mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2025-05-02 17:07:13 +00:00
Allow use of any embedder for any llm/update data handling modal (#386)
* allow use of any embedder for any llm/update data handling modal * Apply embedder override and fallback to OpenAI and Azure models --------- Co-authored-by: timothycarambat <rambat1010@gmail.com>
This commit is contained in:
Sean Hatfield
GitHub
parent
2c2543b4d7
commit
5ad8a5f2d0
9 changed files with 256 additions and 180 deletions
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@ -278,7 +278,7 @@ function SettingsButton() {
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return (
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<a
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href={
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!!user?.role ? paths.settings.system() : paths.settings.appearance()
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!!user?.role ? paths.settings.system() : paths.settings.appearance()
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}
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className="transition-all duration-300 p-2 rounded-full text-white bg-sidebar-button hover:bg-menu-item-selected-gradient hover:border-slate-100 hover:border-opacity-50 border-transparent border"
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>
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@ -133,161 +133,161 @@ export default function GeneralEmbeddingPreference() {
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</p>
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</div>
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{["openai", "azure"].includes(settings.LLMProvider) ? (
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<div className="w-full h-20 items-center justify-center flex">
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<p className="text-gray-800 dark:text-slate-400 text-center">
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Your current LLM preference does not require you to set up
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this part of AnythingLLM.
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<br />
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Embedding is being automatically managed by AnythingLLM.
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</p>
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<>
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<div className="text-white text-sm font-medium py-4">
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Embedding Providers
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</div>
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) : (
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<>
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<div className="text-white text-sm font-medium py-4">
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Embedding Providers
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</div>
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<div className="w-full flex md:flex-wrap overflow-x-scroll gap-4 max-w-[900px]">
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<input
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hidden={true}
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name="EmbeddingEngine"
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value={embeddingChoice}
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/>
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<LLMProviderOption
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name="OpenAI"
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value="openai"
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link="openai.com"
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description="Use OpenAI's text-embedding-ada-002 embedding model."
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checked={embeddingChoice === "openai"}
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image={OpenAiLogo}
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onClick={updateChoice}
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/>
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<LLMProviderOption
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name="Azure OpenAI"
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value="azure"
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link="azure.microsoft.com"
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description="The enterprise option of OpenAI hosted on Azure services."
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checked={embeddingChoice === "azure"}
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image={AzureOpenAiLogo}
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onClick={updateChoice}
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/>
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<LLMProviderOption
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name="LocalAI"
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value="localai"
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link="localai.io"
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description="Self hosted LocalAI embedding engine."
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checked={embeddingChoice === "localai"}
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image={LocalAiLogo}
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onClick={updateChoice}
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/>
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</div>
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<div className="mt-10 flex flex-wrap gap-4 max-w-[800px]">
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{embeddingChoice === "openai" && (
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<>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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API Key
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</label>
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<input
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type="text"
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name="OpenAiKey"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="OpenAI API Key"
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defaultValue={
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settings?.OpenAiKey ? "*".repeat(20) : ""
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}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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</>
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)}
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{embeddingChoice === "azure" && (
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<>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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Azure Service Endpoint
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</label>
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<input
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type="url"
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name="AzureOpenAiEndpoint"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="https://my-azure.openai.azure.com"
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defaultValue={settings?.AzureOpenAiEndpoint}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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API Key
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</label>
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<input
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type="password"
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name="AzureOpenAiKey"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="Azure OpenAI API Key"
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defaultValue={
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settings?.AzureOpenAiKey ? "*".repeat(20) : ""
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}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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Embedding Deployment Name
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</label>
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<input
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type="text"
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name="AzureOpenAiEmbeddingModelPref"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="Azure OpenAI embedding model deployment name"
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defaultValue={
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settings?.AzureOpenAiEmbeddingModelPref
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}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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</>
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)}
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{embeddingChoice === "localai" && (
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<>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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LocalAI Base URL
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</label>
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<input
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type="url"
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name="EmbeddingBasePath"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="http://localhost:8080/v1"
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defaultValue={settings?.EmbeddingBasePath}
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onChange={(e) => setBasePathValue(e.target.value)}
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onBlur={updateBasePath}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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<LocalAIModelSelection
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settings={settings}
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basePath={basePath}
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<div className="w-full flex md:flex-wrap overflow-x-scroll gap-4 max-w-[900px]">
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<input
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hidden={true}
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name="EmbeddingEngine"
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value={embeddingChoice}
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/>
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<LLMProviderOption
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name="OpenAI"
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value="openai"
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link="openai.com"
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description="Use OpenAI's text-embedding-ada-002 embedding model."
