Adds an Info button that links to docs (#539)
This commit is contained in:
Gabriel Luiz Freitas Almeida
GitHub
commit
e362cfcf16
11 changed files with 393 additions and 270 deletions
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@ -1,141 +1,247 @@
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---
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agents:
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- ZeroShotAgent
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- JsonAgent
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- CSVAgent
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- AgentInitializer
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- VectorStoreAgent
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- VectorStoreRouterAgent
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- SQLAgent
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ZeroShotAgent:
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documentation: "https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent"
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JsonAgent:
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documentation: "https://python.langchain.com/docs/modules/agents/toolkits/openapi"
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CSVAgent:
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documentation: "https://python.langchain.com/docs/modules/agents/toolkits/csv"
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AgentInitializer:
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documentation: "https://python.langchain.com/docs/modules/agents/agent_types/"
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VectorStoreAgent:
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documentation: ""
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VectorStoreRouterAgent:
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documentation: ""
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SQLAgent:
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documentation: ""
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chains:
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- LLMChain
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- LLMMathChain
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- LLMCheckerChain
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- ConversationChain
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- SeriesCharacterChain
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- MidJourneyPromptChain
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- TimeTravelGuideChain
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- SQLDatabaseChain
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- RetrievalQA
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- RetrievalQAWithSourcesChain
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- ConversationalRetrievalChain
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- CombineDocsChain
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LLMChain:
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documentation: "https://python.langchain.com/docs/modules/chains/foundational/llm_chain"
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LLMMathChain:
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documentation: "https://python.langchain.com/docs/modules/chains/additional/llm_math"
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LLMCheckerChain:
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documentation: "https://python.langchain.com/docs/modules/chains/additional/llm_checker"
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ConversationChain:
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documentation: ""
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SeriesCharacterChain:
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documentation: ""
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MidJourneyPromptChain:
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documentation: ""
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TimeTravelGuideChain:
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documentation: ""
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SQLDatabaseChain:
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documentation: ""
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RetrievalQA:
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documentation: "https://python.langchain.com/docs/modules/chains/popular/vector_db_qa"
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RetrievalQAWithSourcesChain:
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documentation: ""
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ConversationalRetrievalChain:
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documentation: "https://python.langchain.com/docs/modules/chains/popular/chat_vector_db"
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CombineDocsChain:
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documentation: ""
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documentloaders:
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- AirbyteJSONLoader
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- CoNLLULoader
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- CSVLoader
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- UnstructuredEmailLoader
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- EverNoteLoader
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- FacebookChatLoader
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- GutenbergLoader
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- BSHTMLLoader
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- UnstructuredHTMLLoader
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# - UnstructuredImageLoader # Issue with Python 3.11 (https://github.com/Unstructured-IO/unstructured-inference/issues/83)
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- UnstructuredMarkdownLoader
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- PyPDFLoader
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- UnstructuredPowerPointLoader
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- SRTLoader
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- TelegramChatLoader
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- TextLoader
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- UnstructuredWordDocumentLoader
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- WebBaseLoader
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- AZLyricsLoader
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- CollegeConfidentialLoader
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- HNLoader
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- IFixitLoader
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- IMSDbLoader
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- GitbookLoader
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- ReadTheDocsLoader
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- SlackDirectoryLoader
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- NotionDirectoryLoader
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- DirectoryLoader
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- GitLoader
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AirbyteJSONLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/airbyte_json"
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CoNLLULoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/conll-u"
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CSVLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/csv"
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UnstructuredEmailLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/email"
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EverNoteLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/evernote"
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FacebookChatLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/facebook_chat"
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GutenbergLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/gutenberg"
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BSHTMLLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/html"
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UnstructuredHTMLLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/html"
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UnstructuredMarkdownLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/markdown"
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PyPDFLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/pdf"
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UnstructuredPowerPointLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/microsoft_powerpoint"
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SRTLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/subtitle"
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TelegramChatLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/telegram"
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TextLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/"
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UnstructuredWordDocumentLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/microsoft_word"
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WebBaseLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/web_base"
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AZLyricsLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/azlyrics"
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CollegeConfidentialLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/college_confidential"
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HNLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/hacker_news"
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IFixitLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/ifixit"
