGINX_PORT:-80}'
-      - '${EXPOSE_NGINX_SSL_PORT:-443}:${NGINX_SSL_PORT:-443}'
+      - "${EXPOSE_NGINX_PORT:-80}:${NGINX_PORT:-80}"
+      - "${EXPOSE_NGINX_SSL_PORT:-443}:${NGINX_SSL_PORT:-443}"
 
   # The Weaviate vector store.
   weaviate:
     image: semitechnologies/weaviate:1.19.0
     profiles:
-      - ''
+      - ""
       - weaviate
     restart: always
     volumes:
@@ -940,13 +975,17 @@ services:
     working_dir: /opt/couchbase
     stdin_open: true
     tty: true
-    entrypoint: [ "" ]
+    entrypoint: [""]
     command: sh -c "/opt/couchbase/init/init-cbserver.sh"
     volumes:
       - ./volumes/couchbase/data:/opt/couchbase/var/lib/couchbase/data
     healthcheck:
       # ensure bucket was created before proceeding
-      test: [ "CMD-SHELL", "curl -s -f -u Administrator:password http://localhost:8091/pools/default/buckets | grep -q '\\[{' || exit 1" ]
+      test:
+        [
+          "CMD-SHELL",
+          "curl -s -f -u Administrator:password http://localhost:8091/pools/default/buckets | grep -q '\\[{' || exit 1",
+        ]
       interval: 10s
       retries: 10
       start_period: 30s
@@ -972,9 +1011,9 @@ services:
     volumes:
       - ./volumes/pgvector/data:/var/lib/postgresql/data
       - ./pgvector/docker-entrypoint.sh:/docker-entrypoint.sh
-    entrypoint: [ '/docker-entrypoint.sh' ]
+    entrypoint: ["/docker-entrypoint.sh"]
     healthcheck:
-      test: [ 'CMD', 'pg_isready' ]
+      test: ["CMD", "pg_isready"]
       interval: 1s
       timeout: 3s
       retries: 30
@@ -991,14 +1030,14 @@ services:
       - VB_USERNAME=dify
       - VB_PASSWORD=Difyai123456
     ports:
-      - '5434:5432'
+      - "5434:5432"
     volumes:
       - ./vastbase/lic:/home/vastbase/vastbase/lic
       - ./vastbase/data:/home/vastbase/data
       - ./vastbase/backup:/home/vastbase/backup
       - ./vastbase/backup_log:/home/vastbase/backup_log
     healthcheck:
-      test: [ 'CMD', 'pg_isready' ]
+      test: ["CMD", "pg_isready"]
       interval: 1s
       timeout: 3s
       retries: 30
@@ -1020,7 +1059,7 @@ services:
     volumes:
       - ./volumes/pgvecto_rs/data:/var/lib/postgresql/data
     healthcheck:
-      test: [ 'CMD', 'pg_isready' ]
+      test: ["CMD", "pg_isready"]
       interval: 1s
       timeout: 3s
       retries: 30
@@ -1056,10 +1095,15 @@ services:
       OB_CLUSTER_NAME: ${OCEANBASE_CLUSTER_NAME:-difyai}
       OB_SERVER_IP: 127.0.0.1
       MODE: mini
+      LANG: en_US.UTF-8
     ports:
       - "${OCEANBASE_VECTOR_PORT:-2881}:2881"
     healthcheck:
-      test: [ 'CMD-SHELL', 'obclient -h127.0.0.1 -P2881 -uroot@test -p$${OB_TENANT_PASSWORD} -e "SELECT 1;"' ]
+      test:
+        [
+          "CMD-SHELL",
+          'obclient -h127.0.0.1 -P2881 -uroot@test -p$${OB_TENANT_PASSWORD} -e "SELECT 1;"',
+        ]
       interval: 10s
       retries: 30
       start_period: 30s
@@ -1095,7 +1139,7 @@ services:
       - ./volumes/milvus/etcd:/etcd
     command: etcd -advertise-client-urls=http://127.0.0.1:2379 -listen-client-urls http://0.0.0.0:2379 --data-dir /etcd
     healthcheck:
-      test: [ 'CMD', 'etcdctl', 'endpoint', 'health' ]
+      test: ["CMD", "etcdctl", "endpoint", "health"]
       interval: 30s
       timeout: 20s
       retries: 3
@@ -1114,7 +1158,7 @@ services:
       - ./volumes/milvus/minio:/minio_data
