2749 ollama client auth token ()

* ollama auth token provision

* auth token provision

* ollama auth provision

* ollama auth token

* ollama auth provision

* token input field css fix

* Fix provider handler not using key
sensible fallback to not break existing installs
re-order of input fields
null-check for API key and header optional insert on request
linting

* apply header and auth to agent invocations

* upgrading to ollama 5.10 for passing headers to constructor

* rename Auth systemSetting key to be more descriptive
linting and copy

* remove untracked files + update gitignore

* remove debug

* patch lockfile

---------

Co-authored-by: timothycarambat <rambat1010@gmail.com>
This commit is contained in:
Sushanth Srivatsa 2025-02-19 05:30:17 +05:30 committed by GitHub
parent 3390ccf4b1
commit 3fd0fe8fc5
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
12 changed files with 212 additions and 129 deletions
docker
frontend/src
components/LLMSelection/OllamaLLMOptions
hooks
server
.env.example
models
package.json
storage/models
utils
AiProviders/ollama
agents/aibitat/providers
helpers
yarn.lock

View file

@ -42,6 +42,7 @@ GID='1000'
# OLLAMA_BASE_PATH='http://host.docker.internal:11434'
# OLLAMA_MODEL_PREF='llama2'
# OLLAMA_MODEL_TOKEN_LIMIT=4096
# OLLAMA_AUTH_TOKEN='your-ollama-auth-token-here (optional, only for ollama running behind auth - Bearer token)'
# LLM_PROVIDER='togetherai'
# TOGETHER_AI_API_KEY='my-together-ai-key'