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IMSDbLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/imsdb"
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GitbookLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/gitbook"
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ReadTheDocsLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/readthedocs_documentation"
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SlackDirectoryLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/slack"
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NotionDirectoryLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/notion"
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DirectoryLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/file_directory"
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GitLoader:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/git"
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embeddings:
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- OpenAIEmbeddings
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- HuggingFaceEmbeddings
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- CohereEmbeddings
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OpenAIEmbeddings:
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documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/openai"
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HuggingFaceEmbeddings:
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documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/sentence_transformers"
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CohereEmbeddings:
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documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/cohere"
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llms:
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- OpenAI
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# - AzureOpenAI
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# - AzureChatOpenAI
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- ChatOpenAI
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- LlamaCpp
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- CTransformers
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- Cohere
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- Anthropic
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- ChatAnthropic
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- HuggingFaceHub
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OpenAI:
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documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai"
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ChatOpenAI:
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documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/integrations/openai"
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LlamaCpp:
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documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/llamacpp"
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CTransformers:
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documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/ctransformers"
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Cohere:
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documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/cohere"
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Anthropic:
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documentation: ""
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ChatAnthropic:
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documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/integrations/anthropic"
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HuggingFaceHub:
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documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/huggingface_hub"
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memories:
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- ConversationBufferMemory
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- ConversationSummaryMemory
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- ConversationKGMemory
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ConversationBufferMemory:
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documentation: "https://python.langchain.com/docs/modules/memory/how_to/summary"
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ConversationSummaryMemory:
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documentation: "https://python.langchain.com/docs/modules/memory/how_to/summary"
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ConversationKGMemory:
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documentation: "https://python.langchain.com/docs/modules/memory/how_to/kg"
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ConversationBufferWindowMemory:
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documentation: "https://python.langchain.com/docs/modules/memory/how_to/buffer_window"
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VectorStoreRetrieverMemory:
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documentation: "https://python.langchain.com/docs/modules/memory/how_to/vectorstore_retriever_memory"
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prompts:
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- PromptTemplate
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- FewShotPromptTemplate
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- ZeroShotPrompt
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PromptTemplate:
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documentation: "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/"
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ZeroShotPrompt:
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documentation: "https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent"
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textsplitters:
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- CharacterTextSplitter
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- RecursiveCharacterTextSplitter
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# - LatexTextSplitter
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# - PythonCodeTextSplitter
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CharacterTextSplitter:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter"
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RecursiveCharacterTextSplitter:
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documentation: "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/recursive_text_splitter"
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toolkits:
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- OpenAPIToolkit
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- JsonToolkit
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- VectorStoreInfo
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- VectorStoreRouterToolkit
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- VectorStoreToolkit
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OpenAPIToolkit:
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documentation: ""
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JsonToolkit:
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documentation: ""
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VectorStoreInfo:
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documentation: ""
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VectorStoreRouterToolkit:
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documentation: ""
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VectorStoreToolkit:
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documentation: ""
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tools:
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- Search
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- PAL-MATH
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- Calculator
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- Serper Search
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- Tool
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- PythonFunctionTool
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- PythonFunction
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- JsonSpec
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- News API
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- TMDB API
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- Podcast API
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- QuerySQLDataBaseTool
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- InfoSQLDatabaseTool
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- ListSQLDatabaseTool
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# - QueryCheckerTool
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- BingSearchRun
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- GoogleSearchRun
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- GoogleSearchResults
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- GoogleSerperRun
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- JsonListKeysTool
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- JsonGetValueTool
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- PythonREPLTool
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- PythonAstREPLTool
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- RequestsGetTool
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- RequestsPostTool
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- RequestsPatchTool
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- RequestsPutTool
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- RequestsDeleteTool
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- WikipediaQueryRun
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- WolframAlphaQueryRun
