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Fix variable typo (#8084)
This commit is contained in:
parent
b1918dae5e
commit
2d7954c7da
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@ -46,7 +46,7 @@ class CodeExecutionSandboxConfig(BaseSettings):
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"""
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CODE_EXECUTION_ENDPOINT: HttpUrl = Field(
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description="endpoint URL of code execution servcie",
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description="endpoint URL of code execution service",
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default="http://sandbox:8194",
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)
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@ -415,7 +415,7 @@ class MailConfig(BaseSettings):
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"""
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MAIL_TYPE: Optional[str] = Field(
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description="Mail provider type name, default to None, availabile values are `smtp` and `resend`.",
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description="Mail provider type name, default to None, available values are `smtp` and `resend`.",
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default=None,
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)
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File diff suppressed because one or more lines are too long
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@ -18,7 +18,7 @@ from core.model_runtime.entities.model_entities import ModelType
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from core.provider_manager import ProviderManager
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from core.rag.datasource.vdb.vector_type import VectorType
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from core.rag.extractor.entity.extract_setting import ExtractSetting
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from core.rag.retrieval.retrival_methods import RetrievalMethod
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from core.rag.retrieval.retrieval_methods import RetrievalMethod
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from extensions.ext_database import db
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from fields.app_fields import related_app_list
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from fields.dataset_fields import dataset_detail_fields, dataset_query_detail_fields
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@ -67,7 +67,7 @@ class SegmentApi(DatasetApiResource):
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segments = SegmentService.multi_create_segment(args["segments"], document, dataset)
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return {"data": marshal(segments, segment_fields), "doc_form": document.doc_form}, 200
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else:
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return {"error": "Segemtns is required"}, 400
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return {"error": "Segments is required"}, 400
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def get(self, tenant_id, dataset_id, document_id):
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"""Create single segment."""
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@ -79,7 +79,7 @@ def is_filtered(
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name_func: Callable[[Any], str],
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) -> bool:
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"""
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Chcek if the object should be filtered out.
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Check if the object should be filtered out.
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Overall logic: exclude > include > pin
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:param include_set: the set of names to be included
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:param exclude_set: the set of names to be excluded
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@ -494,7 +494,7 @@ class IndexingRunner:
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hash = helper.generate_text_hash(document_node.page_content)
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document_node.metadata['doc_id'] = doc_id
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document_node.metadata['doc_hash'] = hash
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# delete Spliter character
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# delete Splitter character
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page_content = document_node.page_content
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if page_content.startswith(".") or page_content.startswith("。"):
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page_content = page_content[1:]
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@ -87,7 +87,7 @@ Here is a task description for which I would like you to create a high-quality p
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{{TASK_DESCRIPTION}}
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</task_description>
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Based on task description, please create a well-structured prompt template that another AI could use to consistently complete the task. The prompt template should include:
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- Do not inlcude <input> or <output> section and variables in the prompt, assume user will add them at their own will.
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- Do not include <input> or <output> section and variables in the prompt, assume user will add them at their own will.
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- Clear instructions for the AI that will be using this prompt, demarcated with <instructions> tags. The instructions should provide step-by-step directions on how to complete the task using the input variables. Also Specifies in the instructions that the output should not contain any xml tag.
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- Relevant examples if needed to clarify the task further, demarcated with <example> tags. Do not include variables in the prompt. Give three pairs of input and output examples.
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- Include other relevant sections demarcated with appropriate XML tags like <examples>, <instructions>.
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@ -52,7 +52,7 @@
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- `mode` (string) voice model.(available for model type `tts`)
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- `name` (string) voice model display name.(available for model type `tts`)
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- `language` (string) the voice model supports languages.(available for model type `tts`)
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- `word_limit` (int) Single conversion word limit, paragraphwise by default(available for model type `tts`)
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- `word_limit` (int) Single conversion word limit, paragraph-wise by default(available for model type `tts`)
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- `audio_type` (string) Support audio file extension format, e.g.:mp3,wav(available for model type `tts`)
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- `max_workers` (int) Number of concurrent workers supporting text and audio conversion(available for model type`tts`)
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- `max_characters_per_chunk` (int) Maximum characters per chunk (available for model type `moderation`)
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@ -150,7 +150,7 @@
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- `input` (float) Input price, i.e., Prompt price
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- `output` (float) Output price, i.e., returned content price
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- `unit` (float) Pricing unit, e.g., if the price is meausred in 1M tokens, the corresponding token amount for the unit price is `0.000001`.
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- `unit` (float) Pricing unit, e.g., if the price is measured in 1M tokens, the corresponding token amount for the unit price is `0.000001`.
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- `currency` (string) Currency unit
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### ProviderCredentialSchema
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@ -13,7 +13,7 @@ logger = logging.getLogger(__name__)
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class TTSModel(AIModel):
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"""
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Model class for ttstext model.
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Model class for TTS model.
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"""
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model_type: ModelType = ModelType.TTS
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@ -284,7 +284,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
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try:
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schema = json.loads(json_schema)
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except:
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raise ValueError(f"not currect json_schema format: {json_schema}")
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raise ValueError(f"not correct json_schema format: {json_schema}")
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model_parameters.pop("json_schema")
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model_parameters["response_format"] = {"type": "json_schema", "json_schema": schema}
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else:
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@ -37,7 +37,7 @@ from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors impor
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)
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class BaichuanLarguageModel(LargeLanguageModel):
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class BaichuanLanguageModel(LargeLanguageModel):
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def _invoke(
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self,
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@ -60,7 +60,7 @@ class BaichuanTextEmbeddingModel(TextEmbeddingModel):
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token_usage = 0
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for chunk in chunks:
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# embeding chunk
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# embedding chunk
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chunk_embeddings, chunk_usage = self.embedding(
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model=model,
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api_key=api_key,
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@ -793,11 +793,11 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
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def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
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"""
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Map model invoke error to unified error
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The key is the ermd = genai.GenerativeModel(model)ror type thrown to the caller
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The key is the ermd = genai.GenerativeModel(model) error type thrown to the caller
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The value is the md = genai.GenerativeModel(model) error type thrown by the model,
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which needs to be converted into a unified error type for the caller.
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:return: Invoke emd = genai.GenerativeModel(model)rror mapping
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:return: Invoke emd = genai.GenerativeModel(model) error mapping
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"""
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return {
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InvokeConnectionError: [],
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@ -130,11 +130,11 @@ class BedrockTextEmbeddingModel(TextEmbeddingModel):
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def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
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"""
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Map model invoke error to unified error
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The key is the ermd = genai.GenerativeModel(model)ror type thrown to the caller
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The key is the ermd = genai.GenerativeModel(model) error type thrown to the caller
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The value is the md = genai.GenerativeModel(model) error type thrown by the model,
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which needs to be converted into a unified error type for the caller.
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:return: Invoke emd = genai.GenerativeModel(model)rror mapping
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:return: Invoke emd = genai.GenerativeModel(model) error mapping
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"""
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return {
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InvokeConnectionError: [],
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@ -416,11 +416,11 @@ class GoogleLargeLanguageModel(LargeLanguageModel):
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def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
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"""
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Map model invoke error to unified error
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The key is the ermd = genai.GenerativeModel(model)ror type thrown to the caller
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The key is the ermd = genai.GenerativeModel(model) error type thrown to the caller
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The value is the md = genai.GenerativeModel(model) error type thrown by the model,
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which needs to be converted into a unified error type for the caller.
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:return: Invoke emd = genai.GenerativeModel(model)rror mapping
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:return: Invoke emd = genai.GenerativeModel(model) error mapping
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"""
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return {
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InvokeConnectionError: [
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@ -86,7 +86,7 @@ class MinimaxLargeLanguageModel(LargeLanguageModel):
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Calculate num tokens for minimax model
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not like ChatGLM, Minimax has a special prompt structure, we could not find a proper way
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to caculate the num tokens, so we use str() to convert the prompt to string
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to calculate the num tokens, so we use str() to convert the prompt to string
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Minimax does not provide their own tokenizer of adab5.5 and abab5 model
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therefore, we use gpt2 tokenizer instead
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@ -10,6 +10,7 @@ from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAI
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class NovitaLargeLanguageModel(OAIAPICompatLargeLanguageModel):
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def _update_endpoint_url(self, credentials: dict):
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credentials['endpoint_url'] = "https://api.novita.ai/v3/openai"
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credentials['extra_headers'] = { 'X-Novita-Source': 'dify.ai' }
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return credentials
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@ -243,7 +243,7 @@ class OCILargeLanguageModel(LargeLanguageModel):
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request_args["compartmentId"] = compartment_id
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request_args["servingMode"]["modelId"] = model
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chathistory = []
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chat_history = []
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system_prompts = []
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#if "meta.llama" in model:
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# request_args["chatRequest"]["apiFormat"] = "GENERIC"
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@ -273,16 +273,16 @@ class OCILargeLanguageModel(LargeLanguageModel):
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if isinstance(message.content, str):
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text = message.content
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if isinstance(message, UserPromptMessage):
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chathistory.append({"role": "USER", "message": text})
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chat_history.append({"role": "USER", "message": text})
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else:
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chathistory.append({"role": "CHATBOT", "message": text})
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chat_history.append({"role": "CHATBOT", "message": text})
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if isinstance(message, SystemPromptMessage):
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if isinstance(message.content, str):
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system_prompts.append(message.content)
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args = {"apiFormat": "COHERE",
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"preambleOverride": ' '.join(system_prompts),
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"message": prompt_messages[-1].content,
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"chatHistory": chathistory, }
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"chatHistory": chat_history, }
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request_args["chatRequest"].update(args)
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elif model.startswith("meta"):
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#print("run meta " * 10)
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@ -552,7 +552,7 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
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try:
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schema = json.loads(json_schema)
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except:
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raise ValueError(f"not currect json_schema format: {json_schema}")
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raise ValueError(f"not correct json_schema format: {json_schema}")
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model_parameters.pop("json_schema")
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model_parameters["response_format"] = {"type": "json_schema", "json_schema": schema}
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else:
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@ -67,7 +67,7 @@ class FlashRecognitionRequest:
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class FlashRecognizer:
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"""
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reponse:
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response:
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request_id string
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status Integer
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message String
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@ -132,9 +132,9 @@ class FlashRecognizer:
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signstr = self._format_sign_string(query)
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signature = self._sign(signstr, secret_key)
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header["Authorization"] = signature
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requrl = "https://"
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requrl += signstr[4::]
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return requrl
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req_url = "https://"
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req_url += signstr[4::]
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return req_url
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def _create_query_arr(self, req):
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return {
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@ -695,11 +695,11 @@ class VertexAiLargeLanguageModel(LargeLanguageModel):
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def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
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"""
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Map model invoke error to unified error
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The key is the ermd = gml.GenerativeModel(model)ror type thrown to the caller
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The key is the ermd = gml.GenerativeModel(model) error type thrown to the caller
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The value is the md = gml.GenerativeModel(model) error type thrown by the model,
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which needs to be converted into a unified error type for the caller.
