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JavaScript
import { BaseProvider } from "../core/baseProvider.js";
import { logger } from "../utils/logger.js";
import { TimeoutError } from "../utils/timeout.js";
import { DEFAULT_MAX_TOKENS } from "../core/constants.js";
// Model version constants (configurable via environment)
const DEFAULT_OLLAMA_MODEL = "llama3.1:8b";
const FALLBACK_OLLAMA_MODEL = "llama3.2:latest"; // Used when primary model fails
// Configuration helpers
const getOllamaBaseUrl = () => {
return process.env.OLLAMA_BASE_URL || "http://localhost:11434";
};
// Create AbortController with timeout for better compatibility
const createAbortSignalWithTimeout = (timeoutMs) => {
const controller = new AbortController();
const timeoutId = setTimeout(() => controller.abort(), timeoutMs);
// Clear timeout if signal is aborted through other means
controller.signal.addEventListener("abort", () => {
clearTimeout(timeoutId);
});
return controller.signal;
};
const getDefaultOllamaModel = () => {
return process.env.OLLAMA_MODEL || DEFAULT_OLLAMA_MODEL;
};
const getOllamaTimeout = () => {
return parseInt(process.env.OLLAMA_TIMEOUT || "60000", 10);
};
// Custom LanguageModelV1 implementation for Ollama
class OllamaLanguageModel {
specificationVersion = "v1";
provider = "ollama";
modelId;
maxTokens;
supportsStreaming = true;
defaultObjectGenerationMode = "json";
baseUrl;
timeout;
constructor(modelId, baseUrl, timeout) {
this.modelId = modelId;
this.baseUrl = baseUrl;
this.timeout = timeout;
}
estimateTokens(text) {
return Math.ceil(text.length / 4);
}
convertMessagesToPrompt(messages) {
return messages
.map((msg) => {
if (typeof msg.content === "string") {
return `${msg.role}: ${msg.content}`;
}
return `${msg.role}: ${JSON.stringify(msg.content)}`;
})
.join("\n");
}
async doGenerate(options) {
const messages = options
.messages || [];
const prompt = this.convertMessagesToPrompt(messages);
// Debug: Log what's being sent to Ollama
logger.debug("[OllamaLanguageModel] Messages:", JSON.stringify(messages, null, 2));
logger.debug("[OllamaLanguageModel] Converted Prompt:", JSON.stringify(prompt));
const response = await fetch(`${this.baseUrl}/api/generate`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
model: this.modelId,
prompt,
stream: false,
system: messages.find((m) => m.role === "system")?.content,
options: {
temperature: options.temperature,
num_predict: options.maxTokens,
},
}),
signal: createAbortSignalWithTimeout(this.timeout),
});
if (!response.ok) {
throw new Error(`Ollama API error: ${response.status} ${response.statusText}`);
}
const data = await response.json();
// Debug: Log Ollama API response to understand empty content issue
logger.debug("[OllamaLanguageModel] API Response:", JSON.stringify(data, null, 2));
return {
text: data.response,
usage: {
promptTokens: data.prompt_eval_count || this.estimateTokens(prompt),
completionTokens: data.eval_count || this.estimateTokens(data.response),
totalTokens: (data.prompt_eval_count || this.estimateTokens(prompt)) +
(data.eval_count || this.estimateTokens(data.response)),
},
finishReason: "stop",
rawCall: {
rawPrompt: prompt,
rawSettings: {
model: this.modelId,
temperature: options.temperature,
num_predict: options.maxTokens,
},
},
rawResponse: {
headers: {},
},
};
}
async doStream(options) {
const messages = options
.messages || [];
const prompt = this.convertMessagesToPrompt(messages);
const response = await fetch(`${this.baseUrl}/api/generate`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
model: this.modelId,
prompt,
stream: true,
system: messages.find((m) => m.role === "system")?.content,
options: {
temperature: options.temperature,
num_predict: options.maxTokens,
},
}),
signal: createAbortSignalWithTimeout(this.timeout),
});
if (!response.ok) {
throw new Error(`Ollama API error: ${response.status} ${response.statusText}`);
}
const self = this;
return {
stream: new ReadableStream({
async start(controller) {
try {
for await (const chunk of self.parseStreamResponse(response)) {
controller.enqueue(chunk);
}
controller.close();
}
catch (error) {
controller.error(error);
}
},
}),
rawCall: {
rawPrompt: prompt,
rawSettings: {
model: this.modelId,
temperature: options.temperature,
num_predict: options.maxTokens,
},
},
rawResponse: {
headers: {},
},
};
}
async *parseStreamResponse(response) {
const reader = response.body?.getReader();
if (!reader) {
throw new Error("No response body");
}
const decoder = new TextDecoder();
let buffer = "";
try {
while (true) {
const { done, value } = await reader.read();
if (done) {
break;
}
buffer += decoder.decode(value, { stream: true });
const lines = buffer.split("\n");
buffer = lines.pop() || "";
for (const line of lines) {
if (line.trim()) {
try {
const data = JSON.parse(line);
if (data.response) {
yield {
type: "text-delta",
textDelta: data.response,
};
}
if (data.done) {
yield {
type: "finish",
finishReason: "stop",
usage: {
promptTokens: data.prompt_eval_count ||
this.estimateTokens(data.context || ""),
completionTokens: data.eval_count || 0,
},
};
return;
}
}
catch (error) {
// Ignore JSON parse errors for incomplete chunks
}
}
}
}
}
finally {
reader.releaseLock();
}
}
}
/**
* Ollama Provider v2 - BaseProvider Implementation
*
* PHASE 3.7: BaseProvider wrap around existing custom Ollama implementation
*
* Features:
* - Extends BaseProvider for shared functionality
* - Preserves custom OllamaLanguageModel implementation
* - Local model management and health checking
* - Enhanced error handling with Ollama-specific guidance
*/
export class OllamaProvider extends BaseProvider {
ollamaModel;
baseUrl;
timeout;
constructor(modelName) {
super(modelName, "ollama");
this.baseUrl = getOllamaBaseUrl();
this.timeout = getOllamaTimeout();
// Initialize Ollama model
this.ollamaModel = new OllamaLanguageModel(this.modelName || getDefaultOllamaModel(), this.baseUrl, this.timeout);
logger.debug("Ollama BaseProvider v2 initialized", {
modelName: this.modelName,
baseUrl: this.baseUrl,
timeout: this.timeout,
provider: this.providerName,
});
}
getProviderName() {
return "ollama";
}
getDefaultModel() {
return getDefaultOllamaModel();
}
/**
* Returns the Vercel AI SDK model instance for Ollama
* The OllamaLanguageModel implements LanguageModelV1 interface properly
*/
getAISDKModel() {
return this.ollamaModel;
}
/**
* Ollama tool/function calling support is currently disabled due to integration issues.
*
* **Current Issues:**
* 1. The OllamaLanguageModel from @ai-sdk/provider-utils doesn't properly integrate
* with BaseProvider's tool calling mechanism
* 2. Ollama models require specific prompt formatting for function calls that differs
* from the standardized AI SDK format
* 3. Tool response parsing and execution flow needs custom implementation
*
* **What's needed to enable tool support:**
* - Create a custom OllamaLanguageModel wrapper that handles tool schema formatting
* - Implement Ollama-specific tool calling prompt templates
* - Add proper response parsing for Ollama's function call format
* - Test with models that support function calling (llama3.1, mistral, etc.)
*
* **Tracking:**
* - See BaseProvider tool integration patterns in other providers
* - Monitor Ollama function calling documentation: https://ollama.com/blog/tool-support
* - Track AI SDK updates for better Ollama integration
*
* @returns false to disable tools by default
*/
supportsTools() {
// IMPLEMENTATION STATUS (2025): Ollama function calling actively evolving
//
// Current State:
// - Function calling added in Ollama 2024, improving in 2025
// - Requires compatible models (Llama 3.1+, Code Llama variants)
// - AI SDK integration needs custom adapter for Ollama's tool format
//
// Technical Requirements:
// 1. Replace AI SDK with direct Ollama API tool calls
// 2. Implement Ollama-specific tool schema conversion
// 3. Add function response parsing from Ollama's JSON format
// 4. Handle streaming tool calls with incremental parsing
// 5. Validate model compatibility before enabling tools
//
// Implementation Path:
// - Use Ollama's chat API with 'tools' parameter
// - Parse tool_calls from response.message.tool_calls
// - Execute functions and return results to conversation
//
// Until Ollama-specific implementation, tools disabled for compatibility
return false;
}
// executeGenerate removed - BaseProvider handles all generation with tools
async executeStream(options, analysisSchema) {
try {
this.validateStreamOptions(options);
await this.checkOllamaHealth();
// Direct HTTP streaming implementation for better compatibility
const response = await fetch(`${this.baseUrl}/api/generate`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
model: this.modelName || FALLBACK_OLLAMA_MODEL,
prompt: options.input.text,
system: options.systemPrompt,
stream: true,
options: {
temperature: options.temperature,
num_predict: options.maxTokens || DEFAULT_MAX_TOKENS,
},
}),
signal: createAbortSignalWithTimeout(this.timeout),
});
if (!response.ok) {
throw new Error(`Ollama API error: ${response.status} ${response.statusText}`);
}
// Transform to async generator to match other providers
const self = this;
const transformedStream = async function* () {
const generator = self.createOllamaStream(response);
for await (const chunk of generator) {
yield chunk;
}
};
return {
stream: transformedStream(),
provider: this.providerName,
model: this.modelName,
};
}
catch (error) {
throw this.handleProviderError(error);
}
}
async *createOllamaStream(response) {
const reader = response.body?.getReader();
if (!reader) {
throw new Error("No response body");
}
const decoder = new TextDecoder();
let buffer = "";
try {
while (true) {
const { done, value } = await reader.read();
if (done) {
break;
}
buffer += decoder.decode(value, { stream: true });
const lines = buffer.split("\n");
buffer = lines.pop() || "";
for (const line of lines) {
if (line.trim()) {
try {
const data = JSON.parse(line);
if (data.response) {
yield { content: data.response };
}
if (data.done) {
return;
}
}
catch (error) {
// Ignore JSON parse errors for incomplete chunks
}
}
}
}
}
finally {
reader.releaseLock();
}
}
handleProviderError(error) {
if (error.name === "TimeoutError") {
return new TimeoutError(`Ollama request timed out. The model might be loading or the request is too complex.`, this.defaultTimeout);
}
if (error.message?.includes("ECONNREFUSED") ||
error.message?.includes("fetch failed")) {
return new Error(`ā Ollama Service Not Running\n\nCannot connect to Ollama at ${this.baseUrl}\n\nš§ Steps to Fix:\n1. Install Ollama: https://ollama.ai/\n2. Start Ollama service: 'ollama serve'\n3. Verify it's running: 'curl ${this.baseUrl}/api/version'\n4. Try again`);
}
if (error.message?.includes("model") &&
error.message?.includes("not found")) {
return new Error(`ā Ollama Model Not Found\n\nModel '${this.modelName}' is not available locally.\n\nš§ Install Model:\n1. Run: ollama pull ${this.modelName}\n2. Or try a different model:\n - ollama pull ${FALLBACK_OLLAMA_MODEL}\n - ollama pull mistral:latest\n - ollama pull codellama:latest\n\nš§ List Available Models:\nollama list`);
}
if (error.message?.includes("404")) {
return new Error(`ā Ollama API Endpoint Not Found\n\nThe API endpoint might have changed or Ollama version is incompatible.\n\nš§ Check:\n1. Ollama version: 'ollama --version'\n2. Update Ollama to latest version\n3. Verify API is available: 'curl ${this.baseUrl}/api/version'`);
}
return new Error(`ā Ollama Provider Error\n\n${error.message || "Unknown error occurred"}\n\nš§ Troubleshooting:\n1. Check if Ollama service is running\n2. Verify model is installed: 'ollama list'\n3. Check network connectivity to ${this.baseUrl}\n4. Review Ollama logs for details`);
}
validateStreamOptions(options) {
if (!options.input?.text?.trim()) {
throw new Error("Prompt is required for streaming");
}
if (options.maxTokens && options.maxTokens < 1) {
throw new Error("maxTokens must be greater than 0");
}
if (options.temperature &&
(options.temperature < 0 || options.temperature > 2)) {
throw new Error("temperature must be between 0 and 2");
}
}
/**
* Check if Ollama service is healthy and accessible
*/
async checkOllamaHealth() {
try {
// Use traditional AbortController for better compatibility
const controller = new AbortController();
const timeoutId = setTimeout(() => controller.abort(), 5000);
const response = await fetch(`${this.baseUrl}/api/version`, {
method: "GET",
signal: controller.signal,
});
clearTimeout(timeoutId);
if (!response.ok) {
throw new Error(`Ollama health check failed: ${response.status}`);
}
}
catch (error) {
if (error instanceof Error && error.message.includes("ECONNREFUSED")) {
throw new Error(`ā Ollama Service Not Running\n\nCannot connect to Ollama service.\n\nš§ Start Ollama:\n1. Run: ollama serve\n2. Or start Ollama app\n3. Verify: curl ${this.baseUrl}/api/version`);
}
throw error;
}
}
/**
* Get available models from Ollama
*/
async getAvailableModels() {
try {
const response = await fetch(`${this.baseUrl}/api/tags`);
if (!response.ok) {
throw new Error(`Failed to fetch models: ${response.status}`);
}
const data = await response.json();
return data.models?.map((model) => model.name) || [];
}
catch (error) {
logger.warn("Failed to fetch Ollama models:", error);
return [];
}
}
/**
* Check if a specific model is available
*/
async isModelAvailable(modelName) {
const models = await this.getAvailableModels();
return models.includes(modelName);
}
}
export default OllamaProvider;