     command: minio server /minio_data --console-address ":9001"
     healthcheck:
-      test: [ 'CMD', 'curl', '-f', 'http://localhost:9000/minio/health/live' ]
+      test: ["CMD", "curl", "-f", "http://localhost:9000/minio/health/live"]
       interval: 30s
       timeout: 20s
       retries: 3
@@ -1126,7 +1170,7 @@ services:
     image: milvusdb/milvus:v2.5.15
     profiles:
       - milvus
-    command: [ 'milvus', 'run', 'standalone' ]
+    command: ["milvus", "run", "standalone"]
     environment:
       ETCD_ENDPOINTS: ${ETCD_ENDPOINTS:-etcd:2379}
       MINIO_ADDRESS: ${MINIO_ADDRESS:-minio:9000}
@@ -1134,7 +1178,7 @@ services:
     volumes:
       - ./volumes/milvus/milvus:/var/lib/milvus
     healthcheck:
-      test: [ 'CMD', 'curl', '-f', 'http://localhost:9091/healthz' ]
+      test: ["CMD", "curl", "-f", "http://localhost:9091/healthz"]
       interval: 30s
       start_period: 90s
       timeout: 20s
@@ -1200,7 +1244,7 @@ services:
     volumes:
       - ./volumes/opengauss/data:/var/lib/opengauss/data
     healthcheck:
-      test: [ "CMD-SHELL", "netstat -lntp | grep tcp6 > /dev/null 2>&1" ]
+      test: ["CMD-SHELL", "netstat -lntp | grep tcp6 > /dev/null 2>&1"]
       interval: 10s
       timeout: 10s
       retries: 10
@@ -1253,18 +1297,19 @@ services:
       node.name: dify-es0
       discovery.type: single-node
       xpack.license.self_generated.type: basic
-      xpack.security.enabled: 'true'
-      xpack.security.enrollment.enabled: 'false'
-      xpack.security.http.ssl.enabled: 'false'
+      xpack.security.enabled: "true"
+      xpack.security.enrollment.enabled: "false"
+      xpack.security.http.ssl.enabled: "false"
     ports:
       - ${ELASTICSEARCH_PORT:-9200}:9200
     deploy:
       resources:
         limits:
           memory: 2g
-    entrypoint: [ 'sh', '-c', "sh /docker-entrypoint-mount.sh" ]
+    entrypoint: ["sh", "-c", "sh /docker-entrypoint-mount.sh"]
     healthcheck:
-      test: [ 'CMD', 'curl', '-s', 'http://localhost:9200/_cluster/health?pretty' ]
+      test:
+        ["CMD", "curl", "-s", "http://localhost:9200/_cluster/health?pretty"]
       interval: 30s
       timeout: 10s
       retries: 50
@@ -1282,17 +1327,17 @@ services:
     environment:
       XPACK_ENCRYPTEDSAVEDOBJECTS_ENCRYPTIONKEY: d1a66dfd-c4d3-4a0a-8290-2abcb83ab3aa
       NO_PROXY: localhost,127.0.0.1,elasticsearch,kibana
-      XPACK_SECURITY_ENABLED: 'true'
-      XPACK_SECURITY_ENROLLMENT_ENABLED: 'false'
-      XPACK_SECURITY_HTTP_SSL_ENABLED: 'false'
-      XPACK_FLEET_ISAIRGAPPED: 'true'
+      XPACK_SECURITY_ENABLED: "true"
+      XPACK_SECURITY_ENROLLMENT_ENABLED: "false"
+      XPACK_SECURITY_HTTP_SSL_ENABLED: "false"
+      XPACK_FLEET_ISAIRGAPPED: "true"
       I18N_LOCALE: zh-CN
-      SERVER_PORT: '5601'
+      SERVER_PORT: "5601"
       ELASTICSEARCH_HOSTS: http://elasticsearch:9200
     ports:
       - ${KIBANA_PORT:-5601}:5601
     healthcheck:
-      test: [ 'CMD-SHELL', 'curl -s http://localhost:5601 >/dev/null || exit 1' ]
+      test: ["CMD-SHELL", "curl -s http://localhost:5601 >/dev/null || exit 1"]
       interval: 30s
       timeout: 10s
       retries: 3

docker/middleware.env.example

@@ -79,6 +79,17 @@ WEAVIATE_AUTHORIZATION_ADMINLIST_ENABLED=true
 WEAVIATE_AUTHORIZATION_ADMINLIST_USERS=hello@dify.ai
 WEAVIATE_HOST_VOLUME=./volumes/weaviate
 