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:return: Invoke emd = gml.GenerativeModel(model)rror mapping
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:return: Invoke emd = gml.GenerativeModel(model) error mapping
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"""
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return {
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InvokeConnectionError: [
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@ -135,16 +135,16 @@ class HttpClient:
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**kwargs,
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)
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def _object_to_formfata(self, key: str, value: Data | Mapping[object, object]) -> list[tuple[str, str]]:
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def _object_to_formdata(self, key: str, value: Data | Mapping[object, object]) -> list[tuple[str, str]]:
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items = []
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if isinstance(value, Mapping):
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for k, v in value.items():
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items.extend(self._object_to_formfata(f"{key}[{k}]", v))
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items.extend(self._object_to_formdata(f"{key}[{k}]", v))
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return items
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if isinstance(value, list | tuple):
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for v in value:
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items.extend(self._object_to_formfata(key + "[]", v))
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items.extend(self._object_to_formdata(key + "[]", v))
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return items
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def _primitive_value_to_str(val) -> str:
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@ -165,7 +165,7 @@ class HttpClient:
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def _make_multipartform(self, data: Mapping[object, object]) -> dict[str, object]:
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items = flatten([self._object_to_formfata(k, v) for k, v in data.items()])
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items = flatten([self._object_to_formdata(k, v) for k, v in data.items()])
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serialized: dict[str, object] = {}
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for key, value in items:
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@ -7,7 +7,7 @@ from core.rag.data_post_processor.data_post_processor import DataPostProcessor
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from core.rag.datasource.keyword.keyword_factory import Keyword
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from core.rag.datasource.vdb.vector_factory import Vector
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from core.rag.rerank.constants.rerank_mode import RerankMode
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from core.rag.retrieval.retrival_methods import RetrievalMethod
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from core.rag.retrieval.retrieval_methods import RetrievalMethod
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from extensions.ext_database import db
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from models.dataset import Dataset
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@ -26,7 +26,7 @@ default_retrieval_model = {
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class RetrievalService:
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@classmethod
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def retrieve(cls, retrival_method: str, dataset_id: str, query: str,
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def retrieve(cls, retrieval_method: str, dataset_id: str, query: str,
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top_k: int, score_threshold: Optional[float] = .0,
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reranking_model: Optional[dict] = None, reranking_mode: Optional[str] = 'reranking_model',
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weights: Optional[dict] = None):
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@ -39,7 +39,7 @@ class RetrievalService:
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threads = []
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exceptions = []
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# retrieval_model source with keyword
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if retrival_method == 'keyword_search':
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if retrieval_method == 'keyword_search':
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keyword_thread = threading.Thread(target=RetrievalService.keyword_search, kwargs={
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'flask_app': current_app._get_current_object(),
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'dataset_id': dataset_id,
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@ -51,7 +51,7 @@ class RetrievalService:
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threads.append(keyword_thread)
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keyword_thread.start()
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# retrieval_model source with semantic
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if RetrievalMethod.is_support_semantic_search(retrival_method):
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if RetrievalMethod.is_support_semantic_search(retrieval_method):
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embedding_thread = threading.Thread(target=RetrievalService.embedding_search, kwargs={
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'flask_app': current_app._get_current_object(),
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'dataset_id': dataset_id,
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@ -60,19 +60,19 @@ class RetrievalService:
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'score_threshold': score_threshold,
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'reranking_model': reranking_model,
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'all_documents': all_documents,
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'retrival_method': retrival_method,
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'retrieval_method': retrieval_method,
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'exceptions': exceptions,
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})
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threads.append(embedding_thread)
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embedding_thread.start()
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# retrieval source with full text
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if RetrievalMethod.is_support_fulltext_search(retrival_method):
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if RetrievalMethod.is_support_fulltext_search(retrieval_method):
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full_text_index_thread = threading.Thread(target=RetrievalService.full_text_index_search, kwargs={
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'flask_app': current_app._get_current_object(),
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'dataset_id': dataset_id,
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'query': query,
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'retrival_method': retrival_method,
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'retrieval_method': retrieval_method,
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'score_threshold': score_threshold,
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'top_k': top_k,
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'reranking_model': reranking_model,
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@ -89,7 +89,7 @@ class RetrievalService:
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exception_message = ';\n'.join(exceptions)
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raise Exception(exception_message)
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if retrival_method == RetrievalMethod.HYBRID_SEARCH.value:
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if retrieval_method == RetrievalMethod.HYBRID_SEARCH.value:
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data_post_processor = DataPostProcessor(str(dataset.tenant_id), reranking_mode,
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reranking_model, weights, False)
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all_documents = data_post_processor.invoke(
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@ -124,7 +124,7 @@ class RetrievalService:
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@classmethod
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def embedding_search(cls, flask_app: Flask, dataset_id: str, query: str,
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top_k: int, score_threshold: Optional[float], reranking_model: Optional[dict],
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all_documents: list, retrival_method: str, exceptions: list):
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all_documents: list, retrieval_method: str, exceptions: list):
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with flask_app.app_context():
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try:
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dataset = db.session.query(Dataset).filter(
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@ -146,7 +146,7 @@ class RetrievalService:
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)
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if documents:
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if reranking_model and reranking_model.get('reranking_model_name') and reranking_model.get('reranking_provider_name') and retrival_method == RetrievalMethod.SEMANTIC_SEARCH.value:
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if reranking_model and reranking_model.get('reranking_model_name') and reranking_model.get('reranking_provider_name') and retrieval_method == RetrievalMethod.SEMANTIC_SEARCH.value:
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data_post_processor = DataPostProcessor(str(dataset.tenant_id),
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RerankMode.RERANKING_MODEL.value,
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reranking_model, None, False)
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@ -164,7 +164,7 @@ class RetrievalService:
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@classmethod
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def full_text_index_search(cls, flask_app: Flask, dataset_id: str, query: str,
|
||||
top_k: int, score_threshold: Optional[float], reranking_model: Optional[dict],
|
||||
all_documents: list, retrival_method: str, exceptions: list):
|
||||
all_documents: list, retrieval_method: str, exceptions: list):
|
||||
with flask_app.app_context():
|
||||
try:
|
||||
dataset = db.session.query(Dataset).filter(
|
||||
|
@ -180,7 +180,7 @@ class RetrievalService:
|
|||
top_k=top_k
|
||||
)
|
||||
if documents:
|
||||
if reranking_model and reranking_model.get('reranking_model_name') and reranking_model.get('reranking_provider_name') and retrival_method == RetrievalMethod.FULL_TEXT_SEARCH.value:
|
||||
if reranking_model and reranking_model.get('reranking_model_name') and reranking_model.get('reranking_provider_name') and retrieval_method == RetrievalMethod.FULL_TEXT_SEARCH.value:
|
||||
data_post_processor = DataPostProcessor(str(dataset.tenant_id),
|
||||
RerankMode.RERANKING_MODEL.value,
|
||||
reranking_model, None, False)
|
||||
|
|
|
@ -275,10 +275,10 @@ class NotionExtractor(BaseExtractor):
|
|||
data = res.json()
|
||||
# get table headers text
|
||||
table_header_cell_texts = []
|
||||
tabel_header_cells = data["results"][0]['table_row']['cells']
|
||||
for tabel_header_cell in tabel_header_cells:
|
||||
if tabel_header_cell:
|
||||
for table_header_cell_text in tabel_header_cell:
|
||||
table_header_cells = data["results"][0]['table_row']['cells']
|
||||
for table_header_cell in table_header_cells:
|
||||
if table_header_cell:
|
||||
for table_header_cell_text in table_header_cell:
|
||||
text = table_header_cell_text["text"]["content"]
|
||||
table_header_cell_texts.append(text)
|
||||
else:
|
||||
|
|
|
@ -2,7 +2,7 @@
|
|||
from collections.abc import Iterator
|
||||
from typing import Optional
|
||||
|
||||
from core.rag.extractor.blod.blod import Blob
|
||||
from core.rag.extractor.blob.blob import Blob
|
||||
from core.rag.extractor.extractor_base import BaseExtractor
|
||||
from core.rag.models.document import Document
|
||||
from extensions.ext_storage import storage
|
||||
|
|
|
@ -34,7 +34,7 @@ class BaseIndexProcessor(ABC):
|
|||
raise NotImplementedError
|
||||
|
||||
@abstractmethod
|
||||
def retrieve(self, retrival_method: str, query: str, dataset: Dataset, top_k: int,
|
||||
def retrieve(self, retrieval_method: str, query: str, dataset: Dataset, top_k: int,
|
||||
score_threshold: float, reranking_model: dict) -> list[Document]:
|
||||
raise NotImplementedError
|
||||
|
||||
|
|
|
@ -42,7 +42,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor):
|
|||
hash = helper.generate_text_hash(document_node.page_content)
|
||||
document_node.metadata['doc_id'] = doc_id
|
||||
document_node.metadata['doc_hash'] = hash
|
||||
# delete Spliter character
|
||||
# delete Splitter character
|
||||
page_content = document_node.page_content
|
||||
if page_content.startswith(".") or page_content.startswith("。"):
|
||||
page_content = page_content[1:].strip()
|
||||
|
@ -76,10 +76,10 @@ class ParagraphIndexProcessor(BaseIndexProcessor):
|
|||
else:
|
||||
keyword.delete()
|
||||
|
||||
def retrieve(self, retrival_method: str, query: str, dataset: Dataset, top_k: int,
|
||||
def retrieve(self, retrieval_method: str, query: str, dataset: Dataset, top_k: int,
|
||||
score_threshold: float, reranking_model: dict) -> list[Document]:
|
||||
# Set search parameters.
|
||||
results = RetrievalService.retrieve(retrival_method=retrival_method, dataset_id=dataset.id, query=query,
|
||||
results = RetrievalService.retrieve(retrieval_method=retrieval_method, dataset_id=dataset.id, query=query,
|
||||
top_k=top_k, score_threshold=score_threshold,
|
||||
reranking_model=reranking_model)
|
||||
# Organize results.
|
||||
|
|
|
@ -50,7 +50,7 @@ class QAIndexProcessor(BaseIndexProcessor):
|
|||
hash = helper.generate_text_hash(document_node.page_content)
|
||||
document_node.metadata['doc_id'] = doc_id
|
||||
document_node.metadata['doc_hash'] = hash
|
||||
# delete Spliter character
|
||||
# delete Splitter character
|
||||
page_content = document_node.page_content
|
||||
if page_content.startswith(".") or page_content.startswith("。"):
|
||||
page_content = page_content[1:]
|
||||
|
@ -107,10 +107,10 @@ class QAIndexProcessor(BaseIndexProcessor):
|
|||
else:
|
||||
vector.delete()
|
||||
|
||||
def retrieve(self, retrival_method: str, query: str, dataset: Dataset, top_k: int,
|
||||
def retrieve(self, retrieval_method: str, query: str, dataset: Dataset, top_k: int,
|
||||
score_threshold: float, reranking_model: dict):
|
||||
# Set search parameters.
|
||||
results = RetrievalService.retrieve(retrival_method=retrival_method, dataset_id=dataset.id, query=query,
|
||||
results = RetrievalService.retrieve(retrieval_method=retrieval_method, dataset_id=dataset.id, query=query,
|
||||
top_k=top_k, score_threshold=score_threshold,
|
||||
reranking_model=reranking_model)
|
||||
# Organize results.
|
||||
|
|
|
@ -21,7 +21,7 @@ from core.rag.data_post_processor.data_post_processor import DataPostProcessor
|
|||
from core.rag.datasource.keyword.jieba.jieba_keyword_table_handler import JiebaKeywordTableHandler
|
||||
from core.rag.datasource.retrieval_service import RetrievalService
|
||||
from core.rag.models.document import Document
|
||||
from core.rag.retrieval.retrival_methods import RetrievalMethod
|
||||
from core.rag.retrieval.retrieval_methods import RetrievalMethod
|
||||
from core.rag.retrieval.router.multi_dataset_function_call_router import FunctionCallMultiDatasetRouter
|
||||
from core.rag.retrieval.router.multi_dataset_react_route import ReactMultiDatasetRouter
|
||||
from core.tools.tool.dataset_retriever.dataset_multi_retriever_tool import DatasetMultiRetrieverTool
|
||||
|
@ -261,9 +261,9 @@ class DatasetRetrieval:
|
|||
top_k = retrieval_model_config['top_k']
|
||||
# get retrieval method
|
||||
if dataset.indexing_technique == "economy":
|
||||
retrival_method = 'keyword_search'
|
||||
retrieval_method = 'keyword_search'
|
||||
else:
|
||||
retrival_method = retrieval_model_config['search_method']
|
||||
retrieval_method = retrieval_model_config['search_method']
|
||||
# get reranking model
|
||||
reranking_model = retrieval_model_config['reranking_model'] \
|
||||
if retrieval_model_config['reranking_enable'] else None
|
||||
|
@ -275,7 +275,7 @@ class DatasetRetrieval:
|
|||
|
||||
with measure_time() as timer:
|
||||
results = RetrievalService.retrieve(
|
||||
retrival_method=retrival_method, dataset_id=dataset.id,
|
||||
retrieval_method=retrieval_method, dataset_id=dataset.id,
|
||||
query=query,
|
||||
top_k=top_k, score_threshold=score_threshold,
|
||||
reranking_model=reranking_model,
|
||||
|
@ -285,7 +285,7 @@ class DatasetRetrieval:
|
|||
self._on_query(query, [dataset_id], app_id, user_from, user_id)
|
||||
|
||||
if results:
|
||||
self._on_retrival_end(results, message_id, timer)
|
||||
self._on_retrieval_end(results, message_id, timer)
|
||||
|
||||
return results
|
||||
return []
|
||||
|
@ -347,14 +347,14 @@ class DatasetRetrieval:
|
|||
self._on_query(query, dataset_ids, app_id, user_from, user_id)
|
||||
|
||||
if all_documents:
|
||||
self._on_retrival_end(all_documents, message_id, timer)
|
||||
self._on_retrieval_end(all_documents, message_id, timer)
|
||||
|
||||
return all_documents
|
||||
|
||||
def _on_retrival_end(
|
||||
def _on_retrieval_end(
|
||||
self, documents: list[Document], message_id: Optional[str] = None, timer: Optional[dict] = None
|
||||
) -> None:
|
||||
"""Handle retrival end."""