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Search:
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documentation: ""
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PAL-MATH:
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documentation: ""
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Calculator:
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documentation: ""
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Serper Search:
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documentation: ""
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Tool:
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documentation: ""
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PythonFunctionTool:
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documentation: ""
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PythonFunction:
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documentation: ""
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JsonSpec:
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documentation: ""
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News API:
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documentation: ""
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TMDB API:
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documentation: ""
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Podcast API:
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documentation: ""
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QuerySQLDataBaseTool:
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documentation: ""
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InfoSQLDatabaseTool:
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documentation: ""
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ListSQLDatabaseTool:
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documentation: ""
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BingSearchRun:
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documentation: ""
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GoogleSearchRun:
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documentation: ""
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GoogleSearchResults:
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documentation: ""
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GoogleSerperRun:
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documentation: ""
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JsonListKeysTool:
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documentation: ""
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JsonGetValueTool:
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documentation: ""
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PythonREPLTool:
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documentation: ""
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PythonAstREPLTool:
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documentation: ""
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RequestsGetTool:
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documentation: ""
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RequestsPostTool:
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documentation: ""
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RequestsPatchTool:
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documentation: ""
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RequestsPutTool:
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documentation: ""
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RequestsDeleteTool:
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documentation: ""
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WikipediaQueryRun:
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documentation: ""
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WolframAlphaQueryRun:
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documentation: ""
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utilities:
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- BingSearchAPIWrapper
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- GoogleSearchAPIWrapper
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- GoogleSerperAPIWrapper
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- SearxResults
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- SearxSearchWrapper
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- SerpAPIWrapper
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- WikipediaAPIWrapper
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- WolframAlphaAPIWrapper
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# - ZapierNLAWrapper
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- SQLDatabase
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BingSearchAPIWrapper:
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documentation: ""
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GoogleSearchAPIWrapper:
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documentation: ""
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GoogleSerperAPIWrapper:
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documentation: ""
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SearxResults:
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documentation: ""
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SearxSearchWrapper:
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documentation: ""
|
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SerpAPIWrapper:
|
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documentation: ""
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WikipediaAPIWrapper:
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documentation: ""
|
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WolframAlphaAPIWrapper:
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documentation: ""
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vectorstores:
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- Chroma
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- Qdrant
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- Weaviate
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- FAISS
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- Pinecone
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- SupabaseVectorStore
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- MongoDBAtlasVectorSearch
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Chroma:
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documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/chroma"
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Qdrant:
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documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/qdrant"
|
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Weaviate:
|
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documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/weaviate"
|
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FAISS:
|
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documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/faiss"
|
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Pinecone:
|
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documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/pinecone"
|
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SupabaseVectorStore:
|
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documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/supabase"
|
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MongoDBAtlasVectorSearch:
|
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documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/mongodb_atlas_vector_search"
|
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wrappers:
|
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- RequestsWrapper
|
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# - ChatPromptTemplate
|
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# - SystemMessagePromptTemplate
|
||||
# - HumanMessagePromptTemplate
|
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RequestsWrapper:
|
||||
documentation: ""
|
||||
|
|
|
|||
|
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@ -8,6 +8,7 @@ from langflow.template.field.base import TemplateField
|
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from langflow.template.frontend_node.base import FrontendNode
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from langflow.template.template.base import Template
|
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from langflow.utils.logger import logger
|
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from langflow.settings import settings
|
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|
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# Assuming necessary imports for Field, Template, and FrontendNode classes
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|
||||
|
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@ -15,12 +16,29 @@ from langflow.utils.logger import logger
|
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class LangChainTypeCreator(BaseModel, ABC):
|
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type_name: str
|
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type_dict: Optional[Dict] = None
|
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name_docs_dict: Optional[Dict[str, str]] = None
|
||||
|
||||
@property
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def frontend_node_class(self) -> Type[FrontendNode]:
|
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"""The class type of the FrontendNode created in frontend_node."""
|
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return FrontendNode
|
||||
|
||||
@property
|
||||
def docs_map(self) -> Dict[str, str]:
|
||||
"""A dict with the name of the component as key and the documentation link as value."""
