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Author SHA1 Message Date
QiMington
924c5275e6
Merge 1c1dcc0e18 into 51db59622c 2024-11-15 15:45:34 +08:00
Bowen Liang
51db59622c
chore(lint): cleanup repeated cause exception in logging.exception replaced by helpful message (#10425) 2024-11-15 15:41:40 +08:00
QiMington
1c1dcc0e18 fix: replace setup.py with pyproject.toml 2024-11-15 14:15:55 +08:00
crazywoola
db1d2aaff5
Feat/add Slovensko (Slovenija) (#10731)
Co-authored-by: XHorizont.com <johnny@xhorizont.com>
2024-11-15 13:59:08 +08:00
Steven Lynn
4322fdc910
Feat/add reddit icon (#10733) 2024-11-15 13:55:46 +08:00
非法操作
2a5c5a4e15
fix: remove default model selection for audio tool (#10729) 2024-11-15 12:40:41 +08:00
QiMington
ed07ce1098 refactor: python-client 2024-11-07 23:54:33 +08:00
264 changed files with 8926 additions and 988 deletions

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## Licença
Este repositório está disponível sob a [Licença de Código Aberto Dify](LICENSE), que é essencialmente Apache 2.0 com algumas restrições adicionais.
Este repositório está disponível sob a [Licença de Código Aberto Dify](LICENSE), que é essencialmente Apache 2.0 com algumas restrições adicionais.

180
README_SI.md Normal file
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![cover-v5-optimized](https://github.com/langgenius/dify/assets/13230914/f9e19af5-61ba-4119-b926-d10c4c06ebab)
<p align="center">
📌 <a href="https://dify.ai/blog/introducing-dify-workflow-file-upload-a-demo-on-ai-podcast">Predstavljamo nalaganje datotek Dify Workflow: znova ustvarite Google NotebookLM Podcast</a>
</p>
<p align="center">
<a href="https://cloud.dify.ai">Dify Cloud</a> ·
<a href="https://docs.dify.ai/getting-started/install-self-hosted">Samostojno gostovanje</a> ·
<a href="https://docs.dify.ai">Dokumentacija</a> ·
<a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Povpraševanje za podjetja</a>
</p>
<p align="center">
<a href="https://dify.ai" target="_blank">
<img alt="Static Badge" src="https://img.shields.io/badge/Product-F04438"></a>
<a href="https://dify.ai/pricing" target="_blank">
<img alt="Static Badge" src="https://img.shields.io/badge/free-pricing?logo=free&color=%20%23155EEF&label=pricing&labelColor=%20%23528bff"></a>
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alt="follow on X(Twitter)"></a>
<a href="https://hub.docker.com/u/langgenius" target="_blank">
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
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</p>
<p align="center">
<a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
<a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
<a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
<a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
<a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
<a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
<a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
<a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
<a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
<a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
<a href="./README_SI.md"><img alt="README Slovenščina" src="https://img.shields.io/badge/Sloven%C5%A1%C4%8Dina-d9d9d9"></a>
</p>
Dify je odprtokodna platforma za razvoj aplikacij LLM. Njegov intuitivni vmesnik združuje agentski potek dela z umetno inteligenco, cevovod RAG, zmogljivosti agentov, upravljanje modelov, funkcije opazovanja in več, kar vam omogoča hiter prehod od prototipa do proizvodnje.
## Hitri začetek
> Preden namestite Dify, se prepričajte, da vaša naprava izpolnjuje naslednje minimalne sistemske zahteve:
>
>- CPU >= 2 Core
>- RAM >= 4 GiB
</br>
Najlažji način za zagon strežnika Dify je prek docker compose . Preden zaženete Dify z naslednjimi ukazi, se prepričajte, da sta Docker in Docker Compose nameščena na vašem računalniku:
```bash
cd dify
cd docker
cp .env.example .env
docker compose up -d
```
Po zagonu lahko dostopate do nadzorne plošče Dify v brskalniku na [http://localhost/install](http://localhost/install) in začnete postopek inicializacije.
#### Iskanje pomoči
Prosimo, glejte naša pogosta vprašanja [FAQ](https://docs.dify.ai/getting-started/install-self-hosted/faqs) če naletite na težave pri nastavitvi Dify. Če imate še vedno težave, se obrnite na [skupnost ali nas](#community--contact).
> Če želite prispevati k Difyju ali narediti dodaten razvoj, glejte naš vodnik za [uvajanje iz izvorne kode](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code)
## Ključne značilnosti
**1. Potek dela**:
Zgradite in preizkusite zmogljive poteke dela AI na vizualnem platnu, pri čemer izkoristite vse naslednje funkcije in več.
https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa
**2. Celovita podpora za modele**:
Brezhibna integracija s stotinami lastniških/odprtokodnih LLM-jev ducatov ponudnikov sklepanja in samostojnih rešitev, ki pokrivajo GPT, Mistral, Llama3 in vse modele, združljive z API-jem OpenAI. Celoten seznam podprtih ponudnikov modelov najdete [tukaj](https://docs.dify.ai/getting-started/readme/model-providers).
![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)
**3. Prompt IDE**:
intuitivni vmesnik za ustvarjanje pozivov, primerjavo zmogljivosti modela in dodajanje dodatnih funkcij, kot je pretvorba besedila v govor, aplikaciji, ki temelji na klepetu.
**4. RAG Pipeline**:
E Obsežne zmogljivosti RAG, ki pokrivajo vse od vnosa dokumenta do priklica, s podporo za ekstrakcijo besedila iz datotek PDF, PPT in drugih običajnih formatov dokumentov.
**5. Agent capabilities**:
definirate lahko agente, ki temeljijo na klicanju funkcij LLM ali ReAct, in dodate vnaprej izdelana orodja ali orodja po meri za agenta. Dify ponuja več kot 50 vgrajenih orodij za agente AI, kot so Google Search, DALL·E, Stable Diffusion in WolframAlpha.
**6. LLMOps**:
Spremljajte in analizirajte dnevnike aplikacij in učinkovitost skozi čas. Pozive, nabore podatkov in modele lahko nenehno izboljšujete na podlagi proizvodnih podatkov in opomb.
**7. Backend-as-a-Service**:
AVse ponudbe Difyja so opremljene z ustreznimi API-ji, tako da lahko Dify brez težav integrirate v svojo poslovno logiko.
## Uporaba Dify
- **Cloud </br>**
Gostimo storitev Dify Cloud za vsakogar, ki jo lahko preizkusite brez nastavitev. Zagotavlja vse zmožnosti različice za samostojno namestitev in vključuje 200 brezplačnih klicev GPT-4 v načrtu peskovnika.
- **Self-hosting Dify Community Edition</br>**
Hitro zaženite Dify v svojem okolju s tem [začetnim vodnikom](#quick-start) . Za dodatne reference in podrobnejša navodila uporabite našo [dokumentacijo](https://docs.dify.ai) .
- **Dify za podjetja/organizacije</br>**
Ponujamo dodatne funkcije, osredotočene na podjetja. Zabeležite svoja vprašanja prek tega klepetalnega robota ali nam pošljite e-pošto, da se pogovorimo o potrebah podjetja. </br>
> Za novoustanovljena podjetja in mala podjetja, ki uporabljajo AWS, si oglejte Dify Premium na AWS Marketplace in ga z enim klikom uvedite v svoj AWS VPC. To je cenovno ugodna ponudba AMI z možnostjo ustvarjanja aplikacij z logotipom in blagovno znamko po meri.
## Staying ahead
Star Dify on GitHub and be instantly notified of new releases.
![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)
## Napredne nastavitve
Če morate prilagoditi konfiguracijo, si oglejte komentarje v naši datoteki .env.example in posodobite ustrezne vrednosti v svoji .env datoteki. Poleg tega boste morda morali prilagoditi docker-compose.yamlsamo datoteko, na primer spremeniti različice slike, preslikave vrat ali namestitve nosilca, glede na vaše specifično okolje in zahteve za uvajanje. Po kakršnih koli spremembah ponovno zaženite docker-compose up -d. Celoten seznam razpoložljivih spremenljivk okolja najdete tukaj .
Če želite konfigurirati visoko razpoložljivo nastavitev, so na voljo Helm Charts in datoteke YAML, ki jih prispeva skupnost, ki omogočajo uvedbo Difyja v Kubernetes.
- [Helm Chart by @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
- [Helm Chart by @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
- [YAML file by @Winson-030](https://github.com/Winson-030/dify-kubernetes)
#### Uporaba Terraform za uvajanje
namestite Dify v Cloud Platform z enim klikom z uporabo [terraform](https://www.terraform.io/)
##### Azure Global
- [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)
##### Google Cloud
- [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
## Prispevam
Za tiste, ki bi radi prispevali kodo, si oglejte naš vodnik za prispevke . Hkrati vas prosimo, da podprete Dify tako, da ga delite na družbenih medijih ter na dogodkih in konferencah.
> Iščemo sodelavce za pomoč pri prevajanju Difyja v jezike, ki niso mandarinščina ali angleščina. Če želite pomagati, si oglejte i18n README za več informacij in nam pustite komentar v global-userskanalu našega strežnika skupnosti Discord .
## Skupnost in stik
* [Github Discussion](https://github.com/langgenius/dify/discussions). Najboljše za: izmenjavo povratnih informacij in postavljanje vprašanj.
* [GitHub Issues](https://github.com/langgenius/dify/issues). Najboljše za: hrošče, na katere naletite pri uporabi Dify.AI, in predloge funkcij. Oglejte si naš [vodnik za prispevke](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md).
* [Discord](https://discord.gg/FngNHpbcY7). Najboljše za: deljenje vaših aplikacij in druženje s skupnostjo.
* [X(Twitter)](https://twitter.com/dify_ai). Najboljše za: deljenje vaših aplikacij in druženje s skupnostjo.
**Contributors**
<a href="https://github.com/langgenius/dify/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langgenius/dify" />
</a>
## Star history
[![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
## Varnostno razkritje
Zaradi zaščite vaše zasebnosti se izogibajte objavljanju varnostnih vprašanj na GitHub. Namesto tega pošljite vprašanja na security@dify.ai in zagotovili vam bomo podrobnejši odgovor.
## Licenca
To skladišče je na voljo pod [odprtokodno licenco Dify](LICENSE) , ki je v bistvu Apache 2.0 z nekaj dodatnimi omejitvami.