|
||||
"""Handle retrieval end."""
|
||||
for document in documents:
|
||||
query = db.session.query(DocumentSegment).filter(
|
||||
DocumentSegment.index_node_id == document.metadata['doc_id']
|
||||
|
@ -419,7 +419,7 @@ class DatasetRetrieval:
|
|||
|
||||
if dataset.indexing_technique == "economy":
|
||||
# use keyword table query
|
||||
documents = RetrievalService.retrieve(retrival_method='keyword_search',
|
||||
documents = RetrievalService.retrieve(retrieval_method='keyword_search',
|
||||
dataset_id=dataset.id,
|
||||
query=query,
|
||||
top_k=top_k
|
||||
|
@ -429,7 +429,7 @@ class DatasetRetrieval:
|
|||
else:
|
||||
if top_k > 0:
|
||||
# retrieval source
|
||||
documents = RetrievalService.retrieve(retrival_method=retrieval_model['search_method'],
|
||||
documents = RetrievalService.retrieve(retrieval_method=retrieval_model['search_method'],
|
||||
dataset_id=dataset.id,
|
||||
query=query,
|
||||
top_k=top_k,
|
||||
|
|
|
@ -29,7 +29,7 @@ credentials_for_provider:
|
|||
en_US: Please input your OpenAI API key
|
||||
zh_Hans: 请输入你的 OpenAI API key
|
||||
pt_BR: Please input your OpenAI API key
|
||||
openai_organizaion_id:
|
||||
openai_organization_id:
|
||||
type: text-input
|
||||
required: false
|
||||
label:
|
||||
|
|
|
@ -16,7 +16,7 @@ class DallE2Tool(BuiltinTool):
|
|||
"""
|
||||
invoke tools
|
||||
"""
|
||||
openai_organization = self.runtime.credentials.get('openai_organizaion_id', None)
|
||||
openai_organization = self.runtime.credentials.get('openai_organization_id', None)
|
||||
if not openai_organization:
|
||||
openai_organization = None
|
||||
openai_base_url = self.runtime.credentials.get('openai_base_url', None)
|
||||
|
|
|
@ -17,7 +17,7 @@ class DallE3Tool(BuiltinTool):
|
|||
"""
|
||||
invoke tools
|
||||
"""
|
||||
openai_organization = self.runtime.credentials.get('openai_organizaion_id', None)
|
||||
openai_organization = self.runtime.credentials.get('openai_organization_id', None)
|
||||
if not openai_organization:
|
||||
openai_organization = None
|
||||
openai_base_url = self.runtime.credentials.get('openai_base_url', None)
|
||||
|
|
|
@ -4,7 +4,7 @@ from core.tools.errors import ToolProviderCredentialValidationError
|
|||
from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
|
||||
|
||||
|
||||
class GihubProvider(BuiltinToolProviderController):
|
||||
class GithubProvider(BuiltinToolProviderController):
|
||||
def _validate_credentials(self, credentials: dict) -> None:
|
||||
try:
|
||||
if 'access_tokens' not in credentials or not credentials.get('access_tokens'):
|
||||
|
|
|
@ -9,7 +9,7 @@ from core.tools.entities.tool_entities import ToolInvokeMessage
|
|||
from core.tools.tool.builtin_tool import BuiltinTool
|
||||
|
||||
|
||||
class GihubRepositoriesTool(BuiltinTool):
|
||||
class GithubRepositoriesTool(BuiltinTool):
|
||||
def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
|
||||
"""
|
||||
invoke tools
|
||||
|
|
|
@ -60,7 +60,7 @@ class GitlabCommitsTool(BuiltinTool):
|
|||
project_name = project['name']
|
||||
print(f"Project: {project_name}")
|
||||
|
||||
# Get all of proejct commits
|
||||
# Get all of project commits
|
||||
commits_url = f"{domain}/api/v4/projects/{project_id}/repository/commits"
|
||||
params = {
|
||||
'since': start_time,
|
||||
|
@ -83,7 +83,7 @@ class GitlabCommitsTool(BuiltinTool):
|
|||
diffs = diff_response.json()
|
||||
|
||||
for diff in diffs:
|
||||
# Caculate code lines of changed
|
||||
# Calculate code lines of changed
|
||||
added_lines = diff['diff'].count('\n+')
|
||||
removed_lines = diff['diff'].count('\n-')
|
||||
total_changes = added_lines + removed_lines
|
||||
|
|
|
@ -6,7 +6,7 @@ identity:
|
|||
zh_Hans: GitLab 提交内容查询
|
||||
description:
|
||||
human:
|
||||
en_US: A tool for query GitLab commits, Input should be a exists username or projec.
|
||||
en_US: A tool for query GitLab commits, Input should be a exists username or project.
|
||||
zh_Hans: 一个用于查询 GitLab 代码提交内容的工具,输入的内容应该是一个已存在的用户名或者项目名。
|
||||
llm: A tool for query GitLab commits, Input should be a exists username or project.
|
||||
parameters:
|
||||
|
|
|
@ -29,7 +29,7 @@ class OpenweatherTool(BuiltinTool):
|
|||
# request URL
|
||||
url = "https://api.openweathermap.org/data/2.5/weather"
|
||||
|
||||
# request parmas
|
||||
# request params
|
||||
params = {
|
||||
"q": city,
|
||||
"appid": self.runtime.credentials.get("api_key"),
|
||||
|
|
|
@ -35,20 +35,20 @@ def sha256base64(data):
|
|||
return digest
|
||||
|
||||
|
||||
def parse_url(requset_url):
|
||||
stidx = requset_url.index("://")
|
||||
host = requset_url[stidx + 3 :]
|
||||
schema = requset_url[: stidx + 3]
|
||||
def parse_url(request_url):
|
||||
stidx = request_url.index("://")
|
||||
host = request_url[stidx + 3 :]
|
||||
schema = request_url[: stidx + 3]
|
||||
edidx = host.index("/")
|
||||
if edidx <= 0:
|
||||
raise AssembleHeaderException("invalid request url:" + requset_url)
|
||||
raise AssembleHeaderException("invalid request url:" + request_url)
|
||||
path = host[edidx:]
|
||||
host = host[:edidx]
|
||||
u = Url(host, path, schema)
|
||||
return u
|
||||
|
||||
def assemble_ws_auth_url(requset_url, method="GET", api_key="", api_secret=""):
|
||||
u = parse_url(requset_url)
|
||||
def assemble_ws_auth_url(request_url, method="GET", api_key="", api_secret=""):
|
||||
u = parse_url(request_url)
|
||||
host = u.host
|
||||
path = u.path
|
||||
now = datetime.now()
|
||||
|
@ -69,7 +69,7 @@ def assemble_ws_auth_url(requset_url, method="GET", api_key="", api_secret=""):
|
|||
)
|
||||
values = {"host": host, "date": date, "authorization": authorization}
|
||||
|
||||
return requset_url + "?" + urlencode(values)
|
||||
return request_url + "?" + urlencode(values)
|
||||
|
||||
|
||||
def get_body(appid, text):
|
||||
|
|
|
@ -42,6 +42,6 @@ class ScrapeTool(BuiltinTool):
|
|||
result += "URL: " + i.get('url', '') + "\n"
|
||||
result += "CONTENT: " + i.get('content', '') + "\n\n"
|
||||
except Exception as e:
|
||||
return self.create_text_message("An error occured", str(e))
|
||||
return self.create_text_message("An error occurred", str(e))
|
||||
|
||||
return self.create_text_message(result)
|
||||
|
|
|
@ -8,7 +8,7 @@ from core.model_manager import ModelManager
|
|||
from core.model_runtime.entities.model_entities import ModelType
|
||||
from core.rag.datasource.retrieval_service import RetrievalService
|
||||
from core.rag.rerank.rerank_model import RerankModelRunner
|
||||
from core.rag.retrieval.retrival_methods import RetrievalMethod
|
||||
from core.rag.retrieval.retrieval_methods import RetrievalMethod
|
||||
from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
|
||||
from extensions.ext_database import db
|
||||
from models.dataset import Dataset, Document, DocumentSegment
|
||||
|
@ -163,7 +163,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
|
|||
|
||||
if dataset.indexing_technique == "economy":
|
||||
# use keyword table query
|
||||
documents = RetrievalService.retrieve(retrival_method='keyword_search',
|
||||
documents = RetrievalService.retrieve(retrieval_method='keyword_search',
|
||||
dataset_id=dataset.id,
|
||||
query=query,
|
||||
top_k=self.top_k
|
||||
|
@ -173,7 +173,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
|
|||
else:
|
||||
if self.top_k > 0:
|
||||
# retrieval source
|
||||
documents = RetrievalService.retrieve(retrival_method=retrieval_model['search_method'],
|
||||
documents = RetrievalService.retrieve(retrieval_method=retrieval_model['search_method'],
|
||||
dataset_id=dataset.id,
|
||||
query=query,
|
||||
top_k=self.top_k,
|
||||
|
|
|
@ -2,7 +2,7 @@
|
|||
from pydantic import BaseModel, Field
|
||||
|
||||
from core.rag.datasource.retrieval_service import RetrievalService
|
||||
from core.rag.retrieval.retrival_methods import RetrievalMethod
|
||||
from core.rag.retrieval.retrieval_methods import RetrievalMethod
|
||||
from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
|
||||
from extensions.ext_database import db
|
||||
from models.dataset import Dataset, Document, DocumentSegment
|
||||
|
@ -63,7 +63,7 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
|
|||
retrieval_model = dataset.retrieval_model if dataset.retrieval_model else default_retrieval_model
|
||||
if dataset.indexing_technique == "economy":
|
||||
# use keyword table query
|
||||
documents = RetrievalService.retrieve(retrival_method='keyword_search',
|
||||
documents = RetrievalService.retrieve(retrieval_method='keyword_search',
|
||||
dataset_id=dataset.id,
|
||||
query=query,
|
||||
top_k=self.top_k
|
||||
|
@ -72,7 +72,7 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
|
|||
else:
|
||||
if self.top_k > 0:
|
||||
# retrieval source
|
||||
documents = RetrievalService.retrieve(retrival_method=retrieval_model.get('search_method', 'semantic_search'),
|
||||
documents = RetrievalService.retrieve(retrieval_method=retrieval_model.get('search_method', 'semantic_search'),
|
||||
dataset_id=dataset.id,
|
||||
query=query,
|
||||
top_k=self.top_k,
|
||||
|
|
|
@ -17,7 +17,7 @@ from core.tools.tool.tool import Tool
|
|||
|
||||
|
||||
class DatasetRetrieverTool(Tool):
|
||||
retrival_tool: DatasetRetrieverBaseTool
|
||||
retrieval_tool: DatasetRetrieverBaseTool
|
||||
|
||||
@staticmethod
|
||||
def get_dataset_tools(tenant_id: str,
|
||||
|
@ -42,7 +42,7 @@ class DatasetRetrieverTool(Tool):
|
|||
# Agent only support SINGLE mode
|
||||
original_retriever_mode = retrieve_config.retrieve_strategy
|
||||
retrieve_config.retrieve_strategy = DatasetRetrieveConfigEntity.RetrieveStrategy.SINGLE
|
||||
retrival_tools = feature.to_dataset_retriever_tool(
|
||||
retrieval_tools = feature.to_dataset_retriever_tool(
|
||||
tenant_id=tenant_id,
|
||||
dataset_ids=dataset_ids,
|
||||
retrieve_config=retrieve_config,
|
||||
|
@ -53,17 +53,17 @@ class DatasetRetrieverTool(Tool):
|
|||
# restore retrieve strategy
|
||||
retrieve_config.retrieve_strategy = original_retriever_mode
|
||||
|
||||
# convert retrival tools to Tools
|
||||
# convert retrieval tools to Tools
|
||||
tools = []
|
||||
for retrival_tool in retrival_tools:
|
||||
for retrieval_tool in retrieval_tools:
|
||||
tool = DatasetRetrieverTool(
|
||||
retrival_tool=retrival_tool,
|
||||
identity=ToolIdentity(provider='', author='', name=retrival_tool.name, label=I18nObject(en_US='', zh_Hans='')),
|
||||
retrieval_tool=retrieval_tool,
|
||||
identity=ToolIdentity(provider='', author='', name=retrieval_tool.name, label=I18nObject(en_US='', zh_Hans='')),
|
||||
parameters=[],
|
||||
is_team_authorization=True,
|
||||
description=ToolDescription(
|
||||
human=I18nObject(en_US='', zh_Hans=''),
|
||||
llm=retrival_tool.description),
|
||||
llm=retrieval_tool.description),
|
||||
runtime=DatasetRetrieverTool.Runtime()
|
||||
)
|
||||
|
||||
|
@ -95,7 +95,7 @@ class DatasetRetrieverTool(Tool):
|
|||
return self.create_text_message(text='please input query')
|
||||
|
||||
# invoke dataset retriever tool
|
||||
result = self.retrival_tool._run(query=query)
|
||||
result = self.retrieval_tool._run(query=query)
|
||||
|
||||
return self.create_text_message(text=result)
|
||||
|
||||
|
|
|
@ -189,8 +189,8 @@ def extract_text_blocks_as_plain_text(paragraph_html):
|
|||
|
||||
|
||||
def plain_text_leaf_node(element):
|
||||
# Extract all text, stripped of any child HTML elements and normalise it
|
||||
plain_text = normalise_text(element.get_text())
|
||||
# Extract all text, stripped of any child HTML elements and normalize it
|
||||
plain_text = normalize_text(element.get_text())
|
||||