|
||||
if self.name_docs_dict is None:
|
||||
try:
|
||||
type_settings = getattr(settings, self.type_name)
|
||||
self.name_docs_dict = {
|
||||
name: value_dict["documentation"]
|
||||
for name, value_dict in type_settings.items()
|
||||
}
|
||||
except AttributeError as exc:
|
||||
logger.error(exc)
|
||||
|
||||
self.name_docs_dict = {}
|
||||
return self.name_docs_dict
|
||||
|
||||
@property
|
||||
@abstractmethod
|
||||
def type_to_loader_dict(self) -> Dict:
|
||||
|
|
@ -83,7 +101,7 @@ class LangChainTypeCreator(BaseModel, ABC):
|
|||
|
||||
signature.add_extra_fields()
|
||||
signature.add_extra_base_classes()
|
||||
|
||||
signature.set_documentation(self.docs_map.get(name, ""))
|
||||
return signature
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
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import json
|
||||
from typing import Any, Callable, Dict, Sequence
|
||||
from typing import Any, Callable, Dict, Sequence, Type
|
||||
|
||||
from langchain.agents import ZeroShotAgent
|
||||
from langchain.agents import agent as agent_module
|
||||
|
|
@ -16,6 +16,10 @@ from langflow.interface.toolkits.base import toolkits_creator
|
|||
from langflow.interface.chains.base import chain_creator
|
||||
from langflow.interface.utils import load_file_into_dict
|
||||
from langflow.utils import validate
|
||||
from langchain.chains.base import Chain
|
||||
from langchain.vectorstores.base import VectorStore
|
||||
from langchain.document_loaders.base import BaseLoader
|
||||
from langchain.prompts.base import BasePromptTemplate
|
||||
|
||||
|
||||
def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
|
||||
|
|
@ -76,7 +80,7 @@ def instantiate_based_on_type(class_object, base_type, node_type, params):
|
|||
return class_object(**params)
|
||||
|
||||
|
||||
def instantiate_chains(node_type, class_object, params):
|
||||
def instantiate_chains(node_type, class_object: Type[Chain], params: Dict):
|
||||
if "retriever" in params and hasattr(params["retriever"], "as_retriever"):
|
||||
params["retriever"] = params["retriever"].as_retriever()
|
||||
if node_type in chain_creator.from_method_nodes:
|
||||
|
|
@ -88,11 +92,11 @@ def instantiate_chains(node_type, class_object, params):
|
|||
return class_object(**params)
|
||||
|
||||
|
||||
def instantiate_agent(class_object, params):
|
||||
def instantiate_agent(class_object: Type[agent_module.Agent], params: Dict):
|
||||
return load_agent_executor(class_object, params)
|
||||
|
||||
|
||||
def instantiate_prompt(node_type, class_object, params):
|
||||
def instantiate_prompt(node_type, class_object: Type[BasePromptTemplate], params: Dict):
|
||||
if node_type == "ZeroShotPrompt":
|
||||
if "tools" not in params:
|
||||
params["tools"] = []
|
||||
|
|
@ -100,7 +104,7 @@ def instantiate_prompt(node_type, class_object, params):
|
|||
return class_object(**params)
|
||||
|
||||
|
||||
def instantiate_tool(node_type, class_object, params):
|
||||
def instantiate_tool(node_type, class_object: Type[BaseTool], params: Dict):
|
||||
if node_type == "JsonSpec":
|
||||
params["dict_"] = load_file_into_dict(params.pop("path"))
|
||||
return class_object(**params)
|
||||
|
|
@ -118,7 +122,7 @@ def instantiate_tool(node_type, class_object, params):
|
|||
return class_object(**params)
|
||||
|
||||
|
||||
def instantiate_toolkit(node_type, class_object, params):
|
||||
def instantiate_toolkit(node_type, class_object: Type[BaseToolkit], params: Dict):
|
||||
loaded_toolkit = class_object(**params)
|
||||
# Commenting this out for now to use toolkits as normal tools
|
||||
# if toolkits_creator.has_create_function(node_type):
|
||||
|
|
@ -128,7 +132,7 @@ def instantiate_toolkit(node_type, class_object, params):
|
|||
return loaded_toolkit
|
||||
|
||||
|
||||
def instantiate_embedding(class_object, params):
|
||||
def instantiate_embedding(class_object, params: Dict):
|
||||
params.pop("model", None)
|
||||
params.pop("headers", None)
|
||||
try:
|
||||
|
|
@ -142,7 +146,7 @@ def instantiate_embedding(class_object, params):
|
|||
return class_object(**params)
|
||||
|
||||
|
||||
def instantiate_vectorstore(class_object, params):
|
||||
def instantiate_vectorstore(class_object: Type[VectorStore], params: Dict):
|
||||
search_kwargs = params.pop("search_kwargs", {})
|
||||
if initializer := vecstore_initializer.get(class_object.__name__):
|
||||
vecstore = initializer(class_object, params)
|
||||
|
|
@ -158,7 +162,7 @@ def instantiate_vectorstore(class_object, params):
|
|||
return vecstore
|
||||
|
||||
|
||||
def instantiate_documentloader(class_object, params):
|
||||
def instantiate_documentloader(class_object: Type[BaseLoader], params: Dict):
|
||||
if "file_filter" in params:
|
||||
# file_filter will be a string but we need a function
|
||||
# that will be used to filter the files using file_filter
|
||||
|
|
@ -187,19 +191,29 @@ def instantiate_documentloader(class_object, params):
|
|||
return docs
|
||||
|
||||
|
||||
def instantiate_textsplitter(class_object, params):
|
||||
def instantiate_textsplitter(
|
||||
class_object,
|
||||
params: Dict,
|
||||
):
|
||||
try:
|
||||
documents = params.pop("documents")
|
||||
except KeyError as e:
|
||||
except KeyError as exc:
|
||||
raise ValueError(
|
||||
"The source you provided did not load correctly or was empty."
