Fix variable typo (#8084)
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Nam Vu
GitHub
parent
b1918dae5e
commit
2d7954c7da
215 changed files with 599 additions and 597 deletions
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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 value is the md = genai.GenerativeModel(model)error type thrown by the model,
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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 value is the md = genai.GenerativeModel(model)error type thrown by the model,
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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 value is the md = genai.GenerativeModel(model)error type thrown by the model,
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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 value is the md = gml.GenerativeModel(model)error type thrown by the model,
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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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