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<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
alt="theo dõi trên X(Twitter)"></a>
@ -235,4 +238,4 @@ Triển khai Dify lên nền tảng đám mây với một cú nhấp chuột b
## Giấy phép
Kho lưu trữ này có sẵn theo [Giấy phép Mã nguồn Mở Dify](LICENSE), về cơ bản là Apache 2.0 với một vài hạn chế bổ sung.
Kho lưu trữ này có sẵn theo [Giấy phép Mã nguồn Mở Dify](LICENSE), về cơ bản là Apache 2.0 với một vài hạn chế bổ sung.

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@ -589,7 +589,7 @@ def upgrade_db():
click.echo(click.style("Database migration successful!", fg="green"))
except Exception as e:
logging.exception(f"Database migration failed: {e}")
logging.exception("Failed to execute database migration")
finally:
lock.release()
else:
@ -633,7 +633,7 @@ where sites.id is null limit 1000"""
except Exception as e:
failed_app_ids.append(app_id)
click.echo(click.style("Failed to fix missing site for app {}".format(app_id), fg="red"))
logging.exception(f"Fix app related site missing issue failed, error: {e}")
logging.exception(f"Failed to fix app related site missing issue, app_id: {app_id}")
continue
if not processed_count:

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@ -17,6 +17,7 @@ language_timezone_mapping = {
"hi-IN": "Asia/Kolkata",
"tr-TR": "Europe/Istanbul",
"fa-IR": "Asia/Tehran",
"sl-SI": "Europe/Ljubljana",
}
languages = list(language_timezone_mapping.keys())

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@ -70,7 +70,7 @@ class ChatMessageAudioApi(Resource):
except ValueError as e:
raise e
except Exception as e:
logging.exception(f"internal server error, {str(e)}.")
logging.exception("Failed to handle post request to ChatMessageAudioApi")
raise InternalServerError()
@ -128,7 +128,7 @@ class ChatMessageTextApi(Resource):
except ValueError as e:
raise e
except Exception as e:
logging.exception(f"internal server error, {str(e)}.")
logging.exception("Failed to handle post request to ChatMessageTextApi")
raise InternalServerError()
@ -170,7 +170,7 @@ class TextModesApi(Resource):
except ValueError as e:
raise e
except Exception as e:
logging.exception(f"internal server error, {str(e)}.")
logging.exception("Failed to handle get request to TextModesApi")
raise InternalServerError()

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@ -948,7 +948,7 @@ class DocumentRetryApi(DocumentResource):
raise DocumentAlreadyFinishedError()
retry_documents.append(document)
except Exception as e:
logging.exception(f"Document {document_id} retry failed: {str(e)}")
logging.exception(f"Failed to retry document, document id: {document_id}")
continue
# retry document
DocumentService.retry_document(dataset_id, retry_documents)

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@ -72,7 +72,10 @@ class DefaultModelApi(Resource):
model=model_setting["model"],
)
except Exception as ex:
logging.exception(f"{model_setting['model_type']} save error: {ex}")
logging.exception(
f"Failed to update default model, model type: {model_setting['model_type']},"
f" model:{model_setting.get('model')}"
)
raise ex
return {"result": "success"}
@ -156,7 +159,10 @@ class ModelProviderModelApi(Resource):
credentials=args["credentials"],
)
except CredentialsValidateFailedError as ex:
logging.exception(f"save model credentials error: {ex}")
logging.exception(
f"Failed to save model credentials, tenant_id: {tenant_id},"
f" model: {args.get('model')}, model_type: {args.get('model_type')}"
)
raise ValueError(str(ex))
return {"result": "success"}, 200

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@ -59,7 +59,7 @@ class AudioApi(WebApiResource):
except ValueError as e:
raise e
except Exception as e:
logging.exception(f"internal server error: {str(e)}")
logging.exception("Failed to handle post request to AudioApi")
raise InternalServerError()
@ -117,7 +117,7 @@ class TextApi(WebApiResource):
except ValueError as e:
raise e
except Exception as e:
logging.exception(f"internal server error: {str(e)}")
logging.exception("Failed to handle post request to TextApi")
raise InternalServerError()

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@ -362,5 +362,5 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
if e.args[0] == "I/O operation on closed file.": # ignore this error
raise GenerateTaskStoppedError()
else:
logger.exception(e)
logger.exception(f"Failed to process generate task pipeline, conversation_id: {conversation.id}")
raise e

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@ -242,7 +242,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
start_listener_time = time.time()
yield MessageAudioStreamResponse(audio=audio_trunk.audio, task_id=task_id)
except Exception as e:
logger.exception(e)
logger.exception(f"Failed to listen audio message, task_id: {task_id}")
break
if tts_publisher:
yield MessageAudioEndStreamResponse(audio="", task_id=task_id)

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@ -80,7 +80,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
if e.args[0] == "I/O operation on closed file.": # ignore this error
raise GenerateTaskStoppedError()
else:
logger.exception(e)
logger.exception(f"Failed to handle response, conversation_id: {conversation.id}")
raise e
def _get_conversation_by_user(

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@ -298,5 +298,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
if e.args[0] == "I/O operation on closed file.": # ignore this error
raise GenerateTaskStoppedError()
else:
logger.exception(e)
logger.exception(
f"Fails to process generate task pipeline, task_id: {application_generate_entity.task_id}"
)
raise e

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@ -216,7 +216,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
else:
yield MessageAudioStreamResponse(audio=audio_trunk.audio, task_id=task_id)
except Exception as e:
logger.exception(e)
logger.exception(f"Fails to get audio trunk, task_id: {task_id}")
break
if tts_publisher:
yield MessageAudioEndStreamResponse(audio="", task_id=task_id)

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@ -86,7 +86,7 @@ class MessageCycleManage:
conversation.name = name
except Exception as e:
if dify_config.DEBUG:
logging.exception(f"generate conversation name failed: {e}")
logging.exception(f"generate conversation name failed, conversation_id: {conversation_id}")
pass
db.session.merge(conversation)

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@ -41,7 +41,7 @@ def check_moderation(model_config: ModelConfigWithCredentialsEntity, text: str)
if moderation_result is True:
return True
except Exception as ex:
logger.exception(ex)
logger.exception(f"Fails to check moderation, provider_name: {provider_name}")
raise InvokeBadRequestError("Rate limit exceeded, please try again later.")
return False

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@ -29,7 +29,7 @@ def import_module_from_source(*, module_name: str, py_file_path: AnyStr, use_laz
spec.loader.exec_module(module)
return module
except Exception as e:
logging.exception(f"Failed to load module {module_name} from {py_file_path}: {str(e)}")
logging.exception(f"Failed to load module {module_name} from script file '{py_file_path}'")
raise e

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@ -554,7 +554,7 @@ class IndexingRunner:
qa_documents.append(qa_document)
format_documents.extend(qa_documents)
except Exception as e:
logging.exception(e)
logging.exception("Failed to format qa document")
all_qa_documents.extend(format_documents)

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@ -102,7 +102,7 @@ class LLMGenerator:
except InvokeError:
questions = []
except Exception as e:
logging.exception(e)
logging.exception("Failed to generate suggested questions after answer")
questions = []
return questions
@ -148,7 +148,7 @@ class LLMGenerator:
error = str(e)
error_step = "generate rule config"
except Exception as e:
logging.exception(e)
logging.exception(f"Failed to generate rule config, model: {model_config.get('name')}")
rule_config["error"] = str(e)
rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
@ -234,7 +234,7 @@ class LLMGenerator:
error_step = "generate conversation opener"
except Exception as e:
logging.exception(e)
logging.exception(f"Failed to generate rule config, model: {model_config.get('name')}")
rule_config["error"] = str(e)
rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
@ -286,7 +286,9 @@ class LLMGenerator:
error = str(e)
return {"code": "", "language": code_language, "error": f"Failed to generate code. Error: {error}"}
except Exception as e:
logging.exception(e)
logging.exception(
f"Failed to invoke LLM model, model: {model_config.get('name')}, language: {code_language}"
)
return {"code": "", "language": code_language, "error": f"An unexpected error occurred: {str(e)}"}
@classmethod

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@ -103,7 +103,7 @@ class AzureRerankModel(RerankModel):
return RerankResult(model=model, docs=rerank_documents)
except Exception as e:
logger.exception(f"Exception in Azure rerank: {e}")
logger.exception(f"Failed to invoke rerank model, model: {model}")
raise
def validate_credentials(self, model: str, credentials: dict) -> None:

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@ -113,7 +113,7 @@ class SageMakerRerankModel(RerankModel):
return RerankResult(model=model, docs=rerank_documents)
except Exception as e:
logger.exception(f"Exception {e}, line : {line}")
logger.exception(f"Failed to invoke rerank model, model: {model}")
def validate_credentials(self, model: str, credentials: dict) -> None:
"""

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@ -78,7 +78,7 @@ class SageMakerSpeech2TextModel(Speech2TextModel):
json_obj = json.loads(json_str)
asr_text = json_obj["text"]
except Exception as e:
logger.exception(f"failed to invoke speech2text model, {e}")
logger.exception(f"failed to invoke speech2text model, model: {model}")
raise CredentialsValidateFailedError(str(e))
return asr_text

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@ -117,7 +117,7 @@ class SageMakerEmbeddingModel(TextEmbeddingModel):
return TextEmbeddingResult(embeddings=all_embeddings, usage=usage, model=model)
except Exception as e:
logger.exception(f"Exception {e}, line : {line}")
logger.exception(f"Failed to invoke text embedding model, model: {model}, line: {line}")
def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
"""

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@ -126,6 +126,6 @@ class OutputModeration(BaseModel):
result: ModerationOutputsResult = moderation_factory.moderation_for_outputs(moderation_buffer)
return result
except Exception as e:
logger.exception("Moderation Output error: %s", e)
logger.exception(f"Moderation Output error, app_id: {app_id}")
return None