View file

@ -11,12 +11,15 @@ export default function OllamaLLMOptions({ settings }) {
autoDetecting: loading,
basePath,
basePathValue,
authToken,
authTokenValue,
showAdvancedControls,
setShowAdvancedControls,
handleAutoDetectClick,
} = useProviderEndpointAutoDiscovery({
provider: "ollama",
initialBasePath: settings?.OllamaLLMBasePath,
initialAuthToken: settings?.OllamaLLMAuthToken,
ENDPOINTS: OLLAMA_COMMON_URLS,
});
const [performanceMode, setPerformanceMode] = useState(
@ -32,6 +35,7 @@ export default function OllamaLLMOptions({ settings }) {
<OllamaLLMModelSelection
settings={settings}
basePath={basePath.value}
authToken={authToken.value}
/>
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-2">
@ -73,120 +77,146 @@ export default function OllamaLLMOptions({ settings }) {
</div>
<div hidden={!showAdvancedControls}>
<div className="w-full flex items-start gap-4">
<div className="flex flex-col w-60">
<div className="flex justify-between items-center mb-2">
<label className="text-white text-sm font-semibold">
Ollama Base URL
</label>
{loading ? (
<PreLoader size="6" />
) : (
<>
{!basePathValue.value && (
<button
onClick={handleAutoDetectClick}
className="bg-primary-button text-xs font-medium px-2 py-1 rounded-lg hover:bg-secondary hover:text-white shadow-[0_4px_14px_rgba(0,0,0,0.25)]"
>
Auto-Detect
</button>
)}
</>
)}
</div>
<input
type="url"
name="OllamaLLMBasePath"
className="border-none bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="http://127.0.0.1:11434"
value={basePathValue.value}
required={true}
autoComplete="off"
spellCheck={false}
onChange={basePath.onChange}
onBlur={basePath.onBlur}
/>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Enter the URL where Ollama is running.
</p>
</div>
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-2">
Ollama Keep Alive
</label>
<select
name="OllamaLLMKeepAliveSeconds"
required={true}
className="border-none bg-theme-settings-input-bg border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
defaultValue={settings?.OllamaLLMKeepAliveSeconds ?? "300"}
>
<option value="0">No cache</option>
<option value="300">5 minutes</option>
<option value="3600">1 hour</option>
<option value="-1">Forever</option>
</select>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Choose how long Ollama should keep your model in memory before
unloading.
<a
className="underline text-blue-300"
href="https://github.com/ollama/ollama/blob/main/docs/faq.md#how-do-i-keep-a-model-loaded-in-memory-or-make-it-unload-immediately"
target="_blank"
rel="noreferrer"
>
{" "}
Learn more &rarr;
</a>
</p>
</div>
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold mb-2 flex items-center">
Performance Mode
<Info
size={16}
className="ml-2 text-white"
data-tooltip-id="performance-mode-tooltip"
<div className="flex flex-col">
<div className="w-full flex items-start gap-4">
<div className="flex flex-col w-60">
<div className="flex justify-between items-center mb-2">
<label className="text-white text-sm font-semibold">
Ollama Base URL
</label>
{loading ? (
<PreLoader size="6" />
) : (
<>
{!basePathValue.value && (
<button
onClick={handleAutoDetectClick}
className="bg-primary-button text-xs font-medium px-2 py-1 rounded-lg hover:bg-secondary hover:text-white shadow-[0_4px_14px_rgba(0,0,0,0.25)]"
>
Auto-Detect
</button>
)}
</>
)}
</div>
<input
type="url"
name="OllamaLLMBasePath"
className="border-none bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="http://127.0.0.1:11434"
value={basePathValue.value}
required={true}
autoComplete="off"
spellCheck={false}
onChange={basePath.onChange}
onBlur={basePath.onBlur}
/>
</label>
<select
name="OllamaLLMPerformanceMode"
required={true}
className="border-none bg-theme-settings-input-bg border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
value={performanceMode}
onChange={(e) => setPerformanceMode(e.target.value)}
>
<option value="base">Base (Default)</option>
<option value="maximum">Maximum</option>
</select>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Choose the performance mode for the Ollama model.
</p>
<Tooltip
id="performance-mode-tooltip"
place="bottom"
className="tooltip !text-xs max-w-xs"
>
<p className="text-red-500">
<strong>Note:</strong> Be careful with the Maximum mode. It may
increase resource usage significantly.
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Enter the URL where Ollama is running.
</p>
<br />
<p>
<strong>Base:</strong> Ollama automatically limits the context
to 2048 tokens, keeping resources usage low while maintaining
good performance. Suitable for most users and models.
</div>
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold mb-2 flex items-center">
Performance Mode
<Info
size={16}
className="ml-2 text-white"
data-tooltip-id="performance-mode-tooltip"
/>
</label>
<select
name="OllamaLLMPerformanceMode"
required={true}
className="border-none bg-theme-settings-input-bg border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
value={performanceMode}
onChange={(e) => setPerformanceMode(e.target.value)}
>
<option value="base">Base (Default)</option>
<option value="maximum">Maximum</option>
</select>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Choose the performance mode for the Ollama model.
</p>
<br />
<p>
<strong>Maximum:</strong> Uses the full context window (up to
Max Tokens). Will result in increased resource usage but allows
for larger context conversations. <br />
<Tooltip
id="performance-mode-tooltip"
place="bottom"
className="tooltip !text-xs max-w-xs"
>
<p className="text-red-500">
<strong>Note:</strong> Be careful with the Maximum mode. It
may increase resource usage significantly.
</p>
<br />
This is not recommended for most users.
<p>
<strong>Base:</strong> Ollama automatically limits the context
to 2048 tokens, keeping resources usage low while maintaining
good performance. Suitable for most users and models.
</p>
<br />
<p>
<strong>Maximum:</strong> Uses the full context window (up to
Max Tokens). Will result in increased resource usage but
allows for larger context conversations. <br />
<br />
This is not recommended for most users.
</p>
</Tooltip>
</div>
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-2">
Ollama Keep Alive
</label>
<select
name="OllamaLLMKeepAliveSeconds"
required={true}
className="border-none bg-theme-settings-input-bg border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
defaultValue={settings?.OllamaLLMKeepAliveSeconds ?? "300"}
>
<option value="0">No cache</option>
<option value="300">5 minutes</option>
<option value="3600">1 hour</option>
<option value="-1">Forever</option>
</select>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Choose how long Ollama should keep your model in memory before
unloading.
<a
className="underline text-blue-300"
href="https://github.com/ollama/ollama/blob/main/docs/faq.md#how-do-i-keep-a-model-loaded-in-memory-or-make-it-unload-immediately"
target="_blank"
rel="noreferrer"
>
{" "}
Learn more &rarr;
</a>
</p>
</Tooltip>
</div>
</div>
<div className="w-full flex items-start gap-4">
<div className="flex flex-col w-100">
<label className="text-white text-sm font-semibold">
Auth Token
</label>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Enter a <code>Bearer</code> Auth Token for interacting with your
Ollama server.
<br />
Used <b>only</b> if running Ollama behind an authentication
server.
</p>
<input
type="password"
name="OllamaLLMAuthToken"
className="border-none bg-theme-settings-input-bg mt-2 text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg outline-none block w-full p-2.5"
placeholder="Ollama Auth Token"
value={authTokenValue.value}
onChange={authToken.onChange}
onBlur={authToken.onBlur}
required={false}
autoComplete="off"
spellCheck={false}
/>
</div>
</div>
</div>
</div>
@ -194,7 +224,11 @@ export default function OllamaLLMOptions({ settings }) {
);
}
function OllamaLLMModelSelection({ settings, basePath = null }) {
function OllamaLLMModelSelection({
settings,
basePath = null,
authToken = null,
}) {
const [customModels, setCustomModels] = useState([]);
const [loading, setLoading] = useState(true);
@ -207,7 +241,11 @@ function OllamaLLMModelSelection({ settings, basePath = null }) {
}
setLoading(true);
try {
const { models } = await System.customModels("ollama", null, basePath);
const { models } = await System.customModels(
"ollama",
authToken,
basePath
);
setCustomModels(models || []);
} catch (error) {
console.error("Failed to fetch custom models:", error);
@ -216,7 +254,7 @@ function OllamaLLMModelSelection({ settings, basePath = null }) {
setLoading(false);
}
findCustomModels();
}, [basePath]);
}, [basePath, authToken]);
if (loading || customModels.length == 0) {
return (