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checked={embeddingChoice === "openai"}
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image={OpenAiLogo}
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onClick={updateChoice}
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/>
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<LLMProviderOption
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name="Azure OpenAI"
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value="azure"
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link="azure.microsoft.com"
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description="The enterprise option of OpenAI hosted on Azure services."
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checked={embeddingChoice === "azure"}
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image={AzureOpenAiLogo}
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onClick={updateChoice}
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/>
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<LLMProviderOption
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name="LocalAI"
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value="localai"
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link="localai.io"
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description="Self hosted LocalAI embedding engine."
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checked={embeddingChoice === "localai"}
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image={LocalAiLogo}
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onClick={updateChoice}
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/>
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</div>
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<div className="mt-10 flex flex-wrap gap-4 max-w-[800px]">
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{embeddingChoice === "openai" && (
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<>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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API Key
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</label>
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<input
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type="text"
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name="OpenAiKey"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="OpenAI API Key"
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defaultValue={
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settings?.OpenAiKey ? "*".repeat(20) : ""
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}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</>
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)}
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</div>
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</>
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)}
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</div>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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Model Preference
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</label>
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<select
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disabled={true}
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className="cursor-not-allowed bg-zinc-900 border border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
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>
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<option disabled={true} selected={true}>
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text-embedding-ada-002
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</option>
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</select>
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</div>
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</>
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)}
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{embeddingChoice === "azure" && (
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<>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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Azure Service Endpoint
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</label>
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<input
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type="url"
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name="AzureOpenAiEndpoint"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="https://my-azure.openai.azure.com"
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defaultValue={settings?.AzureOpenAiEndpoint}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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API Key
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</label>
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<input
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type="password"
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name="AzureOpenAiKey"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="Azure OpenAI API Key"
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defaultValue={
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settings?.AzureOpenAiKey ? "*".repeat(20) : ""
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}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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Embedding Deployment Name
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</label>
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<input
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type="text"
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name="AzureOpenAiEmbeddingModelPref"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="Azure OpenAI embedding model deployment name"
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defaultValue={settings?.AzureOpenAiEmbeddingModelPref}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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</>
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)}
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{embeddingChoice === "localai" && (
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<>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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LocalAI Base URL
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</label>
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<input
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type="url"
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name="EmbeddingBasePath"
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className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
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placeholder="http://localhost:8080/v1"
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defaultValue={settings?.EmbeddingBasePath}
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onChange={(e) => setBasePathValue(e.target.value)}
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onBlur={updateBasePath}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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<LocalAIModelSelection
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settings={settings}
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basePath={basePath}
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/>
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</>
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)}
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</div>
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</>
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</div>
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</form>
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</div>
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@ -97,16 +97,44 @@ const VECTOR_DB_PRIVACY = {
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},
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};
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const EMBEDDING_ENGINE_PRIVACY = {
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openai: {
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name: "OpenAI",
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description: [
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"Your documents are visible to OpenAI",
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"Your documents are not used for training",
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],
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logo: OpenAiLogo,
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},
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azure: {
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name: "Azure OpenAI",
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description: [
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"Your documents are not visible to OpenAI or Microsoft",
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"Your documents not used for training",
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],
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logo: AzureOpenAiLogo,
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},
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localai: {
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name: "LocalAI",
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description: [
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"Your documents are only accessible on the server running LocalAI",
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],
