Index
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' + - '' + - _("Hide Search Matches") + - "
" - ) - ); - }, - - /** - * helper function to hide the search marks again - */ - hideSearchWords: () => { - document - .querySelectorAll("#searchbox .highlight-link") - .forEach((el) => el.remove()); - document - .querySelectorAll("span.highlighted") - .forEach((el) => el.classList.remove("highlighted")); - localStorage.removeItem("sphinx_highlight_terms") - }, - - initEscapeListener: () => { - // only install a listener if it is really needed - if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; - - document.addEventListener("keydown", (event) => { - // bail for input elements - if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; - // bail with special keys - if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; - if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { - SphinxHighlight.hideSearchWords(); - event.preventDefault(); - } - }); - }, -}; - -_ready(() => { - /* Do not call highlightSearchWords() when we are on the search page. - * It will highlight words from the *previous* search query. - */ - if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); - SphinxHighlight.initEscapeListener(); -}); diff --git a/api-website/_build/html/genindex.html b/api-website/_build/html/genindex.html deleted file mode 100644 index 331f6c4c..00000000 --- a/api-website/_build/html/genindex.html +++ /dev/null @@ -1,477 +0,0 @@ - - - - - -- | - |
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SalesGPT
SalesGPT.acall()
SalesGPT.acompletion_with_retry()
SalesGPT.astep()
SalesGPT.company_business
SalesGPT.company_name
SalesGPT.company_values
SalesGPT.conversation_history
SalesGPT.conversation_purpose
SalesGPT.conversation_stage_dict
SalesGPT.conversation_stage_id
SalesGPT.conversation_type
SalesGPT.current_conversation_stage
SalesGPT.determine_conversation_stage()
SalesGPT.from_llm()
SalesGPT.human_step()
SalesGPT.input_keys
SalesGPT.knowledge_base
SalesGPT.model_name
SalesGPT.output_keys
SalesGPT.retrieve_conversation_stage()
SalesGPT.sales_agent_executor
SalesGPT.sales_conversation_utterance_chain
SalesGPT.salesperson_name
SalesGPT.salesperson_role
SalesGPT.seed_agent()
SalesGPT.stage_analyzer_chain
SalesGPT.step()
SalesGPT.use_tools
TimeFilter
-time_logger()
- r | ||
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- run_api | - |
- s | ||
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- salesgpt | - |
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- salesgpt.agents | - |
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- salesgpt.chains | - |
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- salesgpt.logger | - |
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- salesgpt.parsers | - |
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- salesgpt.prompts | - |
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- salesgpt.prompts_cn | - |
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- salesgpt.salesgptapi | - |
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- salesgpt.stages | - |
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- salesgpt.templates | - |
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- salesgpt.tools | - |
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- salesgpt.version | - |
Bases: BaseModel
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
-Metadata about the fields defined on the model, -mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].
-This replaces Model.__fields__ from Pydantic V1.
-Bases: Chain
Controller model for the Sales Agent.
-Asynchronously execute the chain.
-only one param. Should contain all inputs specified in -Chain.input_keys except for inputs that will be set by the chain’s -memory.
-response. If True, only new keys generated by this chain will be -returned. If False, both input keys and new keys generated by this -chain will be returned. Defaults to False.
-addition to callbacks passed to the chain during construction, but only -these runtime callbacks will propagate to calls to other objects.
-addition to tags passed to the chain during construction, but only -these runtime tags will propagate to calls to other objects.
-metadata: Optional metadata associated with the chain. Defaults to None -include_run_info: Whether to include run info in the response. Defaults
---to False.
-
Chain.output_keys.
-Use tenacity to retry the async completion call.
-stream (bool): whether or not return -streaming generator object to manipulate streaming chunks in downstream applications.
-Initialize the SalesGPT Controller.
-Keys expected to be in the chain input.
-Keys expected to be in the chain output.
-stream (bool): whether or not return -streaming generator object to manipulate streaming chunks in downstream applications.
-Bases: LLMChain
Chain to generate the next utterance for the conversation.
-Get the response parser.
-Bases: LLMChain
Chain to analyze which conversation stage should the conversation move into.
-Get the response parser.
-Bases: Filter
Determine if the specified record is to be logged.
-Returns True if the record should be logged, or False otherwise. -If deemed appropriate, the record may be modified in-place.
-Decorator function to log time taken by any function.
-Bases: AgentOutputParser
Instructions on how the LLM output should be formatted.
-Parse text into agent action/finish.
-Bases: StringPromptTemplate
Format the prompt with the inputs.
-kwargs: Any arguments to be passed to the prompt template.
-A formatted string.
-Example:
-prompt.format(variable1="foo")
-
We assume that the product catalog is simply a text string.
-Version information.
-docs
directory.
- >
- ),
- },
- {
- title: 'Powered by React',
- Svg: require('@site/static/img/undraw_docusaurus_react.svg').default,
- description: (
- <>
- Extend or customize your website layout by reusing React. Docusaurus can
- be extended while reusing the same header and footer.
- >
- ),
- },
-];
-
-function Feature({Svg, title, description}) {
- return (
- {description}
-