+# ------------------------------
+# Environment Variables for Pinecone Vector Database
+# ------------------------------
+# Get your API key from: https://app.pinecone.io/
+# PINECONE_API_KEY=your-pinecone-api-key
+# PINECONE_ENVIRONMENT=us-west1-gcp
+# PINECONE_INDEX_NAME=dify-pinecone-index
+# PINECONE_CLIENT_TIMEOUT=30
+# PINECONE_BATCH_SIZE=100
+# PINECONE_METRIC=cosine
+
 # ------------------------------
 # Docker Compose Service Expose Host Port Configurations
 # ------------------------------

web/app/components/datasets/external-knowledge-base/create/index.tsx

@@ -28,7 +28,7 @@ const ExternalKnowledgeBaseCreate: React.FC<ExternalKnowledgeBaseCreateProps> =
     external_knowledge_api_id: '',
     external_knowledge_id: '',
     external_retrieval_model: {
-      top_k: 2,
+      top_k: 4,
       score_threshold: 0.5,
       score_threshold_enabled: false,
     },

web/app/components/datasets/hit-testing/textarea.tsx

@@ -49,7 +49,7 @@ const TextAreaWithButton = ({
   const { t } = useTranslation()
   const [isSettingsOpen, setIsSettingsOpen] = useState(false)
   const [externalRetrievalSettings, setExternalRetrievalSettings] = useState({
-    top_k: 2,
+    top_k: 4,
     score_threshold: 0.5,
     score_threshold_enabled: false,
   })

web/context/debug-configuration.ts

@@ -233,7 +233,7 @@ const DebugConfigurationContext = createContext<IDebugConfiguration>({
       reranking_provider_name: '',
       reranking_model_name: '',
     },
-    top_k: 2,
+    top_k: 4,
     score_threshold_enabled: false,
     score_threshold: 0.7,
     datasets: {

web/i18n/de-DE/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
     common: 'Wir respektieren Ihre Privatsphäre und werden diese Informationen nur verwenden, um Ihre Erfahrung mit unseren Entwickler-Tools zu verbessern.',
-    notLoggedIn: 'möchte auf Ihr Dify Cloud-Konto zugreifen',
-    loggedIn: 'möchte auf die folgenden Informationen aus Ihrem Dify Cloud-Konto zugreifen.',
+    notLoggedIn: 'Diese App möchte auf Ihr Dify Cloud-Konto zugreifen',
+    loggedIn: 'Diese App möchte auf die folgenden Informationen aus Ihrem Dify Cloud-Konto zugreifen.',
     needLogin: 'Bitte melden Sie sich an, um zu autorisieren.',
   },
   scopes: {
@@ -21,7 +21,7 @@ const translation = {
   login: 'Anmelden',
   unknownApp: 'Unbekannte App',
   continue: 'Fortsetzen',
-  connect: 'Verbinde zu',
+  connect: 'Verbinden mit',
 }
 
 export default translation

web/i18n/en-US/oauth.ts

@@ -1,7 +1,7 @@
 const translation = {
   tips: {
-    loggedIn: 'wants to access the following information from your Dify Cloud account.',
-    notLoggedIn: 'wants to access your Dify Cloud account',
+    loggedIn: 'This app wants to access the following information from your Dify Cloud account.',
+    notLoggedIn: 'This app wants to access your Dify Cloud account',
     needLogin: 'Please log in to authorize',
     common: 'We respect your privacy and will only use this information to enhance your experience with our developer tools.',
   },
@@ -18,7 +18,7 @@ const translation = {
   },
   error: {
     invalidParams: 'Invalid parameters',
-    authorizeFailed: 'Authorize failed',
+    authorizeFailed: 'Authorization failed',
     authAppInfoFetchFailed: 'Failed to fetch app info for authorization',
   },
   unknownApp: 'Unknown App',

