Native Tool calling (#5071)
* checkpoint * test MCP and flows * add native tool call detection back to LMStudio * add native tool call loops for Ollama * Add ablity detection to DMR (regex parse) * bedrock and generic openai with ENV flag * deepseek native tool calling * localAI native function * groq support * linting, add litellm and OR native tool calling via flag
This commit is contained in:
Timothy Carambat
GitHub
parent
55dc0da488
commit
ac0b1d401d
@ -421,3 +421,8 @@ GID='1000'
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# this can lead to infinite recursive calls of the same function
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# for some model/provider combinations
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# MCP_NO_COOLDOWN="true
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# Allow native tool calling for specific providers.
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# This can VASTLY improve performance and speed of agent calls.
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# Check code for supported providers who can be enabled here via this flag
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# PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING="generic-openai,bedrock,localai,groq,litellm,openrouter"
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@ -424,3 +424,8 @@ TTS_PROVIDER="native"
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# this can lead to infinite recursive calls of the same function
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# for some model/provider combinations
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# MCP_NO_COOLDOWN="true
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# Allow native tool calling for specific providers.
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# This can VASTLY improve performance and speed of agent calls.
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# Check code for supported providers who can be enabled here via this flag
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# PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING="generic-openai,bedrock,localai,groq,litellm,openrouter"
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@ -205,6 +205,47 @@ class DockerModelRunnerLLM {
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return handleDefaultStreamResponseV2(response, stream, responseProps);
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}
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/**
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* Returns the capabilities of the model.
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* Note: This is a heuristic approach to get the capabilities of the model based on the model metadata.
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* It is not perfect, but works since every model metadata is different and may not have key values we rely on.
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* There is no "capabilities" key in the metadata via any API endpoint - so we do this.
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* @returns {Promise<{tools: 'unknown' | boolean, reasoning: 'unknown' | boolean, imageGeneration: 'unknown' | boolean, vision: 'unknown' | boolean}>}
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*/
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async getModelCapabilities() {
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try {
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const endpoint = new URL(
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parseDockerModelRunnerEndpoint(
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process.env.DOCKER_MODEL_RUNNER_BASE_PATH,
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"dmr"
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)
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);
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// eg: /models/ai/qwen3:4B-UD-Q4_K_XL
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endpoint.pathname = `/models/${this.model}`;
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const response = await fetch(endpoint.toString());
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const data = await response.text();
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const tools = /tools|tool|tool_use|tool_call/.test(data);
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const reasoning = /thinking|reason|reasoning|think/.test(data);
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const imageGeneration = /diffusion/.test(data);
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const vision = /vision|vllm|image/.test(data);
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return {
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tools: tools,
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reasoning: reasoning,
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imageGeneration: imageGeneration,
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vision: vision,
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};
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} catch (error) {
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console.error("Error getting model capabilities:", error);
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return {
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tools: "unknown",
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reasoning: "unknown",
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imageGeneration: "unknown",
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vision: "unknown",
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};
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}
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}
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// Simple wrapper for dynamic embedder & normalize interface for all LLM implementations
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async embedTextInput(textInput) {
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return await this.embedder.embedTextInput(textInput);
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@ -232,6 +273,7 @@ function parseDockerModelRunnerEndpoint(basePath = null, to = "openai") {
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try {
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const url = new URL(basePath);
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if (to === "openai") url.pathname = "engines/v1";
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else if (to === "ollama") url.pathname = "api";
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else if (to === "dmr") url.pathname = "";
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return url.toString();
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} catch (e) {
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@ -272,6 +272,60 @@ class LMStudioLLM {
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return handleDefaultStreamResponseV2(response, stream, responseProps);
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}
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/**
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* Returns the capabilities of the model.
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* This uses the new /api/v1 endpoint, which returns the model info in a different format.
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* @returns {Promise<{tools: 'unknown' | boolean, reasoning: 'unknown' | boolean, imageGeneration: 'unknown' | boolean, vision: 'unknown' | boolean}>}
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*/
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async getModelCapabilities() {
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try {
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const endpoint = new URL(
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parseLMStudioBasePath(process.env.LMSTUDIO_BASE_PATH, "v1")
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);
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const apiKey = process.env.LMSTUDIO_AUTH_TOKEN ?? null;
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endpoint.pathname += "/models";
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const modelInfo =
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(await fetch(endpoint.toString(), {
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headers: {
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"Content-Type": "application/json",
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...(apiKey ? { Authorization: `Bearer ${apiKey}` } : {}),
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},
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})
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.then((res) => {
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if (!res.ok)
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throw new Error(
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`LMStudio:getModelCapabilities - ${res.statusText}`
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);
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return res.json();
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})
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.then(({ models = [] }) =>
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models.find((model) => model.key === this.model)
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)) || {};
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const capabilities = modelInfo.hasOwnProperty("capabilities")
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? modelInfo.capabilities
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: {
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trained_for_tool_use: "unknown",
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vision: "unknown",
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};
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return {
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tools: capabilities.trained_for_tool_use,
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reasoning: "unknown",
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imageGeneration: "unknown", // LM Studio does not support image generation yet.
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vision: capabilities.vision,
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};
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} catch (error) {
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console.error("Error getting model capabilities:", error);
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return {
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tools: "unknown",
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reasoning: "unknown",
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imageGeneration: "unknown",
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vision: "unknown",
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};
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}
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}
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// Simple wrapper for dynamic embedder & normalize interface for all LLM implementations
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async embedTextInput(textInput) {
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return await this.embedder.embedTextInput(textInput);
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@ -292,12 +346,15 @@ class LMStudioLLM {
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* Parse the base path for the LMStudio API. Since the base path must end in /v1 and cannot have a trailing slash,
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* and the user can possibly set it to anything and likely incorrectly due to pasting behaviors, we need to ensure it is in the correct format.
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* @param {string} basePath
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* @param {'legacy' | 'v1'} apiVersion
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* @returns {string}
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*/
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function parseLMStudioBasePath(providedBasePath = "") {
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function parseLMStudioBasePath(providedBasePath = "", apiVersion = "legacy") {
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try {
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const baseURL = new URL(providedBasePath);
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const basePath = `${baseURL.origin}/v1`;
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let basePath = `${baseURL.origin}`;
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if (apiVersion === "legacy") basePath += `/v1`;
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if (apiVersion === "v1") basePath += `/api/v1`;
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return basePath;
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} catch (e) {
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return providedBasePath;
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@ -468,6 +468,32 @@ class OllamaAILLM {
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});
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}
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/**
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* Returns the capabilities of the model.
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* @returns {Promise<{tools: 'unknown' | boolean, reasoning: 'unknown' | boolean, imageGeneration: 'unknown' | boolean, vision: 'unknown' | boolean}>}
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*/
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async getModelCapabilities() {
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try {
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const { capabilities = [] } = await this.client.show({
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model: this.model,
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});
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return {
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tools: capabilities.includes("tools") ? true : false,
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reasoning: capabilities.includes("thinking") ? true : false,
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imageGeneration: false, // we dont have any image generation capabilities for Ollama or anywhere right now.
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vision: capabilities.includes("vision") ? true : false,
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};
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} catch (error) {
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console.error("Error getting model capabilities:", error);
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return {
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tools: "unknown",
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reasoning: "unknown",
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imageGeneration: "unknown",
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vision: "unknown",
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};
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}
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}
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// Simple wrapper for dynamic embedder & normalize interface for all LLM implementations
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async embedTextInput(textInput) {
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return await this.embedder.embedTextInput(textInput);
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@ -185,6 +185,24 @@ class AgentFlows {
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.map(([uuid]) => `@@flow_${uuid}`);
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}
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/**
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* Sanitize a flow name into a valid OpenAI-compatible tool name.
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* Must match ^[a-zA-Z0-9_-]{1,64}$
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* @param {string} flowName - The human-readable flow name
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* @returns {string|null} Sanitized tool name, or null if empty after sanitization
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*/
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static sanitizeToolName(flowName) {
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const sanitized = flowName
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.toLowerCase()
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.trim()
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.replace(/\s+/g, "_")
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.replace(/[^a-z0-9_-]/g, "")
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.replace(/_+/g, "_")
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.replace(/^[-_]+|[-_]+$/g, "");
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if (!sanitized) return null;
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return sanitized.slice(0, 64);
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}
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/**
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* Load a flow plugin by its UUID
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* @param {string} uuid - The UUID of the flow to load
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@ -196,17 +214,18 @@ class AgentFlows {
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const startBlock = flow.config.steps?.find((s) => s.type === "start");
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const variables = startBlock?.config?.variables || [];
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const toolName = AgentFlows.sanitizeToolName(flow.name) || `flow_${uuid}`;
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return {
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name: `flow_${uuid}`,
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name: toolName,
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description: `Execute agent flow: ${flow.name}`,
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plugin: (_runtimeArgs = {}) => ({
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name: `flow_${uuid}`,
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name: toolName,
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description:
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flow.config.description || `Execute agent flow: ${flow.name}`,
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setup: (aibitat) => {
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aibitat.function({
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name: `flow_${uuid}`,
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name: toolName,
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description:
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flow.config.description || `Execute agent flow: ${flow.name}`,
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parameters: {
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@ -41,6 +41,7 @@ class AIbitat {
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chats = [],
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interrupt = "NEVER",
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maxRounds = 100,
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maxToolCalls = 10,
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provider = "openai",
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handlerProps = {}, // Inherited props we can spread so aibitat can access.
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...rest
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@ -48,6 +49,7 @@ class AIbitat {
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this._chats = chats;
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this.defaultInterrupt = interrupt;
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this.maxRounds = maxRounds;
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this.maxToolCalls = maxToolCalls;
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this.handlerProps = handlerProps;
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this.defaultProvider = {
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@ -641,7 +643,8 @@ ${this.getHistory({ to: route.to })
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provider,
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messages = [],
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functions = [],
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byAgent = null
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byAgent = null,
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depth = 0
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) {
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const eventHandler = (type, data) => {
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this?.socket?.send(type, data);
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@ -655,6 +658,24 @@ ${this.getHistory({ to: route.to })
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);
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if (completionStream.functionCall) {
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if (depth >= this.maxToolCalls) {
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this.handlerProps?.log?.(
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`[warning]: Maximum tool call limit (${this.maxToolCalls}) reached. Stopping tool execution.`
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);
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this?.introspect?.(
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`Maximum tool call limit (${this.maxToolCalls}) reached. Returning what I have so far.`
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);
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const bailoutMessage =
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completionStream.textResponse ||
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"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.";
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eventHandler?.("reportStreamEvent", {
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type: "fullTextResponse",
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uuid: v4(),
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content: bailoutMessage,
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});
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return bailoutMessage;
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}
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const { name, arguments: args } = completionStream.functionCall;
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const fn = this.functions.get(name);
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@ -673,7 +694,8 @@ ${this.getHistory({ to: route.to })
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},
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],
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functions,
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byAgent
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byAgent,
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depth + 1
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);
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}
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@ -730,7 +752,8 @@ ${this.getHistory({ to: route.to })
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},
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],
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functions,
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byAgent
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byAgent,
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depth + 1
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);
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}
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@ -752,12 +775,26 @@ ${this.getHistory({ to: route.to })
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provider,
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messages = [],
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functions = [],
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byAgent = null
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byAgent = null,
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depth = 0
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) {
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// get the chat completion
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const completion = await provider.complete(messages, functions);
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if (completion.functionCall) {
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if (depth >= this.maxToolCalls) {
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this.handlerProps?.log?.(
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`[warning]: Maximum tool call limit (${this.maxToolCalls}) reached. Stopping tool execution.`
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);
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this?.introspect?.(
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`Maximum tool call limit (${this.maxToolCalls}) reached. Returning what I have so far.`
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);
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return (
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completion.textResponse ||
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"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."
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);
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}
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const { name, arguments: args } = completion.functionCall;
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const fn = this.functions.get(name);
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@ -776,7 +813,8 @@ ${this.getHistory({ to: route.to })
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},
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],
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functions,
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byAgent
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byAgent,
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depth + 1
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);
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}
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@ -824,7 +862,8 @@ ${this.getHistory({ to: route.to })
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},
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],
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functions,
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byAgent
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byAgent,
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depth + 1
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);
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}
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@ -31,6 +31,15 @@ class ApiPieProvider extends InheritMultiple([Provider, UnTooled]) {
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return true;
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}
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/**
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* Whether this provider supports native OpenAI-compatible tool calling.
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* Override in subclass and return true to use native tool calling instead of UnTooled.
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* @returns {boolean|Promise<boolean>}
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*/
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supportsNativeToolCalling() {
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return false;
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}
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async #handleFunctionCallChat({ messages = [] }) {
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return await this.client.chat.completions
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.create({
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@ -1,14 +1,12 @@
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const { OpenAI } = require("openai");
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const { AzureOpenAiLLM } = require("../../../AiProviders/azureOpenAi");
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const Provider = require("./ai-provider.js");
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const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
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const { RetryError } = require("../error.js");
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const { v4 } = require("uuid");
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const { safeJsonParse } = require("../../../http");
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/**
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* The agent provider for the Azure OpenAI API.
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* Uses the tool calling format (not legacy function calling) for compatibility
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* with newer Azure OpenAI models.
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* Uses the shared native tool calling helper for OpenAI-compatible tool calling.
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*/
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class AzureOpenAiProvider extends Provider {
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model;
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@ -28,199 +26,27 @@ class AzureOpenAiProvider extends Provider {
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}
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/**
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* Convert legacy function definitions to the tools format.
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* @param {Array} functions - Legacy function definitions
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* @returns {Array} Tools in the new format
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*/
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#formatFunctionsToTools(functions) {
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if (!Array.isArray(functions) || functions.length === 0) return [];
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return functions.map((func) => ({
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type: "function",
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function: {
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name: func.name,
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description: func.description,
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parameters: func.parameters,
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},
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}));
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}
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/**
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* Format messages to use tool calling format instead of legacy function format.
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* Converts role: "function" messages to role: "tool" messages.
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* @param {Array} messages - Messages array that may contain legacy function messages
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* @returns {Array} Messages formatted for tool calling
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*/
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#formatMessagesForTools(messages) {
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const formattedMessages = [];
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for (const message of messages) {
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if (message.role === "function") {
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// Convert legacy function result to tool result format
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// We need the tool_call_id from the originalFunctionCall
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if (message.originalFunctionCall?.id) {
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// First, add the assistant message with the tool_call if not already present
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// Check if previous message already has this tool call
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const prevMsg = formattedMessages[formattedMessages.length - 1];
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if (!prevMsg || prevMsg.role !== "assistant" || !prevMsg.tool_calls) {
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formattedMessages.push({
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role: "assistant",
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content: null,
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tool_calls: [
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{
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id: message.originalFunctionCall.id,
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type: "function",
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function: {
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name: message.originalFunctionCall.name,
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arguments:
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typeof message.originalFunctionCall.arguments === "string"
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? message.originalFunctionCall.arguments
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: JSON.stringify(
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message.originalFunctionCall.arguments
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),
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},
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},
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],
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});
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}
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// Add the tool result
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formattedMessages.push({
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role: "tool",
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tool_call_id: message.originalFunctionCall.id,
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content:
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typeof message.content === "string"
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? message.content
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: JSON.stringify(message.content),
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});
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} else {
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// Fallback: generate a tool_call_id if not present
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const toolCallId = `call_${v4()}`;
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formattedMessages.push({
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role: "assistant",
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content: null,
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tool_calls: [
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{
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id: toolCallId,
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type: "function",
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||||
function: {
|
||||
name: message.name,
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arguments: "{}",
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},
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},
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],
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});
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formattedMessages.push({
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role: "tool",
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tool_call_id: toolCallId,
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content:
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typeof message.content === "string"
|
||||
? message.content
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||||
: JSON.stringify(message.content),
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||||
});
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}
|
||||
} else {
|
||||
formattedMessages.push(message);
|
||||
}
|
||||
}
|
||||
|
||||
return formattedMessages;
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion from the LLM with tool calling.
|
||||
* Uses the tool calling format instead of legacy function calling.
|
||||
* Stream a chat completion from Azure OpenAI with tool calling.
|
||||
*
|
||||
* @param {any[]} messages - The messages to send to the LLM.
|
||||
* @param {any[]} functions - The functions to use in the LLM.
|
||||
* @param {function} eventHandler - The event handler to use to report stream events.
|
||||
* @returns {Promise<{ functionCall: any, textResponse: string }>} - The result of the chat completion.
|
||||
* @param {any[]} messages
|
||||
* @param {any[]} functions
|
||||
* @param {function} eventHandler
|
||||
* @returns {Promise<{ functionCall: any, textResponse: string }>}
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
this.providerLog("Provider.stream - will process this chat completion.");
|
||||
const msgUUID = v4();
|
||||
|
||||
try {
|
||||
const formattedMessages = this.#formatMessagesForTools(messages);
|
||||
const tools = this.#formatFunctionsToTools(functions);
|
||||
|
||||
const stream = await this.client.chat.completions.create({
|
||||
model: this.model,
|
||||
stream: true,
|
||||
messages: formattedMessages,
|
||||
...(tools.length > 0 ? { tools } : {}),
|
||||
});
|
||||
|
||||
const result = {
|
||||
functionCall: null,
|
||||
textResponse: "",
|
||||
};
|
||||
|
||||
// For accumulating tool calls during streaming
|
||||
let currentToolCall = null;
|
||||
|
||||
for await (const chunk of stream) {
|
||||
if (!chunk?.choices?.[0]) continue;
|
||||
const choice = chunk.choices[0];
|
||||
|
||||
if (choice.delta?.content) {
|
||||
result.textResponse += choice.delta.content;
|
||||
eventHandler?.("reportStreamEvent", {
|
||||
type: "textResponseChunk",
|
||||
uuid: msgUUID,
|
||||
content: choice.delta.content,
|
||||
});
|
||||
}
|
||||
|
||||
// Handle tool calls (new format)
|
||||
if (choice.delta?.tool_calls) {
|
||||
for (const toolCall of choice.delta.tool_calls) {
|
||||
if (toolCall.id) {
|
||||
// New tool call starting
|
||||
currentToolCall = {
|
||||
id: toolCall.id,
|
||||
name: toolCall.function?.name || "",
|
||||
arguments: toolCall.function?.arguments || "",
|
||||
};
|
||||
} else if (currentToolCall) {
|
||||
// Continuation of existing tool call
|
||||
if (toolCall.function?.name) {
|
||||
currentToolCall.name += toolCall.function.name;
|
||||
}
|
||||
if (toolCall.function?.arguments) {
|
||||
currentToolCall.arguments += toolCall.function.arguments;
|
||||
}
|
||||
}
|
||||
|
||||
if (currentToolCall) {
|
||||
eventHandler?.("reportStreamEvent", {
|
||||
uuid: `${msgUUID}:tool_call_invocation`,
|
||||
type: "toolCallInvocation",
|
||||
content: `Assembling Tool Call: ${currentToolCall.name}(${currentToolCall.arguments})`,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Set the function call result if we have a tool call
|
||||
if (currentToolCall) {
|
||||
result.functionCall = {
|
||||
id: currentToolCall.id,
|
||||
name: currentToolCall.name,
|
||||
arguments: safeJsonParse(currentToolCall.arguments, {}),
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
textResponse: result.textResponse,
|
||||
functionCall: result.functionCall,
|
||||
};
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
|
||||
// If invalid Auth error we need to abort because no amount of waiting
|
||||
// will make auth better.
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
@ -228,91 +54,41 @@ class AzureOpenAiProvider extends Provider {
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a completion based on the received messages.
|
||||
* Uses the tool calling format instead of legacy function calling.
|
||||
* Create a completion based on the received messages with tool calling.
|
||||
*
|
||||
* @param messages A list of messages to send to the OpenAI API.
|
||||
* @param functions
|
||||
* @param {any[]} messages
|
||||
* @param {any[]} functions
|
||||
* @returns The completion.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
try {
|
||||
const formattedMessages = this.#formatMessagesForTools(messages);
|
||||
const tools = this.#formatFunctionsToTools(functions);
|
||||
|
||||
const response = await this.client.chat.completions.create({
|
||||
model: this.model,
|
||||
stream: false,
|
||||
messages: formattedMessages,
|
||||
...(tools.length > 0 ? { tools } : {}),
|
||||
});
|
||||
|
||||
// Right now, we only support one completion,
|
||||
// so we just take the first one in the list
|
||||
const completion = response.choices[0].message;
|
||||
const cost = this.getCost(response.usage);
|
||||
|
||||
// Handle tool calls (new format)
|
||||
if (completion.tool_calls && completion.tool_calls.length > 0) {
|
||||
const toolCall = completion.tool_calls[0];
|
||||
let functionArgs = {};
|
||||
try {
|
||||
functionArgs = JSON.parse(toolCall.function.arguments);
|
||||
} catch (error) {
|
||||
// Call the complete function again in case of JSON error
|
||||
const toolCallId = toolCall.id;
|
||||
return this.complete(
|
||||
[
|
||||
...messages,
|
||||
{
|
||||
role: "function",
|
||||
name: toolCall.function.name,
|
||||
content: error?.message,
|
||||
originalFunctionCall: {
|
||||
id: toolCallId,
|
||||
name: toolCall.function.name,
|
||||
arguments: toolCall.function.arguments,
|
||||
},
|
||||
},
|
||||
],
|
||||
functions
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this)
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return {
|
||||
textResponse: null,
|
||||
functionCall: {
|
||||
id: toolCall.id,
|
||||
name: toolCall.function.name,
|
||||
arguments: functionArgs,
|
||||
},
|
||||
cost,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
textResponse: completion.content,
|
||||
cost,
|
||||
};
|
||||
return result;
|
||||
} catch (error) {
|
||||
// If invalid Auth error we need to abort because no amount of waiting
|
||||
// will make auth better.
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError // Also will catch AuthenticationError!!!
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
@ -7,10 +7,13 @@ const { AWSBedrockLLM } = require("../../../AiProviders/bedrock/index.js");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { safeJsonParse } = require("../../../http");
|
||||
const { v4 } = require("uuid");
|
||||
const {
|
||||
HumanMessage,
|
||||
SystemMessage,
|
||||
AIMessage,
|
||||
ToolMessage,
|
||||
} = require("@langchain/core/messages");
|
||||
|
||||
/**
|
||||
@ -32,6 +35,7 @@ class AWSBedrockProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
this._client = client;
|
||||
this.model = model;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
}
|
||||
|
||||
/**
|
||||
@ -45,6 +49,27 @@ class AWSBedrockProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native tool calling via the Bedrock Converse API.
|
||||
* Checks the ENV to see if the provider supports tool calling.
|
||||
* If the ENV is not set, we default to false.
|
||||
* @returns {boolean}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const supportsToolCalling =
|
||||
process.env.PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING?.includes("bedrock");
|
||||
|
||||
if (supportsToolCalling)
|
||||
this.providerLog("AWS Bedrock native tool calling is ENABLED via ENV.");
|
||||
else
|
||||
this.providerLog(
|
||||
"AWS Bedrock native tool calling is DISABLED via ENV. Will use UnTooled instead."
|
||||
);
|
||||
this._supportsToolCalling = supportsToolCalling;
|
||||
return supportsToolCalling;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets the credentials for the AWS Bedrock LLM based on the authentication method provided.
|
||||
* @returns {object} The credentials object.
|
||||
@ -85,6 +110,99 @@ class AWSBedrockProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return langchainChats;
|
||||
}
|
||||
|
||||
/**
|
||||
* Convert aibitat message history to Langchain message prototypes with
|
||||
* proper tool call / tool result handling for native tool calling.
|
||||
* role:"function" messages (from previous aibitat tool runs) are converted
|
||||
* to AIMessage(tool_calls) + ToolMessage pairs that Langchain expects.
|
||||
* @param {Array} chats - The aibitat message history.
|
||||
* @returns {Array} Langchain message instances.
|
||||
*/
|
||||
#convertToLangchainPrototypesWithTools(chats = []) {
|
||||
const langchainChats = [];
|
||||
|
||||
for (const chat of chats) {
|
||||
if (chat.role === "function") {
|
||||
if (chat.originalFunctionCall?.id) {
|
||||
const prevMsg = langchainChats[langchainChats.length - 1];
|
||||
if (
|
||||
!prevMsg ||
|
||||
!(prevMsg instanceof AIMessage) ||
|
||||
!prevMsg.tool_calls?.length
|
||||
) {
|
||||
langchainChats.push(
|
||||
new AIMessage({
|
||||
content: "",
|
||||
tool_calls: [
|
||||
{
|
||||
name: chat.originalFunctionCall.name,
|
||||
args:
|
||||
typeof chat.originalFunctionCall.arguments === "string"
|
||||
? safeJsonParse(chat.originalFunctionCall.arguments, {})
|
||||
: chat.originalFunctionCall.arguments,
|
||||
id: chat.originalFunctionCall.id,
|
||||
},
|
||||
],
|
||||
})
|
||||
);
|
||||
}
|
||||
langchainChats.push(
|
||||
new ToolMessage({
|
||||
content:
|
||||
typeof chat.content === "string"
|
||||
? chat.content
|
||||
: JSON.stringify(chat.content),
|
||||
tool_call_id: chat.originalFunctionCall.id,
|
||||
})
|
||||
);
|
||||
} else {
|
||||
const toolCallId = `call_${v4()}`;
|
||||
langchainChats.push(
|
||||
new AIMessage({
|
||||
content: "",
|
||||
tool_calls: [{ name: chat.name, args: {}, id: toolCallId }],
|
||||
})
|
||||
);
|
||||
langchainChats.push(
|
||||
new ToolMessage({
|
||||
content:
|
||||
typeof chat.content === "string"
|
||||
? chat.content
|
||||
: JSON.stringify(chat.content),
|
||||
tool_call_id: toolCallId,
|
||||
})
|
||||
);
|
||||
}
|
||||
} else if (chat.role === "system") {
|
||||
langchainChats.push(new SystemMessage({ content: chat.content }));
|
||||
} else if (chat.role === "user") {
|
||||
langchainChats.push(new HumanMessage({ content: chat.content }));
|
||||
} else if (chat.role === "assistant") {
|
||||
langchainChats.push(new AIMessage({ content: chat.content }));
|
||||
}
|
||||
}
|
||||
|
||||
return langchainChats;
|
||||
}
|
||||
|
||||
/**
|
||||
* Convert aibitat function definitions to the format expected by
|
||||
* Langchain's ChatBedrockConverse.bindTools().
|
||||
* @param {Array<{name: string, description: string, parameters: object}>} functions
|
||||
* @returns {Array<{type: "function", function: {name: string, description: string, parameters: object}}>}
|
||||
*/
|
||||
#formatFunctionsToLangchainTools(functions) {
|
||||
if (!Array.isArray(functions) || functions.length === 0) return [];
|
||||
return functions.map((func) => ({
|
||||
type: "function",
|
||||
function: {
|
||||
name: func.name,
|
||||
description: func.description,
|
||||
parameters: func.parameters,
|
||||
},
|
||||
}));
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
const response = await this.client
|
||||
.invoke(this.#convertToLangchainPrototypes(messages))
|
||||
@ -141,6 +259,7 @@ class AWSBedrockProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
|
||||
/**
|
||||
* Stream a chat completion from the Bedrock LLM with tool calling.
|
||||
* Uses native Bedrock Converse tool calling when supported, otherwise falls back to UnTooled.
|
||||
*
|
||||
* @param {any[]} messages - The messages to send to the LLM.
|
||||
* @param {any[]} functions - The functions to use in the LLM.
|
||||
@ -148,6 +267,9 @@ class AWSBedrockProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
* @returns {Promise<{ functionCall: any, textResponse: string }>} - The result of the chat completion.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative = functions.length > 0 && this.supportsNativeToolCalling();
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream
|
||||
.call(
|
||||
this,
|
||||
@ -164,16 +286,89 @@ class AWSBedrockProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
const langchainMessages =
|
||||
this.#convertToLangchainPrototypesWithTools(messages);
|
||||
const tools = this.#formatFunctionsToLangchainTools(functions);
|
||||
const modelWithTools = this.client.bindTools(tools);
|
||||
const stream = await modelWithTools.stream(langchainMessages);
|
||||
|
||||
const msgUUID = v4();
|
||||
let textResponse = "";
|
||||
let finalMessage = null;
|
||||
|
||||
for await (const chunk of stream) {
|
||||
finalMessage =
|
||||
finalMessage === null ? chunk : finalMessage.concat(chunk);
|
||||
|
||||
const content = typeof chunk.content === "string" ? chunk.content : "";
|
||||
if (content) {
|
||||
textResponse += content;
|
||||
eventHandler?.("reportStreamEvent", {
|
||||
type: "textResponseChunk",
|
||||
uuid: msgUUID,
|
||||
content,
|
||||
});
|
||||
}
|
||||
|
||||
if (chunk.tool_call_chunks?.length) {
|
||||
for (const toolChunk of chunk.tool_call_chunks) {
|
||||
if (toolChunk.name) {
|
||||
eventHandler?.("reportStreamEvent", {
|
||||
uuid: `${msgUUID}:tool_call_invocation`,
|
||||
type: "toolCallInvocation",
|
||||
content: `Assembling Tool Call: ${toolChunk.name}`,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (finalMessage?.tool_calls?.length > 0) {
|
||||
const toolCall = finalMessage.tool_calls[0];
|
||||
return {
|
||||
textResponse,
|
||||
functionCall: {
|
||||
id: toolCall.id || `call_${v4()}`,
|
||||
name: toolCall.name,
|
||||
arguments: toolCall.args || {},
|
||||
},
|
||||
cost: 0,
|
||||
};
|
||||
}
|
||||
|
||||
return { textResponse, functionCall: null, cost: 0 };
|
||||
} catch (e) {
|
||||
AWSBedrockLLM.errorToHumanReadable(e, {
|
||||
method: "stream",
|
||||
model: this.model,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a completion based on the received messages.
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native Bedrock Converse tool calling when supported, otherwise falls back to UnTooled.
|
||||
*
|
||||
* @param messages A list of messages to send to the API.
|
||||
* @param functions
|
||||
* @param {any[]} messages A list of messages to send to the API.
|
||||
* @param {any[]} functions The function definitions available to the model.
|
||||
* @returns The completion.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative = functions.length > 0 && this.supportsNativeToolCalling();
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete
|
||||
.call(this, messages, functions, this.#handleFunctionCallChat.bind(this))
|
||||
.call(
|
||||
this,
|
||||
messages,
|
||||
functions,
|
||||
this.#handleFunctionCallChat.bind(this)
|
||||
)
|
||||
.catch((e) => {
|
||||
AWSBedrockLLM.errorToHumanReadable(e, {
|
||||
method: "complete",
|
||||
@ -182,6 +377,41 @@ class AWSBedrockProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
try {
|
||||
const langchainMessages =
|
||||
this.#convertToLangchainPrototypesWithTools(messages);
|
||||
const tools = this.#formatFunctionsToLangchainTools(functions);
|
||||
const modelWithTools = this.client.bindTools(tools);
|
||||
const response = await modelWithTools.invoke(langchainMessages);
|
||||
|
||||
if (response.tool_calls?.length > 0) {
|
||||
const toolCall = response.tool_calls[0];
|
||||
return {
|
||||
textResponse: null,
|
||||
functionCall: {
|
||||
id: toolCall.id || `call_${v4()}`,
|
||||
name: toolCall.name,
|
||||
arguments: toolCall.args || {},
|
||||
},
|
||||
cost: 0,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
textResponse:
|
||||
typeof response.content === "string"
|
||||
? response.content
|
||||
: JSON.stringify(response.content),
|
||||
cost: 0,
|
||||
};
|
||||
} catch (e) {
|
||||
AWSBedrockLLM.errorToHumanReadable(e, {
|
||||
method: "complete",
|
||||
model: this.model,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
|
||||
@ -28,6 +28,15 @@ class CohereProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
#convertChatHistoryCohere(chatHistory = []) {
|
||||
let cohereHistory = [];
|
||||
chatHistory.forEach((message) => {
|
||||
|
||||
@ -35,6 +35,15 @@ class CometApiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return false;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -2,6 +2,8 @@ const OpenAI = require("openai");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
const { RetryError } = require("../error.js");
|
||||
const { toValidNumber } = require("../../../http/index.js");
|
||||
|
||||
class DeepSeekProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
@ -32,6 +34,23 @@ class DeepSeekProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* All current DeepSeek models (deepseek-chat and deepseek-reasoner)
|
||||
* support native OpenAI-compatible tool calling.
|
||||
* @returns {boolean}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return true;
|
||||
}
|
||||
|
||||
get #isThinkingModel() {
|
||||
return this.model === "deepseek-reasoner";
|
||||
}
|
||||
|
||||
get #tooledOptions() {
|
||||
return this.#isThinkingModel ? { injectReasoningContent: true } : {};
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
@ -60,6 +79,9 @@ class DeepSeekProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
}
|
||||
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative = functions.length > 0 && this.supportsNativeToolCalling();
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream.call(
|
||||
this,
|
||||
messages,
|
||||
@ -69,7 +91,37 @@ class DeepSeekProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler,
|
||||
this.#tooledOptions
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
async complete(messages, functions = []) {
|
||||
const useNative = functions.length > 0 && this.supportsNativeToolCalling();
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete.call(
|
||||
this,
|
||||
messages,
|
||||
@ -78,6 +130,34 @@ class DeepSeekProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this),
|
||||
this.#tooledOptions
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return result;
|
||||
} catch (error) {
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
|
||||
@ -37,6 +37,15 @@ class DellProAiStudioProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -2,7 +2,10 @@ const OpenAI = require("openai");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
const { RetryError } = require("../error.js");
|
||||
const {
|
||||
DockerModelRunnerLLM,
|
||||
parseDockerModelRunnerEndpoint,
|
||||
} = require("../../../AiProviders/dockerModelRunner/index.js");
|
||||
|
||||
@ -31,6 +34,7 @@ class DockerModelRunnerProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
this._client = client;
|
||||
this.model = model;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
}
|
||||
|
||||
get client() {
|
||||
@ -41,6 +45,19 @@ class DockerModelRunnerProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
async supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const dmr = new DockerModelRunnerLLM(null, this.model);
|
||||
const capabilities = await dmr.getModelCapabilities();
|
||||
this._supportsToolCalling = capabilities.tools === true;
|
||||
return this._supportsToolCalling;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
@ -67,7 +84,15 @@ class DockerModelRunnerProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream.call(
|
||||
this,
|
||||
messages,
|
||||
@ -77,7 +102,41 @@ class DockerModelRunnerProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete.call(
|
||||
this,
|
||||
messages,
|
||||
@ -86,6 +145,33 @@ class DockerModelRunnerProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this)
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return result;
|
||||
} catch (error) {
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
|
||||
@ -33,6 +33,15 @@ class FireworksAIProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -40,6 +40,15 @@ class FoundryProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
await FoundryLLM.cacheContextWindows();
|
||||
return await this.client.chat.completions
|
||||
|
||||
@ -2,6 +2,8 @@ const OpenAI = require("openai");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
const { RetryError } = require("../error.js");
|
||||
const { toValidNumber } = require("../../../http/index.js");
|
||||
const { getAnythingLLMUserAgent } = require("../../../../endpoints/utils");
|
||||
const { GenericOpenAiLLM } = require("../../../AiProviders/genericOpenAi");
|
||||
@ -31,6 +33,7 @@ class GenericOpenAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
this._client = client;
|
||||
this.model = model;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
this.maxTokens = process.env.GENERIC_OPEN_AI_MAX_TOKENS
|
||||
? toValidNumber(process.env.GENERIC_OPEN_AI_MAX_TOKENS, 1024)
|
||||
: 1024;
|
||||
@ -46,6 +49,32 @@ class GenericOpenAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* - This can be any OpenAI compatible provider that supports tool calling
|
||||
* - We check the ENV to see if the provider supports tool calling.
|
||||
* - If the ENV is not set, we default to false.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const supportsToolCalling =
|
||||
process.env.PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING?.includes(
|
||||
"generic-openai"
|
||||
);
|
||||
|
||||
if (supportsToolCalling)
|
||||
this.providerLog(
|
||||
"Generic OpenAI supports native tool calling is ENABLED via ENV."
|
||||
);
|
||||
else
|
||||
this.providerLog(
|
||||
"Generic OpenAI supports native tool calling is DISABLED via ENV. Will use UnTooled instead."
|
||||
);
|
||||
this._supportsToolCalling = supportsToolCalling;
|
||||
return supportsToolCalling;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
@ -74,7 +103,15 @@ class GenericOpenAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream.call(
|
||||
this,
|
||||
messages,
|
||||
@ -84,7 +121,41 @@ class GenericOpenAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete.call(
|
||||
this,
|
||||
messages,
|
||||
@ -93,6 +164,33 @@ class GenericOpenAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this)
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return result;
|
||||
} catch (error) {
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
|
||||
@ -26,6 +26,15 @@ class GiteeAIProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -2,10 +2,13 @@ const OpenAI = require("openai");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
const { RetryError } = require("../error.js");
|
||||
|
||||
/**
|
||||
* The agent provider for the GroqAI provider.
|
||||
* We wrap Groq in UnTooled because its tool-calling built in is quite bad and wasteful.
|
||||
* Supports true OpenAI-compatible tool calling when enabled via ENV,
|
||||
* falling back to the UnTooled prompt-based approach otherwise.
|
||||
*/
|
||||
class GroqProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
model;
|
||||
@ -22,6 +25,7 @@ class GroqProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
this._client = client;
|
||||
this.model = model;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
}
|
||||
|
||||
get client() {
|
||||
@ -32,6 +36,27 @@ class GroqProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* - Since Groq models vary in tool calling support, we check the ENV.
|
||||
* - If the ENV is not set, we default to false.
|
||||
* @returns {boolean}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const supportsToolCalling =
|
||||
process.env.PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING?.includes("groq");
|
||||
|
||||
if (supportsToolCalling)
|
||||
this.providerLog("Groq supports native tool calling is ENABLED via ENV.");
|
||||
else
|
||||
this.providerLog(
|
||||
"Groq supports native tool calling is DISABLED via ENV. Will use UnTooled instead."
|
||||
);
|
||||
this._supportsToolCalling = supportsToolCalling;
|
||||
return supportsToolCalling;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
@ -58,7 +83,15 @@ class GroqProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion with tool calling support.
|
||||
* Uses native tool calling when enabled via ENV, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream.call(
|
||||
this,
|
||||
messages,
|
||||
@ -68,7 +101,41 @@ class GroqProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native tool calling when enabled via ENV, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete.call(
|
||||
this,
|
||||
messages,
|
||||
@ -77,12 +144,37 @@ class GroqProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this)
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return result;
|
||||
} catch (error) {
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
* @param _usage The completion to get the cost for.
|
||||
* @returns The cost of the completion.
|
||||
* Stubbed since LMStudio has no cost basis.
|
||||
*/
|
||||
getCost(_usage) {
|
||||
return 0;
|
||||
|
||||
298
server/utils/agents/aibitat/providers/helpers/tooled.js
Normal file
298
server/utils/agents/aibitat/providers/helpers/tooled.js
Normal file
@ -0,0 +1,298 @@
|
||||
const { v4 } = require("uuid");
|
||||
const { safeJsonParse } = require("../../../../http");
|
||||
|
||||
/**
|
||||
* Shared native OpenAI-compatible tool calling utilities.
|
||||
* Any provider with an OpenAI-compatible client can use these functions
|
||||
* instead of the UnTooled prompt-based approach when the model supports
|
||||
* native tool calling.
|
||||
*
|
||||
* Usage in a provider:
|
||||
* const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
*
|
||||
* async stream(messages, functions, eventHandler) {
|
||||
* if (functions.length > 0 && await this.supportsNativeToolCalling()) {
|
||||
* return tooledStream(this.client, this.model, messages, functions, eventHandler);
|
||||
* }
|
||||
* // ... fallback to UnTooled ...
|
||||
* }
|
||||
*/
|
||||
|
||||
/**
|
||||
* Convert aibitat function definitions to the OpenAI tools format.
|
||||
* @param {Array<{name: string, description: string, parameters: object}>} functions
|
||||
* @returns {Array<{type: "function", function: {name: string, description: string, parameters: object}}>}
|
||||
*/
|
||||
function formatFunctionsToTools(functions) {
|
||||
if (!Array.isArray(functions) || functions.length === 0) return [];
|
||||
return functions.map((func) => ({
|
||||
type: "function",
|
||||
function: {
|
||||
name: func.name,
|
||||
description: func.description,
|
||||
parameters: func.parameters,
|
||||
},
|
||||
}));
|
||||
}
|
||||
|
||||
/**
|
||||
* Convert the aibitat message history (which uses role:"function" with
|
||||
* `originalFunctionCall` metadata) into the OpenAI tool-calling message
|
||||
* format (assistant `tool_calls` + role:"tool" pairs).
|
||||
* @param {Array} messages
|
||||
* @param {{injectReasoningContent?: boolean}} options
|
||||
* - injectReasoningContent: when true, ensures every assistant message has
|
||||
* a `reasoning_content` field (required by DeepSeek thinking-mode models).
|
||||
* @returns {Array} Messages formatted for the OpenAI tools API
|
||||
*/
|
||||
function formatMessagesForTools(messages, options = {}) {
|
||||
const formattedMessages = [];
|
||||
const { injectReasoningContent = false } = options;
|
||||
|
||||
for (const message of messages) {
|
||||
if (message.role === "function") {
|
||||
if (message.originalFunctionCall?.id) {
|
||||
const prevMsg = formattedMessages[formattedMessages.length - 1];
|
||||
if (!prevMsg || prevMsg.role !== "assistant" || !prevMsg.tool_calls) {
|
||||
formattedMessages.push({
|
||||
role: "assistant",
|
||||
content: null,
|
||||
...(injectReasoningContent ? { reasoning_content: "" } : {}),
|
||||
tool_calls: [
|
||||
{
|
||||
id: message.originalFunctionCall.id,
|
||||
type: "function",
|
||||
function: {
|
||||
name: message.originalFunctionCall.name,
|
||||
arguments:
|
||||
typeof message.originalFunctionCall.arguments === "string"
|
||||
? message.originalFunctionCall.arguments
|
||||
: JSON.stringify(message.originalFunctionCall.arguments),
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
}
|
||||
formattedMessages.push({
|
||||
role: "tool",
|
||||
tool_call_id: message.originalFunctionCall.id,
|
||||
content:
|
||||
typeof message.content === "string"
|
||||
? message.content
|
||||
: JSON.stringify(message.content),
|
||||
});
|
||||
} else {
|
||||
const toolCallId = `call_${v4()}`;
|
||||
formattedMessages.push({
|
||||
role: "assistant",
|
||||
content: null,
|
||||
...(injectReasoningContent ? { reasoning_content: "" } : {}),
|
||||
tool_calls: [
|
||||
{
|
||||
id: toolCallId,
|
||||
type: "function",
|
||||
function: {
|
||||
name: message.name,
|
||||
arguments: "{}",
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
formattedMessages.push({
|
||||
role: "tool",
|
||||
tool_call_id: toolCallId,
|
||||
content:
|
||||
typeof message.content === "string"
|
||||
? message.content
|
||||
: JSON.stringify(message.content),
|
||||
});
|
||||
}
|
||||
} else if (
|
||||
injectReasoningContent &&
|
||||
message.role === "assistant" &&
|
||||
!("reasoning_content" in message)
|
||||
) {
|
||||
formattedMessages.push({ ...message, reasoning_content: "" });
|
||||
} else {
|
||||
formattedMessages.push(message);
|
||||
}
|
||||
}
|
||||
|
||||
return formattedMessages;
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion using native OpenAI-compatible tool calling.
|
||||
* Handles parallel tool calls by tracking each tool call by its streaming
|
||||
* index, then returning only the first one for the agent framework to process.
|
||||
*
|
||||
* @param {import("openai").OpenAI} client - OpenAI-compatible client
|
||||
* @param {string} model - Model identifier
|
||||
* @param {Array} messages - Raw aibitat message history
|
||||
* @param {Array} functions - Aibitat function definitions
|
||||
* @param {function|null} eventHandler - Stream event handler
|
||||
* @param {{injectReasoningContent?: boolean}} options - Provider-specific options forwarded to formatMessagesForTools
|
||||
* @returns {Promise<{textResponse: string, functionCall: object|null}>}
|
||||
*/
|
||||
async function tooledStream(
|
||||
client,
|
||||
model,
|
||||
messages,
|
||||
functions = [],
|
||||
eventHandler = null,
|
||||
options = {}
|
||||
) {
|
||||
const msgUUID = v4();
|
||||
const formattedMessages = formatMessagesForTools(messages, options);
|
||||
const tools = formatFunctionsToTools(functions);
|
||||
|
||||
const stream = await client.chat.completions.create({
|
||||
model,
|
||||
stream: true,
|
||||
messages: formattedMessages,
|
||||
...(tools.length > 0 ? { tools } : {}),
|
||||
});
|
||||
|
||||
const result = {
|
||||
functionCall: null,
|
||||
textResponse: "",
|
||||
};
|
||||
|
||||
const toolCallsByIndex = {};
|
||||
|
||||
for await (const chunk of stream) {
|
||||
if (!chunk?.choices?.[0]) continue;
|
||||
const choice = chunk.choices[0];
|
||||
|
||||
if (choice.delta?.content) {
|
||||
result.textResponse += choice.delta.content;
|
||||
eventHandler?.("reportStreamEvent", {
|
||||
type: "textResponseChunk",
|
||||
uuid: msgUUID,
|
||||
content: choice.delta.content,
|
||||
});
|
||||
}
|
||||
|
||||
if (choice.delta?.tool_calls) {
|
||||
for (const toolCall of choice.delta.tool_calls) {
|
||||
const idx = toolCall.index ?? 0;
|
||||
|
||||
if (toolCall.id) {
|
||||
toolCallsByIndex[idx] = {
|
||||
id: toolCall.id,
|
||||
name: toolCall.function?.name || "",
|
||||
arguments: toolCall.function?.arguments || "",
|
||||
};
|
||||
} else if (toolCallsByIndex[idx]) {
|
||||
if (toolCall.function?.name) {
|
||||
toolCallsByIndex[idx].name += toolCall.function.name;
|
||||
}
|
||||
if (toolCall.function?.arguments) {
|
||||
toolCallsByIndex[idx].arguments += toolCall.function.arguments;
|
||||
}
|
||||
}
|
||||
|
||||
if (toolCallsByIndex[idx]) {
|
||||
eventHandler?.("reportStreamEvent", {
|
||||
uuid: `${msgUUID}:tool_call_invocation`,
|
||||
type: "toolCallInvocation",
|
||||
content: `Assembling Tool Call: ${toolCallsByIndex[idx].name}(${toolCallsByIndex[idx].arguments})`,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const toolCallIndices = Object.keys(toolCallsByIndex).map(Number);
|
||||
if (toolCallIndices.length > 0) {
|
||||
const firstToolCall = toolCallsByIndex[Math.min(...toolCallIndices)];
|
||||
result.functionCall = {
|
||||
id: firstToolCall.id,
|
||||
name: firstToolCall.name,
|
||||
arguments: safeJsonParse(firstToolCall.arguments, {}),
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
textResponse: result.textResponse,
|
||||
functionCall: result.functionCall,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Non-streaming chat completion using native OpenAI-compatible tool calling.
|
||||
* Returns the first tool call if the model requests any, otherwise the text response.
|
||||
*
|
||||
* @param {import("openai").OpenAI} client - OpenAI-compatible client
|
||||
* @param {string} model - Model identifier
|
||||
* @param {Array} messages - Raw aibitat message history
|
||||
* @param {Array} functions - Aibitat function definitions
|
||||
* @param {function} getCostFn - Provider's getCost function
|
||||
* @param {{injectReasoningContent?: boolean}} options - Provider-specific options forwarded to formatMessagesForTools
|
||||
* @returns {Promise<{textResponse: string|null, functionCall: object|null, cost: number}>}
|
||||
*/
|
||||
async function tooledComplete(
|
||||
client,
|
||||
model,
|
||||
messages,
|
||||
functions = [],
|
||||
getCostFn = () => 0,
|
||||
options = {}
|
||||
) {
|
||||
const formattedMessages = formatMessagesForTools(messages, options);
|
||||
const tools = formatFunctionsToTools(functions);
|
||||
|
||||
const response = await client.chat.completions.create({
|
||||
model,
|
||||
stream: false,
|
||||
messages: formattedMessages,
|
||||
...(tools.length > 0 ? { tools } : {}),
|
||||
});
|
||||
|
||||
const completion = response.choices[0].message;
|
||||
const cost = getCostFn(response.usage);
|
||||
|
||||
if (completion.tool_calls && completion.tool_calls.length > 0) {
|
||||
const toolCall = completion.tool_calls[0];
|
||||
const functionArgs = safeJsonParse(toolCall.function.arguments, null);
|
||||
|
||||
if (functionArgs === null) {
|
||||
return {
|
||||
textResponse: null,
|
||||
retryWithError: {
|
||||
role: "function",
|
||||
name: toolCall.function.name,
|
||||
content: `Failed to parse tool call arguments as JSON. Raw arguments: ${toolCall.function.arguments}`,
|
||||
originalFunctionCall: {
|
||||
id: toolCall.id,
|
||||
name: toolCall.function.name,
|
||||
arguments: toolCall.function.arguments,
|
||||
},
|
||||
},
|
||||
cost,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
textResponse: null,
|
||||
functionCall: {
|
||||
id: toolCall.id,
|
||||
name: toolCall.function.name,
|
||||
arguments: functionArgs,
|
||||
},
|
||||
cost,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
textResponse: completion.content,
|
||||
cost,
|
||||
};
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
formatFunctionsToTools,
|
||||
formatMessagesForTools,
|
||||
tooledStream,
|
||||
tooledComplete,
|
||||
};
|
||||
@ -32,6 +32,15 @@ class KoboldCPPProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -2,9 +2,13 @@ const OpenAI = require("openai");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
const { RetryError } = require("../error.js");
|
||||
|
||||
/**
|
||||
* The agent provider for LiteLLM.
|
||||
* Supports true OpenAI-compatible tool calling when enabled via ENV,
|
||||
* falling back to the UnTooled prompt-based approach otherwise.
|
||||
*/
|
||||
class LiteLLMProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
model;
|
||||
@ -21,6 +25,7 @@ class LiteLLMProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
this._client = client;
|
||||
this.model = model || process.env.LITE_LLM_MODEL_PREF;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
}
|
||||
|
||||
get client() {
|
||||
@ -31,6 +36,29 @@ class LiteLLMProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* - Since LiteLLM models vary in tool calling support, we check the ENV.
|
||||
* - If the ENV is not set, we default to false.
|
||||
* @returns {boolean}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const supportsToolCalling =
|
||||
process.env.PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING?.includes("litellm");
|
||||
|
||||
if (supportsToolCalling)
|
||||
this.providerLog(
|
||||
"LiteLLM supports native tool calling is ENABLED via ENV."
|
||||
);
|
||||
else
|
||||
this.providerLog(
|
||||
"LiteLLM supports native tool calling is DISABLED via ENV. Will use UnTooled instead."
|
||||
);
|
||||
this._supportsToolCalling = supportsToolCalling;
|
||||
return supportsToolCalling;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
@ -57,7 +85,15 @@ class LiteLLMProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion with tool calling support.
|
||||
* Uses native tool calling when enabled via ENV, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream.call(
|
||||
this,
|
||||
messages,
|
||||
@ -67,7 +103,41 @@ class LiteLLMProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native tool calling when enabled via ENV, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete.call(
|
||||
this,
|
||||
messages,
|
||||
@ -76,6 +146,38 @@ class LiteLLMProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this)
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return result;
|
||||
} catch (error) {
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
* @param _usage The completion to get the cost for.
|
||||
* @returns The cost of the completion.
|
||||
*/
|
||||
getCost(_usage) {
|
||||
return 0;
|
||||
}
|
||||
|
||||
@ -2,6 +2,8 @@ const OpenAI = require("openai");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
const { RetryError } = require("../error.js");
|
||||
const {
|
||||
LMStudioLLM,
|
||||
parseLMStudioBasePath,
|
||||
@ -9,12 +11,13 @@ const {
|
||||
|
||||
/**
|
||||
* The agent provider for the LMStudio.
|
||||
* Supports true OpenAI-compatible tool calling when the model supports it,
|
||||
* falling back to the UnTooled prompt-based approach otherwise.
|
||||
*/
|
||||
class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
model;
|
||||
|
||||
/**
|
||||
*
|
||||
* @param {{model?: string}} config
|
||||
*/
|
||||
constructor(config = {}) {
|
||||
@ -32,6 +35,7 @@ class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
this._client = client;
|
||||
this.model = model;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
}
|
||||
|
||||
get client() {
|
||||
@ -42,6 +46,21 @@ class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether the loaded model supports native OpenAI-compatible tool calling.
|
||||
* Checks the LMStudio /api/v1/models endpoint for the model's capabilities.
|
||||
* @returns {Promise<boolean>}
|
||||
*/
|
||||
async supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const lmstudio = new LMStudioLLM(null, this.model);
|
||||
const capabilities = await lmstudio.getModelCapabilities();
|
||||
this._supportsToolCalling = capabilities.tools === true;
|
||||
return this._supportsToolCalling;
|
||||
}
|
||||
|
||||
// ---- UnTooled callbacks (used when native tool calling is not supported) ----
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
await LMStudioLLM.cacheContextWindows();
|
||||
return await this.client.chat.completions
|
||||
@ -70,7 +89,15 @@ class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream.call(
|
||||
this,
|
||||
messages,
|
||||
@ -80,7 +107,42 @@ class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
await LMStudioLLM.cacheContextWindows();
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete.call(
|
||||
this,
|
||||
messages,
|
||||
@ -89,12 +151,39 @@ class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
await LMStudioLLM.cacheContextWindows();
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this)
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return result;
|
||||
} catch (error) {
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
* Stubbed since LMStudio has no cost basis.
|
||||
* @param _usage The completion to get the cost for.
|
||||
* @returns The cost of the completion.
|
||||
* Stubbed since LMStudio has no cost basis.
|
||||
*/
|
||||
getCost(_usage) {
|
||||
return 0;
|
||||
|
||||
@ -2,9 +2,13 @@ const OpenAI = require("openai");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
const { RetryError } = require("../error.js");
|
||||
|
||||
/**
|
||||
* The agent provider for the LocalAI provider.
|
||||
* Supports native OpenAI-compatible tool calling when enabled via ENV,
|
||||
* falling back to the UnTooled prompt-based approach otherwise.
|
||||
*/
|
||||
class LocalAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
model;
|
||||
@ -21,6 +25,7 @@ class LocalAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
this._client = client;
|
||||
this.model = model;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
}
|
||||
|
||||
get client() {
|
||||
@ -31,6 +36,31 @@ class LocalAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Since LocalAI does not expose model capabilities via API, we check
|
||||
* the PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING ENV flag for "localai".
|
||||
* @returns {boolean}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const supportsToolCalling =
|
||||
process.env.PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING?.includes("localai");
|
||||
|
||||
if (supportsToolCalling)
|
||||
this.providerLog(
|
||||
"LocalAI supports native tool calling is ENABLED via ENV."
|
||||
);
|
||||
else
|
||||
this.providerLog(
|
||||
"LocalAI supports native tool calling is DISABLED via ENV. Will use UnTooled instead."
|
||||
);
|
||||
this._supportsToolCalling = supportsToolCalling;
|
||||
return supportsToolCalling;
|
||||
}
|
||||
|
||||
// ---- UnTooled callbacks (used when native tool calling is not supported) ----
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
@ -40,10 +70,8 @@ class LocalAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
.then((result) => {
|
||||
if (!result.hasOwnProperty("choices"))
|
||||
throw new Error("LocalAI chat: No results!");
|
||||
|
||||
if (result.choices.length === 0)
|
||||
throw new Error("LocalAI chat: No results length!");
|
||||
|
||||
return result.choices[0].message.content;
|
||||
})
|
||||
.catch((_) => {
|
||||
@ -59,7 +87,15 @@ class LocalAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream.call(
|
||||
this,
|
||||
messages,
|
||||
@ -69,7 +105,41 @@ class LocalAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete.call(
|
||||
this,
|
||||
messages,
|
||||
@ -78,6 +148,33 @@ class LocalAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this)
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return result;
|
||||
} catch (error) {
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
|
||||
@ -35,6 +35,15 @@ class MistralProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -35,6 +35,15 @@ class MoonshotAiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -35,6 +35,15 @@ class NovitaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -33,6 +33,15 @@ class NvidiaNimProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -1,6 +1,7 @@
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { formatFunctionsToTools } = require("./helpers/tooled.js");
|
||||
const { OllamaAILLM } = require("../../../AiProviders/ollama");
|
||||
const { Ollama } = require("ollama");
|
||||
const { v4 } = require("uuid");
|
||||
@ -8,6 +9,8 @@ const { safeJsonParse } = require("../../../http");
|
||||
|
||||
/**
|
||||
* The agent provider for the Ollama provider.
|
||||
* Supports true OpenAI-compatible tool calling when the model supports it,
|
||||
* falling back to the UnTooled prompt-based approach otherwise.
|
||||
*/
|
||||
class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
model;
|
||||
@ -19,16 +22,17 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
} = config;
|
||||
|
||||
super();
|
||||
const headers = process.env.OLLAMA_AUTH_TOKEN
|
||||
? { Authorization: `Bearer ${process.env.OLLAMA_AUTH_TOKEN}` }
|
||||
: {};
|
||||
const authToken = process.env.OLLAMA_AUTH_TOKEN;
|
||||
const basePath = process.env.OLLAMA_BASE_PATH;
|
||||
const headers = authToken ? { Authorization: `Bearer ${authToken}` } : {};
|
||||
this._client = new Ollama({
|
||||
host: process.env.OLLAMA_BASE_PATH,
|
||||
host: basePath,
|
||||
headers: headers,
|
||||
fetch: this.#applyFetch(),
|
||||
});
|
||||
this.model = model;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
}
|
||||
|
||||
get client() {
|
||||
@ -39,6 +43,19 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
async supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const ollama = new OllamaAILLM(null, this.model);
|
||||
const capabilities = await ollama.getModelCapabilities();
|
||||
this._supportsToolCalling = capabilities.tools === true;
|
||||
return this._supportsToolCalling;
|
||||
}
|
||||
|
||||
get queryOptions() {
|
||||
this.providerLog(
|
||||
`${this.model} is using a max context window of ${OllamaAILLM.promptWindowLimit(this.model)}/${OllamaAILLM.maxContextWindow(this.model)} tokens.`
|
||||
@ -74,6 +91,49 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Convert aibitat's internal message history (which uses role:"function" with
|
||||
* originalFunctionCall metadata) into the Ollama tool-calling message format
|
||||
* (assistant tool_calls + role:"tool" result pairs).
|
||||
* @param {Array} messages
|
||||
* @returns {Array}
|
||||
*/
|
||||
#formatMessagesForOllamaTools(messages) {
|
||||
const formatted = [];
|
||||
for (const message of messages) {
|
||||
if (message.role === "function") {
|
||||
const funcName =
|
||||
message.originalFunctionCall?.name || message.name || "unknown";
|
||||
const funcArgs = message.originalFunctionCall?.arguments || {};
|
||||
formatted.push({
|
||||
role: "assistant",
|
||||
content: "",
|
||||
tool_calls: [
|
||||
{
|
||||
function: {
|
||||
name: funcName,
|
||||
arguments:
|
||||
typeof funcArgs === "string"
|
||||
? safeJsonParse(funcArgs, {})
|
||||
: funcArgs,
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
formatted.push({
|
||||
role: "tool",
|
||||
content:
|
||||
typeof message.content === "string"
|
||||
? message.content
|
||||
: JSON.stringify(message.content),
|
||||
});
|
||||
} else {
|
||||
formatted.push(message);
|
||||
}
|
||||
}
|
||||
return formatted;
|
||||
}
|
||||
|
||||
async streamingFunctionCall(
|
||||
messages,
|
||||
functions,
|
||||
@ -168,9 +228,9 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion from the LLM with tool calling
|
||||
* This is overriding the inherited `stream` method since Ollamas
|
||||
* SDK has different response structures to other OpenAI.
|
||||
* Stream a chat completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to the
|
||||
* Ollama SDK + UnTooled prompt-based approach.
|
||||
*
|
||||
* @param messages A list of messages to send to the API.
|
||||
* @param functions
|
||||
@ -178,8 +238,74 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
* @returns The completion.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (useNative) {
|
||||
this.providerLog(
|
||||
"OllamaProvider.complete - will process this chat completion."
|
||||
"OllamaProvider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
await OllamaAILLM.cacheContextWindows();
|
||||
const msgUUID = v4();
|
||||
const formattedMessages = this.#formatMessagesForOllamaTools(messages);
|
||||
const tools = formatFunctionsToTools(functions);
|
||||
|
||||
const stream = await this.client.chat({
|
||||
model: this.model,
|
||||
messages: formattedMessages,
|
||||
tools,
|
||||
stream: true,
|
||||
options: this.queryOptions,
|
||||
});
|
||||
|
||||
let textResponse = "";
|
||||
let toolCalls = null;
|
||||
|
||||
for await (const chunk of stream) {
|
||||
if (!chunk?.message) continue;
|
||||
|
||||
if (chunk.message.content) {
|
||||
textResponse += chunk.message.content;
|
||||
eventHandler?.("reportStreamEvent", {
|
||||
type: "textResponseChunk",
|
||||
uuid: msgUUID,
|
||||
content: chunk.message.content,
|
||||
});
|
||||
}
|
||||
|
||||
if (chunk.message.tool_calls?.length > 0) {
|
||||
toolCalls = chunk.message.tool_calls;
|
||||
eventHandler?.("reportStreamEvent", {
|
||||
uuid: `${msgUUID}:tool_call_invocation`,
|
||||
type: "toolCallInvocation",
|
||||
content: `Tool Call: ${toolCalls[0].function.name}(${JSON.stringify(toolCalls[0].function.arguments)})`,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (toolCalls && toolCalls.length > 0) {
|
||||
const toolCall = toolCalls[0];
|
||||
const args =
|
||||
typeof toolCall.function.arguments === "string"
|
||||
? safeJsonParse(toolCall.function.arguments, {})
|
||||
: toolCall.function.arguments || {};
|
||||
|
||||
return {
|
||||
textResponse,
|
||||
functionCall: {
|
||||
id: `ollama_${v4()}`,
|
||||
name: toolCall.function.name,
|
||||
arguments: args,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
return { textResponse, functionCall: null };
|
||||
}
|
||||
|
||||
// Fallback: UnTooled prompt-based approach via the native Ollama SDK
|
||||
this.providerLog(
|
||||
"OllamaProvider.stream - will process this chat completion."
|
||||
);
|
||||
try {
|
||||
let completion = { content: "" };
|
||||
@ -281,9 +407,6 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
}
|
||||
}
|
||||
|
||||
// The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
|
||||
// from calling the exact same function over and over in a loop within a single chat exchange
|
||||
// _but_ we should enable it to call previously used tools in a new chat interaction.
|
||||
this.deduplicator.reset("runs");
|
||||
return {
|
||||
textResponse: completion.content,
|
||||
@ -295,13 +418,54 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a completion based on the received messages.
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native tool calling when supported, otherwise falls back to UnTooled.
|
||||
*
|
||||
* @param messages A list of messages to send to the API.
|
||||
* @param functions
|
||||
* @returns The completion.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (useNative) {
|
||||
await OllamaAILLM.cacheContextWindows();
|
||||
const formattedMessages = this.#formatMessagesForOllamaTools(messages);
|
||||
const tools = formatFunctionsToTools(functions);
|
||||
|
||||
const response = await this.client.chat({
|
||||
model: this.model,
|
||||
messages: formattedMessages,
|
||||
tools,
|
||||
options: this.queryOptions,
|
||||
});
|
||||
|
||||
if (response.message?.tool_calls?.length > 0) {
|
||||
const toolCall = response.message.tool_calls[0];
|
||||
const args =
|
||||
typeof toolCall.function.arguments === "string"
|
||||
? safeJsonParse(toolCall.function.arguments, {})
|
||||
: toolCall.function.arguments || {};
|
||||
|
||||
return {
|
||||
textResponse: null,
|
||||
functionCall: {
|
||||
id: `ollama_${v4()}`,
|
||||
name: toolCall.function.name,
|
||||
arguments: args,
|
||||
},
|
||||
cost: 0,
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
textResponse: response.message?.content || null,
|
||||
cost: 0,
|
||||
};
|
||||
}
|
||||
|
||||
// Fallback: UnTooled prompt-based approach via the native Ollama SDK
|
||||
this.providerLog(
|
||||
"OllamaProvider.complete - will process this chat completion."
|
||||
);
|
||||
@ -341,9 +505,6 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
completion.content = textResponse;
|
||||
}
|
||||
|
||||
// The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
|
||||
// from calling the exact same function over and over in a loop within a single chat exchange
|
||||
// _but_ we should enable it to call previously used tools in a new chat interaction.
|
||||
this.deduplicator.reset("runs");
|
||||
return {
|
||||
textResponse: completion.content,
|
||||
@ -356,10 +517,9 @@ class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
* Stubbed since Ollama has no cost basis.
|
||||
* @param _usage The completion to get the cost for.
|
||||
* @returns The cost of the completion.
|
||||
* Stubbed since LMStudio has no cost basis.
|
||||
*/
|
||||
getCost(_usage) {
|
||||
return 0;
|
||||
|
||||
@ -2,9 +2,13 @@ const OpenAI = require("openai");
|
||||
const Provider = require("./ai-provider.js");
|
||||
const InheritMultiple = require("./helpers/classes.js");
|
||||
const UnTooled = require("./helpers/untooled.js");
|
||||
const { tooledStream, tooledComplete } = require("./helpers/tooled.js");
|
||||
const { RetryError } = require("../error.js");
|
||||
|
||||
/**
|
||||
* The agent provider for the OpenRouter provider.
|
||||
* Supports true OpenAI-compatible tool calling when enabled via ENV,
|
||||
* falling back to the UnTooled prompt-based approach otherwise.
|
||||
* @extends {Provider}
|
||||
* @extends {UnTooled}
|
||||
*/
|
||||
@ -27,6 +31,7 @@ class OpenRouterProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
this._client = client;
|
||||
this.model = model;
|
||||
this.verbose = true;
|
||||
this._supportsToolCalling = null;
|
||||
}
|
||||
|
||||
get client() {
|
||||
@ -37,6 +42,29 @@ class OpenRouterProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* - Since OpenRouter models vary in tool calling support, we check the ENV.
|
||||
* - If the ENV is not set, we default to false.
|
||||
* @returns {boolean}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
if (this._supportsToolCalling !== null) return this._supportsToolCalling;
|
||||
const supportsToolCalling =
|
||||
process.env.PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING?.includes("openrouter");
|
||||
|
||||
if (supportsToolCalling)
|
||||
this.providerLog(
|
||||
"OpenRouter supports native tool calling is ENABLED via ENV."
|
||||
);
|
||||
else
|
||||
this.providerLog(
|
||||
"OpenRouter supports native tool calling is DISABLED via ENV. Will use UnTooled instead."
|
||||
);
|
||||
this._supportsToolCalling = supportsToolCalling;
|
||||
return supportsToolCalling;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
@ -65,7 +93,15 @@ class OpenRouterProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream a chat completion with tool calling support.
|
||||
* Uses native tool calling when enabled via ENV, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async stream(messages, functions = [], eventHandler = null) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.stream.call(
|
||||
this,
|
||||
messages,
|
||||
@ -75,7 +111,41 @@ class OpenRouterProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
this.providerLog(
|
||||
"Provider.stream (tooled) - will process this chat completion."
|
||||
);
|
||||
|
||||
try {
|
||||
return await tooledStream(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
eventHandler
|
||||
);
|
||||
} catch (error) {
|
||||
console.error(error.message, error);
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a non-streaming completion with tool calling support.
|
||||
* Uses native tool calling when enabled via ENV, otherwise falls back to UnTooled.
|
||||
*/
|
||||
async complete(messages, functions = []) {
|
||||
const useNative =
|
||||
functions.length > 0 && (await this.supportsNativeToolCalling());
|
||||
|
||||
if (!useNative) {
|
||||
return await UnTooled.prototype.complete.call(
|
||||
this,
|
||||
messages,
|
||||
@ -84,12 +154,37 @@ class OpenRouterProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
const result = await tooledComplete(
|
||||
this.client,
|
||||
this.model,
|
||||
messages,
|
||||
functions,
|
||||
this.getCost.bind(this)
|
||||
);
|
||||
|
||||
if (result.retryWithError) {
|
||||
return this.complete([...messages, result.retryWithError], functions);
|
||||
}
|
||||
|
||||
return result;
|
||||
} catch (error) {
|
||||
if (error instanceof OpenAI.AuthenticationError) throw error;
|
||||
if (
|
||||
error instanceof OpenAI.RateLimitError ||
|
||||
error instanceof OpenAI.InternalServerError ||
|
||||
error instanceof OpenAI.APIError
|
||||
) {
|
||||
throw new RetryError(error.message);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the cost of the completion.
|
||||
*
|
||||
* @param _usage The completion to get the cost for.
|
||||
* @returns The cost of the completion.
|
||||
* Stubbed since OpenRouter has no cost basis.
|
||||
*/
|
||||
getCost(_usage) {
|
||||
return 0;
|
||||
|
||||
@ -31,6 +31,15 @@ class PerplexityProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -35,6 +35,15 @@ class PPIOProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return false;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -36,6 +36,15 @@ class PrivatemodelProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -35,6 +35,15 @@ class SambaNovaProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -30,6 +30,15 @@ class TextWebGenUiProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -31,6 +31,15 @@ class TogetherAIProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -31,6 +31,15 @@ class XAIProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -35,6 +35,15 @@ class ZAIProvider extends InheritMultiple([Provider, UnTooled]) {
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Whether this provider supports native OpenAI-compatible tool calling.
|
||||
* Override in subclass and return true to use native tool calling instead of UnTooled.
|
||||
* @returns {boolean|Promise<boolean>}
|
||||
*/
|
||||
supportsNativeToolCalling() {
|
||||
return false;
|
||||
}
|
||||
|
||||
async #handleFunctionCallChat({ messages = [] }) {
|
||||
return await this.client.chat.completions
|
||||
.create({
|
||||
|
||||
@ -227,6 +227,8 @@ class EphemeralAgentHandler extends AgentHandler {
|
||||
}
|
||||
|
||||
// Load flow plugin. This is marked by `@@flow_` in the array of functions to load.
|
||||
// Replace the @@flow_ placeholder in the agent's function list with the actual
|
||||
// tool name so the function lookup in reply() can find it.
|
||||
if (name.startsWith("@@flow_")) {
|
||||
const uuid = name.replace("@@flow_", "");
|
||||
const plugin = AgentFlows.loadFlowPlugin(uuid, this.aibitat);
|
||||
@ -237,6 +239,11 @@ class EphemeralAgentHandler extends AgentHandler {
|
||||
continue;
|
||||
}
|
||||
|
||||
this.aibitat.agents.get("@agent").functions = this.aibitat.agents
|
||||
.get("@agent")
|
||||
.functions.filter((f) => f !== name);
|
||||
this.aibitat.agents.get("@agent").functions.push(plugin.name);
|
||||
|
||||
this.aibitat.use(plugin.plugin());
|
||||
this.log(
|
||||
`Attached flow ${plugin.name} (${plugin.flowName}) plugin to Agent cluster`
|
||||
|
||||
@ -458,6 +458,8 @@ class AgentHandler {
|
||||
}
|
||||
|
||||
// Load flow plugin. This is marked by `@@flow_` in the array of functions to load.
|
||||
// Replace the @@flow_ placeholder in the agent's function list with the actual
|
||||
// tool name so the function lookup in reply() can find it.
|
||||
if (name.startsWith("@@flow_")) {
|
||||
const uuid = name.replace("@@flow_", "");
|
||||
const plugin = AgentFlows.loadFlowPlugin(uuid, this.aibitat);
|
||||
@ -468,6 +470,11 @@ class AgentHandler {
|
||||
continue;
|
||||
}
|
||||
|
||||
this.aibitat.agents.get("@agent").functions = this.aibitat.agents
|
||||
.get("@agent")
|
||||
.functions.filter((f) => f !== name);
|
||||
this.aibitat.agents.get("@agent").functions.push(plugin.name);
|
||||
|
||||
this.aibitat.use(plugin.plugin());
|
||||
this.log(
|
||||
`Attached flow ${plugin.name} (${plugin.flowName}) plugin to Agent cluster`
|
||||
|
||||
@ -1303,6 +1303,9 @@ function dumpENV() {
|
||||
|
||||
// Allow disabling of streaming for AWS Bedrock
|
||||
"AWS_BEDROCK_STREAMING_DISABLED",
|
||||
|
||||
// Allow native tool calling for specific providers.
|
||||
"PROVIDER_SUPPORTS_NATIVE_TOOL_CALLING",
|
||||
];
|
||||
|
||||
// Simple sanitization of each value to prevent ENV injection via newline or quote escaping.
|
||||
|
||||
Loading…
Reference in New Issue
Block a user