View file

@ -5,11 +5,15 @@ import showToast from "@/utils/toast";
export default function useProviderEndpointAutoDiscovery({
provider = null,
initialBasePath = "",
initialAuthToken = null,
ENDPOINTS = [],
}) {
const [loading, setLoading] = useState(false);
const [basePath, setBasePath] = useState(initialBasePath);
const [basePathValue, setBasePathValue] = useState(initialBasePath);
const [authToken, setAuthToken] = useState(initialAuthToken);
const [authTokenValue, setAuthTokenValue] = useState(initialAuthToken);
const [autoDetectAttempted, setAutoDetectAttempted] = useState(false);
const [showAdvancedControls, setShowAdvancedControls] = useState(true);
@ -20,7 +24,7 @@ export default function useProviderEndpointAutoDiscovery({
ENDPOINTS.forEach((endpoint) => {
possibleEndpoints.push(
new Promise((resolve, reject) => {
System.customModels(provider, null, endpoint, 2_000)
System.customModels(provider, authTokenValue, endpoint, 2_000)
.then((results) => {
if (!results?.models || results.models.length === 0)
throw new Error("No models");
@ -74,9 +78,18 @@ export default function useProviderEndpointAutoDiscovery({
setBasePath(basePathValue);
}
function handleAuthTokenChange(e) {
const value = e.target.value;
setAuthTokenValue(value);
}
function handleAuthTokenBlur() {
setAuthToken(authTokenValue);
}
useEffect(() => {
if (!initialBasePath && !autoDetectAttempted) autoDetect(true);
}, [initialBasePath, autoDetectAttempted]);
}, [initialBasePath, initialAuthToken, autoDetectAttempted]);
return {
autoDetecting: loading,
@ -93,6 +106,16 @@ export default function useProviderEndpointAutoDiscovery({
value: basePathValue,
set: setBasePathValue,
},
authToken: {
value: authToken,
set: setAuthTokenValue,
onChange: handleAuthTokenChange,
onBlur: handleAuthTokenBlur,
},
authTokenValue: {
value: authTokenValue,
set: setAuthTokenValue,
},
handleAutoDetectClick,
runAutoDetect: autoDetect,
};

View file

@ -39,6 +39,7 @@ SIG_SALT='salt' # Please generate random string at least 32 chars long.
# OLLAMA_BASE_PATH='http://host.docker.internal:11434'
# OLLAMA_MODEL_PREF='llama2'
# OLLAMA_MODEL_TOKEN_LIMIT=4096
# OLLAMA_AUTH_TOKEN='your-ollama-auth-token-here (optional, only for ollama running behind auth - Bearer token)'
# LLM_PROVIDER='togetherai'
# TOGETHER_AI_API_KEY='my-together-ai-key'

View file

@ -471,6 +471,7 @@ const SystemSettings = {
OllamaLLMTokenLimit: process.env.OLLAMA_MODEL_TOKEN_LIMIT,
OllamaLLMKeepAliveSeconds: process.env.OLLAMA_KEEP_ALIVE_TIMEOUT ?? 300,
OllamaLLMPerformanceMode: process.env.OLLAMA_PERFORMANCE_MODE ?? "base",
OllamaLLMAuthToken: process.env.OLLAMA_AUTH_TOKEN ?? null,
// Novita LLM Keys
NovitaLLMApiKey: !!process.env.NOVITA_LLM_API_KEY,

View file

@ -63,7 +63,7 @@
"mssql": "^10.0.2",
"multer": "^1.4.5-lts.1",
"mysql2": "^3.9.8",
"ollama": "^0.5.0",
"ollama": "^0.5.10",
"openai": "4.38.5",
"pg": "^8.11.5",
"pinecone-client": "^1.1.0",
@ -97,4 +97,4 @@
"nodemon": "^2.0.22",
"prettier": "^3.0.3"
}
}
}