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@ -711,7 +711,7 @@ class TraceQueueManager:
trace_task.app_id = self.app_id
trace_manager_queue.put(trace_task)
except Exception as e:
logging.exception(f"Error adding trace task: {e}")
logging.exception(f"Error adding trace task, trace_type {trace_task.trace_type}")
finally:
self.start_timer()
@ -730,7 +730,7 @@ class TraceQueueManager:
if tasks:
self.send_to_celery(tasks)
except Exception as e:
logging.exception(f"Error processing trace tasks: {e}")
logging.exception("Error processing trace tasks")
def start_timer(self):
global trace_manager_timer

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@ -242,7 +242,7 @@ class CouchbaseVector(BaseVector):
try:
self._cluster.query(query, named_parameters={"doc_ids": ids}).execute()
except Exception as e:
logger.exception(e)
logger.exception(f"Failed to delete documents, ids: {ids}")
def delete_by_document_id(self, document_id: str):
query = f"""

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@ -79,7 +79,7 @@ class LindormVectorStore(BaseVector):
existing_docs = self._client.mget(index=self._collection_name, body={"ids": batch_ids}, _source=False)
return {doc["_id"] for doc in existing_docs["docs"] if doc["found"]}
except Exception as e:
logger.exception(f"Error fetching batch {batch_ids}: {e}")
logger.exception(f"Error fetching batch {batch_ids}")
return set()
@retry(stop=stop_after_attempt(3), wait=wait_fixed(60))
@ -96,7 +96,7 @@ class LindormVectorStore(BaseVector):
)
return {doc["_id"] for doc in existing_docs["docs"] if doc["found"]}
except Exception as e:
logger.exception(f"Error fetching batch {batch_ids}: {e}")
logger.exception(f"Error fetching batch ids: {batch_ids}")
return set()
if ids is None:
@ -177,7 +177,7 @@ class LindormVectorStore(BaseVector):
else:
logger.warning(f"Index '{self._collection_name}' does not exist. No deletion performed.")
except Exception as e:
logger.exception(f"Error occurred while deleting the index: {e}")
logger.exception(f"Error occurred while deleting the index: {self._collection_name}")
raise e
def text_exists(self, id: str) -> bool:
@ -201,7 +201,7 @@ class LindormVectorStore(BaseVector):
try:
response = self._client.search(index=self._collection_name, body=query)
except Exception as e:
logger.exception(f"Error executing search: {e}")
logger.exception(f"Error executing vector search, query: {query}")
raise
docs_and_scores = []

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@ -142,7 +142,7 @@ class MyScaleVector(BaseVector):
for r in self._client.query(sql).named_results()
]
except Exception as e:
logging.exception(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m")
logging.exception(f"\033[91m\033[1m{type(e)}\033[0m \033[95m{str(e)}\033[0m") # noqa:TRY401
return []
def delete(self) -> None:

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@ -158,7 +158,7 @@ class OpenSearchVector(BaseVector):
try:
response = self._client.search(index=self._collection_name.lower(), body=query)
except Exception as e:
logger.exception(f"Error executing search: {e}")
logger.exception(f"Error executing vector search, query: {query}")
raise
docs = []

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@ -69,7 +69,7 @@ class CacheEmbedding(Embeddings):
except IntegrityError:
db.session.rollback()
except Exception as e:
logging.exception("Failed transform embedding: %s", e)
logging.exception("Failed transform embedding")
cache_embeddings = []
try:
for i, embedding in zip(embedding_queue_indices, embedding_queue_embeddings):
@ -89,7 +89,7 @@ class CacheEmbedding(Embeddings):
db.session.rollback()
except Exception as ex:
db.session.rollback()
logger.exception("Failed to embed documents: %s", ex)
logger.exception("Failed to embed documents: %s")
raise ex
return text_embeddings
@ -112,7 +112,7 @@ class CacheEmbedding(Embeddings):
embedding_results = (embedding_results / np.linalg.norm(embedding_results)).tolist()
except Exception as ex:
if dify_config.DEBUG:
logging.exception(f"Failed to embed query text: {ex}")
logging.exception(f"Failed to embed query text '{text[:10]}...({len(text)} chars)'")
raise ex
try:
@ -126,7 +126,7 @@ class CacheEmbedding(Embeddings):
redis_client.setex(embedding_cache_key, 600, encoded_str)
except Exception as ex:
if dify_config.DEBUG:
logging.exception("Failed to add embedding to redis %s", ex)
logging.exception(f"Failed to add embedding to redis for the text '{text[:10]}...({len(text)} chars)'")
raise ex
return embedding_results

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@ -229,7 +229,7 @@ class WordExtractor(BaseExtractor):
for i in url_pattern.findall(x.text):
hyperlinks_url = str(i)
except Exception as e:
logger.exception(e)
logger.exception("Failed to parse HYPERLINK xml")
def parse_paragraph(paragraph):
paragraph_content = []

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@ -159,7 +159,7 @@ class QAIndexProcessor(BaseIndexProcessor):
qa_documents.append(qa_document)
format_documents.extend(qa_documents)
except Exception as e:
logging.exception(e)
logging.exception("Failed to format qa document")
all_qa_documents.extend(format_documents)

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@ -57,13 +57,12 @@ class ASRTool(BuiltinTool):
name="model",
label=I18nObject(en_US="Model", zh_Hans="Model"),
human_description=I18nObject(
en_US="All available ASR models",
zh_Hans="所有可用的 ASR 模型",
en_US="All available ASR models. You can config model in the Model Provider of Settings.",
zh_Hans="所有可用的 ASR 模型。你可以在设置中的模型供应商里配置。",
),
type=ToolParameter.ToolParameterType.SELECT,
form=ToolParameter.ToolParameterForm.FORM,
required=True,
default=options[0].value,
options=options,
)
)

View File

@ -77,13 +77,12 @@ class TTSTool(BuiltinTool):
name="model",
label=I18nObject(en_US="Model", zh_Hans="Model"),
human_description=I18nObject(
en_US="All available TTS models",
zh_Hans="所有可用的 TTS 模型",
en_US="All available TTS models. You can config model in the Model Provider of Settings.",
zh_Hans="所有可用的 TTS 模型。你可以在设置中的模型供应商里配置。",
),
type=ToolParameter.ToolParameterType.SELECT,
form=ToolParameter.ToolParameterForm.FORM,
required=True,
default=options[0].value,
options=options,
),
)

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@ -38,7 +38,7 @@ def send_mail(parmas: SendEmailToolParameters):
server.sendmail(parmas.email_account, parmas.sender_to, msg.as_string())
return True
except Exception as e:
logging.exception("send email failed: %s", e)
logging.exception("send email failed")
return False
else: # NONE or TLS
try:
@ -49,5 +49,5 @@ def send_mail(parmas: SendEmailToolParameters):
server.sendmail(parmas.email_account, parmas.sender_to, msg.as_string())
return True
except Exception as e:
logging.exception("send email failed: %s", e)
logging.exception("send email failed")
return False

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@ -175,7 +175,7 @@ class WorkflowTool(Tool):
files.append(file_dict)
except Exception as e:
logger.exception(e)
logger.exception(f"Failed to transform file {file}")
else:
parameters_result[parameter.name] = tool_parameters.get(parameter.name)

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@ -98,7 +98,7 @@ class ToolFileManager:
response.raise_for_status()
blob = response.content
except Exception as e:
logger.exception(f"Failed to download file from {file_url}: {e}")
logger.exception(f"Failed to download file from {file_url}")
raise
mimetype = guess_type(file_url)[0] or "octet/stream"

View File

@ -388,7 +388,7 @@ class ToolManager:
yield provider
except Exception as e:
logger.exception(f"load builtin provider {provider} error: {e}")
logger.exception(f"load builtin provider {provider}")
continue
# set builtin providers loaded
cls._builtin_providers_loaded = True

View File

@ -40,7 +40,7 @@ class ToolFileMessageTransformer:
)
)
except Exception as e:
logger.exception(e)
logger.exception(f"Failed to download image from {url}")
result.append(
ToolInvokeMessage(
type=ToolInvokeMessage.MessageType.TEXT,

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@ -172,7 +172,7 @@ class GraphEngine:
"answer"
].strip()
except Exception as e:
logger.exception(f"Graph run failed: {str(e)}")
logger.exception("Graph run failed")
yield GraphRunFailedEvent(error=str(e))
return
@ -692,7 +692,7 @@ class GraphEngine:
)
return
except Exception as e:
logger.exception(f"Node {node_instance.node_data.title} run failed: {str(e)}")
logger.exception(f"Node {node_instance.node_data.title} run failed")
raise e
finally:
db.session.close()

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@ -69,7 +69,7 @@ class BaseNode(Generic[GenericNodeData]):
try:
result = self._run()
except Exception as e:
logger.exception(f"Node {self.node_id} failed to run: {e}")
logger.exception(f"Node {self.node_id} failed to run")
result = NodeRunResult(
status=WorkflowNodeExecutionStatus.FAILED,
error=str(e),

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@ -70,7 +70,7 @@ class Storage:
try:
self.storage_runner.save(filename, data)
except Exception as e:
logging.exception("Failed to save file: %s", e)
logging.exception(f"Failed to save file {filename}")
raise e
def load(self, filename: str, /, *, stream: bool = False) -> Union[bytes, Generator]:
@ -80,42 +80,42 @@ class Storage:
else:
return self.load_once(filename)
except Exception as e:
logging.exception("Failed to load file: %s", e)
logging.exception(f"Failed to load file {filename}")
raise e
def load_once(self, filename: str) -> bytes:
try:
return self.storage_runner.load_once(filename)
except Exception as e:
logging.exception("Failed to load_once file: %s", e)
logging.exception(f"Failed to load_once file {filename}")
raise e
def load_stream(self, filename: str) -> Generator:
try:
return self.storage_runner.load_stream(filename)
except Exception as e:
logging.exception("Failed to load_stream file: %s", e)
logging.exception(f"Failed to load_stream file {filename}")
raise e
def download(self, filename, target_filepath):
try:
self.storage_runner.download(filename, target_filepath)
except Exception as e:
logging.exception("Failed to download file: %s", e)
logging.exception(f"Failed to download file {filename}")
raise e
def exists(self, filename):
try:
return self.storage_runner.exists(filename)
except Exception as e:
logging.exception("Failed to check file exists: %s", e)
logging.exception(f"Failed to check file exists {filename}")
raise e
def delete(self, filename):
try:
return self.storage_runner.delete(filename)
except Exception as e:
logging.exception("Failed to delete file: %s", e)
logging.exception(f"Failed to delete file {filename}")
raise e

