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Merge branch 'master' of github.com:Mintplex-Labs/anything-llm

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This commit is contained in:
Timothy Carambat
2026-04-08 14:17:49 -07:00
parent 4af0257263 b2404801d1
commit 82ef164314
8 changed files with 105 additions and 59 deletions
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64
server/utils/AiProviders/lemonade/index.js
View File

@@ -22,7 +22,7 @@ class LemonadeLLM {
process.env.LEMONADE_LLM_BASE_PATH,
"openai"
),
apiKey: process.env.LEMONADE_LLM_API_KEY ?? null,
apiKey: process.env.LEMONADE_LLM_API_KEY || null,
});
this.model = modelPreference || process.env.LEMONADE_LLM_MODEL_PREF;
@@ -202,7 +202,7 @@ class LemonadeLLM {
process.env.LEMONADE_LLM_BASE_PATH,
"openai"
),
apiKey: process.env.LEMONADE_LLM_API_KEY ?? null,
apiKey: process.env.LEMONADE_LLM_API_KEY || null,
});
const { labels = [] } = await client.models.retrieve(this.model);
@@ -223,6 +223,41 @@ class LemonadeLLM {
}
}
/**
* Get the currently loaded models from the Lemonade server.
* @returns {Promise<string[]>}
*/
static async getCurrentlyLoadedModels() {
const endpoint = new URL(
parseLemonadeServerEndpoint(process.env.LEMONADE_LLM_BASE_PATH, "openai")
);
endpoint.pathname += "/health";
const loadedModels = await fetch(endpoint.toString(), {
method: "GET",
headers: {
...(process.env.LEMONADE_LLM_API_KEY
? { Authorization: `Bearer ${process.env.LEMONADE_LLM_API_KEY}` }
: {}),
},
})
.then((response) => {
if (!response.ok)
throw new Error(
`Failed to get currently loaded models: ${response.statusText}`
);
return response.json();
})
.then(({ all_models_loaded = [] } = {}) => {
return all_models_loaded.map((model) => {
return {
model_name: model.model_name,
ctx_size: model?.recipe_options?.ctx_size ?? 8192,
};
});
});
return loadedModels;
}
/**
* Utility function to load a model from the Lemonade server.
* Does not check if the model is already loaded or unloads any models.
@@ -230,12 +265,33 @@ class LemonadeLLM {
*/
static async loadModel(model, basePath = process.env.LEMONADE_LLM_BASE_PATH) {
try {
const desiredCtxSize = Number(this.promptWindowLimit());
const currentlyLoadedModels =
await LemonadeLLM.getCurrentlyLoadedModels();
const modelAlreadyLoaded = currentlyLoadedModels.find(
(m) => m.model_name === model
);
if (modelAlreadyLoaded) {
if (modelAlreadyLoaded.ctx_size === desiredCtxSize) {
LemonadeLLM.slog(
`Model ${model} already loaded with ctx size ${desiredCtxSize}`
);
return true;
}
LemonadeLLM.slog(
`Model ${model} needs to be reloaded again with ctx size ${desiredCtxSize}`
);
}
const endpoint = new URL(parseLemonadeServerEndpoint(basePath, "openai"));
endpoint.pathname += "/load";
LemonadeLLM.slog(
`Loading model ${model} with context size ${this.promptWindowLimit()}`
`Loading model ${model} with context size ${desiredCtxSize}`
);
await fetch(endpoint.toString(), {
method: "POST",
headers: {
@@ -246,7 +302,7 @@ class LemonadeLLM {
},
body: JSON.stringify({
model_name: String(model),
ctx_size: Number(this.promptWindowLimit()),
ctx_size: desiredCtxSize,
}),
})
.then((response) => {

2
server/utils/EmbeddingEngines/lemonade/index.js
View File

@@ -14,7 +14,7 @@ class LemonadeEmbedder {
process.env.EMBEDDING_BASE_PATH,
"openai"
),
apiKey: process.env.LEMONADE_LLM_API_KEY ?? null,
apiKey: process.env.LEMONADE_LLM_API_KEY || null,
});
this.model = process.env.EMBEDDING_MODEL_PREF;

16
server/utils/agentFlows/executors/llm-instruction.js
View File

@@ -23,13 +23,17 @@ async function executeLLMInstruction(config, context) {
if (typeof input === "object") input = JSON.stringify(input);
if (typeof input !== "string") input = String(input);
let completion;
const provider = aibitat.getProviderForConfig(aibitat.defaultProvider);
const completion = await provider.complete([
{
role: "user",
content: input,
},
]);
if (provider.supportsAgentStreaming) {
completion = await provider.stream(
[{ role: "user", content: input }],
[],
null
);
} else {
completion = await provider.complete([{ role: "user", content: input }]);
}
introspect(`Successfully received LLM response`);
if (resultVariable) config.resultVariable = resultVariable;