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logo: LocalAiLogo,
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},
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};
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function DataHandling({ nextStep, prevStep, currentStep }) {
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const [llmChoice, setLLMChoice] = useState("openai");
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const [loading, setLoading] = useState(true);
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const [vectorDb, setVectorDb] = useState("pinecone");
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const [embeddingEngine, setEmbeddingEngine] = useState("openai");
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useEffect(() => {
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async function fetchKeys() {
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const _settings = await System.keys();
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setLLMChoice(_settings?.LLMProvider);
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setVectorDb(_settings?.VectorDB);
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setEmbeddingEngine(_settings?.EmbeddingEngine);
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setLoading(false);
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}
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@ -124,8 +152,8 @@ function DataHandling({ nextStep, prevStep, currentStep }) {
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return (
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<div className="max-w-[750px]">
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<div className="p-8 flex gap-x-16">
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<div className="w-1/2 flex flex-col gap-y-3.5">
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<div className="p-8 flex flex-col gap-8">
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<div className="flex flex-col gap-y-3.5 border-b border-zinc-500/50 pb-8">
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<div className="text-white text-base font-bold">LLM Selection</div>
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<div className="flex items-center gap-2.5">
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<img
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@ -146,7 +174,28 @@ function DataHandling({ nextStep, prevStep, currentStep }) {
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</div>
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</div>
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<div className="w-1/2 flex flex-col gap-y-3.5">
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<div className="flex flex-col gap-y-3.5 border-b border-zinc-500/50 pb-8">
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<div className="text-white text-base font-bold">Embedding Engine</div>
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<div className="flex items-center gap-2.5">
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<img
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src={EMBEDDING_ENGINE_PRIVACY[embeddingEngine].logo}
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alt="Vector DB Logo"
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className="w-8 h-8 rounded"
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/>
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<p className="text-white text-sm font-bold">
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{EMBEDDING_ENGINE_PRIVACY[embeddingEngine].name}
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</p>
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</div>
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<ul className="flex flex-col list-disc">
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{EMBEDDING_ENGINE_PRIVACY[embeddingEngine].description.map(
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(desc) => (
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<li className="text-white/90 text-sm">{desc}</li>
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)
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)}
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</ul>
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</div>
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<div className="flex flex-col gap-y-3.5 ">
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<div className="text-white text-base font-bold">Vector Database</div>
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<div className="flex items-center gap-2.5">
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<img
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|
|
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@ -113,6 +113,19 @@ function EmbeddingSelection({ nextStep, prevStep, currentStep }) {
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spellCheck={false}
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/>
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</div>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-4">
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Model Preference
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</label>
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<select
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disabled={true}
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className="cursor-not-allowed bg-zinc-900 border border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
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>
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<option disabled={true} selected={true}>
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text-embedding-ada-002
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</option>
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</select>
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||||
</div>
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||||
</>
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)}
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|
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|||
|
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@ -46,15 +46,7 @@ function LLMSelection({ nextStep, prevStep, currentStep }) {
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alert(`Failed to save LLM settings: ${error}`, "error");
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return;
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}
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switch (data.LLMProvider) {
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case "anthropic":
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case "lmstudio":
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case "localai":
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return nextStep("embedding_preferences");
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default:
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return nextStep("vector_database");
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}
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nextStep("embedding_preferences");
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};
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if (loading)
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|
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@ -65,8 +65,7 @@ const STEPS = {
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},
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embedding_preferences: {
|
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title: "Embedding Preference",
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||||
description:
|
||||
"Due to your LLM selection you need to set up a provider for embedding files and text.",
|
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description: "Choose a provider for embedding files and text.",
|
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component: EmbeddingSelection,
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},
|
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};
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|
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|
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@ -1,9 +1,8 @@
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const { AzureOpenAiEmbedder } = require("../../EmbeddingEngines/azureOpenAi");
|
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const { chatPrompt } = require("../../chats");
|
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|
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class AzureOpenAiLLM extends AzureOpenAiEmbedder {
|
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constructor() {
|
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super();
|
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class AzureOpenAiLLM {
|
||||
constructor(embedder = null) {
|
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const { OpenAIClient, AzureKeyCredential } = require("@azure/openai");
|
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if (!process.env.AZURE_OPENAI_ENDPOINT)
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throw new Error("No Azure API endpoint was set.");
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||||
|
|
@ -20,6 +19,12 @@ class AzureOpenAiLLM extends AzureOpenAiEmbedder {
|
|||
system: this.promptWindowLimit() * 0.15,
|
||||
user: this.promptWindowLimit() * 0.7,
|
||||
};
|
||||
|
||||
if (!embedder)
|
||||
console.warn(
|
||||
"No embedding provider defined for AzureOpenAiLLM - falling back to AzureOpenAiEmbedder for embedding!"