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@ -39,13 +39,13 @@ class SMTPClient:
smtp.sendmail(self._from, mail["to"], msg.as_string())
except smtplib.SMTPException as e:
logging.exception(f"SMTP error occurred: {str(e)}")
logging.exception("SMTP error occurred")
raise
except TimeoutError as e:
logging.exception(f"Timeout occurred while sending email: {str(e)}")
logging.exception("Timeout occurred while sending email")
raise
except Exception as e:
logging.exception(f"Unexpected error occurred while sending email: {str(e)}")
logging.exception(f"Unexpected error occurred while sending email to {mail['to']}")
raise
finally:
if smtp:

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@ -679,7 +679,7 @@ class DatasetKeywordTable(db.Model):
return json.loads(keyword_table_text.decode("utf-8"), cls=SetDecoder)
return None
except Exception as e:
logging.exception(str(e))
logging.exception(f"Failed to load keyword table from file: {file_key}")
return None

View File

@ -35,6 +35,7 @@ select = [
"S506", # unsafe-yaml-load
"SIM", # flake8-simplify rules
"TRY400", # error-instead-of-exception
"TRY401", # verbose-log-message
"UP", # pyupgrade rules
"W191", # tab-indentation
"W605", # invalid-escape-sequence

View File

@ -779,7 +779,7 @@ class RegisterService:
db.session.query(Tenant).delete()
db.session.commit()
logging.exception(f"Setup failed: {e}")
logging.exception(f"Setup account failed, email: {email}, name: {name}")
raise ValueError(f"Setup failed: {e}")
@classmethod
@ -821,7 +821,7 @@ class RegisterService:
db.session.rollback()
except Exception as e:
db.session.rollback()
logging.exception(f"Register failed: {e}")
logging.exception("Register failed")
raise AccountRegisterError(f"Registration failed: {e}") from e
return account

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@ -88,7 +88,7 @@ class AppService:
except (ProviderTokenNotInitError, LLMBadRequestError):
model_instance = None
except Exception as e:
logging.exception(e)
logging.exception(f"Get default model instance failed, tenant_id: {tenant_id}")
model_instance = None
if model_instance:

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@ -195,7 +195,7 @@ class ApiToolManageService:
# try to parse schema, avoid SSRF attack
ApiToolManageService.parser_api_schema(schema)
except Exception as e:
logger.exception(f"parse api schema error: {str(e)}")
logger.exception("parse api schema error")
raise ValueError("invalid schema, please check the url you provided")
return {"schema": schema}

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@ -183,7 +183,7 @@ class ToolTransformService:
try:
username = db_provider.user.name
except Exception as e:
logger.exception(f"failed to get user name for api provider {db_provider.id}: {str(e)}")
logger.exception(f"failed to get user name for api provider {db_provider.id}")
# add provider into providers
credentials = db_provider.credentials
result = UserToolProvider(

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@ -38,4 +38,4 @@ def delete_annotation_index_task(annotation_id: str, app_id: str, tenant_id: str
click.style("App annotations index deleted : {} latency: {}".format(app_id, end_at - start_at), fg="green")
)
except Exception as e:
logging.exception("Annotation deleted index failed:{}".format(str(e)))
logging.exception("Annotation deleted index failed")

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@ -60,7 +60,7 @@ def disable_annotation_reply_task(job_id: str, app_id: str, tenant_id: str):
click.style("App annotations index deleted : {} latency: {}".format(app_id, end_at - start_at), fg="green")
)
except Exception as e:
logging.exception("Annotation batch deleted index failed:{}".format(str(e)))
logging.exception("Annotation batch deleted index failed")
redis_client.setex(disable_app_annotation_job_key, 600, "error")
disable_app_annotation_error_key = "disable_app_annotation_error_{}".format(str(job_id))
redis_client.setex(disable_app_annotation_error_key, 600, str(e))

View File

@ -93,7 +93,7 @@ def enable_annotation_reply_task(
click.style("App annotations added to index: {} latency: {}".format(app_id, end_at - start_at), fg="green")
)
except Exception as e:
logging.exception("Annotation batch created index failed:{}".format(str(e)))
logging.exception("Annotation batch created index failed")
redis_client.setex(enable_app_annotation_job_key, 600, "error")
enable_app_annotation_error_key = "enable_app_annotation_error_{}".format(str(job_id))
redis_client.setex(enable_app_annotation_error_key, 600, str(e))

View File

@ -103,5 +103,5 @@ def batch_create_segment_to_index_task(
click.style("Segment batch created job: {} latency: {}".format(job_id, end_at - start_at), fg="green")
)
except Exception as e:
logging.exception("Segments batch created index failed:{}".format(str(e)))
logging.exception("Segments batch created index failed")
redis_client.setex(indexing_cache_key, 600, "error")

View File

@ -1 +1 @@
recursive-include dify_client *.py
recursive-include dify_oapi *.py

View File

@ -1,185 +1,96 @@
# dify-client
# dify-oapi
A Dify App Service-API Client, using for build a webapp by request Service-API
## Usage
First, install `dify-client` python sdk package:
First, install `dify-oapi` python sdk package:
```
pip install dify-client
pip install dify-oapi
```
Write your code with sdk:
- completion generate with `blocking` response_mode
- chat generate with `blocking` response_mode
```python
from dify_client import CompletionClient
from dify_oapi.api.chat.v1.model.chat_request import ChatRequest
from dify_oapi.api.chat.v1.model.chat_request_body import ChatRequestBody
from dify_oapi.api.chat.v1.model.chat_request_file import ChatRequestFile
from dify_oapi.client import Client
from dify_oapi.core.model.request_option import RequestOption
api_key = "your_api_key"
def main():
client = Client.builder().domain("https://api.dify.ai").build()
req_file = (
ChatRequestFile.builder()
.type("image")
.transfer_method("remote_url")
.url("https://cloud.dify.ai/logo/logo-site.png")
.build()
)
req_body = (
ChatRequestBody.builder()
.inputs({})
.query("What are the specs of the iPhone 13 Pro Max?")
.response_mode("blocking")
.conversation_id("")
.user("abc-123")
.files([req_file])
.build()
)
req = ChatRequest.builder().request_body(req_body).build()
req_option = RequestOption.builder().api_key("<your-api-key>").build()
response = client.chat.v1.chat.chat(req, req_option, False)
# response = await client.chat.v1.chat.achat(req, req_option, False)
print(response.success)
print(response.code)
print(response.msg)
print(response.answer)
# Initialize CompletionClient
completion_client = CompletionClient(api_key)
# Create Completion Message using CompletionClient
completion_response = completion_client.create_completion_message(inputs={"query": "What's the weather like today?"},
response_mode="blocking", user="user_id")
completion_response.raise_for_status()
if __name__ == "__main__":
main()
result = completion_response.json()
print(result.get('answer'))
```
- completion using vision model, like gpt-4-vision
```python
from dify_client import CompletionClient
api_key = "your_api_key"
# Initialize CompletionClient
completion_client = CompletionClient(api_key)
files = [{
"type": "image",
"transfer_method": "remote_url",
"url": "your_image_url"
}]
# files = [{
# "type": "image",
# "transfer_method": "local_file",
# "upload_file_id": "your_file_id"
# }]
# Create Completion Message using CompletionClient
completion_response = completion_client.create_completion_message(inputs={"query": "Describe the picture."},
response_mode="blocking", user="user_id", files=files)
completion_response.raise_for_status()
result = completion_response.json()
print(result.get('answer'))
```
- chat generate with `streaming` response_mode
```python
import json
from dify_client import ChatClient
from dify_oapi.api.chat.v1.model.chat_request import ChatRequest
from dify_oapi.api.chat.v1.model.chat_request_body import ChatRequestBody
from dify_oapi.api.chat.v1.model.chat_request_file import ChatRequestFile
from dify_oapi.client import Client
from dify_oapi.core.model.request_option import RequestOption
api_key = "your_api_key"
def main():
client = Client.builder().domain("https://api.dify.ai").build()
req_file = (
ChatRequestFile.builder()
.type("image")
.transfer_method("remote_url")
.url("https://cloud.dify.ai/logo/logo-site.png")
.build()
)
req_body = (
ChatRequestBody.builder()
.inputs({})
.query("What are the specs of the iPhone 13 Pro Max?")
.response_mode("streaming")
.conversation_id("")
.user("abc-123")
.files([req_file])
.build()
)
req = ChatRequest.builder().request_body(req_body).build()
req_option = RequestOption.builder().api_key("<your-api-key>").build()
response = client.chat.v1.chat.chat(req, req_option, True)
# response = await client.chat.v1.chat.achat(req, req_option, True)
for chunk in response:
print(chunk)
# Initialize ChatClient
chat_client = ChatClient(api_key)
# Create Chat Message using ChatClient
chat_response = chat_client.create_chat_message(inputs={}, query="Hello", user="user_id", response_mode="streaming")
chat_response.raise_for_status()
for line in chat_response.iter_lines(decode_unicode=True):
line = line.split('data:', 1)[-1]
if line.strip():
line = json.loads(line.strip())
print(line.get('answer'))
```
- chat using vision model, like gpt-4-vision
```python
from dify_client import ChatClient
api_key = "your_api_key"
# Initialize ChatClient
chat_client = ChatClient(api_key)
files = [{
"type": "image",
"transfer_method": "remote_url",
"url": "your_image_url"
}]
# files = [{
# "type": "image",
# "transfer_method": "local_file",
# "upload_file_id": "your_file_id"
# }]
# Create Chat Message using ChatClient
chat_response = chat_client.create_chat_message(inputs={}, query="Describe the picture.", user="user_id",
response_mode="blocking", files=files)
chat_response.raise_for_status()
result = chat_response.json()
print(result.get("answer"))
```
- upload file when using vision model
```python
from dify_client import DifyClient
api_key = "your_api_key"
# Initialize Client
dify_client = DifyClient(api_key)
file_path = "your_image_file_path"
file_name = "panda.jpeg"
mime_type = "image/jpeg"
with open(file_path, "rb") as file:
files = {
"file": (file_name, file, mime_type)
}
response = dify_client.file_upload("user_id", files)
result = response.json()
print(f'upload_file_id: {result.get("id")}')
```
- Others
```python
from dify_client import ChatClient
api_key = "your_api_key"
# Initialize Client
client = ChatClient(api_key)
# Get App parameters
parameters = client.get_application_parameters(user="user_id")
parameters.raise_for_status()
print('[parameters]')
print(parameters.json())
# Get Conversation List (only for chat)
conversations = client.get_conversations(user="user_id")
conversations.raise_for_status()
print('[conversations]')
print(conversations.json())
# Get Message List (only for chat)
messages = client.get_conversation_messages(user="user_id", conversation_id="conversation_id")
messages.raise_for_status()
print('[messages]')
print(messages.json())
# Rename Conversation (only for chat)
rename_conversation_response = client.rename_conversation(conversation_id="conversation_id",
name="new_name", user="user_id")
rename_conversation_response.raise_for_status()
print('[rename result]')
print(rename_conversation_response.json())
if __name__ == "__main__":
main()
```

