mirror of
https://github.com/danny-avila/LibreChat.git
synced 2025-12-17 08:50:15 +01:00
* refactor: pass model in message edit payload, use encoder in standalone util function * feat: add summaryBuffer helper * refactor(api/messages): use new countTokens helper and add auth middleware at top * wip: ConversationSummaryBufferMemory * refactor: move pre-generation helpers to prompts dir * chore: remove console log * chore: remove test as payload will no longer carry tokenCount * chore: update getMessagesWithinTokenLimit JSDoc * refactor: optimize getMessagesForConversation and also break on summary, feat(ci): getMessagesForConversation tests * refactor(getMessagesForConvo): count '00000000-0000-0000-0000-000000000000' as root message * chore: add newer model to token map * fix: condition was point to prop of array instead of message prop * refactor(BaseClient): use object for refineMessages param, rename 'summary' to 'summaryMessage', add previous_summary refactor(getMessagesWithinTokenLimit): replace text and tokenCount if should summarize, summary, and summaryTokenCount are present fix/refactor(handleContextStrategy): use the right comparison length for context diff, and replace payload first message when a summary is present * chore: log previous_summary if debugging * refactor(formatMessage): assume if role is defined that it's a valid value * refactor(getMessagesWithinTokenLimit): remove summary logic refactor(handleContextStrategy): add usePrevSummary logic in case only summary was pruned refactor(loadHistory): initial message query will return all ordered messages but keep track of the latest summary refactor(getMessagesForConversation): use object for single param, edit jsdoc, edit all files using the method refactor(ChatGPTClient): order messages before buildPrompt is called, TODO: add convoSumBuffMemory logic * fix: undefined handling and summarizing only when shouldRefineContext is true * chore(BaseClient): fix test results omitting system role for summaries and test edge case * chore: export summaryBuffer from index file * refactor(OpenAIClient/BaseClient): move refineMessages to subclass, implement LLM initialization for summaryBuffer * feat: add OPENAI_SUMMARIZE to enable summarizing, refactor: rename client prop 'shouldRefineContext' to 'shouldSummarize', change contextStrategy value to 'summarize' from 'refine' * refactor: rename refineMessages method to summarizeMessages for clarity * chore: clarify summary future intent in .env.example * refactor(initializeLLM): handle case for either 'model' or 'modelName' being passed * feat(gptPlugins): enable summarization for plugins * refactor(gptPlugins): utilize new initializeLLM method and formatting methods for messages, use payload array for currentMessages and assign pastMessages sooner * refactor(agents): use ConversationSummaryBufferMemory for both agent types * refactor(formatMessage): optimize original method for langchain, add helper function for langchain messages, add JSDocs and tests * refactor(summaryBuffer): add helper to createSummaryBufferMemory, and use new formatting helpers * fix: forgot to spread formatMessages also took opportunity to pluralize filename * refactor: pass memory to tools, namely openapi specs. not used and may never be used by new method but added for testing * ci(formatMessages): add more exhaustive checks for langchain messages * feat: add debug env var for OpenAI * chore: delete unnecessary comments * chore: add extra note about summary feature * fix: remove tokenCount from payload instructions * fix: test fail * fix: only pass instructions to payload when defined or not empty object * refactor: fromPromptMessages is deprecated, use renamed method fromMessages * refactor: use 'includes' instead of 'startsWith' for extended OpenRouter compatibility * fix(PluginsClient.buildPromptBody): handle undefined message strings * chore: log langchain titling error * feat: getModelMaxTokens helper * feat: tokenSplit helper * feat: summary prompts updated * fix: optimize _CUT_OFF_SUMMARIZER prompt * refactor(summaryBuffer): use custom summary prompt, allow prompt to be passed, pass humanPrefix and aiPrefix to memory, along with any future variables, rename messagesToRefine to context * fix(summaryBuffer): handle edge case where messagesToRefine exceeds summary context, refactor(BaseClient): allow custom maxContextTokens to be passed to getMessagesWithinTokenLimit, add defined check before unshifting summaryMessage, update shouldSummarize based on this refactor(OpenAIClient): use getModelMaxTokens, use cut-off message method for summary if no messages were left after pruning * fix(handleContextStrategy): handle case where incoming prompt is bigger than model context * chore: rename refinedContent to splitText * chore: remove unnecessary debug log
