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4
README.md
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@ -49,6 +49,8 @@ You can configure the agent's name, model, and prompts in their profile like `an
| Qwen | `QWEN_API_KEY` | `qwen-max` | [Intl.](https://www.alibabacloud.com/help/en/model-studio/developer-reference/use-qwen-by-calling-api)/[cn](https://help.aliyun.com/zh/model-studio/getting-started/models) |
| Mistral | `MISTRAL_API_KEY` | `mistral-large-latest` | [docs](https://docs.mistral.ai/getting-started/models/models_overview/) |
| xAI | `XAI_API_KEY` | `grok-beta` | [docs](https://docs.x.ai/docs) |
| Deepseek | `DEEPSEEK_API_KEY` | `deepseek-chat` | [docs](https://api-docs.deepseek.com/) |
| Openrouter | `OPENROUTER_API_KEY` | `openrouter/anthropic/claude-3.5-sonnet` | [docs](https://openrouter.ai/models) |
| glhf.chat | `GHLF_API_KEY` | `hf:meta-llama/Llama-3.1-405B-Instruct` | [docs](https://glhf.chat/user-settings/api) |
| Hyperbolic | `HYPERBOLIC_API_KEY` | `hb:deepseek-ai/DeepSeek-V3` | [docs](https://docs.hyperbolic.xyz/docs/getting-started) |
@ -133,7 +135,7 @@ All apis have default models and urls, so those fields are optional. The `params
Embedding models are used to embed and efficiently select relevant examples for conversation and coding.
Supported Embedding APIs: `openai`, `google`, `replicate`, `huggingface`, `groq`, `novita`
Supported Embedding APIs: `openai`, `google`, `replicate`, `huggingface`, `novita`
If you try to use an unsupported model, then it will default to a simple word-overlap method. Expect reduced performance, recommend mixing APIs to ensure embedding support.

4
keys.example.json
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@ -11,5 +11,7 @@
"MISTRAL_API_KEY": "",
"DEEPSEEK_API_KEY": "",
"GHLF_API_KEY": "",
"HYPERBOLIC_API_KEY": ""
"HYPERBOLIC_API_KEY": "",
"NOVITA_API_KEY": "",
"OPENROUTER_API_KEY": ""
}

19
src/agent/library/skill_library.js
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@ -13,13 +13,18 @@ export class SkillLibrary {
const skillDocs = getSkillDocs();
this.skill_docs = skillDocs;
if (this.embedding_model) {
const embeddingPromises = skillDocs.map((doc) => {
return (async () => {
let func_name_desc = doc.split('\n').slice(0, 2).join('');
this.skill_docs_embeddings[doc] = await this.embedding_model.embed(func_name_desc);
})();
});
await Promise.all(embeddingPromises);
try {
const embeddingPromises = skillDocs.map((doc) => {
return (async () => {
let func_name_desc = doc.split('\n').slice(0, 2).join('');
this.skill_docs_embeddings[doc] = await this.embedding_model.embed(func_name_desc);
})();
});
await Promise.all(embeddingPromises);
} catch (error) {
console.warn('Error with embedding model, using word-overlap instead.');
this.embedding_model = null;
}
}
}

58
src/models/openrouter.js Normal file
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@ -0,0 +1,58 @@
import OpenAIApi from 'openai';
import { getKey, hasKey } from '../utils/keys.js';
import { strictFormat } from '../utils/text.js';
export class OpenRouter {
constructor(model_name, url) {
this.model_name = model_name;
let config = {};
config.baseURL = url || 'https://openrouter.ai/api/v1';
const apiKey = getKey('OPENROUTER_API_KEY');
if (!apiKey) {
console.error('Error: OPENROUTER_API_KEY not found. Make sure it is set properly.');
}
// Pass the API key to OpenAI compatible Api
config.apiKey = apiKey;
this.openai = new OpenAIApi(config);
}
async sendRequest(turns, systemMessage, stop_seq='*') {
let messages = [{ role: 'system', content: systemMessage }, ...turns];
messages = strictFormat(messages);
// Choose a valid model from openrouter.ai (for example, "openai/gpt-4o")
const pack = {
model: this.model_name,
messages,
stop: stop_seq
};
let res = null;
try {
console.log('Awaiting openrouter api response...');
let completion = await this.openai.chat.completions.create(pack);
if (!completion?.choices?.[0]) {
console.error('No completion or choices returned:', completion);
return 'No response received.';
}
if (completion.choices[0].finish_reason === 'length') {
throw new Error('Context length exceeded');
}
console.log('Received.');
res = completion.choices[0].message.content;
} catch (err) {
console.error('Error while awaiting response:', err);
// If the error indicates a context-length problem, we can slice the turns array, etc.
res = 'My brain disconnected, try again.';
}
return res;
}
async embed(text) {
throw new Error('Embeddings are not supported by Openrouter.');
}
}