web/i18n/es-ES/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
     needLogin: 'Por favor inicie sesión para autorizar',
-    notLoggedIn: 'quiere acceder a su cuenta de Dify Cloud',
-    loggedIn: 'quiere acceder a la siguiente información de su cuenta de Dify Cloud.',
+    notLoggedIn: 'Esta aplicación quiere acceder a su cuenta de Dify Cloud',
+    loggedIn: 'Esta aplicación quiere acceder a la siguiente información de su cuenta de Dify Cloud.',
     common: 'Respetamos su privacidad y solo utilizaremos esta información para mejorar su experiencia con nuestras herramientas para desarrolladores.',
   },
   scopes: {

web/i18n/fa-IR/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
     needLogin: 'لطفاً برای تأیید وارد شوید',
-    notLoggedIn: 'می‌خواهد به حساب Dify Cloud شما دسترسی پیدا کند',
-    loggedIn: 'می‌خواهد به اطلاعات زیر از حساب ابر دیفی شما دسترسی پیدا کند.',
+    notLoggedIn: 'این برنامه می‌خواهد به حساب Dify Cloud شما دسترسی پیدا کند',
+    loggedIn: 'این برنامه می‌خواهد به اطلاعات زیر از حساب ابر دیفی شما دسترسی پیدا کند.',
     common: 'ما به حریم خصوصی شما احترام می‌گذاریم و تنها از این اطلاعات برای بهبود تجربه شما با ابزارهای توسعه‌دهنده‌مان استفاده خواهیم کرد.',
   },
   scopes: {

web/i18n/fr-FR/oauth.ts

@@ -1,9 +1,9 @@
 const translation = {
   tips: {
     needLogin: 'Veuillez vous connecter pour autoriser',
-    notLoggedIn: 'veut accéder à votre compte Dify Cloud',
+    notLoggedIn: 'Cette application veut accéder à votre compte Dify Cloud',
     common: 'Nous respectons votre vie privée et n\'utiliserons ces informations que pour améliorer votre expérience avec nos outils de développement.',
-    loggedIn: 'veut accéder aux informations suivantes de votre compte Dify Cloud.',
+    loggedIn: 'Cette application veut accéder aux informations suivantes de votre compte Dify Cloud.',
   },
   scopes: {
     email: 'E-mail',

web/i18n/hi-IN/oauth.ts

@@ -1,9 +1,9 @@
 const translation = {
   tips: {
     needLogin: 'कृपया प्राधिकरण के लिए लॉग इन करें',
-    notLoggedIn: 'आप आपके Dify Cloud खाते तक पहुंचना चाहते हैं',
+    notLoggedIn: 'यह ऐप आपके Dify Cloud खाते तक पहुंचना चाहता है',
     common: 'हम आपकी गोपनीयता का सम्मान करते हैं और इस जानकारी का उपयोग केवल आपके हमारे विकास उपकरणों के साथ अनुभव को बेहतर बनाने के लिए करेंगे।',
-    loggedIn: 'आप आपके Dify Cloud खाते से निम्नलिखित जानकारी तक पहुंचना चाहते हैं।',
+    loggedIn: 'यह ऐप आपके Dify Cloud खाते से निम्नलिखित जानकारी तक पहुंचना चाहता है।',
   },
   scopes: {
     name: 'नाम',
@@ -13,7 +13,7 @@ const translation = {
     timezone: 'समय क्षेत्र',
   },
   error: {
-    authorizeFailed: 'अनु autorización विफल',
+    authorizeFailed: 'प्राधिकरण विफल',
     invalidParams: 'अमान्य पैरामीटर',
     authAppInfoFetchFailed: 'प्राधिकरण के लिए ऐप जानकारी प्राप्त करने में असफल हुआ',
   },