|
||||
"Try changing the chunk_size of the Text Splitter."
|
||||
) from e
|
||||
text_splitter = class_object(**params)
|
||||
) from exc
|
||||
|
||||
if "separator_type" in params and params["separator_type"] == "Text":
|
||||
text_splitter = class_object(**params)
|
||||
else:
|
||||
params["language"] = params.pop("separator_type", None)
|
||||
params.pop("separators", None)
|
||||
text_splitter = class_object.from_language(**params)
|
||||
|
||||
return text_splitter.split_documents(documents)
|
||||
|
||||
|
||||
def instantiate_utility(node_type, class_object, params):
|
||||
def instantiate_utility(node_type, class_object, params: Dict):
|
||||
if node_type == "SQLDatabase":
|
||||
return class_object.from_uri(params.pop("uri"))
|
||||
return class_object(**params)
|
||||
|
|
|
|||
|
|
@ -1,24 +1,23 @@
|
|||
import os
|
||||
from typing import List
|
||||
|
||||
import yaml
|
||||
from pydantic import BaseSettings, root_validator
|
||||
|
||||
|
||||
class Settings(BaseSettings):
|
||||
chains: List[str] = []
|
||||
agents: List[str] = []
|
||||
prompts: List[str] = []
|
||||
llms: List[str] = []
|
||||
tools: List[str] = []
|
||||
memories: List[str] = []
|
||||
embeddings: List[str] = []
|
||||
vectorstores: List[str] = []
|
||||
documentloaders: List[str] = []
|
||||
wrappers: List[str] = []
|
||||
toolkits: List[str] = []
|
||||
textsplitters: List[str] = []
|
||||
utilities: List[str] = []
|
||||
chains: dict = {}
|
||||
agents: dict = {}
|
||||
prompts: dict = {}
|
||||
llms: dict = {}
|
||||
tools: dict = {}
|
||||
memories: dict = {}
|
||||
embeddings: dict = {}
|
||||
vectorstores: dict = {}
|
||||
documentloaders: dict = {}
|
||||
wrappers: dict = {}
|
||||
toolkits: dict = {}
|
||||
textsplitters: dict = {}
|
||||
utilities: dict = {}
|
||||
dev: bool = False
|
||||
database_url: str = "sqlite:///./langflow.db"
|
||||
cache: str = "InMemoryCache"
|
||||
|
|
@ -38,16 +37,16 @@ class Settings(BaseSettings):
|
|||
|
||||
def update_from_yaml(self, file_path: str, dev: bool = False):
|
||||
new_settings = load_settings_from_yaml(file_path)
|
||||
self.chains = new_settings.chains or []
|
||||
self.agents = new_settings.agents or []
|
||||
self.prompts = new_settings.prompts or []
|
||||
self.llms = new_settings.llms or []
|
||||
self.tools = new_settings.tools or []
|
||||
self.memories = new_settings.memories or []
|
||||
self.wrappers = new_settings.wrappers or []
|
||||
self.toolkits = new_settings.toolkits or []
|
||||
self.textsplitters = new_settings.textsplitters or []
|
||||
self.utilities = new_settings.utilities or []
|
||||
self.chains = new_settings.chains or {}
|
||||
self.agents = new_settings.agents or {}
|
||||
self.prompts = new_settings.prompts or {}
|
||||
self.llms = new_settings.llms or {}
|
||||
self.tools = new_settings.tools or {}
|
||||
self.memories = new_settings.memories or {}
|
||||
self.wrappers = new_settings.wrappers or {}
|
||||
self.toolkits = new_settings.toolkits or {}
|
||||
self.textsplitters = new_settings.textsplitters or {}
|
||||
self.utilities = new_settings.utilities or {}
|
||||
self.dev = dev
|
||||
|
||||
def update_settings(self, **kwargs):
|
||||
|
|
|
|||
|
|
@ -15,14 +15,21 @@ class FrontendNode(BaseModel):
|
|||
base_classes: List[str]
|
||||
name: str = ""
|
||||
display_name: str = ""
|
||||
documentation: str = ""
|
||||
|
||||
def set_documentation(self, documentation: str) -> None:
|
||||
"""Sets the documentation of the frontend node."""