25
src/models/prompter.js
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@ -21,6 +21,7 @@ import { Grok } from "./grok.js";
import { DeepSeek } from './deepseek.js';
import { hyperbolic } from './hyperbolic.js';
import { glhf } from './glhf.js';
import { OpenRouter } from './openrouter.js';
export class Prompter {
constructor(agent, fp) {
@ -94,8 +95,6 @@ export class Prompter {
this.embedding_model = new Mistral(embedding.model, embedding.url);
else if (embedding.api === 'huggingface')
this.embedding_model = new HuggingFace(embedding.model, embedding.url);
else if (embedding.api === 'groq')
this.embedding_model = new GroqCloudAPI(embedding.model, embedding.url);
else if (embedding.api === 'novita')
this.embedding_model = new Novita(embedding.model, embedding.url);
else {
@ -126,6 +125,8 @@ export class Prompter {
if (!profile.api) {
if (profile.model.includes('gemini'))
profile.api = 'google';
else if (profile.model.includes('openrouter/'))
profile.api = 'openrouter'; // must do before others bc shares model names
else if (profile.model.includes('gpt') || profile.model.includes('o1')|| profile.model.includes('o3'))
profile.api = 'openai';
else if (profile.model.includes('claude'))
@ -150,8 +151,10 @@ export class Prompter {
profile.api = 'xai';
else if (profile.model.includes('deepseek'))
profile.api = 'deepseek';
else
profile.api = 'ollama';
else if (profile.model.includes('llama3'))
profile.api = 'ollama';
else
throw new Error('Unknown model:', profile.model);
}
return profile;
}
@ -165,7 +168,7 @@ export class Prompter {
else if (profile.api === 'anthropic')
model = new Claude(profile.model, profile.url, profile.params);
else if (profile.api === 'replicate')
model = new ReplicateAPI(profile.model, profile.url, profile.params);
model = new ReplicateAPI(profile.model.replace('replicate/', ''), profile.url, profile.params);
else if (profile.api === 'ollama')
model = new Local(profile.model, profile.url, profile.params);
else if (profile.api === 'mistral')
@ -186,6 +189,8 @@ export class Prompter {
model = new Grok(profile.model, profile.url, profile.params);
else if (profile.api === 'deepseek')
model = new DeepSeek(profile.model, profile.url, profile.params);
else if (profile.api === 'openrouter')
model = new OpenRouter(profile.model.replace('openrouter/', ''), profile.url, profile.params);
else
throw new Error('Unknown API:', profile.api);
return model;
@ -209,12 +214,18 @@ export class Prompter {
this.convo_examples.load(this.profile.conversation_examples),
this.coding_examples.load(this.profile.coding_examples),
this.skill_libary.initSkillLibrary()
]);
]).catch(error => {
// Preserve error details
console.error('Failed to initialize examples. Error details:', error);
console.error('Stack trace:', error.stack);
throw error;
});
console.log('Examples initialized.');
} catch (error) {
console.error('Failed to initialize examples:', error);
throw error;
console.error('Stack trace:', error.stack);
throw error; // Re-throw with preserved details
}
}

2
src/utils/examples.js
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@ -38,7 +38,7 @@ export class Examples {
// Wait for all embeddings to complete
await Promise.all(embeddingPromises);
} catch (err) {
console.warn('Error with embedding model, using word overlap instead:', err);
console.warn('Error with embedding model, using word-overlap instead.');
this.model = null;
}
}