web/i18n/it-IT/oauth.ts

@@ -1,7 +1,7 @@
 const translation = {
   tips: {
-    notLoggedIn: 'vuole accedere al tuo account Dify Cloud',
-    loggedIn: 'vuole accedere alle seguenti informazioni dal tuo account Dify Cloud.',
+    notLoggedIn: 'Questa app vuole accedere al tuo account Dify Cloud',
+    loggedIn: 'Questa app vuole accedere alle seguenti informazioni dal tuo account Dify Cloud.',
     common: 'Rispettiamo la tua privacy e utilizzeremo queste informazioni solo per migliorare la tua esperienza con i nostri strumenti per sviluppatori.',
     needLogin: 'Per favore, accedi per autorizzare',
   },

web/i18n/ja-JP/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
-    notLoggedIn: 'あなたのDify Cloudアカウントにアクセスしたいです',
+    notLoggedIn: 'このアプリはあなたのDify Cloudアカウントにアクセスしたいです',
     needLogin: 'ログインして認証してください',
-    loggedIn: 'あなたのDify Cloudアカウントから以下の情報にアクセスしたいと思っています。',
+    loggedIn: 'このアプリはあなたのDify Cloudアカウントから以下の情報にアクセスしたいと思っています。',
     common: '私たちはあなたのプライバシーを尊重し、この情報を私たちの開発者ツールによる体験を向上させるためにのみ使用します。',
   },
   scopes: {
@@ -17,10 +17,10 @@ const translation = {
     invalidParams: '無効なパラメータ',
     authAppInfoFetchFailed: '認証のためのアプリ情報の取得に失敗しました',
   },
-  unknownApp: '未知のアプリ',
+  unknownApp: '不明なアプリ',
   login: 'ログイン',
   switchAccount: 'アカウントを切り替える',
-  continue: '続けてください',
+  continue: '続行',
   connect: '接続する',
 }
 

web/i18n/ko-KR/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
     needLogin: '로그인하여 인증해 주세요.',
-    notLoggedIn: 'Dify Cloud 계정에 접근하고 싶어합니다.',
-    loggedIn: '다음 정보를 귀하의 Dify Cloud 계정에서 액세스하려고 합니다.',
+    notLoggedIn: '이 앱은 Dify Cloud 계정에 접근하고 싶어합니다.',
+    loggedIn: '이 앱은 다음 정보를 귀하의 Dify Cloud 계정에서 액세스하려고 합니다.',
     common: '우리는 귀하의 개인 정보를 존중하며, 이 정보를 개발자 도구를 통한 귀하의 경험 향상에만 사용할 것입니다.',
   },
   scopes: {
@@ -17,11 +17,11 @@ const translation = {
     authorizeFailed: '권한 부여 실패',
     authAppInfoFetchFailed: '인증을 위한 앱 정보를 가져오지 못했습니다.',
   },
-  continue: '계속하다',
+  continue: '계속',
   unknownApp: '알 수 없는 앱',
   switchAccount: '계정 전환',
   login: '로그인',
-  connect: '연결하다',
+  connect: '연결',
 }
 
 export default translation

web/i18n/pl-PL/oauth.ts

@@ -1,9 +1,9 @@
 const translation = {
   tips: {
     needLogin: 'Proszę się zalogować, aby autoryzować',
-    notLoggedIn: 'chce uzyskać dostęp do twojego konta Dify Cloud',
+    notLoggedIn: 'Ta aplikacja chce uzyskać dostęp do twojego konta Dify Cloud',
     common: 'Szanujemy Twoją prywatność i będziemy wykorzystywać te informacje tylko w celu ulepszenia Twojego doświadczenia z naszymi narzędziami deweloperskimi.',
-    loggedIn: 'chce uzyskać dostęp do następujących informacji z twojego konta Dify Cloud.',
+    loggedIn: 'Ta aplikacja chce uzyskać dostęp do następujących informacji z twojego konta Dify Cloud.',
   },
   scopes: {
     timezone: 'Strefa czasowa',

web/i18n/pt-BR/oauth.ts

@@ -1,7 +1,7 @@
 const translation = {
   tips: {
-    notLoggedIn: 'quer acessar sua conta do Dify Cloud',
-    loggedIn: 'quer acessar as seguintes informações da sua conta Dify Cloud.',
+    notLoggedIn: 'Este aplicativo quer acessar sua conta do Dify Cloud',
+    loggedIn: 'Este aplicativo quer acessar as seguintes informações da sua conta Dify Cloud.',
     common: 'Respeitamos sua privacidade e usaremos essas informações apenas para melhorar sua experiência com nossas ferramentas de desenvolvedor.',
     needLogin: 'Por favor, faça login para autorizar',
   },