if plain_text != "" and element.name == "li":
|
||||
plain_text = "* {}, ".format(plain_text)
|
||||
if plain_text == "":
|
||||
|
@ -231,8 +231,8 @@ def plain_element(element, content_digests, node_indexes):
|
|||
# For leaf node elements, extract the text content, discarding any HTML tags
|
||||
# 1. Get element contents as text
|
||||
plain_text = element.get_text()
|
||||
# 2. Normalise the extracted text string to a canonical representation
|
||||
plain_text = normalise_text(plain_text)
|
||||
# 2. Normalize the extracted text string to a canonical representation
|
||||
plain_text = normalize_text(plain_text)
|
||||
# 3. Update element content to be plain text
|
||||
element.string = plain_text
|
||||
elif is_text(element):
|
||||
|
@ -243,7 +243,7 @@ def plain_element(element, content_digests, node_indexes):
|
|||
element = type(element)("")
|
||||
else:
|
||||
plain_text = element.string
|
||||
plain_text = normalise_text(plain_text)
|
||||
plain_text = normalize_text(plain_text)
|
||||
element = type(element)(plain_text)
|
||||
else:
|
||||
# If not a leaf node or leaf type call recursively on child nodes, replacing
|
||||
|
@ -267,12 +267,12 @@ def add_node_indexes(element, node_index="0"):
|
|||
return element
|
||||
|
||||
|
||||
def normalise_text(text):
|
||||
"""Normalise unicode and whitespace."""
|
||||
# Normalise unicode first to try and standardise whitespace characters as much as possible before normalising them
|
||||
def normalize_text(text):
|
||||
"""Normalize unicode and whitespace."""
|
||||
# Normalize unicode first to try and standardize whitespace characters as much as possible before normalizing them
|
||||
text = strip_control_characters(text)
|
||||
text = normalise_unicode(text)
|
||||
text = normalise_whitespace(text)
|
||||
text = normalize_unicode(text)
|
||||
text = normalize_whitespace(text)
|
||||
return text
|
||||
|
||||
|
||||
|
@ -291,14 +291,14 @@ def strip_control_characters(text):
|
|||
return "".join(["" if (unicodedata.category(char) in control_chars) and (char not in retained_chars) else char for char in text])
|
||||
|
||||
|
||||
def normalise_unicode(text):
|
||||
"""Normalise unicode such that things that are visually equivalent map to the same unicode string where possible."""
|
||||
def normalize_unicode(text):
|
||||
"""Normalize unicode such that things that are visually equivalent map to the same unicode string where possible."""
|
||||
normal_form = "NFKC"
|
||||
text = unicodedata.normalize(normal_form, text)
|
||||
return text
|
||||
|
||||
|
||||
def normalise_whitespace(text):
|
||||
def normalize_whitespace(text):
|
||||
"""Replace runs of whitespace characters with a single space as this is what happens when HTML text is displayed."""
|
||||
text = regex.sub(r"\s+", " ", text)
|
||||
# Remove leading and trailing whitespace
|
||||
|
|
|
@ -31,7 +31,7 @@ class VariablePool:
|
|||
# 'files': []
|
||||
# }
|
||||
|
||||
# Varaible dictionary is a dictionary for looking up variables by their selector.
|
||||
# Variable dictionary is a dictionary for looking up variables by their selector.
|
||||
# The first element of the selector is the node id, it's the first-level key in the dictionary.
|
||||
# Other elements of the selector are the keys in the second-level dictionary. To get the key, we hash the
|
||||
# elements of the selector except the first one.
|
||||
|
|
|
@ -11,7 +11,7 @@ from core.model_manager import ModelInstance, ModelManager
|
|||
from core.model_runtime.entities.model_entities import ModelFeature, ModelType
|
||||
from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
|
||||
from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
|
||||
from core.rag.retrieval.retrival_methods import RetrievalMethod
|
||||
from core.rag.retrieval.retrieval_methods import RetrievalMethod
|
||||
from core.workflow.entities.base_node_data_entities import BaseNodeData
|
||||
from core.workflow.entities.node_entities import NodeRunResult, NodeType
|
||||
from core.workflow.entities.variable_pool import VariablePool
|
||||
|
|
|
@ -3,8 +3,8 @@ from .clean_when_document_deleted import handle
|
|||
from .create_document_index import handle
|
||||
from .create_installed_app_when_app_created import handle
|
||||
from .create_site_record_when_app_created import handle
|
||||
from .deduct_quota_when_messaeg_created import handle
|
||||
from .deduct_quota_when_message_created import handle
|
||||
from .delete_tool_parameters_cache_when_sync_draft_workflow import handle
|
||||
from .update_app_dataset_join_when_app_model_config_updated import handle
|
||||
from .update_app_dataset_join_when_app_published_workflow_updated import handle
|
||||
from .update_provider_last_used_at_when_messaeg_created import handle
|
||||
from .update_provider_last_used_at_when_message_created import handle
|
||||
|
|
|
@ -14,7 +14,7 @@ from sqlalchemy import func
|
|||
from sqlalchemy.dialects.postgresql import JSONB
|
||||
|
||||
from configs import dify_config
|
||||
from core.rag.retrieval.retrival_methods import RetrievalMethod
|
||||
from core.rag.retrieval.retrieval_methods import RetrievalMethod
|
||||
from extensions.ext_database import db
|
||||
from extensions.ext_storage import storage
|
||||
|
||||
|
|
|
@ -15,7 +15,7 @@ from core.model_manager import ModelManager
|
|||
from core.model_runtime.entities.model_entities import ModelType
|
||||
from core.rag.datasource.keyword.keyword_factory import Keyword
|
||||
from core.rag.models.document import Document as RAGDocument
|
||||
from core.rag.retrieval.retrival_methods import RetrievalMethod
|
||||
from core.rag.retrieval.retrieval_methods import RetrievalMethod
|
||||
from events.dataset_event import dataset_was_deleted
|
||||
from events.document_event import document_was_deleted
|
||||
from extensions.ext_database import db
|
||||
|
|
|
@ -3,7 +3,7 @@ import time
|
|||
|
||||
from core.rag.datasource.retrieval_service import RetrievalService
|
||||
from core.rag.models.document import Document
|
||||
from core.rag.retrieval.retrival_methods import RetrievalMethod
|
||||
from core.rag.retrieval.retrieval_methods import RetrievalMethod
|
||||
from extensions.ext_database import db
|
||||
from models.account import Account
|
||||
from models.dataset import Dataset, DatasetQuery, DocumentSegment
|
||||
|
@ -36,7 +36,7 @@ class HitTestingService:
|
|||
retrieval_model = dataset.retrieval_model if dataset.retrieval_model else default_retrieval_model
|
||||
|
||||
all_documents = RetrievalService.retrieve(
|
||||
retrival_method=retrieval_model.get("search_method", "semantic_search"),
|
||||
retrieval_method=retrieval_model.get("search_method", "semantic_search"),
|
||||
dataset_id=dataset.id,
|
||||
query=cls.escape_query_for_search(query),
|
||||
top_k=retrieval_model.get("top_k", 2),
|
||||
|
|
|
@ -20,7 +20,7 @@ def sync_website_document_indexing_task(dataset_id: str, document_id: str):
|
|||
:param dataset_id:
|
||||
:param document_id:
|
||||
|
||||
Usage: sunc_website_document_indexing_task.delay(dataset_id, document_id)
|
||||
Usage: sync_website_document_indexing_task.delay(dataset_id, document_id)
|
||||
"""
|
||||
start_at = time.perf_counter()
|
||||
|
||||
|
|
|
@ -8,11 +8,11 @@ from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk,
|
|||
from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage
|
||||
from core.model_runtime.entities.model_entities import AIModelEntity
|
||||
from core.model_runtime.errors.validate import CredentialsValidateFailedError
|
||||
from core.model_runtime.model_providers.baichuan.llm.llm import BaichuanLarguageModel
|
||||
from core.model_runtime.model_providers.baichuan.llm.llm import BaichuanLanguageModel
|
||||
|
||||
|
||||
def test_predefined_models():
|
||||
model = BaichuanLarguageModel()
|
||||
model = BaichuanLanguageModel()
|
||||
model_schemas = model.predefined_models()
|
||||
assert len(model_schemas) >= 1
|
||||
assert isinstance(model_schemas[0], AIModelEntity)
|
||||
|
@ -20,7 +20,7 @@ def test_predefined_models():
|
|||
|
||||
def test_validate_credentials_for_chat_model():
|
||||
sleep(3)
|
||||
model = BaichuanLarguageModel()
|
||||
model = BaichuanLanguageModel()
|
||||
|
||||
with pytest.raises(CredentialsValidateFailedError):
|
||||
model.validate_credentials(
|
||||
|
@ -38,7 +38,7 @@ def test_validate_credentials_for_chat_model():
|
|||
|
||||
def test_invoke_model():
|
||||
sleep(3)
|
||||
model = BaichuanLarguageModel()
|
||||
model = BaichuanLanguageModel()
|
||||
|
||||
response = model.invoke(
|
||||
model="baichuan2-turbo",
|
||||
|
@ -64,7 +64,7 @@ def test_invoke_model():
|
|||
|
||||
def test_invoke_model_with_system_message():
|
||||
sleep(3)
|
||||
model = BaichuanLarguageModel()
|
||||
model = BaichuanLanguageModel()
|
||||
|
||||
response = model.invoke(
|
||||
model="baichuan2-turbo",
|
||||
|
@ -93,7 +93,7 @@ def test_invoke_model_with_system_message():
|
|||
|
||||
def test_invoke_stream_model():
|
||||
sleep(3)
|
||||
model = BaichuanLarguageModel()
|
||||
model = BaichuanLanguageModel()
|
||||
|
||||
response = model.invoke(
|
||||
model="baichuan2-turbo",
|
||||
|
@ -122,7 +122,7 @@ def test_invoke_stream_model():
|
|||
|
||||
def test_invoke_with_search():
|
||||
sleep(3)
|
||||
model = BaichuanLarguageModel()
|
||||
model = BaichuanLanguageModel()
|
||||
|
||||
response = model.invoke(
|
||||
model="baichuan2-turbo",
|
||||
|
@ -156,7 +156,7 @@ def test_invoke_with_search():
|
|||
|
||||
def test_get_num_tokens():
|
||||
sleep(3)
|
||||
model = BaichuanLarguageModel()
|
||||
model = BaichuanLanguageModel()
|
||||
|
||||
response = model.get_num_tokens(
|
||||
model="baichuan2-turbo",
|
||||
|
|
|
@ -155,7 +155,7 @@ def test_invoke_chat_model_with_vision_multi_pics(setup_google_mock):
|
|||
user="abc-123",
|
||||
)
|
||||
|
||||
print(f"resultz: {result.message.content}")
|
||||
print(f"result: {result.message.content}")
|
||||
assert isinstance(result, LLMResult)
|
||||
assert len(result.message.content) > 0
|
||||
|
||||
|
|
|
@ -109,7 +109,7 @@ def test_invoke_stream_chat_model(setup_openai_mock, setup_xinference_mock):
|
|||
|
||||
|
||||
"""
|
||||
Funtion calling of xinference does not support stream mode currently
|
||||
Function calling of xinference does not support stream mode currently
|
||||
"""
|
||||
# def test_invoke_stream_chat_model_with_functions():
|
||||
# model = XinferenceAILargeLanguageModel()
|
||||
|
|
|
@ -31,5 +31,5 @@ class PGVectoRSVectorTest(AbstractVectorTest):
|
|||
assert len(ids) == 1
|
||||
|
||||
|
||||
def test_pgvecot_rs(setup_mock_redis):
|
||||
def test_pgvecto_rs(setup_mock_redis):
|
||||
PGVectoRSVectorTest().run_all_tests()
|
||||
|
|
|
@ -1,13 +1,13 @@
|
|||
#!/usr/bin/env bash
|
||||
|
||||
DB_INITIALISED="/opt/oracle/oradata/dbinit"
|
||||
#[ -f ${DB_INITIALISED} ] && exit
|
||||
#touch ${DB_INITIALISED}
|
||||
if [ -f ${DB_INITIALISED} ]; then
|
||||
DB_INITIALIZED="/opt/oracle/oradata/dbinit"
|
||||
#[ -f ${DB_INITIALIZED} ] && exit
|
||||
#touch ${DB_INITIALIZED}
|
||||
if [ -f ${DB_INITIALIZED} ]; then
|
||||
echo 'File exists. Standards for have been Init'
|
||||
exit
|
||||
else
|
||||
echo 'File does not exist. Standards for first time Strart up this DB'
|
||||
echo 'File does not exist. Standards for first time Start up this DB'
|
||||
"$ORACLE_HOME"/bin/sqlplus -s "/ as sysdba" @"/opt/oracle/scripts/startup/init_user.script";
|
||||
touch ${DB_INITIALISED}
|
||||
touch ${DB_INITIALIZED}
|
||||
fi
|
||||
|
|
|
@ -18,7 +18,7 @@ const query = 'Please tell me a short story in 10 words or less.'