68
server/utils/agents/aibitat/index.js
View File

@@ -843,25 +843,18 @@ https://docs.anythingllm.com/agent/intelligent-tool-selection
);
if (completionStream.functionCall) {
if (depth >= this.maxToolCalls) {
this.handlerProps?.log?.(
`[warning]: Maximum tool call limit (${this.maxToolCalls}) reached. Making final response without tools.`
);
this?.introspect?.(
`Maximum tool call limit (${this.maxToolCalls}) reached. Generating a final response from what I have so far.`
);
const finalStream = await this.#safeProviderCall(() =>
provider.stream(messages, [], eventHandler)
);
const finalResponse =
finalStream?.textResponse ||
"I reached the maximum number of tool calls allowed for a single response. Here is what I have so far based on the tools I was able to run.";
return finalResponse;
}
const { name, arguments: args } = completionStream.functionCall;
const fn = this.functions.get(name);
const reachedToolLimit = depth >= this.maxToolCalls;
if (reachedToolLimit) {
this.handlerProps?.log?.(
`[warning]: Maximum tool call limit (${this.maxToolCalls}) reached. Executing final tool call then generating response.`
);
this?.introspect?.(
`Maximum tool call limit (${this.maxToolCalls}) reached. After this tool I will generate a final response.`
);
}
if (!fn) {
return await this.handleAsyncExecution(
@@ -875,7 +868,7 @@ https://docs.anythingllm.com/agent/intelligent-tool-selection
originalFunctionCall: completionStream.functionCall,
},
],
functions,
reachedToolLimit ? [] : functions,
byAgent,
depth + 1
);
@@ -951,7 +944,7 @@ https://docs.anythingllm.com/agent/intelligent-tool-selection
return await this.handleAsyncExecution(
provider,
newMessages,
functions,
reachedToolLimit ? [] : functions,
byAgent,
depth + 1
);
@@ -1000,31 +993,18 @@ https://docs.anythingllm.com/agent/intelligent-tool-selection
);
if (completion.functionCall) {
if (depth >= this.maxToolCalls) {
this.handlerProps?.log?.(
`[warning]: Maximum tool call limit (${this.maxToolCalls}) reached. Making final response without tools.`
);
this?.introspect?.(
`Maximum tool call limit (${this.maxToolCalls}) reached. Generating a final response from what I have so far.`
);
const finalCompletion = await this.#safeProviderCall(() =>
provider.complete(messages, [])
);
eventHandler?.("reportStreamEvent", {
type: "usageMetrics",
uuid: msgUUID,
metrics: provider.getUsage(),
});
this?.flushCitations?.(msgUUID);
return (
finalCompletion?.textResponse ||
"I reached the maximum number of tool calls allowed for a single response. Here is what I have so far based on the tools I was able to run."
);
}
const { name, arguments: args } = completion.functionCall;
const fn = this.functions.get(name);
const reachedToolLimit = depth >= this.maxToolCalls;
if (reachedToolLimit) {
this.handlerProps?.log?.(
`[warning]: Maximum tool call limit (${this.maxToolCalls}) reached. Executing final tool call then generating response.`
);
this?.introspect?.(
`Maximum tool call limit (${this.maxToolCalls}) reached. After this tool I will generate a final response.`
);
}
if (!fn) {
return await this.handleExecution(
@@ -1038,7 +1018,7 @@ https://docs.anythingllm.com/agent/intelligent-tool-selection
originalFunctionCall: completion.functionCall,
},
],
functions,
reachedToolLimit ? [] : functions,
byAgent,
depth + 1,
msgUUID
@@ -1103,7 +1083,7 @@ https://docs.anythingllm.com/agent/intelligent-tool-selection
return await this.handleExecution(
provider,
newMessages,
functions,
reachedToolLimit ? [] : functions,
byAgent,
depth + 1,
msgUUID

2
server/utils/agents/aibitat/providers/ai-provider.js
View File

@@ -402,7 +402,7 @@ class Provider {
configuration: {
baseURL: process.env.LEMONADE_LLM_BASE_PATH,
},
apiKey: process.env.LEMONADE_LLM_API_KEY ?? null,
apiKey: process.env.LEMONADE_LLM_API_KEY || null,
...config,
});
default:

2
server/utils/agents/aibitat/providers/lemonade.js
View File

@@ -27,7 +27,7 @@ class LemonadeProvider extends InheritMultiple([Provider, UnTooled]) {
process.env.LEMONADE_LLM_BASE_PATH,
"openai"
),
apiKey: process.env.LEMONADE_LLM_API_KEY ?? null,
apiKey: process.env.LEMONADE_LLM_API_KEY || null,
maxRetries: 3,
});