160 lines
4.2 KiB
JavaScript
160 lines
4.2 KiB
JavaScript
const { formatMessage, formatLangChainMessages } = require('./formatMessages'); // Adjust the path accordingly
|
|
const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
|
|
|
|
describe('formatMessage', () => {
|
|
it('formats user message', () => {
|
|
const input = {
|
|
message: {
|
|
sender: 'user',
|
|
text: 'Hello',
|
|
},
|
|
userName: 'John',
|
|
};
|
|
const result = formatMessage(input);
|
|
expect(result).toEqual({
|
|
role: 'user',
|
|
content: 'Hello',
|
|
name: 'John',
|
|
});
|
|
});
|
|
|
|
it('formats a realistic user message', () => {
|
|
const input = {
|
|
message: {
|
|
_id: '6512cdfb92cbf69fea615331',
|
|
messageId: 'b620bf73-c5c3-4a38-b724-76886aac24c4',
|
|
__v: 0,
|
|
cancelled: false,
|
|
conversationId: '5c23d24f-941f-4aab-85df-127b596c8aa5',
|
|
createdAt: Date.now(),
|
|
error: false,
|
|
finish_reason: null,
|
|
isCreatedByUser: true,
|
|
isEdited: false,
|
|
model: null,
|
|
parentMessageId: '00000000-0000-0000-0000-000000000000',
|
|
sender: 'User',
|
|
text: 'hi',
|
|
tokenCount: 5,
|
|
unfinished: false,
|
|
updatedAt: Date.now(),
|
|
user: '6512cdf475f05c86d44c31d2',
|
|
},
|
|
userName: 'John',
|
|
};
|
|
const result = formatMessage(input);
|
|
expect(result).toEqual({
|
|
role: 'user',
|
|
content: 'hi',
|
|
name: 'John',
|
|
});
|
|
});
|
|
|
|
it('formats assistant message', () => {
|
|
const input = {
|
|
message: {
|
|
sender: 'assistant',
|
|
text: 'Hi there',
|
|
},
|
|
assistantName: 'Assistant',
|
|
};
|
|
const result = formatMessage(input);
|
|
expect(result).toEqual({
|
|
role: 'assistant',
|
|
content: 'Hi there',
|
|
name: 'Assistant',
|
|
});
|
|
});
|
|
|
|
it('formats system message', () => {
|
|
const input = {
|
|
message: {
|
|
role: 'system',
|
|
text: 'Hi there',
|
|
},
|
|
};
|
|
const result = formatMessage(input);
|
|
expect(result).toEqual({
|
|
role: 'system',
|
|
content: 'Hi there',
|
|
});
|
|
});
|
|
|
|
it('formats user message with langChain', () => {
|
|
const input = {
|
|
message: {
|
|
sender: 'user',
|
|
text: 'Hello',
|
|
},
|
|
userName: 'John',
|
|
langChain: true,
|
|
};
|
|
const result = formatMessage(input);
|
|
expect(result).toBeInstanceOf(HumanMessage);
|
|
expect(result.lc_kwargs.content).toEqual(input.message.text);
|
|
expect(result.lc_kwargs.name).toEqual(input.userName);
|
|
});
|
|
|
|
it('formats assistant message with langChain', () => {
|
|
const input = {
|
|
message: {
|
|
sender: 'assistant',
|
|
text: 'Hi there',
|
|
},
|
|
assistantName: 'Assistant',
|
|
langChain: true,
|
|
};
|
|
const result = formatMessage(input);
|
|
expect(result).toBeInstanceOf(AIMessage);
|
|
expect(result.lc_kwargs.content).toEqual(input.message.text);
|
|
expect(result.lc_kwargs.name).toEqual(input.assistantName);
|
|
});
|
|
|
|
it('formats system message with langChain', () => {
|
|
const input = {
|
|
message: {
|
|
role: 'system',
|
|
text: 'This is a system message.',
|
|
},
|
|
langChain: true,
|
|
};
|
|
const result = formatMessage(input);
|
|
expect(result).toBeInstanceOf(SystemMessage);
|
|
expect(result.lc_kwargs.content).toEqual(input.message.text);
|
|
});
|
|
});
|
|
|
|
describe('formatLangChainMessages', () => {
|
|
it('formats an array of messages for LangChain', () => {
|
|
const messages = [
|
|
{
|
|
role: 'system',
|
|
content: 'This is a system message',
|
|
},
|
|
{
|
|
sender: 'user',
|
|
text: 'Hello',
|
|
},
|
|
{
|
|
sender: 'assistant',
|
|
text: 'Hi there',
|
|
},
|
|
];
|
|
const formatOptions = {
|
|
userName: 'John',
|
|
assistantName: 'Assistant',
|
|
};
|
|
const result = formatLangChainMessages(messages, formatOptions);
|
|
expect(result).toHaveLength(3);
|
|
expect(result[0]).toBeInstanceOf(SystemMessage);
|
|
expect(result[1]).toBeInstanceOf(HumanMessage);
|
|
expect(result[2]).toBeInstanceOf(AIMessage);
|
|
|
|
expect(result[0].lc_kwargs.content).toEqual(messages[0].content);
|
|
expect(result[1].lc_kwargs.content).toEqual(messages[1].text);
|
|
expect(result[2].lc_kwargs.content).toEqual(messages[2].text);
|
|
|
|
expect(result[1].lc_kwargs.name).toEqual(formatOptions.userName);
|
|
expect(result[2].lc_kwargs.name).toEqual(formatOptions.assistantName);
|
|
});
|
|
});
|