|
||||
self.documentation = documentation
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""Returns a dict representation of the frontend node."""
|
||||
return {
|
||||
self.name: {
|
||||
"template": self.template.to_dict(self.format_field),
|
||||
"description": self.description,
|
||||
"base_classes": self.base_classes,
|
||||
"display_name": self.display_name or self.name,
|
||||
"documentation": self.documentation,
|
||||
},
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
from langflow.template.field.base import TemplateField
|
||||
from langflow.template.frontend_node.base import FrontendNode
|
||||
from langchain.text_splitter import Language
|
||||
|
||||
|
||||
class TextSplittersFrontendNode(FrontendNode):
|
||||
|
|
@ -17,6 +18,22 @@ class TextSplittersFrontendNode(FrontendNode):
|
|||
name = "separator"
|
||||
elif self.template.type_name == "RecursiveCharacterTextSplitter":
|
||||
name = "separators"
|
||||
# Add a field for type of separator
|
||||
# which will have Text or any value from the
|
||||
# Language enum
|
||||
self.template.add_field(
|
||||
TemplateField(
|
||||
field_type="str",
|
||||
required=True,
|
||||
show=True,
|
||||
name="separator_type",
|
||||
advanced=False,
|
||||
is_list=True,
|
||||
options=[x.value for x in Language],
|
||||
value="Text",
|
||||
display_name="Separator Type",
|
||||
)
|
||||
)
|
||||
self.template.add_field(
|
||||
TemplateField(
|
||||
field_type="str",
|
||||
|
|
|
|||
|
|
@ -200,7 +200,7 @@ class VectorStoreFrontendNode(FrontendNode):
|
|||
self.template.add_field(field)
|
||||
|
||||
def add_extra_base_classes(self) -> None:
|
||||
self.base_classes.append("BaseRetriever")
|
||||
self.base_classes.extend(("BaseRetriever", "VectorStoreRetriever"))
|
||||
|
||||
@staticmethod
|
||||
def format_field(field: TemplateField, name: Optional[str] = None) -> None:
|
||||
|
|
|
|||
|
|
@ -6,16 +6,7 @@ import {
|
|||
} from "../../utils";
|
||||
import ParameterComponent from "./components/parameterComponent";
|
||||
import { typesContext } from "../../contexts/typesContext";
|
||||
import {
|
||||
useContext,
|
||||
useState,
|
||||
useEffect,
|
||||
useRef,
|
||||
ForwardRefExoticComponent,
|
||||
ComponentType,
|
||||
SVGProps,
|
||||
ReactNode,
|
||||
} from "react";
|
||||
import { useContext, useState, useEffect, useRef } from "react";
|
||||
import { NodeDataType } from "../../types/flow";
|
||||
import { alertContext } from "../../contexts/alertContext";
|
||||
import { PopUpContext } from "../../contexts/popUpContext";
|
||||
|
|
@ -23,10 +14,9 @@ import NodeModal from "../../modals/NodeModal";
|
|||
import Tooltip from "../../components/TooltipComponent";
|
||||
import { NodeToolbar } from "reactflow";
|
||||
import NodeToolbarComponent from "../../pages/FlowPage/components/nodeToolbarComponent";
|
||||
|
||||
import { FileText, Info } from "lucide-react";
|
||||
import ShadTooltip from "../../components/ShadTooltipComponent";
|
||||
import { useSSE } from "../../contexts/SSEContext";
|
||||
import { ReactElement } from "react-markdown/lib/react-markdown";
|
||||
|
||||
export default function GenericNode({
|
||||
data,
|
||||
|
|
@ -46,6 +36,7 @@ export default function GenericNode({
|
|||
const [validationStatus, setValidationStatus] = useState(null);
|
||||
// State for outline color
|
||||
const { sseData, isBuilding } = useSSE();
|
||||
const refHtml = useRef(null);
|
||||
|
||||
// useEffect(() => {
|
||||
// if (reactFlowInstance) {
|
||||
|
|
@ -79,6 +70,22 @@ export default function GenericNode({
|
|||
|
||||
useEffect(() => {}, [closePopUp, data.node.template]);
|
||||