|
|||
const remote_url_files = [{
|
||||
type: 'image',
|
||||
transfer_method: 'remote_url',
|
||||
url: 'your_url_addresss'
|
||||
url: 'your_url_address'
|
||||
}]
|
||||
|
||||
// Create a completion client
|
||||
|
|
|
@ -108,7 +108,7 @@ const AppDetailLayout: FC<IAppDetailLayoutProps> = (props) => {
|
|||
useEffect(() => {
|
||||
setAppDetail()
|
||||
fetchAppDetail({ url: '/apps', id: appId }).then((res) => {
|
||||
// redirections
|
||||
// redirection
|
||||
if ((res.mode === 'workflow' || res.mode === 'advanced-chat') && (pathname).endsWith('configuration')) {
|
||||
router.replace(`/app/${appId}/workflow`)
|
||||
}
|
||||
|
|
|
@ -21,7 +21,7 @@ import Divider from '@/app/components/base/divider'
|
|||
import { getRedirection } from '@/utils/app-redirection'
|
||||
import { useProviderContext } from '@/context/provider-context'
|
||||
import { NEED_REFRESH_APP_LIST_KEY } from '@/config'
|
||||
import { AiText, ChatBot, CuteRobote } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { AiText, ChatBot, CuteRobot } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { Route } from '@/app/components/base/icons/src/vender/solid/mapsAndTravel'
|
||||
import type { CreateAppModalProps } from '@/app/components/explore/create-app-modal'
|
||||
import EditAppModal from '@/app/components/explore/create-app-modal'
|
||||
|
@ -273,7 +273,7 @@ const AppCard = ({ app, onRefresh }: AppCardProps) => {
|
|||
<ChatBot className='w-3 h-3 text-[#1570EF]' />
|
||||
)}
|
||||
{app.mode === 'agent-chat' && (
|
||||
<CuteRobote className='w-3 h-3 text-indigo-600' />
|
||||
<CuteRobot className='w-3 h-3 text-indigo-600' />
|
||||
)}
|
||||
{app.mode === 'chat' && (
|
||||
<ChatBot className='w-3 h-3 text-[#1570EF]' />
|
||||
|
|
|
@ -35,7 +35,7 @@ import { DataSourceType } from '@/models/datasets'
|
|||
import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
|
||||
import { LanguagesSupported } from '@/i18n/language'
|
||||
import { useStore } from '@/app/components/app/store'
|
||||
import { AiText, ChatBot, CuteRobote } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { AiText, ChatBot, CuteRobot } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { Route } from '@/app/components/base/icons/src/vender/solid/mapsAndTravel'
|
||||
import { getLocaleOnClient } from '@/i18n'
|
||||
import { useAppContext } from '@/context/app-context'
|
||||
|
@ -67,7 +67,7 @@ const LikedItem = ({
|
|||
<ChatBot className='w-2.5 h-2.5 text-[#1570EF]' />
|
||||
)}
|
||||
{detail.mode === 'agent-chat' && (
|
||||
<CuteRobote className='w-2.5 h-2.5 text-indigo-600' />
|
||||
<CuteRobot className='w-2.5 h-2.5 text-indigo-600' />
|
||||
)}
|
||||
{detail.mode === 'chat' && (
|
||||
<ChatBot className='w-2.5 h-2.5 text-[#1570EF]' />
|
||||
|
|
|
@ -148,7 +148,7 @@ import { Row, Col, Properties, Property, Heading, SubProperty, Paragraph } from
|
|||
- original_document_id Source document ID (optional)
|
||||
- Used to re-upload the document or modify the document cleaning and segmentation configuration. The missing information is copied from the source document
|
||||
- The source document cannot be an archived document
|
||||
- When original_document_id is passed in, the update operation is performed on behalf of the document. process_rule is a fillable item. If not filled in, the segmentation method of the source document will be used by defaul
|
||||
- When original_document_id is passed in, the update operation is performed on behalf of the document. process_rule is a fillable item. If not filled in, the segmentation method of the source document will be used by default
|
||||
- When original_document_id is not passed in, the new operation is performed on behalf of the document, and process_rule is required
|
||||
|
||||
- indexing_technique Index mode
|
||||
|
|
|
@ -142,7 +142,7 @@ import { Row, Col, Properties, Property, Heading, SubProperty, Paragraph } from
|
|||
</Property>
|
||||
</Properties>
|
||||
|
||||
### Request Bodys
|
||||
### Request Body
|
||||
<Properties>
|
||||
<Property name='data' type='multipart/form-data json string' key='data'>
|
||||
- original_document_id 源文档 ID (选填)
|
||||
|
|
|
@ -22,7 +22,7 @@ import { copyApp, deleteApp, exportAppConfig, updateAppInfo } from '@/service/ap
|
|||
import DuplicateAppModal from '@/app/components/app/duplicate-modal'
|
||||
import type { DuplicateAppModalProps } from '@/app/components/app/duplicate-modal'
|
||||
import CreateAppModal from '@/app/components/explore/create-app-modal'
|
||||
import { AiText, ChatBot, CuteRobote } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { AiText, ChatBot, CuteRobot } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { Route } from '@/app/components/base/icons/src/vender/solid/mapsAndTravel'
|
||||
import type { CreateAppModalProps } from '@/app/components/explore/create-app-modal'
|
||||
import { NEED_REFRESH_APP_LIST_KEY } from '@/config'
|
||||
|
@ -214,7 +214,7 @@ const AppInfo = ({ expand }: IAppInfoProps) => {
|
|||
<ChatBot className={cn('w-3 h-3 text-[#1570EF]', !expand && '!w-2.5 !h-2.5')} />
|
||||
)}
|
||||
{appDetail.mode === 'agent-chat' && (
|
||||
<CuteRobote className={cn('w-3 h-3 text-indigo-600', !expand && '!w-2.5 !h-2.5')} />
|
||||
<CuteRobot className={cn('w-3 h-3 text-indigo-600', !expand && '!w-2.5 !h-2.5')} />
|
||||
)}
|
||||
{appDetail.mode === 'chat' && (
|
||||
<ChatBot className={cn('w-3 h-3 text-[#1570EF]', !expand && '!w-2.5 !h-2.5')} />
|
||||
|
@ -280,7 +280,7 @@ const AppInfo = ({ expand }: IAppInfoProps) => {
|
|||
<ChatBot className='w-3 h-3 text-[#1570EF]' />
|
||||
)}
|
||||
{appDetail.mode === 'agent-chat' && (
|
||||
<CuteRobote className='w-3 h-3 text-indigo-600' />
|
||||
<CuteRobot className='w-3 h-3 text-indigo-600' />
|
||||
)}
|
||||
{appDetail.mode === 'chat' && (
|
||||
<ChatBot className='w-3 h-3 text-[#1570EF]' />
|
||||
|
@ -323,7 +323,7 @@ const AppInfo = ({ expand }: IAppInfoProps) => {
|
|||
</div>
|
||||
</div>
|
||||
</div>
|
||||
{/* desscription */}
|
||||
{/* description */}
|
||||
{appDetail.description && (
|
||||
<div className='px-4 py-2 text-gray-500 text-xs leading-[18px]'>{appDetail.description}</div>
|
||||
)}
|
||||
|
|
|
@ -232,8 +232,8 @@ const Annotation: FC<Props> = ({
|
|||
middlePagesSiblingCount={1}
|
||||
setCurrentPage={setCurrPage}
|
||||
totalPages={Math.ceil(total / APP_PAGE_LIMIT)}
|
||||
truncableClassName="w-8 px-0.5 text-center"
|
||||
truncableText="..."
|
||||
truncatableClassName="w-8 px-0.5 text-center"
|
||||
truncatableText="..."
|
||||
>
|
||||
<Pagination.PrevButton
|
||||
disabled={currPage === 0}
|
||||
|
|
|
@ -156,8 +156,8 @@ const ViewAnnotationModal: FC<Props> = ({
|
|||
middlePagesSiblingCount={1}
|
||||
setCurrentPage={setCurrPage}
|
||||
totalPages={Math.ceil(total / APP_PAGE_LIMIT)}
|
||||
truncableClassName="w-8 px-0.5 text-center"
|
||||
truncableText="..."
|
||||
truncatableClassName="w-8 px-0.5 text-center"
|
||||
truncatableText="..."