View file

@ -7,4 +7,5 @@ novita
mixedbread-ai*
gemini
togetherAi
tesseract
tesseract
ppio

View file

@ -15,6 +15,7 @@ class OllamaAILLM {
if (!process.env.OLLAMA_BASE_PATH)
throw new Error("No Ollama Base Path was set.");
this.authToken = process.env.OLLAMA_AUTH_TOKEN;
this.basePath = process.env.OLLAMA_BASE_PATH;
this.model = modelPreference || process.env.OLLAMA_MODEL_PREF;
this.performanceMode = process.env.OLLAMA_PERFORMANCE_MODE || "base";
@ -27,7 +28,10 @@ class OllamaAILLM {
user: this.promptWindowLimit() * 0.7,
};
this.client = new Ollama({ host: this.basePath });
const headers = this.authToken
? { Authorization: `Bearer ${this.authToken}` }
: {};
this.client = new Ollama({ host: this.basePath, headers: headers });
this.embedder = embedder ?? new NativeEmbedder();
this.defaultTemp = 0.7;
this.#log(
@ -273,9 +277,8 @@ class OllamaAILLM {
type: "textResponseChunk",
textResponse: "",
close: true,
error: `Ollama:streaming - could not stream chat. ${
error?.cause ?? error.message
}`,
error: `Ollama:streaming - could not stream chat. ${error?.cause ?? error.message
}`,
});
response.removeListener("close", handleAbort);
stream?.endMeasurement(usage);

View file

@ -16,7 +16,13 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
} = config;
super();
this._client = new Ollama({ host: process.env.OLLAMA_BASE_PATH });
const headers = process.env.OLLAMA_AUTH_TOKEN
? { Authorization: `Bearer ${process.env.OLLAMA_AUTH_TOKEN}` }
: {};
this._client = new Ollama({
host: process.env.OLLAMA_BASE_PATH,
headers: headers,
});
this.model = model;
this.verbose = true;
}

View file

@ -41,7 +41,7 @@ async function getCustomModels(provider = "", apiKey = null, basePath = null) {
case "localai":
return await localAIModels(basePath, apiKey);
case "ollama":
return await ollamaAIModels(basePath);
return await ollamaAIModels(basePath, apiKey);
case "togetherai":
return await getTogetherAiModels(apiKey);
case "fireworksai":
@ -292,7 +292,7 @@ async function getKoboldCPPModels(basePath = null) {
}
}
async function ollamaAIModels(basePath = null) {
async function ollamaAIModels(basePath = null, _authToken = null) {
let url;
try {
let urlPath = basePath ?? process.env.OLLAMA_BASE_PATH;
@ -304,7 +304,9 @@ async function ollamaAIModels(basePath = null) {
return { models: [], error: "Not a valid URL." };
}
const models = await fetch(`${url}/api/tags`)
const authToken = _authToken || process.env.OLLAMA_AUTH_TOKEN || null;
const headers = authToken ? { Authorization: `Bearer ${authToken}` } : {};
const models = await fetch(`${url}/api/tags`, { headers: headers })
.then((res) => {
if (!res.ok)
throw new Error(`Could not reach Ollama server! ${res.status}`);
@ -321,6 +323,9 @@ async function ollamaAIModels(basePath = null) {
return [];
});
// Api Key was successful so lets save it for future uses
if (models.length > 0 && !!authToken)
process.env.OLLAMA_AUTH_TOKEN = authToken;
return { models, error: null };
}

View file

@ -120,6 +120,10 @@ const KEY_MAPPING = {
envKey: "OLLAMA_KEEP_ALIVE_TIMEOUT",
checks: [isInteger],
},
OllamaLLMAuthToken: {
envKey: "OLLAMA_AUTH_TOKEN",
checks: [],
},
// Mistral AI API Settings
MistralApiKey: {

View file

@ -5198,10 +5198,10 @@ object.values@^1.1.6, object.values@^1.1.7:
define-properties "^1.2.1"
es-object-atoms "^1.0.0"
ollama@^0.5.0:
version "0.5.0"
resolved "https://registry.yarnpkg.com/ollama/-/ollama-0.5.0.tgz#cb9bc709d4d3278c9f484f751b0d9b98b06f4859"
integrity sha512-CRtRzsho210EGdK52GrUMohA2pU+7NbgEaBG3DcYeRmvQthDO7E2LHOkLlUUeaYUlNmEd8icbjC02ug9meSYnw==
ollama@^0.5.10:
version "0.5.12"
resolved "https://registry.yarnpkg.com/ollama/-/ollama-0.5.12.tgz#d8aadfaff076b2852cf826d928a03d9a40f308b9"
integrity sha512-flVH1fn1c9NF7VV3bW9kSu0E+bYc40b4DxL/gS2Debhao35osJFRDiPOj9sIWTMvcyj78Paw1OuhfIe7uhDWfQ==
dependencies:
whatwg-fetch "^3.6.20"