|
||||
useEffect(() => {
|
||||
refHtml.current = (
|
||||
<div className="flex">
|
||||
<span>{`${data.node.display_name} Documentation`}</span>
|
||||
<span
|
||||
className="self-center"
|
||||
style={{
|
||||
color: nodeColors[types[data.type]] ?? nodeColors.unknown,
|
||||
}}
|
||||
>
|
||||
<FileText className="h-4 w-4 ml-2" />
|
||||
</span>
|
||||
</div>
|
||||
);
|
||||
}, []);
|
||||
|
||||
return (
|
||||
<>
|
||||
<NodeToolbar>
|
||||
|
|
@ -103,7 +110,7 @@ export default function GenericNode({
|
|||
color: nodeColors[types[data.type]] ?? nodeColors.unknown,
|
||||
}}
|
||||
/>
|
||||
<div className="ml-2 truncate">
|
||||
<div className="ml-2 truncate flex">
|
||||
<ShadTooltip
|
||||
delayDuration={1500}
|
||||
content={data.node.display_name}
|
||||
|
|
@ -112,6 +119,29 @@ export default function GenericNode({
|
|||
{data.node.display_name}
|
||||
</div>
|
||||
</ShadTooltip>
|
||||
<div className="">
|
||||
{data.node.documentation !== "" && (
|
||||
<ShadTooltip
|
||||
open={true}
|
||||
delayDuration={1000}
|
||||
content={refHtml.current}
|
||||
>
|
||||
<a
|
||||
href={data.node.documentation}
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
>
|
||||
<Info
|
||||
style={{
|
||||
color:
|
||||
nodeColors[types[data.type]] ?? nodeColors.unknown,
|
||||
}}
|
||||
className="ml-2 self-center w-4 h-4"
|
||||
/>
|
||||
</a>
|
||||
</ShadTooltip>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div className="flex gap-3">
|
||||
|
|
|
|||
|
|
@ -192,39 +192,49 @@ export function TabsProvider({ children }: { children: ReactNode }) {
|
|||
}
|
||||
|
||||
function processFlowEdges(flow) {
|
||||
if(!flow.data || !flow.data.edges) return;
|
||||
if (!flow.data || !flow.data.edges) return;
|
||||
flow.data.edges.forEach((edge) => {
|
||||
edge.className = "";
|
||||
edge.style = { stroke: "#555555" };
|
||||
});
|
||||
}
|
||||
function updateDisplay_name(node:NodeType,template:APIClassType) {
|
||||
node.data.node.display_name = template["display_name"]?template["display_name"]:node.data.type;
|
||||
|
||||
function updateDisplay_name(node: NodeType, template: APIClassType) {
|
||||
node.data.node.display_name = template["display_name"] || node.data.type;
|
||||
}
|
||||
|
||||
function updateNodeDocumentation(node: NodeType, template: APIClassType) {
|
||||
node.data.node.documentation = template["documentation"];
|
||||
}
|
||||
|
||||
function processFlowNodes(flow) {
|
||||
if(!flow.data || !flow.data.nodes) return;
|
||||
flow.data.nodes.forEach((node:NodeType) => {
|
||||
if (!flow.data || !flow.data.nodes) return;
|
||||
flow.data.nodes.forEach((node: NodeType) => {
|
||||
const template = templates[node.data.type];
|
||||
if (!template) {
|
||||
setErrorData({ title: `Unknown node type: ${node.data.type}` });
|
||||
return;
|
||||
}
|
||||
if (Object.keys(template["template"]).length > 0) {
|
||||
updateDisplay_name(node,template);
|
||||
updateDisplay_name(node, template);
|
||||
updateNodeBaseClasses(node, template);
|
||||
updateNodeEdges(flow, node, template);
|
||||
updateNodeDescription(node, template);
|
||||
updateNodeTemplate(node, template);
|
||||
updateNodeDocumentation(node, template);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function updateNodeBaseClasses(node:NodeType,template:APIClassType) {
|
||||
function updateNodeBaseClasses(node: NodeType, template: APIClassType) {
|
||||
node.data.node.base_classes = template["base_classes"];
|
||||
}
|
||||
|
||||
function updateNodeEdges(flow:FlowType, node:NodeType,template:APIClassType) {
|
||||
function updateNodeEdges(
|
||||
flow: FlowType,
|
||||