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@ -1 +0,0 @@
from dify_client.client import ChatClient, CompletionClient, DifyClient

View File

@ -1,446 +0,0 @@
import json
import requests
class DifyClient:
def __init__(self, api_key, base_url: str = "https://api.dify.ai/v1"):
self.api_key = api_key
self.base_url = base_url
def _send_request(self, method, endpoint, json=None, params=None, stream=False):
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json",
}
url = f"{self.base_url}{endpoint}"
response = requests.request(
method, url, json=json, params=params, headers=headers, stream=stream
)
return response
def _send_request_with_files(self, method, endpoint, data, files):
headers = {"Authorization": f"Bearer {self.api_key}"}
url = f"{self.base_url}{endpoint}"
response = requests.request(
method, url, data=data, headers=headers, files=files
)
return response
def message_feedback(self, message_id, rating, user):
data = {"rating": rating, "user": user}
return self._send_request("POST", f"/messages/{message_id}/feedbacks", data)
def get_application_parameters(self, user):
params = {"user": user}
return self._send_request("GET", "/parameters", params=params)
def file_upload(self, user, files):
data = {"user": user}
return self._send_request_with_files(
"POST", "/files/upload", data=data, files=files
)
def text_to_audio(self, text: str, user: str, streaming: bool = False):
data = {"text": text, "user": user, "streaming": streaming}
return self._send_request("POST", "/text-to-audio", data=data)
def get_meta(self, user):
params = {"user": user}
return self._send_request("GET", "/meta", params=params)
class CompletionClient(DifyClient):
def create_completion_message(self, inputs, response_mode, user, files=None):
data = {
"inputs": inputs,
"response_mode": response_mode,
"user": user,
"files": files,
}
return self._send_request(
"POST",
"/completion-messages",
data,
stream=True if response_mode == "streaming" else False,
)
class ChatClient(DifyClient):
def create_chat_message(
self,
inputs,
query,
user,
response_mode="blocking",
conversation_id=None,
files=None,
):
data = {
"inputs": inputs,
"query": query,
"user": user,
"response_mode": response_mode,
"files": files,
}
if conversation_id:
data["conversation_id"] = conversation_id
return self._send_request(
"POST",
"/chat-messages",
data,
stream=True if response_mode == "streaming" else False,
)
def get_suggested(self, message_id, user: str):
params = {"user": user}
return self._send_request(
"GET", f"/messages/{message_id}/suggested", params=params
)
def stop_message(self, task_id, user):
data = {"user": user}
return self._send_request("POST", f"/chat-messages/{task_id}/stop", data)
def get_conversations(self, user, last_id=None, limit=None, pinned=None):
params = {"user": user, "last_id": last_id, "limit": limit, "pinned": pinned}
return self._send_request("GET", "/conversations", params=params)
def get_conversation_messages(
self, user, conversation_id=None, first_id=None, limit=None
):
params = {"user": user}
if conversation_id:
params["conversation_id"] = conversation_id
if first_id:
params["first_id"] = first_id
if limit:
params["limit"] = limit
return self._send_request("GET", "/messages", params=params)
def rename_conversation(
self, conversation_id, name, auto_generate: bool, user: str
):
data = {"name": name, "auto_generate": auto_generate, "user": user}
return self._send_request(
"POST", f"/conversations/{conversation_id}/name", data
)
def delete_conversation(self, conversation_id, user):
data = {"user": user}
return self._send_request("DELETE", f"/conversations/{conversation_id}", data)
def audio_to_text(self, audio_file, user):
data = {"user": user}
files = {"audio_file": audio_file}
return self._send_request_with_files("POST", "/audio-to-text", data, files)
class WorkflowClient(DifyClient):
def run(
self, inputs: dict, response_mode: str = "streaming", user: str = "abc-123"
):
data = {"inputs": inputs, "response_mode": response_mode, "user": user}
return self._send_request("POST", "/workflows/run", data)
def stop(self, task_id, user):
data = {"user": user}
return self._send_request("POST", f"/workflows/tasks/{task_id}/stop", data)
def get_result(self, workflow_run_id):
return self._send_request("GET", f"/workflows/run/{workflow_run_id}")
class KnowledgeBaseClient(DifyClient):
def __init__(
self, api_key, base_url: str = "https://api.dify.ai/v1", dataset_id: str = None
):
"""
Construct a KnowledgeBaseClient object.
Args:
api_key (str): API key of Dify.
base_url (str, optional): Base URL of Dify API. Defaults to 'https://api.dify.ai/v1'.
dataset_id (str, optional): ID of the dataset. Defaults to None. You don't need this if you just want to
create a new dataset. or list datasets. otherwise you need to set this.
"""
super().__init__(api_key=api_key, base_url=base_url)
self.dataset_id = dataset_id
def _get_dataset_id(self):
if self.dataset_id is None:
raise ValueError("dataset_id is not set")
return self.dataset_id
def create_dataset(self, name: str, **kwargs):
return self._send_request("POST", "/datasets", {"name": name}, **kwargs)
def list_datasets(self, page: int = 1, page_size: int = 20, **kwargs):
return self._send_request(
"GET", f"/datasets?page={page}&limit={page_size}", **kwargs
)
def create_document_by_text(self, name, text, extra_params: dict = None, **kwargs):
"""
Create a document by text.
:param name: Name of the document
:param text: Text content of the document
:param extra_params: extra parameters pass to the API, such as indexing_technique, process_rule. (optional)
e.g.
{
'indexing_technique': 'high_quality',
'process_rule': {
'rules': {
'pre_processing_rules': [
{'id': 'remove_extra_spaces', 'enabled': True},
{'id': 'remove_urls_emails', 'enabled': True}
],
'segmentation': {
'separator': '\n',
'max_tokens': 500
}
},
'mode': 'custom'
}
}
:return: Response from the API
"""
data = {
"indexing_technique": "high_quality",
"process_rule": {"mode": "automatic"},
"name": name,
"text": text,
}
if extra_params is not None and isinstance(extra_params, dict):
data.update(extra_params)
url = f"/datasets/{self._get_dataset_id()}/document/create_by_text"
return self._send_request("POST", url, json=data, **kwargs)
def update_document_by_text(
self, document_id, name, text, extra_params: dict = None, **kwargs
):
"""
Update a document by text.
:param document_id: ID of the document
:param name: Name of the document
:param text: Text content of the document
:param extra_params: extra parameters pass to the API, such as indexing_technique, process_rule. (optional)
e.g.
{
'indexing_technique': 'high_quality',
'process_rule': {
'rules': {
'pre_processing_rules': [
{'id': 'remove_extra_spaces', 'enabled': True},
{'id': 'remove_urls_emails', 'enabled': True}
],
'segmentation': {
'separator': '\n',
'max_tokens': 500
}
},
'mode': 'custom'
}
}
:return: Response from the API
"""
data = {"name": name, "text": text}
if extra_params is not None and isinstance(extra_params, dict):
data.update(extra_params)
url = (
f"/datasets/{self._get_dataset_id()}/documents/{document_id}/update_by_text"
)
return self._send_request("POST", url, json=data, **kwargs)
def create_document_by_file(
self, file_path, original_document_id=None, extra_params: dict = None
):
"""
Create a document by file.
:param file_path: Path to the file
:param original_document_id: pass this ID if you want to replace the original document (optional)
:param extra_params: extra parameters pass to the API, such as indexing_technique, process_rule. (optional)
e.g.
{
'indexing_technique': 'high_quality',
'process_rule': {
'rules': {
'pre_processing_rules': [
{'id': 'remove_extra_spaces', 'enabled': True},
{'id': 'remove_urls_emails', 'enabled': True}
],
'segmentation': {
'separator': '\n',
'max_tokens': 500
}
},
'mode': 'custom'
}
}
:return: Response from the API
"""
files = {"file": open(file_path, "rb")}
data = {
"process_rule": {"mode": "automatic"},
"indexing_technique": "high_quality",
}
if extra_params is not None and isinstance(extra_params, dict):
data.update(extra_params)
if original_document_id is not None:
data["original_document_id"] = original_document_id
url = f"/datasets/{self._get_dataset_id()}/document/create_by_file"
return self._send_request_with_files(
"POST", url, {"data": json.dumps(data)}, files
)
def update_document_by_file(
self, document_id, file_path, extra_params: dict = None
):
"""
Update a document by file.
:param document_id: ID of the document
:param file_path: Path to the file
:param extra_params: extra parameters pass to the API, such as indexing_technique, process_rule. (optional)
e.g.
{
'indexing_technique': 'high_quality',
'process_rule': {
'rules': {
'pre_processing_rules': [
{'id': 'remove_extra_spaces', 'enabled': True},
{'id': 'remove_urls_emails', 'enabled': True}
],
'segmentation': {
'separator': '\n',
'max_tokens': 500
}
},
'mode': 'custom'
}
}
:return:
"""
files = {"file": open(file_path, "rb")}
data = {}
if extra_params is not None and isinstance(extra_params, dict):
data.update(extra_params)
url = (
f"/datasets/{self._get_dataset_id()}/documents/{document_id}/update_by_file"
)
return self._send_request_with_files(
"POST", url, {"data": json.dumps(data)}, files
)
def batch_indexing_status(self, batch_id: str, **kwargs):
"""
Get the status of the batch indexing.
:param batch_id: ID of the batch uploading
:return: Response from the API
"""
url = f"/datasets/{self._get_dataset_id()}/documents/{batch_id}/indexing-status"
return self._send_request("GET", url, **kwargs)
def delete_dataset(self):
"""
Delete this dataset.
:return: Response from the API
"""
url = f"/datasets/{self._get_dataset_id()}"
return self._send_request("DELETE", url)
def delete_document(self, document_id):
"""
Delete a document.
:param document_id: ID of the document
:return: Response from the API
"""
url = f"/datasets/{self._get_dataset_id()}/documents/{document_id}"
return self._send_request("DELETE", url)
def list_documents(
self, page: int = None, page_size: int = None, keyword: str = None, **kwargs
):
"""
Get a list of documents in this dataset.
:return: Response from the API
"""
params = {}
if page is not None:
params["page"] = page
if page_size is not None:
params["limit"] = page_size
if keyword is not None:
params["keyword"] = keyword
url = f"/datasets/{self._get_dataset_id()}/documents"
return self._send_request("GET", url, params=params, **kwargs)
def add_segments(self, document_id, segments, **kwargs):
"""
Add segments to a document.
:param document_id: ID of the document
:param segments: List of segments to add, example: [{"content": "1", "answer": "1", "keyword": ["a"]}]
:return: Response from the API
"""
data = {"segments": segments}
url = f"/datasets/{self._get_dataset_id()}/documents/{document_id}/segments"
return self._send_request("POST", url, json=data, **kwargs)
def query_segments(
self, document_id, keyword: str = None, status: str = None, **kwargs
):
"""
Query segments in this document.
:param document_id: ID of the document
:param keyword: query keyword, optional
:param status: status of the segment, optional, e.g. completed
"""
url = f"/datasets/{self._get_dataset_id()}/documents/{document_id}/segments"
params = {}
if keyword is not None:
params["keyword"] = keyword
if status is not None:
params["status"] = status
if "params" in kwargs:
params.update(kwargs["params"])
return self._send_request("GET", url, params=params, **kwargs)
def delete_document_segment(self, document_id, segment_id):
"""
Delete a segment from a document.
:param document_id: ID of the document
:param segment_id: ID of the segment
:return: Response from the API
"""
url = f"/datasets/{self._get_dataset_id()}/documents/{document_id}/segments/{segment_id}"
return self._send_request("DELETE", url)
def update_document_segment(self, document_id, segment_id, segment_data, **kwargs):
"""
Update a segment in a document.
:param document_id: ID of the document
:param segment_id: ID of the segment
:param segment_data: Data of the segment, example: {"content": "1", "answer": "1", "keyword": ["a"], "enabled": True}
:return: Response from the API
"""
data = {"segment": segment_data}
url = f"/datasets/{self._get_dataset_id()}/documents/{document_id}/segments/{segment_id}"
return self._send_request("POST", url, json=data, **kwargs)