web/i18n/ro-RO/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
     needLogin: 'Vă rugăm să vă conectați pentru a autoriza',
-    loggedIn: 'vrea să acceseze următoarele informații din contul tău Dify Cloud.',
-    notLoggedIn: 'vrea să acceseze contul tău Dify Cloud',
+    loggedIn: 'Această aplicație vrea să acceseze următoarele informații din contul tău Dify Cloud.',
+    notLoggedIn: 'Această aplicație vrea să acceseze contul tău Dify Cloud',
     common: 'Respectăm confidențialitatea dvs. și vom folosi aceste informații doar pentru a îmbunătăți experiența dvs. cu instrumentele noastre pentru dezvoltatori.',
   },
   scopes: {

web/i18n/ru-RU/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
     needLogin: 'Пожалуйста, войдите, чтобы авторизоваться',
-    notLoggedIn: 'хочет получить доступ к вашей учетной записи Dify Cloud',
-    loggedIn: 'хочет получить следующую информацию из вашего аккаунта Dify Cloud.',
+    notLoggedIn: 'Это приложение хочет получить доступ к вашей учетной записи Dify Cloud',
+    loggedIn: 'Это приложение хочет получить следующую информацию из вашего аккаунта Dify Cloud.',
     common: 'Мы уважаем вашу конфиденциальность и будем использовать эту информацию только для улучшения вашего опыта с нашими инструментами разработчика.',
   },
   scopes: {
@@ -17,7 +17,7 @@ const translation = {
     authorizeFailed: 'Авторизация не удалась',
     authAppInfoFetchFailed: 'Не удалось получить информацию об приложении для авторизации',
   },
-  continue: 'Продолжайте',
+  continue: 'Продолжить',
   connect: 'Подключиться к',
   switchAccount: 'Сменить аккаунт',
   unknownApp: 'Неизвестное приложение',

web/i18n/sl-SI/oauth.ts

@@ -1,7 +1,7 @@
 const translation = {
   tips: {
-    notLoggedIn: 'želi dostopati do vašega Dify Cloud računa',
-    loggedIn: 'želi dostopati do naslednjih informacij iz vašega računa Dify Cloud.',
+    notLoggedIn: 'Ta aplikacija želi dostopati do vašega Dify Cloud računa',
+    loggedIn: 'Ta aplikacija želi dostopati do naslednjih informacij iz vašega računa Dify Cloud.',
     common: 'Soočamo se z vašo zasebnostjo in te informacije bomo uporabili le za izboljšanje vaših izkušenj z našimi orodji za razvijalce.',
     needLogin: 'Prosimo, prijavite se za avtorizacijo',
   },

web/i18n/th-TH/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
     needLogin: 'โปรดเข้าสู่ระบบเพื่ออนุญาต',
-    notLoggedIn: 'ต้องการเข้าถึงบัญชี Dify Cloud ของคุณ',
-    loggedIn: 'ต้องการเข้าถึงข้อมูลต่อไปนี้จากบัญชี Dify Cloud ของคุณ.',
+    notLoggedIn: 'แอปพลิเคชันนี้ต้องการเข้าถึงบัญชี Dify Cloud ของคุณ',
+    loggedIn: 'แอปพลิเคชันนี้ต้องการเข้าถึงข้อมูลต่อไปนี้จากบัญชี Dify Cloud ของคุณ.',
     common: 'เรามีความเคารพต่อความเป็นส่วนตัวของคุณและจะใช้ข้อมูลนี้เพื่อปรับปรุงประสบการณ์ของคุณกับเครื่องมือนักพัฒนาของเราเท่านั้น.',
   },
   scopes: {