|
||||
>
|
||||
<Pagination.PrevButton
|
||||
disabled={currPage === 0}
|
||||
|
|
|
@ -262,7 +262,7 @@ const AdvancedPromptInput: FC<Props> = ({
|
|||
{isShowConfirmAddVar && (
|
||||
<ConfirmAddVar
|
||||
varNameArr={newPromptVariables.map(v => v.name)}
|
||||
onConfrim={handleAutoAdd(true)}
|
||||
onConfirm={handleAutoAdd(true)}
|
||||
onCancel={handleAutoAdd(false)}
|
||||
onHide={hideConfirmAddVar}
|
||||
/>
|
||||
|
|
|
@ -7,7 +7,7 @@ import Button from '@/app/components/base/button'
|
|||
|
||||
export type IConfirmAddVarProps = {
|
||||
varNameArr: string[]
|
||||
onConfrim: () => void
|
||||
onConfirm: () => void
|
||||
onCancel: () => void
|
||||
onHide: () => void
|
||||
}
|
||||
|
@ -22,7 +22,7 @@ const VarIcon = (
|
|||
|
||||
const ConfirmAddVar: FC<IConfirmAddVarProps> = ({
|
||||
varNameArr,
|
||||
onConfrim,
|
||||
onConfirm,
|
||||
onCancel,
|
||||
// onHide,
|
||||
}) => {
|
||||
|
@ -63,7 +63,7 @@ const ConfirmAddVar: FC<IConfirmAddVarProps> = ({
|
|||
</div>
|
||||
<div className='mt-7 flex justify-end space-x-2'>
|
||||
<Button onClick={onCancel}>{t('common.operation.cancel')}</Button>
|
||||
<Button variant='primary' onClick={onConfrim}>{t('common.operation.add')}</Button>
|
||||
<Button variant='primary' onClick={onConfirm}>{t('common.operation.add')}</Button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
|
|
@ -33,7 +33,7 @@ export type ISimplePromptInput = {
|
|||
promptTemplate: string
|
||||
promptVariables: PromptVariable[]
|
||||
readonly?: boolean
|
||||
onChange?: (promp: string, promptVariables: PromptVariable[]) => void
|
||||
onChange?: (prompt: string, promptVariables: PromptVariable[]) => void
|
||||
noTitle?: boolean
|
||||
gradientBorder?: boolean
|
||||
editorHeight?: number
|
||||
|
@ -239,7 +239,7 @@ const Prompt: FC<ISimplePromptInput> = ({
|
|||
{isShowConfirmAddVar && (
|
||||
<ConfirmAddVar
|
||||
varNameArr={newPromptVariables.map(v => v.name)}
|
||||
onConfrim={handleAutoAdd(true)}
|
||||
onConfirm={handleAutoAdd(true)}
|
||||
onCancel={handleAutoAdd(false)}
|
||||
onHide={hideConfirmAddVar}
|
||||
/>
|
||||
|
|
|
@ -5,7 +5,7 @@ import { useTranslation } from 'react-i18next'
|
|||
import { RiCloseLine } from '@remixicon/react'
|
||||
import ItemPanel from './item-panel'
|
||||
import Button from '@/app/components/base/button'
|
||||
import { CuteRobote } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { CuteRobot } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { Unblur } from '@/app/components/base/icons/src/vender/solid/education'
|
||||
import Slider from '@/app/components/base/slider'
|
||||
import type { AgentConfig } from '@/models/debug'
|
||||
|
@ -65,7 +65,7 @@ const AgentSetting: FC<Props> = ({
|
|||
<ItemPanel
|
||||
className='mb-4'
|
||||
icon={
|
||||
<CuteRobote className='w-4 h-4 text-indigo-600' />
|
||||
<CuteRobot className='w-4 h-4 text-indigo-600' />
|
||||
}
|
||||
name={t('appDebug.agent.agentMode')}
|
||||
description={t('appDebug.agent.agentModeDes')}
|
||||
|
|
|
@ -12,7 +12,7 @@ import {
|
|||
} from '@/app/components/base/portal-to-follow-elem'
|
||||
import { BubbleText } from '@/app/components/base/icons/src/vender/solid/education'
|
||||
import Radio from '@/app/components/base/radio/ui'
|
||||
import { CuteRobote } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { CuteRobot } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { Settings04 } from '@/app/components/base/icons/src/vender/line/general'
|
||||
import { ArrowUpRight } from '@/app/components/base/icons/src/vender/line/arrows'
|
||||
import type { AgentConfig } from '@/models/debug'
|
||||
|
@ -117,7 +117,7 @@ const AssistantTypePicker: FC<Props> = ({
|
|||
>
|
||||
<PortalToFollowElemTrigger onClick={() => setOpen(v => !v)}>
|
||||
<div className={cn(open && 'bg-gray-50', 'flex items-center h-8 px-3 border border-black/5 rounded-lg cursor-pointer select-none space-x-1 text-indigo-600')}>
|
||||
{isAgent ? <BubbleText className='w-3 h-3' /> : <CuteRobote className='w-3 h-3' />}
|
||||
{isAgent ? <BubbleText className='w-3 h-3' /> : <CuteRobot className='w-3 h-3' />}
|
||||
<div className='text-xs font-medium'>{t(`appDebug.assistantType.${isAgent ? 'agentAssistant' : 'chatAssistant'}.name`)}</div>
|
||||
<RiArrowDownSLine className='w-3 h-3' />
|
||||
</div>
|
||||
|
@ -135,7 +135,7 @@ const AssistantTypePicker: FC<Props> = ({
|
|||
onClick={handleChange}
|
||||
/>
|
||||
<SelectItem
|
||||
Icon={CuteRobote}
|
||||
Icon={CuteRobot}
|
||||
value='agent'
|
||||
disabled={disabled}
|
||||
text={t('appDebug.assistantType.agentAssistant.name')}
|
||||
|
|
|
@ -35,7 +35,7 @@ function useFeature({
|
|||
moderation: boolean
|
||||
setModeration: (moderation: boolean) => void
|
||||
}) {
|
||||
const [tempshowOpeningStatement, setTempShowOpeningStatement] = React.useState(!!introduction)
|
||||
const [tempShowOpeningStatement, setTempShowOpeningStatement] = React.useState(!!introduction)
|
||||
useEffect(() => {
|
||||
// wait to api data back
|
||||
if (introduction)
|
||||
|
@ -48,7 +48,7 @@ function useFeature({
|
|||
// }, [moreLikeThis])
|
||||
|
||||
const featureConfig = {
|
||||
openingStatement: tempshowOpeningStatement,
|
||||
openingStatement: tempShowOpeningStatement,
|
||||
moreLikeThis,
|
||||
suggestedQuestionsAfterAnswer,
|
||||
speechToText,
|
||||
|
|
|
@ -7,9 +7,9 @@ import { useBoolean, useScroll } from 'ahooks'
|
|||
import { useFormattingChangedDispatcher } from '../debug/hooks'
|
||||
import DatasetConfig from '../dataset-config'
|
||||
import ChatGroup from '../features/chat-group'
|
||||
import ExperienceEnchanceGroup from '../features/experience-enchance-group'
|
||||
import ExperienceEnhanceGroup from '../features/experience-enhance-group'
|
||||
import Toolbox from '../toolbox'
|
||||
import HistoryPanel from '../config-prompt/conversation-histroy/history-panel'
|
||||
import HistoryPanel from '../config-prompt/conversation-history/history-panel'
|
||||
import ConfigVision from '../config-vision'
|
||||
import useAnnotationConfig from '../toolbox/annotation/use-annotation-config'
|
||||
import AddFeatureBtn from './feature/add-feature-btn'
|
||||
|
@ -254,7 +254,7 @@ const Config: FC = () => {
|
|||
/>
|
||||
)}
|
||||
|
||||
{/* ChatConifig */}
|
||||
{/* ChatConfig */}
|
||||
{
|
||||
hasChatConfig && (
|
||||
<ChatGroup
|
||||
|
@ -277,7 +277,7 @@ const Config: FC = () => {
|
|||
|
||||
{/* Text Generation config */}{
|
||||
hasCompletionConfig && (
|
||||
<ExperienceEnchanceGroup
|
||||
<ExperienceEnhanceGroup
|
||||
isShowMoreLike={moreLikeThisConfig.enabled}
|
||||
isShowTextToSpeech={featureConfig.textToSpeech && !!text2speechDefaultModel}
|
||||
/>
|
||||
|
|
|
@ -70,13 +70,13 @@ const ParamsConfig = ({
|
|||
|
||||
const {
|
||||
defaultModel: rerankDefaultModel,
|
||||
currentModel: isRerankDefaultModelVaild,
|
||||
currentModel: isRerankDefaultModelValid,
|
||||
} = useModelListAndDefaultModelAndCurrentProviderAndModel(ModelTypeEnum.rerank)
|
||||
|
||||
const isValid = () => {
|
||||
let errMsg = ''
|
||||
if (tempDataSetConfigs.retrieval_model === RETRIEVE_TYPE.multiWay) {
|
||||
if (!tempDataSetConfigs.reranking_model?.reranking_model_name && (!rerankDefaultModel && isRerankDefaultModelVaild))
|
||||
if (!tempDataSetConfigs.reranking_model?.reranking_model_name && (!rerankDefaultModel && isRerankDefaultModelValid))
|
||||
errMsg = t('appDebug.datasetConfig.rerankModelRequired')
|
||||
}
|
||||
if (errMsg) {
|
||||
|
|
|
@ -135,7 +135,7 @@ const SelectDataSet: FC<ISelectDataSetProps> = ({
|
|||
</div>
|
||||
<div className={cn('max-w-[200px] text-[13px] font-medium text-gray-800 overflow-hidden text-ellipsis whitespace-nowrap', !item.embedding_available && 'opacity-50 !max-w-[120px]')}>{item.name}</div>
|
||||
{!item.embedding_available && (
|
||||
<span className='ml-1 shrink-0 px-1 border boder-gray-200 rounded-md text-gray-500 text-xs font-normal leading-[18px]'>{t('dataset.unavailable')}</span>
|
||||
<span className='ml-1 shrink-0 px-1 border border-gray-200 rounded-md text-gray-500 text-xs font-normal leading-[18px]'>{t('dataset.unavailable')}</span>
|
||||
)}
|
||||
</div>
|
||||
{
|
||||
|
|
|
@ -51,7 +51,7 @@ const SettingsModal: FC<SettingsModalProps> = ({
|
|||
const {
|
||||
modelList: rerankModelList,
|
||||
defaultModel: rerankDefaultModel,
|
||||
currentModel: isRerankDefaultModelVaild,
|
||||
currentModel: isRerankDefaultModelValid,
|
||||
} = useModelListAndDefaultModelAndCurrentProviderAndModel(ModelTypeEnum.rerank)
|
||||
const { t } = useTranslation()
|
||||
const { notify } = useToastContext()
|
||||
|
@ -83,7 +83,7 @@ const SettingsModal: FC<SettingsModalProps> = ({
|
|||
if (
|
||||
!isReRankModelSelected({
|
||||
rerankDefaultModel,
|
||||
isRerankDefaultModelVaild: !!isRerankDefaultModelVaild,
|
||||
isRerankDefaultModelValid: !!isRerankDefaultModelValid,
|
||||
rerankModelList,
|
||||
retrievalConfig,
|
||||
indexMethod,
|
||||
|
|
|
@ -89,7 +89,7 @@ const ChatItem: FC<ChatItemProps> = ({
|
|||
`apps/${appId}/chat-messages`,
|
||||
data,
|
||||
{
|
||||
onGetConvesationMessages: (conversationId, getAbortController) => fetchConversationMessages(appId, conversationId, getAbortController),
|
||||
onGetConversationMessages: (conversationId, getAbortController) => fetchConversationMessages(appId, conversationId, getAbortController),
|
||||
onGetSuggestedQuestions: (responseItemId, getAbortController) => fetchSuggestedQuestions(appId, responseItemId, getAbortController),
|
||||
},
|
||||
)
|
||||
|
|
|
@ -94,7 +94,7 @@ const DebugWithSingleModel = forwardRef<DebugWithSingleModelRefType, DebugWithSi
|
|||
`apps/${appId}/chat-messages`,
|
||||
data,
|
||||
{
|
||||
onGetConvesationMessages: (conversationId, getAbortController) => fetchConversationMessages(appId, conversationId, getAbortController),
|
||||
onGetConversationMessages: (conversationId, getAbortController) => fetchConversationMessages(appId, conversationId, getAbortController),