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@ -0,0 +1,8 @@
from dify_oapi.core.model.config import Config
from .v1.version import V1
class ChatService:
def __init__(self, config: Config) -> None:
self.v1: V1 = V1(config)

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@ -0,0 +1,41 @@
from __future__ import annotations
from io import BytesIO
from dify_oapi.core.enum import HttpMethod
from dify_oapi.core.model.base_request import BaseRequest
from .audio_to_text_request_body import AudioToTextRequestBody
class AudioToTextRequest(BaseRequest):
def __init__(self):
super().__init__()
self.file: BytesIO | None = None
self.request_body: AudioToTextRequestBody | None = None
@staticmethod
def builder() -> AudioToTextRequestBuilder:
return AudioToTextRequestBuilder()
class AudioToTextRequestBuilder(object):
def __init__(self):
audio_to_text_request = AudioToTextRequest()
audio_to_text_request.http_method = HttpMethod.POST
audio_to_text_request.uri = "/v1/audio-to-text"
self._audio_to_text_request = audio_to_text_request
def build(self) -> AudioToTextRequest:
return self._audio_to_text_request
def request_body(
self, request_body: AudioToTextRequestBody
) -> AudioToTextRequestBuilder:
self._audio_to_text_request.request_body = request_body
self._audio_to_text_request.body = request_body.model_dump(exclude_none=True)
return self
def file(self, file: BytesIO, file_name: str) -> AudioToTextRequestBuilder:
self._audio_to_text_request.file = file
self._audio_to_text_request.files = {"file": (file_name, file)}
return self

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@ -0,0 +1,23 @@
from __future__ import annotations
from pydantic import BaseModel
class AudioToTextRequestBody(BaseModel):
user: str | None = None
@staticmethod
def builder() -> AudioToTextRequestBodyBuilder:
return AudioToTextRequestBodyBuilder()
class AudioToTextRequestBodyBuilder(object):
def __init__(self):
self._audio_to_text_request_body = AudioToTextRequestBody()
def build(self) -> AudioToTextRequestBody:
return self._audio_to_text_request_body
def user(self, user: str) -> AudioToTextRequestBodyBuilder:
self._audio_to_text_request_body.user = user
return self

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@ -0,0 +1,5 @@
from dify_oapi.core.model.base_response import BaseResponse
class AudioToTextResponse(BaseResponse):
text: str | None = None

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@ -0,0 +1,32 @@
from __future__ import annotations
from dify_oapi.core.enum import HttpMethod
from dify_oapi.core.model.base_request import BaseRequest
from .chat_request_body import ChatRequestBody
class ChatRequest(BaseRequest):
def __init__(self) -> None:
super().__init__()
self.request_body: ChatRequestBody | None = None
@staticmethod
def builder() -> ChatRequestBuilder:
return ChatRequestBuilder()
class ChatRequestBuilder:
def __init__(self) -> None:
chat_request = ChatRequest()
chat_request.http_method = HttpMethod.POST
chat_request.uri = "/v1/chat-messages"
self._chat_request: ChatRequest = chat_request
def request_body(self, request_body: ChatRequestBody) -> ChatRequestBuilder:
self._chat_request.request_body = request_body
self._chat_request.body = request_body.model_dump(exclude_none=True)
return self
def build(self) -> ChatRequest:
return self._chat_request

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from __future__ import annotations
from pydantic import BaseModel
from .chat_request_file import ChatRequestFile
class ChatRequestBody(BaseModel):
query: str | None = None
inputs: dict | None = None
response_mode: str | None = None
user: str | None = None
conversation_id: str | None = None
files: list[ChatRequestFile] | None = None
auto_generate_name: bool | None = None
@staticmethod
def builder() -> ChatRequestBodyBuilder:
return ChatRequestBodyBuilder()
class ChatRequestBodyBuilder:
def __init__(self):
self._chat_request_body = ChatRequestBody()
def query(self, query: str) -> ChatRequestBodyBuilder:
self._chat_request_body.query = query
return self
def inputs(self, inputs: dict) -> ChatRequestBodyBuilder:
self._chat_request_body.inputs = inputs
return self
def response_mode(self, response_mode: str) -> ChatRequestBodyBuilder:
if response_mode not in ["streaming", "blocking"]:
raise ValueError('response_mode must be either "streaming" or "blocking"')
self._chat_request_body.response_mode = response_mode
return self
def user(self, user: str) -> ChatRequestBodyBuilder:
self._chat_request_body.user = user
return self
def conversation_id(self, conversation_id: str) -> ChatRequestBodyBuilder:
self._chat_request_body.conversation_id = conversation_id
return self
def files(self, files: list[ChatRequestFile]) -> ChatRequestBodyBuilder:
self._chat_request_body.files = files
return self
def auto_generate_name(self, auto_generate_name: bool) -> ChatRequestBodyBuilder:
self._chat_request_body.auto_generate_name = auto_generate_name
return self
def build(self):
return self._chat_request_body

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from __future__ import annotations
from pydantic import BaseModel, HttpUrl
class ChatRequestFile(BaseModel):
type: str | None = None
transfer_method: str | None = None
url: HttpUrl | None = None
upload_file_id: str | None = None
@staticmethod
def builder() -> ChatRequestFileBuilder:
return ChatRequestFileBuilder()
class ChatRequestFileBuilder:
def __init__(self):
self._chat_request_file = ChatRequestFile()
def type(self, type_: str):
if type_ != "image":
raise ValueError("Only 'image' is supported")
self._chat_request_file.type = type_
return self
def transfer_method(self, transfer_method: str):
if transfer_method not in ("remote_url", "local_file"):
raise ValueError("Only 'remote_url' and 'local_file' are supported")
self._chat_request_file.transfer_method = transfer_method
return self
def url(self, url: str):
self._chat_request_file.url = HttpUrl(url=url)
return self
def upload_file_id(self, upload_file_id: str):
self._chat_request_file.upload_file_id = upload_file_id
return self
def build(self) -> ChatRequestFile:
if (
self._chat_request_file.transfer_method == "remote_url"
and self._chat_request_file.url is None
):
raise ValueError(
"Url needs to be set when transfer_method is set as remote_url"
)
if (
self._chat_request_file.transfer_method == "local_file"
and self._chat_request_file.upload_file_id is None
):
raise ValueError(
"Upload file_id needs to be set when transfer_method is set as local_file"
)
return self._chat_request_file

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from __future__ import annotations
from pydantic import BaseModel
from dify_oapi.core.model.base_response import BaseResponse
class ChatResponse(BaseResponse):
message_id: str | None = None
conversation_id: str | None = None
mode: str | None = None
answer: str | None = None
metadata: ChatResponseMetadata | None = None
created_at: int | None = None
class ChatResponseMetadata(BaseModel):
usage: dict | None = None
retriever_resources: list[dict] | None = None