web/i18n/tr-TR/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
-    notLoggedIn: 'Dify Cloud hesabınıza erişmek istiyor',
+    notLoggedIn: 'Bu uygulama Dify Cloud hesabınıza erişmek istiyor',
     common: 'Gizliliğinize saygı gösteriyoruz ve bu bilgiyi yalnızca geliştirici araçlarımızla deneyiminizi geliştirmek için kullanacağız.',
-    loggedIn: 'Dify Cloud hesabınızdaki aşağıdaki bilgilere erişmek istiyor.',
+    loggedIn: 'Bu uygulama Dify Cloud hesabınızdaki aşağıdaki bilgilere erişmek istiyor.',
     needLogin: 'Lütfen yetkilendirmek için giriş yapın',
   },
   scopes: {

web/i18n/uk-UA/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
-    notLoggedIn: 'хоче отримати доступ до вашого облікового запису Dify Cloud',
+    notLoggedIn: 'Цей додаток хоче отримати доступ до вашого облікового запису Dify Cloud',
     needLogin: 'Будь ласка, увійдіть, щоб авторизуватися.',
-    loggedIn: 'хоче отримати доступ до наступної інформації з вашого облікового запису Dify Cloud.',
+    loggedIn: 'Цей додаток хоче отримати доступ до наступної інформації з вашого облікового запису Dify Cloud.',
     common: 'Ми поважаємо вашу конфіденційність і використовуватимемо цю інформацію лише для покращення вашого досвіду з нашими інструментами для розробників.',
   },
   scopes: {

web/i18n/vi-VN/oauth.ts

@@ -1,8 +1,8 @@
 const translation = {
   tips: {
     needLogin: 'Vui lòng đăng nhập để xác thực',
-    notLoggedIn: 'muốn truy cập vào tài khoản Dify Cloud của bạn',
-    loggedIn: 'muốn truy cập thông tin sau từ tài khoản Dify Cloud của bạn.',
+    notLoggedIn: 'Ứng dụng này muốn truy cập vào tài khoản Dify Cloud của bạn',
+    loggedIn: 'Ứng dụng này muốn truy cập thông tin sau từ tài khoản Dify Cloud của bạn.',
     common: 'Chúng tôi tôn trọng quyền riêng tư của bạn và sẽ chỉ sử dụng thông tin này để cải thiện trải nghiệm của bạn với các công cụ phát triển của chúng tôi.',
   },
   scopes: {

web/next.config.js

@@ -1,4 +1,3 @@
-const { basePath, assetPrefix } = require('./utils/var-basePath')
 const { codeInspectorPlugin } = require('code-inspector-plugin')
 const withMDX = require('@next/mdx')({
   extension: /\.mdx?$/,
@@ -24,8 +23,7 @@ const remoteImageURLs = [hasSetWebPrefix ? new URL(`${process.env.NEXT_PUBLIC_WE
 
 /** @type {import('next').NextConfig} */
 const nextConfig = {
-  basePath,
-  assetPrefix,
+  basePath: process.env.NEXT_PUBLIC_BASE_PATH || '',
   webpack: (config, { dev, isServer }) => {
     if (dev) {
       config.plugins.push(codeInspectorPlugin({ bundler: 'webpack' }))

web/service/use-share.ts

@@ -6,12 +6,7 @@ const NAME_SPACE = 'webapp'
 export const useGetWebAppAccessModeByCode = (code: string | null) => {
   return useQuery({
     queryKey: [NAME_SPACE, 'appAccessMode', code],
-    queryFn: () => {
-      if (!code || code.length === 0)
-        return Promise.reject(new Error('App code is required to get access mode'))
-
-      return getAppAccessModeByAppCode(code)
-    },
+    queryFn: () => getAppAccessModeByAppCode(code!),
     enabled: !!code,
   })
 }

web/utils/var-basePath.js

@@ -1,6 +0,0 @@
-// export basePath to next.config.js
-// same as the one exported from var.ts
-module.exports = {
-  basePath: process.env.NEXT_PUBLIC_BASE_PATH || '',
-  assetPrefix: '',
-}

web/utils/var.ts

@@ -118,7 +118,7 @@ export const getVars = (value: string) => {
 
 // Set the value of basePath
 // example: /dify
-export const basePath = ''
+export const basePath = process.env.NEXT_PUBLIC_BASE_PATH || ''
 
 export function getMarketplaceUrl(path: string, params?: Record<string, string | undefined>) {
   const searchParams = new URLSearchParams({ source: encodeURIComponent(window.location.origin) })