|
||||
onGetSuggestedQuestions: (responseItemId, getAbortController) => fetchSuggestedQuestions(appId, responseItemId, getAbortController),
|
||||
},
|
||||
)
|
||||
|
|
|
@ -287,7 +287,7 @@ const OpeningStatement: FC<IOpeningStatementProps> = ({
|
|||
{isShowConfirmAddVar && (
|
||||
<ConfirmAddVar
|
||||
varNameArr={notIncludeKeys}
|
||||
onConfrim={autoAddVar}
|
||||
onConfirm={autoAddVar}
|
||||
onCancel={cancelAutoAddVar}
|
||||
onHide={hideConfirmAddVar}
|
||||
/>
|
||||
|
|
|
@ -16,7 +16,7 @@ type ExperienceGroupProps = {
|
|||
isShowMoreLike: boolean
|
||||
}
|
||||
|
||||
const ExperienceEnchanceGroup: FC<ExperienceGroupProps> = ({
|
||||
const ExperienceEnhanceGroup: FC<ExperienceGroupProps> = ({
|
||||
isShowTextToSpeech,
|
||||
isShowMoreLike,
|
||||
}) => {
|
||||
|
@ -40,4 +40,4 @@ const ExperienceEnchanceGroup: FC<ExperienceGroupProps> = ({
|
|||
</div>
|
||||
)
|
||||
}
|
||||
export default React.memo(ExperienceEnchanceGroup)
|
||||
export default React.memo(ExperienceEnhanceGroup)
|
|
@ -14,7 +14,7 @@ import Loading from '../../base/loading'
|
|||
import AppPublisher from '../app-publisher'
|
||||
import AgentSettingButton from './config/agent-setting-button'
|
||||
import useAdvancedPromptConfig from './hooks/use-advanced-prompt-config'
|
||||
import EditHistoryModal from './config-prompt/conversation-histroy/edit-modal'
|
||||
import EditHistoryModal from './config-prompt/conversation-history/edit-modal'
|
||||
import {
|
||||
useDebugWithSingleOrMultipleModel,
|
||||
useFormattingChangedDispatcher,
|
||||
|
|
|
@ -64,7 +64,7 @@ const ModerationSettingModal: FC<ModerationSettingModalProps> = ({
|
|||
const systemOpenaiProviderQuota = systemOpenaiProviderEnabled ? openaiProvider?.system_configuration.quota_configurations.find(item => item.quota_type === openaiProvider.system_configuration.current_quota_type) : undefined
|
||||
const systemOpenaiProviderCanUse = systemOpenaiProviderQuota?.is_valid
|
||||
const customOpenaiProvidersCanUse = openaiProvider?.custom_configuration.status === CustomConfigurationStatusEnum.active
|
||||
const openaiProviderConfiged = customOpenaiProvidersCanUse || systemOpenaiProviderCanUse
|
||||
const isOpenAIProviderConfigured = customOpenaiProvidersCanUse || systemOpenaiProviderCanUse
|
||||
const providers: Provider[] = [
|
||||
{
|
||||
key: 'openai_moderation',
|
||||
|
@ -190,7 +190,7 @@ const ModerationSettingModal: FC<ModerationSettingModalProps> = ({
|
|||
}
|
||||
|
||||
const handleSave = () => {
|
||||
if (localeData.type === 'openai_moderation' && !openaiProviderConfiged)
|
||||
if (localeData.type === 'openai_moderation' && !isOpenAIProviderConfigured)
|
||||
return
|
||||
|
||||
if (!localeData.config?.inputs_config?.enabled && !localeData.config?.outputs_config?.enabled) {
|
||||
|
@ -254,7 +254,7 @@ const ModerationSettingModal: FC<ModerationSettingModalProps> = ({
|
|||
className={`
|
||||
flex items-center px-3 py-2 rounded-lg text-sm text-gray-900 cursor-pointer
|
||||
${localeData.type === provider.key ? 'bg-white border-[1.5px] border-primary-400 shadow-sm' : 'border border-gray-100 bg-gray-25'}
|
||||
${localeData.type === 'openai_moderation' && provider.key === 'openai_moderation' && !openaiProviderConfiged && 'opacity-50'}
|
||||
${localeData.type === 'openai_moderation' && provider.key === 'openai_moderation' && !isOpenAIProviderConfigured && 'opacity-50'}
|
||||
`}
|
||||
onClick={() => handleDataTypeChange(provider.key)}
|
||||
>
|
||||
|
@ -267,7 +267,7 @@ const ModerationSettingModal: FC<ModerationSettingModalProps> = ({
|
|||
}
|
||||
</div>
|
||||
{
|
||||
!isLoading && !openaiProviderConfiged && localeData.type === 'openai_moderation' && (
|
||||
!isLoading && !isOpenAIProviderConfigured && localeData.type === 'openai_moderation' && (
|
||||
<div className='flex items-center mt-2 px-3 py-2 bg-[#FFFAEB] rounded-lg border border-[#FEF0C7]'>
|
||||
<InfoCircle className='mr-1 w-4 h-4 text-[#F79009]' />
|
||||
<div className='flex items-center text-xs font-medium text-gray-700'>
|
||||
|
@ -361,7 +361,7 @@ const ModerationSettingModal: FC<ModerationSettingModalProps> = ({
|
|||
<Button
|
||||
variant='primary'
|
||||
onClick={handleSave}
|
||||
disabled={localeData.type === 'openai_moderation' && !openaiProviderConfiged}
|
||||
disabled={localeData.type === 'openai_moderation' && !isOpenAIProviderConfigured}
|
||||
>
|
||||
{t('common.operation.save')}
|
||||
</Button>
|
||||
|
|
|
@ -172,12 +172,12 @@ const ExternalDataToolModal: FC<ExternalDataToolModalProps> = ({
|
|||
}
|
||||
}
|
||||
|
||||
const formatedData = formatData(localeData)
|
||||
const formattedData = formatData(localeData)
|
||||
|
||||
if (onValidateBeforeSave && !onValidateBeforeSave(formatedData))
|
||||
if (onValidateBeforeSave && !onValidateBeforeSave(formattedData))
|
||||
return
|
||||
|
||||
onSave(formatData(formatedData))
|
||||
onSave(formatData(formattedData))
|
||||
}
|
||||
|
||||
const action = data.type ? t('common.operation.edit') : t('common.operation.add')
|
||||
|
|
|
@ -21,7 +21,7 @@ import Modal from '@/app/components/base/modal'
|
|||
import Button from '@/app/components/base/button'
|
||||
import AppIcon from '@/app/components/base/app-icon'
|
||||
import AppsFull from '@/app/components/billing/apps-full-in-dialog'
|
||||
import { AiText, ChatBot, CuteRobote } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { AiText, ChatBot, CuteRobot } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { Route } from '@/app/components/base/icons/src/vender/solid/mapsAndTravel'
|
||||
import Tooltip from '@/app/components/base/tooltip'
|
||||
import { NEED_REFRESH_APP_LIST_KEY } from '@/config'
|
||||
|
@ -158,7 +158,7 @@ const CreateAppModal = ({ show, onSuccess, onClose }: CreateAppDialogProps) => {
|
|||
setShowChatBotType(false)
|
||||
}}
|
||||
>
|
||||
<CuteRobote className='w-6 h-6 text-indigo-600' />
|
||||
<CuteRobot className='w-6 h-6 text-indigo-600' />
|
||||
<div className='h-5 text-[13px] font-medium leading-[18px]'>{t('app.types.agent')}</div>
|
||||
</div>
|
||||
</Tooltip>
|
||||
|
|
|
@ -119,8 +119,8 @@ const Logs: FC<ILogsProps> = ({ appDetail }) => {
|
|||
middlePagesSiblingCount={1}
|
||||
setCurrentPage={setCurrPage}
|
||||
totalPages={Math.ceil(total / APP_PAGE_LIMIT)}
|
||||
truncableClassName="w-8 px-0.5 text-center"
|
||||
truncableText="..."
|
||||
truncatableClassName="w-8 px-0.5 text-center"
|
||||
truncatableText="..."
|
||||
>
|
||||
<Pagination.PrevButton
|
||||
disabled={currPage === 0}
|
||||
|
|
|
@ -19,7 +19,7 @@ import { useTranslation } from 'react-i18next'
|
|||
import s from './style.module.css'
|
||||
import VarPanel from './var-panel'
|
||||
import cn from '@/utils/classnames'
|
||||
import type { FeedbackFunc, Feedbacktype, IChatItem, SubmitAnnotationFunc } from '@/app/components/base/chat/chat/type'
|
||||
import type { FeedbackFunc, FeedbackType, IChatItem, SubmitAnnotationFunc } from '@/app/components/base/chat/chat/type'
|
||||
import type { Annotation, ChatConversationFullDetailResponse, ChatConversationGeneralDetail, ChatConversationsResponse, ChatMessage, ChatMessagesRequest, CompletionConversationFullDetailResponse, CompletionConversationGeneralDetail, CompletionConversationsResponse, LogAnnotation } from '@/models/log'
|
||||
import type { App } from '@/types/app'
|
||||
import Loading from '@/app/components/base/loading'
|
||||
|
@ -541,7 +541,7 @@ const CompletionConversationDetailComp: FC<{ appId?: string; conversationId?: st
|
|||
const { notify } = useContext(ToastContext)
|
||||
const { t } = useTranslation()
|
||||
|
||||
const handleFeedback = async (mid: string, { rating }: Feedbacktype): Promise<boolean> => {
|
||||
const handleFeedback = async (mid: string, { rating }: FeedbackType): Promise<boolean> => {
|
||||
try {
|
||||
await updateLogMessageFeedbacks({ url: `/apps/${appId}/feedbacks`, body: { message_id: mid, rating } })
|
||||
conversationDetailMutate()
|
||||
|
@ -586,7 +586,7 @@ const ChatConversationDetailComp: FC<{ appId?: string; conversationId?: string }
|
|||
const { notify } = useContext(ToastContext)
|
||||
const { t } = useTranslation()
|
||||
|
||||
const handleFeedback = async (mid: string, { rating }: Feedbacktype): Promise<boolean> => {
|
||||
const handleFeedback = async (mid: string, { rating }: FeedbackType): Promise<boolean> => {
|
||||
try {
|
||||
await updateLogMessageFeedbacks({ url: `/apps/${appId}/feedbacks`, body: { message_id: mid, rating } })
|
||||
notify({ type: 'success', message: t('common.actionMsg.modifiedSuccessfully') })
|
||||
|
|
|
@ -16,13 +16,13 @@ import { Markdown } from '@/app/components/base/markdown'
|
|||
import Loading from '@/app/components/base/loading'
|
||||
import Toast from '@/app/components/base/toast'
|
||||
import AudioBtn from '@/app/components/base/audio-btn'
|
||||
import type { Feedbacktype } from '@/app/components/base/chat/chat/type'
|
||||
import type { FeedbackType } from '@/app/components/base/chat/chat/type'
|
||||
import { fetchMoreLikeThis, updateFeedback } from '@/service/share'
|
||||
import { File02 } from '@/app/components/base/icons/src/vender/line/files'
|
||||
import { Bookmark } from '@/app/components/base/icons/src/vender/line/general'
|
||||
import { Stars02 } from '@/app/components/base/icons/src/vender/line/weather'
|
||||
import { RefreshCcw01 } from '@/app/components/base/icons/src/vender/line/arrows'
|
||||
import { fetchTextGenerationMessge } from '@/service/debug'
|
||||
import { fetchTextGenerationMessage } from '@/service/debug'
|
||||
import AnnotationCtrlBtn from '@/app/components/app/configuration/toolbox/annotation/annotation-ctrl-btn'
|
||||
import EditReplyModal from '@/app/components/app/annotation/edit-annotation-modal'
|
||||
import { useStore as useAppStore } from '@/app/components/app/store'
|
||||
|
@ -47,8 +47,8 @@ export type IGenerationItemProps = {
|
|||
isInWebApp?: boolean