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from __future__ import annotations
from dify_oapi.core.enum import HttpMethod
from dify_oapi.core.model.base_request import BaseRequest
from .delete_conversation_request_body import DeleteConversationRequestBody
class DeleteConversationRequest(BaseRequest):
def __init__(self):
super().__init__()
self.conversation_id: str | None = None
self.request_body: DeleteConversationRequestBody | None = None
@staticmethod
def builder() -> DeleteConversationRequestBuilder:
return DeleteConversationRequestBuilder()
class DeleteConversationRequestBuilder:
def __init__(self):
delete_conversation_request = DeleteConversationRequest()
delete_conversation_request.http_method = HttpMethod.DELETE
delete_conversation_request.uri = "/v1/conversations/:conversation_id"
self._delete_conversation_request = delete_conversation_request
def request_body(
self, request_body: DeleteConversationRequestBody
) -> DeleteConversationRequestBuilder:
self._delete_conversation_request.request_body = request_body
self._delete_conversation_request.body = request_body.model_dump(
exclude_none=True
)
return self
def conversation_id(self, conversation_id: str) -> DeleteConversationRequestBuilder:
self._delete_conversation_request.conversation_id = conversation_id
self._delete_conversation_request.paths["conversation_id"] = conversation_id
return self
def build(self) -> DeleteConversationRequest:
return self._delete_conversation_request

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from __future__ import annotations
from pydantic import BaseModel
class DeleteConversationRequestBody(BaseModel):
user: str | None = None
@staticmethod
def builder() -> DeleteConversationRequestBodyBuilder:
return DeleteConversationRequestBodyBuilder()
class DeleteConversationRequestBodyBuilder:
def __init__(self):
self._delete_conversation_request_body = DeleteConversationRequestBody()
def user(self, user: str):
self._delete_conversation_request_body.user = user
return self
def build(self) -> DeleteConversationRequestBody:
return self._delete_conversation_request_body

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from dify_oapi.core.model.base_response import BaseResponse
class DeleteConversationResponse(BaseResponse):
result: str | None = None

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from __future__ import annotations
from dify_oapi.core.enum import HttpMethod
from dify_oapi.core.model.base_request import BaseRequest
class GetConversationListRequest(BaseRequest):
def __init__(self):
super().__init__()
self.user: str | None = None
self.last_id: str | None = None
self.limit: int | None = None
self.pinned: bool | None = None
@staticmethod
def builder() -> GetConversationListRequestBuilder:
return GetConversationListRequestBuilder()
class GetConversationListRequestBuilder:
def __init__(self):
get_conversation_list_request = GetConversationListRequest()
get_conversation_list_request.http_method = HttpMethod.GET
get_conversation_list_request.uri = "/v1/conversations"
self._get_conversation_list_request = get_conversation_list_request
def user(self, user: str) -> GetConversationListRequestBuilder:
self._get_conversation_list_request.user = user
self._get_conversation_list_request.add_query("user", user)
return self
def last_id(self, last_id: str) -> GetConversationListRequestBuilder:
self._get_conversation_list_request.last_id = last_id
self._get_conversation_list_request.add_query("last_id", last_id)
return self
def limit(self, limit: int) -> GetConversationListRequestBuilder:
self._get_conversation_list_request.limit = limit
self._get_conversation_list_request.add_query("limit", limit)
return self
def pinned(self, pinned: bool) -> GetConversationListRequestBuilder:
self._get_conversation_list_request.pinned = pinned
self._get_conversation_list_request.add_query("pinned", str(pinned).lower())
return self
def build(self) -> GetConversationListRequest:
return self._get_conversation_list_request

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from __future__ import annotations
from pydantic import BaseModel
from dify_oapi.core.model.base_response import BaseResponse
class GetConversationListResponse(BaseResponse):
data: list[GetConversationListData] | None = None
has_more: bool | None = None
limit: int | None = None
class GetConversationListData(BaseModel):
id: str | None = None
name: str | None = None
inputs: dict | None = None
status: str | None = None
introduction: str | None = None
created_at: int | None = None
updated_at: int | None = None

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from __future__ import annotations
from dify_oapi.core.enum import HttpMethod
from dify_oapi.core.model.base_request import BaseRequest
class MessageHistoryRequest(BaseRequest):
def __init__(self):
super().__init__()
self.conversation_id: str | None = None
self.user: str | None = None
self.first_id: str | None = None
self.limit: int | None = None
@staticmethod
def builder() -> MessageHistoryRequestBuilder:
return MessageHistoryRequestBuilder()
class MessageHistoryRequestBuilder:
def __init__(self):
message_history_request = MessageHistoryRequest()
message_history_request.http_method = HttpMethod.GET
message_history_request.uri = "/v1/messages"
self._message_history_request = message_history_request
def build(self) -> MessageHistoryRequest:
return self._message_history_request
def conversation_id(self, conversation_id: str):
self._message_history_request.conversation_id = conversation_id
self._message_history_request.add_query("conversation_id", conversation_id)
return self
def user(self, user: str):
self._message_history_request.user = user
self._message_history_request.add_query("user", user)
return self
def first_id(self, first_id: str):
self._message_history_request.first_id = first_id
self._message_history_request.add_query("first_id", first_id)
return self
def limit(self, limit: int):
self._message_history_request.limit = limit
self._message_history_request.add_query("limit", limit)
return self

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from __future__ import annotations
from pydantic import BaseModel
from dify_oapi.core.model.base_response import BaseResponse
class MessageHistoryResponse(BaseResponse):
data: list[dict] | None = None
id: str | None = None
conversation_id: str | None = None
inputs: list[dict] | None = None
query: str | None = None
message_files: list[MessageHistoryResponseFile] | None = None
answer: str | None = None
created_at: int | None = None
feedback: MessageHistoryResponseFeedback | None = None
retriever_resources: list[dict] | None = None
has_more: bool | None = None
limit: int | None = None
class MessageHistoryResponseFeedback(BaseModel):
rating: str | None = None
class MessageHistoryResponseFile(BaseModel):
id: str | None = None
type: str | None = None
url: str | None = None
belongs_to: str | None = None
agent_thoughts: list[MessageHistoryResponseFileAgentThought] | None = None
class MessageHistoryResponseFileAgentThought(BaseResponse):
id: str | None = None
message_id: str | None = None
position: int | None = None
thought: str | None = None
observation: str | None = None
tool: str | None = None
tool_input: str | None = None
created_at: int | None = None
message_files: list[MessageHistoryResponseFileAgentThoughtFile] | None = None
conversation_id: str | None = None
class MessageHistoryResponseFileAgentThoughtFile(BaseModel):
file_id: str | None = None

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from __future__ import annotations
from dify_oapi.core.enum import HttpMethod
from dify_oapi.core.model.base_request import BaseRequest
class MessageSuggestedRequest(BaseRequest):
def __init__(self):
super().__init__()
self.message_id: str | None = None
self.user: str | None = None
@staticmethod
def builder() -> MessageSuggestedRequestBuilder:
return MessageSuggestedRequestBuilder()
class MessageSuggestedRequestBuilder:
def __init__(self):
message_suggested_request = MessageSuggestedRequest()
message_suggested_request.http_method = HttpMethod.GET
message_suggested_request.uri = "/v1/messages/:message_id/suggested"
self._message_suggested_request = message_suggested_request
def build(self) -> MessageSuggestedRequest:
return self._message_suggested_request
def message_id(self, message_id: str):
self._message_suggested_request.message_id = message_id
self._message_suggested_request.paths["message_id"] = message_id
return self
def user(self, user: str):
self._message_suggested_request.user = user
self._message_suggested_request.add_query("user", user)
return self

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from dify_oapi.core.model.base_response import BaseResponse
class MessageSuggestedResponse(BaseResponse):
result: str | None = None
data: list[str] | None = None

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from __future__ import annotations
from dify_oapi.core.enum import HttpMethod
from dify_oapi.core.model.base_request import BaseRequest
from .rename_conversation_request_body import RenameConversationRequestBody
class RenameConversationRequest(BaseRequest):
def __init__(self):
super().__init__()
self.conversation_id: str | None = None
self.request_body: RenameConversationRequestBody | None = None
@staticmethod
def builder() -> RenameConversationRequestBuilder:
return RenameConversationRequestBuilder()
class RenameConversationRequestBuilder:
def __init__(self):
rename_conversation_request = RenameConversationRequest()
rename_conversation_request.http_method = HttpMethod.POST
rename_conversation_request.uri = "/v1/conversations/:conversation_id/name"
self._rename_conversation_request = rename_conversation_request
def build(self) -> RenameConversationRequest:
return self._rename_conversation_request
def request_body(
self, request_body: RenameConversationRequestBody
) -> RenameConversationRequestBuilder:
self._rename_conversation_request.request_body = request_body
self._rename_conversation_request.body = request_body.model_dump(
exclude_none=True
)
return self
def conversation_id(self, conversation_id: str) -> RenameConversationRequestBuilder:
self._rename_conversation_request.conversation_id = conversation_id
self._rename_conversation_request.paths["conversation_id"] = conversation_id
return self

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from __future__ import annotations
from pydantic import BaseModel
class RenameConversationRequestBody(BaseModel):
name: str | None = None
auto_generate: bool | None = None
user: str | None = None
@staticmethod
def builder() -> RenameConversationRequestBodyBuilder:
return RenameConversationRequestBodyBuilder()
class RenameConversationRequestBodyBuilder:
def __init__(self):
self._rename_conversation_request_body = RenameConversationRequestBody()
def builder(self) -> RenameConversationRequestBody:
return self._rename_conversation_request_body
def name(self, name: str) -> RenameConversationRequestBodyBuilder:
self._rename_conversation_request_body.name = name
return self
def auto_generate(
self, auto_generate: bool
) -> RenameConversationRequestBodyBuilder:
self._rename_conversation_request_body.auto_generate = auto_generate
return self
def user(self, user: str) -> RenameConversationRequestBodyBuilder:
self._rename_conversation_request_body.user = user
return self

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from dify_oapi.core.model.base_response import BaseResponse
class RenameConversationResponse(BaseResponse):
id: str | None = None
result: str | None = None
inputs: dict | None = None
status: str | None = None
introduction: str | None = None
created_at: int | None = None
updated_at: int | None = None

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from __future__ import annotations
from dify_oapi.core.enum import HttpMethod
from dify_oapi.core.model.base_request import BaseRequest
from .stop_chat_request_body import StopChatRequestBody
class StopChatRequest(BaseRequest):
def __init__(self) -> None:
super().__init__()
self.task_id: str | None = None
self.request_body: StopChatRequestBody | None = None
@staticmethod
def builder() -> StopChatRequestBuilder:
return StopChatRequestBuilder()
class StopChatRequestBuilder:
def __init__(self) -> None:
stop_chat_request = StopChatRequest()
stop_chat_request.http_method = HttpMethod.POST
stop_chat_request.uri = "/v1/chat-messages/:task_id/stop"
self._stop_chat_request: StopChatRequest = stop_chat_request
def task_id(self, task_id: str) -> StopChatRequestBuilder:
self._stop_chat_request.task_id = task_id
self._stop_chat_request.paths["task_id"] = str(task_id)
return self
def request_body(self, request_body: StopChatRequestBody) -> StopChatRequestBuilder:
self._stop_chat_request.request_body = request_body
self._stop_chat_request.body = request_body.model_dump(exclude_none=True)
return self
def build(self) -> StopChatRequest:
return self._stop_chat_request

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from __future__ import annotations
from pydantic import BaseModel
class StopChatRequestBody(BaseModel):
user: str | None = None
@staticmethod
def builder() -> StopChatRequestBodyBuilder:
return StopChatRequestBodyBuilder()
class StopChatRequestBodyBuilder:
def __init__(self):
self._stop_chat_request_body = StopChatRequestBody()
def user(self, user: str) -> StopChatRequestBodyBuilder:
self._stop_chat_request_body.user = user
return self
def build(self) -> StopChatRequestBody:
return self._stop_chat_request_body

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from dify_oapi.core.model.base_response import BaseResponse
class StopChatResponse(BaseResponse):
result: str | None = None

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from .chat import * # noqa F403
from .conversation import * # noqa 403
from .message import * # noqa 403
from .audio import * # noqa 403

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from dify_oapi.core.http.transport import ATransport, Transport
from dify_oapi.core.model.config import Config
from dify_oapi.core.model.request_option import RequestOption
from ..model.audio_to_text_request import AudioToTextRequest
from ..model.audio_to_text_response import AudioToTextResponse
class Audio:
def __init__(self, config: Config) -> None:
self.config: Config = config
def to_text(
self, request: AudioToTextRequest, option: RequestOption | None = None
) -> AudioToTextResponse:
return Transport.execute(
self.config, request, unmarshal_as=AudioToTextResponse, option=option
)
async def ato_text(
self, request: AudioToTextRequest, option: RequestOption | None = None
) -> AudioToTextResponse:
return await ATransport.aexecute(
self.config, request, unmarshal_as=AudioToTextResponse, option=option
)

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from collections.abc import AsyncGenerator, Generator
from typing import Literal, overload
from dify_oapi.core.const import APPLICATION_JSON, CONTENT_TYPE
from dify_oapi.core.http.transport import ATransport, Transport
from dify_oapi.core.model.config import Config
from dify_oapi.core.model.request_option import RequestOption
from ..model.chat_request import ChatRequest
from ..model.chat_response import ChatResponse
from ..model.stop_chat_request import StopChatRequest
from ..model.stop_chat_response import StopChatResponse
class Chat:
def __init__(self, config: Config) -> None:
self.config: Config = config
@overload
def chat(
self, request: ChatRequest, option: RequestOption | None, stream: Literal[True]
) -> Generator[bytes, None, None]: ...
@overload
def chat(
self, request: ChatRequest, option: RequestOption | None, stream: Literal[False]
) -> ChatResponse: ...
@overload
def chat(
self, request: ChatRequest, option: RequestOption | None
) -> ChatResponse: ...
def chat(
self,
request: ChatRequest,
option: RequestOption | None = None,
stream: bool = False,
):
if request.body is not None:
option.headers[CONTENT_TYPE] = f"{APPLICATION_JSON}; charset=utf-8"
if stream:
return Transport.execute(self.config, request, option=option, stream=True)
else:
return Transport.execute(
self.config, request, unmarshal_as=ChatResponse, option=option
)
@overload
async def achat(
self, request: ChatRequest, option: RequestOption | None, stream: Literal[True]
) -> AsyncGenerator[bytes, None]: ...
@overload
def achat(
self, request: ChatRequest, option: RequestOption | None, stream: Literal[False]
) -> ChatResponse: ...
@overload
async def achat(
self, request: ChatRequest, option: RequestOption | None
) -> ChatResponse: ...
async def achat(
self,
request: ChatRequest,
option: RequestOption | None = None,
stream: bool = False,
):
if stream:
return await ATransport.aexecute(
self.config, request, option=option, stream=True
)
else:
return await ATransport.aexecute(
self.config, request, unmarshal_as=ChatResponse, option=option
)
def stop(
self, request: StopChatRequest, option: RequestOption | None = None
) -> StopChatResponse:
if request.body is not None:
option.headers[CONTENT_TYPE] = f"{APPLICATION_JSON}; charset=utf-8"
return Transport.execute(
self.config, request, unmarshal_as=StopChatResponse, option=option
)
async def astop(
self, request: StopChatRequest, option: RequestOption | None = None
) -> StopChatResponse:
return await ATransport.aexecute(
self.config, request, unmarshal_as=StopChatResponse, option=option
)

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from dify_oapi.core.const import APPLICATION_JSON, CONTENT_TYPE
from dify_oapi.core.http.transport import ATransport, Transport
from dify_oapi.core.model.config import Config
from dify_oapi.core.model.request_option import RequestOption
from ..model.delete_conversation_request import DeleteConversationRequest
from ..model.delete_conversation_response import DeleteConversationResponse
from ..model.get_conversation_list_request import GetConversationListRequest
from ..model.get_conversation_list_response import GetConversationListResponse
from ..model.rename_conversation_request import RenameConversationRequest
from ..model.rename_conversation_response import RenameConversationResponse
class Conversation:
def __init__(self, config: Config) -> None:
self.config: Config = config
def list(
self, request: GetConversationListRequest, option: RequestOption | None = None
) -> GetConversationListResponse:
# 添加 content-type
if request.body is not None:
option.headers[CONTENT_TYPE] = f"{APPLICATION_JSON}; charset=utf-8"
# 发起请求
return Transport.execute(
self.config,
request,
unmarshal_as=GetConversationListResponse,
option=option,
)
async def alist(
self, request: GetConversationListRequest, option: RequestOption | None = None
) -> GetConversationListResponse:
# 发起请求
return await ATransport.aexecute(
self.config,
request,
unmarshal_as=GetConversationListResponse,
option=option,
)
def delete(
self, request: DeleteConversationRequest, option: RequestOption | None = None
) -> DeleteConversationResponse:
if request.body is not None:
option.headers[CONTENT_TYPE] = f"{APPLICATION_JSON}; charset=utf-8"
return Transport.execute(
self.config, request, unmarshal_as=DeleteConversationResponse, option=option
)
async def adelete(
self, request: DeleteConversationRequest, option: RequestOption | None = None
) -> DeleteConversationResponse:
# 发起请求
return await ATransport.aexecute(
self.config, request, unmarshal_as=DeleteConversationResponse, option=option
)
def rename(
self, request: RenameConversationRequest, option: RequestOption | None = None
) -> RenameConversationResponse:
if request.body is not None:
option.headers[CONTENT_TYPE] = f"{APPLICATION_JSON}; charset=utf-8"
return Transport.execute(
self.config, request, unmarshal_as=RenameConversationResponse, option=option
)
async def arename(
self, request: RenameConversationRequest, option: RequestOption | None = None
) -> RenameConversationResponse:
# 发起请求
return await ATransport.aexecute(
self.config, request, unmarshal_as=RenameConversationResponse, option=option
)

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from dify_oapi.core.const import APPLICATION_JSON, CONTENT_TYPE
from dify_oapi.core.http.transport import ATransport, Transport
from dify_oapi.core.model.config import Config
from dify_oapi.core.model.request_option import RequestOption
from ..model.message_history_request import MessageHistoryRequest
from ..model.message_history_response import MessageHistoryResponse
from ..model.message_suggested_request import MessageSuggestedRequest
from ..model.message_suggested_response import MessageSuggestedResponse
class Message:
def __init__(self, config: Config) -> None:
self.config: Config = config
def suggested(
self, request: MessageSuggestedRequest, option: RequestOption | None = None
) -> MessageSuggestedResponse:
# 添加 content-type
if request.body is not None:
option.headers[CONTENT_TYPE] = f"{APPLICATION_JSON}; charset=utf-8"
# 发起请求
return Transport.execute(
self.config, request, unmarshal_as=MessageSuggestedResponse, option=option
)
async def asuggested(
self, request: MessageSuggestedRequest, option: RequestOption | None = None
) -> MessageSuggestedResponse:
# 发起请求
return await ATransport.aexecute(
self.config, request, unmarshal_as=MessageSuggestedResponse, option=option
)
def history(
self, request: MessageHistoryRequest, option: RequestOption | None = None
) -> MessageHistoryResponse:
# 添加 content-type
if request.body is not None:
option.headers[CONTENT_TYPE] = f"{APPLICATION_JSON}; charset=utf-8"
# 发起请求
return Transport.execute(
self.config, request, unmarshal_as=MessageHistoryResponse, option=option
)
async def ahistory(
self, request: MessageHistoryRequest, option: RequestOption | None = None
) -> MessageHistoryResponse:
# 发起请求
return await ATransport.aexecute(
self.config, request, unmarshal_as=MessageHistoryResponse, option=option
)

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from dify_oapi.core.model.config import Config
from .resource import Chat, Conversation, Message, Audio
class V1:
def __init__(self, config: Config):
self.chat: Chat = Chat(config)
self.conversation: Conversation = Conversation(config)
self.message: Message = Message(config)
self.audio: Audio = Audio(config)

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