|
||||
);
|
||||
this.embedder = !embedder ? new AzureOpenAiEmbedder() : embedder;
|
||||
}
|
||||
|
||||
streamingEnabled() {
|
||||
|
|
@ -114,6 +119,14 @@ Context:
|
|||
return data.choices[0].message.content;
|
||||
}
|
||||
|
||||
// Simple wrapper for dynamic embedder & normalize interface for all LLM implementations
|
||||
async embedTextInput(textInput) {
|
||||
return await this.embedder.embedTextInput(textInput);
|
||||
}
|
||||
async embedChunks(textChunks = []) {
|
||||
return await this.embedder.embedChunks(textChunks);
|
||||
}
|
||||
|
||||
async compressMessages(promptArgs = {}, rawHistory = []) {
|
||||
const { messageArrayCompressor } = require("../../helpers/chat");
|
||||
const messageArray = this.constructPrompt(promptArgs);
|
||||
|
|
|
|||
|
|
@ -1,9 +1,8 @@
|
|||
const { OpenAiEmbedder } = require("../../EmbeddingEngines/openAi");
|
||||
const { chatPrompt } = require("../../chats");
|
||||
|
||||
class OpenAiLLM extends OpenAiEmbedder {
|
||||
constructor() {
|
||||
super();
|
||||
class OpenAiLLM {
|
||||
constructor(embedder = null) {
|
||||
const { Configuration, OpenAIApi } = require("openai");
|
||||
if (!process.env.OPEN_AI_KEY) throw new Error("No OpenAI API key was set.");
|
||||
|
||||
|
|
@ -17,6 +16,12 @@ class OpenAiLLM extends OpenAiEmbedder {
|
|||
system: this.promptWindowLimit() * 0.15,
|
||||
user: this.promptWindowLimit() * 0.7,
|
||||
};
|
||||
|
||||
if (!embedder)
|
||||
console.warn(
|
||||
"No embedding provider defined for OpenAiLLM - falling back to OpenAiEmbedder for embedding!"
|
||||
);
|
||||
this.embedder = !embedder ? new OpenAiEmbedder() : embedder;
|
||||
}
|
||||
|
||||
streamingEnabled() {
|
||||
|
|
@ -203,6 +208,14 @@ Context:
|
|||
return streamRequest;
|
||||
}
|
||||
|
||||
// Simple wrapper for dynamic embedder & normalize interface for all LLM implementations
|
||||
async embedTextInput(textInput) {
|
||||
return await this.embedder.embedTextInput(textInput);
|
||||
}
|
||||
async embedChunks(textChunks = []) {
|
||||
return await this.embedder.embedChunks(textChunks);
|
||||
}
|
||||
|
||||
async compressMessages(promptArgs = {}, rawHistory = []) {
|
||||
const { messageArrayCompressor } = require("../../helpers/chat");
|
||||
const messageArray = this.constructPrompt(promptArgs);
|
||||
|
|
|
|||
|
|
@ -23,25 +23,22 @@ function getVectorDbClass() {
|
|||
|
||||
function getLLMProvider() {
|
||||
const vectorSelection = process.env.LLM_PROVIDER || "openai";
|
||||
let embedder = null;
|
||||
const embedder = getEmbeddingEngineSelection();
|
||||
switch (vectorSelection) {
|
||||
case "openai":
|
||||
const { OpenAiLLM } = require("../AiProviders/openAi");
|
||||
return new OpenAiLLM();
|
||||
return new OpenAiLLM(embedder);
|
||||
case "azure":
|
||||
const { AzureOpenAiLLM } = require("../AiProviders/azureOpenAi");
|
||||
return new AzureOpenAiLLM();
|
||||
return new AzureOpenAiLLM(embedder);
|
||||
case "anthropic":
|
||||
const { AnthropicLLM } = require("../AiProviders/anthropic");
|
||||
embedder = getEmbeddingEngineSelection();
|
||||
return new AnthropicLLM(embedder);
|
||||
case "lmstudio":
|
||||
const { LMStudioLLM } = require("../AiProviders/lmStudio");
|
||||
embedder = getEmbeddingEngineSelection();
|
||||
return new LMStudioLLM(embedder);
|
||||
case "localai":
|
||||
const { LocalAiLLM } = require("../AiProviders/localAi");
|
||||
embedder = getEmbeddingEngineSelection();
|
||||
return new LocalAiLLM(embedder);
|
||||
default:
|
||||
throw new Error("ENV: No LLM_PROVIDER value found in environment!");
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue