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cleaned up the LLM providers.

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This commit is contained in:
Xiaohan-Tian
2025-08-16 16:25:45 -07:00
parent cf4f3edb30
commit 429efaf629
6 changed files with 100 additions and 319 deletions
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src/agent/core/AgentCore.ts
-25
View File
@@ -93,31 +93,6 @@ export class AgentCore {
}
}
/**
* Process user input and get complete response (non-streaming)
*/
async processUserInputComplete(userInput: string): Promise<string> {
if (!this.llmProvider) {
throw new Error('No LLM provider configured');
}
// Add user message to state
this.agentState.addMessage('user', userInput);
// Get system prompt with current context
const systemPrompt = await SystemPrompts.getSystemPromptWithContext();
// Get full conversation history with preserved roles
const conversationHistory = this.agentState.getMessages();
// Generate complete response with full conversation context
const response = await this.llmProvider.generateCompletion(conversationHistory, systemPrompt);
// Add assistant response to state
this.agentState.addMessage('assistant', response.content);
return response.content;
}
/**
* Abort the current streaming request and clean up messages
src/agent/llm/ClaudeProvider.ts
+1 -68
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@@ -1,5 +1,5 @@
import { LLMProvider } from './LLMProvider';
import type { StreamChunk, LLMResponse } from './StreamingTypes';
import type { StreamChunk } from './StreamingTypes';
import type { Message } from '../core/AgentState';
import { ConfigManager } from '../../core/config/ConfigManager';
@@ -159,71 +159,4 @@ export class ClaudeProvider extends LLMProvider {
}
}
async generateCompletion(
messages: Message[],
systemPrompt?: string,
tools?: Record<string, unknown>[]
): Promise<LLMResponse> {
const { system, messages: claudeMessages } = this.convertMessages(messages, systemPrompt);
const requestBody: {
model: string;
max_tokens: number;
messages: Array<{ role: 'user' | 'assistant'; content: string }>;
stream: boolean;
system?: string;
tools?: Record<string, unknown>[];
} = {
model: this.model,
max_tokens: 8192,
messages: claudeMessages,
stream: false
};
if (system) {
requestBody.system = system;
}
if (tools && tools.length > 0) {
requestBody.tools = tools;
}
const response = await fetch(this.apiEndpoint, {
method: 'POST',
headers: {
'x-api-key': this.apiKey,
'Content-Type': 'application/json',
'anthropic-version': '2023-06-01'
},
body: JSON.stringify(requestBody),
mode: 'cors'
});
if (!response.ok) {
throw new Error(`Claude API error: ${response.status} ${response.statusText}`);
}
const data = await response.json();
// Extract content from Claude's response format
const content = data.content
?.filter((block: { type: string }) => block.type === 'text')
?.map((block: { text: string }) => block.text)
?.join('') || '';
// Extract tool calls if present
const toolCalls = data.content
?.filter((block: { type: string }) => block.type === 'tool_use')
?.map((block: { id: string; name: string; input: Record<string, unknown> }) => ({
id: block.id,
name: block.name,
parameters: block.input
})) || [];
return {
content,
toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
finished: data.stop_reason === 'end_turn' || data.stop_reason === 'tool_use'
};
}
}
src/agent/llm/GeminiProvider.ts
+1 -63
View File
@@ -1,5 +1,5 @@
import { LLMProvider } from './LLMProvider';
import type { StreamChunk, LLMResponse } from './StreamingTypes';
import type { StreamChunk } from './StreamingTypes';
import type { Message } from '../core/AgentState';
import { ConfigManager } from '../../core/config/ConfigManager';
@@ -180,66 +180,4 @@ export class GeminiProvider extends LLMProvider {
reader.releaseLock();
}
}
async generateCompletion(
messages: Message[],
systemPrompt?: string,
tools?: Record<string, unknown>[]
): Promise<LLMResponse> {
const { systemInstruction, contents } = this.convertMessages(messages, systemPrompt);
const requestBody: {
contents: Array<{ role: 'user' | 'model'; parts: Array<{ text: string }> }>;
generationConfig: { temperature: number; maxOutputTokens: number };
systemInstruction?: { parts: Array<{ text: string }> };
tools?: Record<string, unknown>[];
} = {
contents,
generationConfig: {
temperature: 0.7,
maxOutputTokens: 8192,
}
};
if (systemInstruction) {
requestBody.systemInstruction = systemInstruction;
}
if (tools && tools.length > 0) {
requestBody.tools = tools;
}
const response = await fetch(`${this.apiEndpoint}:generateContent?key=${this.apiKey}`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify(requestBody),
});
if (!response.ok) {
throw new Error(`Gemini API error: ${response.status} ${response.statusText}`);
}
const data = await response.json();
// Extract content from Gemini's response format
const candidate = data.candidates?.[0];
const content = candidate?.content?.parts?.[0]?.text || '';
// Extract tool calls if present (Gemini format)
const toolCalls = candidate?.content?.parts
?.filter((part: { functionCall?: unknown }) => part.functionCall)
?.map((part: { functionCall: { name: string; args: Record<string, unknown> } }) => ({
id: `tool_${Date.now()}_${Math.random().toString(36).substring(2, 9)}`, // Generate ID
name: part.functionCall.name,
parameters: part.functionCall.args
})) || [];
return {
content,
toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
finished: candidate?.finishReason === 'STOP' || candidate?.finishReason === 'MAX_TOKENS'
};
}
}
src/agent/llm/LLMProvider.ts
+1 -13
View File
@@ -1,4 +1,4 @@
import type { StreamChunk, LLMResponse } from './StreamingTypes';
import type { StreamChunk } from './StreamingTypes';
import type { Message } from '../core/AgentState';
/**
@@ -18,16 +18,4 @@ export abstract class LLMProvider {
systemPrompt?: string,
tools?: Record<string, unknown>[]
): AsyncIterableIterator<StreamChunk>;
/**
* Generate a complete response from the LLM (non-streaming)
* @param messages The full conversation history with preserved roles
* @param systemPrompt The system prompt (optional, can be included in messages)
* @param tools Available tools (optional for now)
*/
abstract generateCompletion(
messages: Message[],
systemPrompt?: string,
tools?: Record<string, unknown>[]
): Promise<LLMResponse>;
}
src/agent/llm/OpenAIProvider.ts
+86 -149
View File
@@ -1,8 +1,9 @@
import { LLMProvider } from './LLMProvider';
import type { StreamChunk, LLMResponse } from './StreamingTypes';
import type { StreamChunk } from './StreamingTypes';
import type { Message } from '../core/AgentState';
import { ConfigManager } from '../../core/config/ConfigManager';
import { URL_CONSTANTS } from '../../constants/coreConstants';
import { LLM_PROTOCOL } from '../../constants/llmConstants';
/**
* OpenAI API provider implementation
@@ -16,6 +17,78 @@ export class OpenAIProvider extends LLMProvider {
super();
}
/**
* Build OpenAI-compatible messages array from input messages and system prompt
*/
private buildRequestMessages(messages: Message[], systemPrompt?: string): Array<{ role: string; content: string }> {
const openAIMessages: Array<{ role: string; content: string }> = [];
// Add system prompt if provided
if (systemPrompt) {
openAIMessages.push({ role: 'system', content: systemPrompt });
}
// Add conversation history with preserved roles
openAIMessages.push(...messages.map(msg => ({
role: msg.role,
content: msg.content
})));
return openAIMessages;
}
/**
* Create API request with proper headers and body
*/
private async createApiRequest(messages: Array<{ role: string; content: string }>, config: ReturnType<typeof this.getCurrentConfig>, streaming: boolean): Promise<Response> {
const response = await fetch(config.apiEndpoint, {
method: 'POST',
headers: {
'Authorization': `Bearer ${config.apiKey}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: config.model,
...(config.flexMode && !config.isCompatibleProvider ? { service_tier: 'flex' } : {}),
messages,
stream: streaming,
}),
});
if (!response.ok) {
const errorText = await response.text().catch(() => 'Unknown error');
throw new Error(`${this.name} API request failed (${response.status}): ${response.statusText}. ${errorText}`);
}
return response;
}
/**
* Process thinking and content chunks, yielding appropriate StreamChunks
*/
private async *processContentChunk(
thinking: string | undefined,
content: string | undefined,
lastSegmentType: { current: 'thinking' | 'content' | null }
): AsyncIterableIterator<StreamChunk> {
if (typeof thinking === 'string' && thinking.length > 0) {
if (lastSegmentType.current && lastSegmentType.current !== 'thinking') {
yield { type: 'text', content: LLM_PROTOCOL.SEGMENT_SEPARATOR };
}
yield { type: 'text', content: thinking };
lastSegmentType.current = 'thinking';
}
if (typeof content === 'string' && content.length > 0) {
if (lastSegmentType.current && lastSegmentType.current !== 'content') {
yield { type: 'text', content: LLM_PROTOCOL.SEGMENT_SEPARATOR };
}
yield { type: 'text', content: content };
lastSegmentType.current = 'content';
}
}
/**
* Get current configuration values from ConfigManager
*/
@@ -50,7 +123,7 @@ export class OpenAIProvider extends LLMProvider {
*/
private detectStreamFormat(firstChunk: string): boolean {
// If it starts with "data: ", it's OpenAI SSE format
if (firstChunk.trim().startsWith('data: ')) {
if (firstChunk.trim().startsWith(LLM_PROTOCOL.SSE_DATA_PREFIX)) {
return false; // Not Ollama format
}
@@ -85,12 +158,12 @@ export class OpenAIProvider extends LLMProvider {
* Parse OpenAI's SSE format chunk
*/
private parseOpenAIChunk(line: string): { thinking?: string; content?: string; isDone?: boolean } {
if (!line.startsWith('data: ')) {
if (!line.startsWith(LLM_PROTOCOL.SSE_DATA_PREFIX)) {
return {};
}
const data = line.slice(6);
if (data === '[DONE]') {
const data = line.slice(LLM_PROTOCOL.SSE_DATA_PREFIX.length);
if (data === LLM_PROTOCOL.SSE_DONE_MARKER) {
return { isDone: true };
}
@@ -109,51 +182,19 @@ export class OpenAIProvider extends LLMProvider {
messages: Message[],
systemPrompt?: string
): AsyncIterableIterator<StreamChunk> {
// Get fresh config values
const config = this.getCurrentConfig();
// Build OpenAI messages array with role preservation
const openAIMessages: Array<{ role: string; content: string }> = [];
// Add system prompt if provided
if (systemPrompt) {
openAIMessages.push({ role: 'system', content: systemPrompt });
}
// Add conversation history with preserved roles
openAIMessages.push(...messages.map(msg => ({
role: msg.role,
content: msg.content
})));
const response = await fetch(config.apiEndpoint, {
method: 'POST',
headers: {
'Authorization': `Bearer ${config.apiKey}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: config.model,
...(config.flexMode && !config.isCompatibleProvider ? { service_tier: 'flex' } : {}),
messages: openAIMessages,
stream: true,
}),
});
if (!response.ok) {
throw new Error(`OpenAI API error: ${response.status} ${response.statusText}`);
}
const requestMessages = this.buildRequestMessages(messages, systemPrompt);
const response = await this.createApiRequest(requestMessages, config, true);
const reader = response.body?.getReader();
if (!reader) {
throw new Error('Failed to get response reader');
throw new Error(`${this.name} streaming: Failed to get response reader from API response`);
}
const decoder = new TextDecoder();
let buffer = '';
let firstChunkProcessed = false;
let lastSegmentType: 'thinking' | 'content' | null = null;
const lastSegmentType = { current: null as 'thinking' | 'content' | null };
try {
while (true) {
@@ -177,124 +218,20 @@ export class OpenAIProvider extends LLMProvider {
firstChunkProcessed = true;
}
if (this.isOllamaFormat) {
const { thinking, content, isDone } = this.parseOllamaChunk(trimmedLine);
if (isDone) {
yield { type: 'done', content: '' };
return;
}
const { thinking, content, isDone } = this.isOllamaFormat
? this.parseOllamaChunk(trimmedLine)
: this.parseOpenAIChunk(trimmedLine);
if (typeof thinking === 'string' && thinking.length > 0) {
if (lastSegmentType && lastSegmentType !== 'thinking') {
yield { type: 'text', content: '\n\n' };
}
yield { type: 'text', content: thinking };
lastSegmentType = 'thinking';
}
if (typeof content === 'string' && content.length > 0) {
if (lastSegmentType && lastSegmentType !== 'content') {
yield { type: 'text', content: '\n\n' };
}
yield { type: 'text', content: content };
lastSegmentType = 'content';
}
continue;
}
const { thinking, content, isDone } = this.parseOpenAIChunk(trimmedLine);
if (isDone) {
yield { type: 'done', content: '' };
return;
}
if (typeof thinking === 'string' && thinking.length > 0) {
if (lastSegmentType && lastSegmentType !== 'thinking') {
yield { type: 'text', content: '\n\n' };
}
yield { type: 'text', content: thinking };
lastSegmentType = 'thinking';
}
if (typeof content === 'string' && content.length > 0) {
if (lastSegmentType && lastSegmentType !== 'content') {
yield { type: 'text', content: '\n\n' };
}
yield { type: 'text', content };
lastSegmentType = 'content';
}
yield* this.processContentChunk(thinking, content, lastSegmentType);
}
}
} finally {
reader.releaseLock();
}
}
async generateCompletion(
messages: Message[],
systemPrompt?: string
): Promise<LLMResponse> {
// Get fresh config values
const config = this.getCurrentConfig();
// Build OpenAI messages array with role preservation
const openAIMessages: Array<{ role: string; content: string }> = [];
// Add system prompt if provided
if (systemPrompt) {
openAIMessages.push({ role: 'system', content: systemPrompt });
}
// Add conversation history with preserved roles
openAIMessages.push(...messages.map(msg => ({
role: msg.role,
content: msg.content
})));
const response = await fetch(config.apiEndpoint, {
method: 'POST',
headers: {
'Authorization': `Bearer ${config.apiKey}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: config.model,
...(config.flexMode && !config.isCompatibleProvider ? { service_tier: 'flex' } : {}),
messages: openAIMessages,
stream: false,
}),
});
if (!response.ok) {
throw new Error(`OpenAI API error: ${response.status} ${response.statusText}`);
}
const data = await response.json();
// Handle different response formats
if (data.message) {
// Ollama/compatible format
const thinking: string = data.message.thinking || '';
const contentText: string = data.message.content || data.response || '';
const textCombined = thinking && contentText ? `${thinking}\n\n${contentText}` : (thinking || contentText);
return {
content: textCombined,
finished: data.done === true || data.done_reason === 'stop'
};
} else {
// OpenAI format
const choice = data.choices?.[0];
const thinking: string = choice?.message?.thinking || '';
const contentText: string = choice?.message?.content || '';
const textCombined = thinking && contentText ? `${thinking}\n\n${contentText}` : (thinking || contentText);
return {
content: textCombined,
finished: choice?.finish_reason === 'stop'
};
}
}
}
src/constants/llmConstants.ts
+10
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@@ -0,0 +1,10 @@
/**
* Constants related to LLM providers and API interactions
*/
// Protocol markers and special character combinations used in LLM communications
export const LLM_PROTOCOL = {
SSE_DATA_PREFIX: 'data: ',
SSE_DONE_MARKER: '[DONE]',
SEGMENT_SEPARATOR: '\n\n'
} as const;