|
||||
moreLikeThis?: boolean
|
||||
depth?: number
|
||||
feedback?: Feedbacktype
|
||||
onFeedback?: (feedback: Feedbacktype) => void
|
||||
feedback?: FeedbackType
|
||||
onFeedback?: (feedback: FeedbackType) => void
|
||||
onSave?: (messageId: string) => void
|
||||
isMobile?: boolean
|
||||
isInstalledApp: boolean
|
||||
|
@ -125,7 +125,7 @@ const GenerationItem: FC<IGenerationItemProps> = ({
|
|||
const [completionRes, setCompletionRes] = useState('')
|
||||
const [childMessageId, setChildMessageId] = useState<string | null>(null)
|
||||
const hasChild = !!childMessageId
|
||||
const [childFeedback, setChildFeedback] = useState<Feedbacktype>({
|
||||
const [childFeedback, setChildFeedback] = useState<FeedbackType>({
|
||||
rating: null,
|
||||
})
|
||||
const {
|
||||
|
@ -135,7 +135,7 @@ const GenerationItem: FC<IGenerationItemProps> = ({
|
|||
const setCurrentLogItem = useAppStore(s => s.setCurrentLogItem)
|
||||
const setShowPromptLogModal = useAppStore(s => s.setShowPromptLogModal)
|
||||
|
||||
const handleFeedback = async (childFeedback: Feedbacktype) => {
|
||||
const handleFeedback = async (childFeedback: FeedbackType) => {
|
||||
await updateFeedback({ url: `/messages/${childMessageId}/feedbacks`, body: { rating: childFeedback.rating } }, isInstalledApp, installedAppId)
|
||||
setChildFeedback(childFeedback)
|
||||
}
|
||||
|
@ -205,7 +205,7 @@ const GenerationItem: FC<IGenerationItemProps> = ({
|
|||
}, [isLoading])
|
||||
|
||||
const handleOpenLogModal = async () => {
|
||||
const data = await fetchTextGenerationMessge({
|
||||
const data = await fetchTextGenerationMessage({
|
||||
appId: params.appId as string,
|
||||
messageId: messageId!,
|
||||
})
|
||||
|
|
|
@ -9,7 +9,7 @@ import {
|
|||
} from '@/app/components/base/portal-to-follow-elem'
|
||||
import { Check, DotsGrid } from '@/app/components/base/icons/src/vender/line/general'
|
||||
import { XCircle } from '@/app/components/base/icons/src/vender/solid/general'
|
||||
import { ChatBot, CuteRobote } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { ChatBot, CuteRobot } from '@/app/components/base/icons/src/vender/solid/communication'
|
||||
import { Route } from '@/app/components/base/icons/src/vender/solid/mapsAndTravel'
|
||||
export type AppSelectorProps = {
|
||||
value: string
|
||||
|
@ -65,7 +65,7 @@ const AppTypeSelector = ({ value, onChange }: AppSelectorProps) => {
|
|||
{value === 'agent' && (
|
||||
<>
|
||||
<div className='w-4 h-4 p-[1px]'>
|
||||
<CuteRobote className='w-3.5 h-3.5 text-indigo-600' />
|
||||
<CuteRobot className='w-3.5 h-3.5 text-indigo-600' />
|
||||
</div>
|
||||
<div className=''>{t('app.typeSelector.agent')}</div>
|
||||
<div className='w-4 h-4 p-[1px]' onClick={(e) => {
|
||||
|
@ -106,7 +106,7 @@ const AppTypeSelector = ({ value, onChange }: AppSelectorProps) => {
|
|||
onChange('agent')
|
||||
setOpen(false)
|
||||
}}>
|
||||
<CuteRobote className='mr-2 w-4 h-4 text-indigo-600' />
|
||||
<CuteRobot className='mr-2 w-4 h-4 text-indigo-600' />
|
||||
<div className='grow text-gray-700 text-[13px] font-medium leading-[18px]'>{t('app.typeSelector.agent')}</div>
|
||||
{value === 'agent' && <Check className='w-4 h-4 text-primary-600' />}
|
||||
</div>
|
||||
|
|
|
@ -93,8 +93,8 @@ const Logs: FC<ILogsProps> = ({ appDetail }) => {
|
|||
middlePagesSiblingCount={1}
|
||||
setCurrentPage={setCurrPage}
|
||||
totalPages={Math.ceil(total / APP_PAGE_LIMIT)}
|
||||
truncableClassName="w-8 px-0.5 text-center"
|
||||
truncableText="..."
|
||||
truncatableClassName="w-8 px-0.5 text-center"
|
||||
truncatableText="..."
|
||||
>
|
||||
<Pagination.PrevButton
|
||||
disabled={currPage === 0}
|
||||
|
|
|
@ -97,7 +97,7 @@ const AgentLogDetail: FC<AgentLogDetailProps> = ({
|
|||
onClick={() => switchTab('TRACING')}
|
||||
>{t('runLog.tracing')}</div>
|
||||
</div>
|
||||
{/* panel detal */}
|
||||
{/* panel detail */}
|
||||
<div className={cn('grow bg-white h-0 overflow-y-auto rounded-b-2xl', currentTab !== 'DETAIL' && '!bg-gray-50')}>
|
||||
{loading && (
|
||||
<div className='flex h-full items-center justify-center bg-white'>
|
||||
|
|
|
@ -53,7 +53,7 @@ const BlockInput: FC<IBlockInputProps> = ({
|
|||
const [isEditing, setIsEditing] = useState<boolean>(false)
|
||||
useEffect(() => {
|
||||
if (isEditing && contentEditableRef.current) {
|
||||
// TODO: Focus at the click positon
|
||||
// TODO: Focus at the click position
|
||||
if (currentValue)
|
||||
contentEditableRef.current.setSelectionRange(currentValue.length, currentValue.length)
|
||||
|
||||
|
@ -119,7 +119,7 @@ const BlockInput: FC<IBlockInputProps> = ({
|
|||
onBlur={() => {
|
||||
blur()
|
||||
setIsEditing(false)
|
||||
// click confirm also make blur. Then outter value is change. So below code has problem.
|
||||
// click confirm also make blur. Then outer value is change. So below code has problem.
|
||||
// setTimeout(() => {
|
||||
// handleCancel()
|
||||
// }, 1000)
|
||||
|
|
|
@ -217,12 +217,12 @@ export const useChatWithHistory = (installedAppInfo?: InstalledApp) => {
|
|||
}, [newConversation])
|
||||
|
||||
const currentConversationItem = useMemo(() => {
|
||||
let coversationItem = conversationList.find(item => item.id === currentConversationId)
|
||||
let conversationItem = conversationList.find(item => item.id === currentConversationId)
|
||||
|
||||
if (!coversationItem && pinnedConversationList.length)
|
||||
coversationItem = pinnedConversationList.find(item => item.id === currentConversationId)
|
||||
if (!conversationItem && pinnedConversationList.length)
|
||||
conversationItem = pinnedConversationList.find(item => item.id === currentConversationId)
|
||||
|
||||
return coversationItem
|
||||
return conversationItem
|
||||
}, [conversationList, currentConversationId, pinnedConversationList])
|
||||
|
||||
const { notify } = useToastContext()
|
||||
|
|
|
@ -24,7 +24,7 @@ const Citation: FC<CitationProps> = ({
|
|||
}) => {
|
||||
const { t } = useTranslation()
|
||||
const elesRef = useRef<HTMLDivElement[]>([])
|
||||
const [limitNumberInOneLine, setlimitNumberInOneLine] = useState(0)
|
||||
const [limitNumberInOneLine, setLimitNumberInOneLine] = useState(0)
|
||||
const [showMore, setShowMore] = useState(false)
|
||||
const resources = useMemo(() => data.reduce((prev: Resources[], next) => {
|
||||
const documentId = next.document_id
|
||||
|
@ -57,14 +57,14 @@ const Citation: FC<CitationProps> = ({
|
|||
totalWidth -= elesRef.current[i].clientWidth
|
||||
|
||||
if (totalWidth + 34 > containerWidth!)
|
||||
setlimitNumberInOneLine(i - 1)
|
||||
setLimitNumberInOneLine(i - 1)
|
||||
else
|
||||
setlimitNumberInOneLine(i)
|
||||
setLimitNumberInOneLine(i)
|
||||
|
||||
break
|
||||
}
|
||||
else {
|
||||
setlimitNumberInOneLine(i + 1)
|
||||
setLimitNumberInOneLine(i + 1)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
@ -26,7 +26,7 @@ import { AudioPlayerManager } from '@/app/components/base/audio-btn/audio.player
|
|||
|
||||
type GetAbortController = (abortController: AbortController) => void
|
||||
type SendCallback = {
|
||||
onGetConvesationMessages?: (conversationId: string, getAbortController: GetAbortController) => Promise<any>
|
||||
onGetConversationMessages?: (conversationId: string, getAbortController: GetAbortController) => Promise<any>
|
||||
onGetSuggestedQuestions?: (responseItemId: string, getAbortController: GetAbortController) => Promise<any>
|
||||
onConversationComplete?: (conversationId: string) => void
|
||||
isPublicAPI?: boolean
|
||||
|
@ -198,7 +198,7 @@ export const useChat = (
|
|||
url: string,
|
||||
data: any,
|
||||
{
|
||||
onGetConvesationMessages,
|
||||
onGetConversationMessages,
|
||||
onGetSuggestedQuestions,
|
||||
onConversationComplete,
|
||||
isPublicAPI,
|
||||
|
@ -324,8 +324,8 @@ export const useChat = (
|
|||
if (onConversationComplete)
|
||||
onConversationComplete(conversationId.current)
|
||||
|
||||
if (conversationId.current && !hasStopResponded.current && onGetConvesationMessages) {
|
||||
const { data }: any = await onGetConvesationMessages(
|
||||
if (conversationId.current && !hasStopResponded.current && onGetConversationMessages) {
|
||||
const { data }: any = await onGetConversationMessages(
|
||||
conversationId.current,
|
||||
newAbortController => conversationMessagesAbortControllerRef.current = newAbortController,
|
||||
)
|
||||
|
|
|
@ -106,7 +106,7 @@ const Chat: FC<ChatProps> = ({
|
|||
const chatFooterInnerRef = useRef<HTMLDivElement>(null)
|
||||
const userScrolledRef = useRef(false)
|
||||
|
||||
const handleScrolltoBottom = useCallback(() => {
|
||||
const handleScrollToBottom = useCallback(() => {
|
||||
if (chatContainerRef.current && !userScrolledRef.current)
|
||||
chatContainerRef.current.scrollTop = chatContainerRef.current.scrollHeight
|
||||
}, [])
|
||||
|
@ -123,14 +123,14 @@ const Chat: FC<ChatProps> = ({
|
|||
}, [])
|
||||
|
||||
useEffect(() => {
|
||||
handleScrolltoBottom()
|
||||
handleScrollToBottom()
|
||||
handleWindowResize()
|
||||
}, [handleScrolltoBottom, handleWindowResize])
|
||||
}, [handleScrollToBottom, handleWindowResize])
|
||||
|
||||
useEffect(() => {
|
||||
if (chatContainerRef.current) {
|
||||
requestAnimationFrame(() => {
|
||||
handleScrolltoBottom()
|
||||
handleScrollToBottom()
|
||||
handleWindowResize()
|
||||
})
|
||||
}
|
||||
|
@ -148,7 +148,7 @@ const Chat: FC<ChatProps> = ({
|
|||
const { blockSize } = entry.borderBoxSize[0]
|
||||
|
||||
chatContainerRef.current!.style.paddingBottom = `${blockSize}px`
|
||||
handleScrolltoBottom()
|
||||
handleScrollToBottom()
|
||||
}
|
||||
})
|
||||
|
||||
|
@ -158,7 +158,7 @@ const Chat: FC<ChatProps> = ({
|
|||
resizeObserver.disconnect()
|
||||
}
|
||||
}
|
||||
}, [handleScrolltoBottom])
|
||||
}, [handleScrollToBottom])
|
||||
|
||||
useEffect(() => {
|
||||
const chatContainer = chatContainerRef.current
|
||||
|
|
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user