node: NodeType,
|
||||
template: APIClassType
|
||||
) {
|
||||
flow.data.edges.forEach((edge) => {
|
||||
if (edge.source === node.id) {
|
||||
edge.sourceHandle = edge.sourceHandle
|
||||
|
|
@ -236,11 +246,11 @@ export function TabsProvider({ children }: { children: ReactNode }) {
|
|||
});
|
||||
}
|
||||
|
||||
function updateNodeDescription(node:NodeType,template:APIClassType) {
|
||||
function updateNodeDescription(node: NodeType, template: APIClassType) {
|
||||
node.data.node.description = template["description"];
|
||||
}
|
||||
|
||||
function updateNodeTemplate(node:NodeType,template:APIClassType) {
|
||||
function updateNodeTemplate(node: NodeType, template: APIClassType) {
|
||||
node.data.node.template = updateTemplate(
|
||||
template["template"] as unknown as APITemplateType,
|
||||
node.data.node.template as APITemplateType
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ export type APIClassType = {
|
|||
description: string;
|
||||
template: APITemplateType;
|
||||
display_name: string;
|
||||
documentation: string;
|
||||
[key: string]: Array<string> | string | APITemplateType;
|
||||
};
|
||||
export type TemplateVariableType = {
|
||||
|
|
|
|||
|
|
@ -88,85 +88,6 @@ def test_prompt_template(client: TestClient):
|
|||
}
|
||||
|
||||
|
||||
def test_few_shot_prompt_template(client: TestClient):
|
||||
response = client.get("api/v1/all")
|
||||
assert response.status_code == 200
|
||||
json_response = response.json()
|
||||
prompts = json_response["prompts"]
|
||||
|
||||
prompt = prompts["FewShotPromptTemplate"]
|
||||
template = prompt["template"]
|
||||
# Test other fields in the template similar to PromptTemplate
|
||||
assert template["examples"] == {
|
||||
"required": False,
|
||||
"placeholder": "",
|
||||
"show": True,
|
||||
"multiline": True,
|
||||
"password": False,
|
||||
"name": "examples",
|
||||
"type": "prompt",
|
||||
"list": True,
|
||||
"advanced": False,
|
||||
}
|
||||
assert template["example_selector"] == {
|
||||
"required": False,
|
||||
"placeholder": "",
|
||||
"show": False,
|
||||
"multiline": False,
|
||||
"password": False,
|
||||
"name": "example_selector",
|
||||
"type": "BaseExampleSelector",
|
||||
"list": False,
|
||||
"advanced": False,
|
||||
}
|
||||
assert template["example_prompt"] == {
|
||||
"required": True,
|
||||
"placeholder": "",
|
||||
"show": True,
|
||||
"multiline": False,
|
||||
"password": False,
|
||||
"name": "example_prompt",
|
||||
"type": "PromptTemplate",
|
||||
"list": False,
|
||||
"advanced": False,
|
||||
}
|
||||
assert template["suffix"] == {
|
||||
"required": True,
|
||||
"placeholder": "",
|
||||
"show": True,
|
||||
"multiline": True,
|
||||
"password": False,
|
||||
"name": "suffix",
|
||||
"type": "prompt",
|
||||
"list": False,
|
||||
"advanced": False,
|
||||
}
|
||||
assert template["example_separator"] == {
|
||||
"required": False,
|
||||
"placeholder": "",
|
||||
"show": False,
|
||||
"multiline": False,
|
||||
"value": "\n\n",
|
||||
"password": False,
|
||||
"name": "example_separator",
|
||||
"type": "str",
|
||||
"list": False,
|
||||
"advanced": False,
|
||||
}
|
||||
assert template["prefix"] == {
|
||||
"required": False,
|
||||
"placeholder": "",
|
||||
"show": True,
|
||||
"multiline": True,
|
||||
"value": "",
|
||||
"password": False,
|
||||
"name": "prefix",
|
||||
"type": "prompt",
|
||||
"list": False,
|
||||
"advanced": False,
|
||||
}
|
||||
|
||||
|
||||
def test_zero_shot_prompt(client: TestClient):
|
||||
response = client.get("api/v1/all")
|
||||
assert response.status_code == 200
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue