diff --git a/server/utils/AiProviders/anthropic/index.js b/server/utils/AiProviders/anthropic/index.js
index 6a8ad3c42..d5ee1f9d3 100644
--- a/server/utils/AiProviders/anthropic/index.js
+++ b/server/utils/AiProviders/anthropic/index.js
@@ -1,5 +1,4 @@
const { v4 } = require("uuid");
-const { chatPrompt } = require("../../chats");
const {
writeResponseChunk,
clientAbortedHandler,
@@ -33,7 +32,7 @@ class AnthropicLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
@@ -110,31 +109,6 @@ class AnthropicLLM {
}
}
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!this.isValidChatCompletionModel(this.model))
- throw new Error(
- `Anthropic chat: ${this.model} is not valid for chat completion!`
- );
-
- const messages = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- );
-
- const streamRequest = await this.anthropic.messages.stream({
- model: this.model,
- max_tokens: 4096,
- system: messages[0].content, // Strip out the system message
- messages: messages.slice(1), // Pop off the system message
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- });
- return streamRequest;
- }
-
async streamGetChatCompletion(messages = null, { temperature = 0.7 }) {
if (!this.isValidChatCompletionModel(this.model))
throw new Error(
diff --git a/server/utils/AiProviders/azureOpenAi/index.js b/server/utils/AiProviders/azureOpenAi/index.js
index 21fc5cd91..a2ab556db 100644
--- a/server/utils/AiProviders/azureOpenAi/index.js
+++ b/server/utils/AiProviders/azureOpenAi/index.js
@@ -1,5 +1,4 @@
const { AzureOpenAiEmbedder } = require("../../EmbeddingEngines/azureOpenAi");
-const { chatPrompt } = require("../../chats");
const {
writeResponseChunk,
clientAbortedHandler,
@@ -45,7 +44,7 @@ class AzureOpenAiLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
// Sure the user selected a proper value for the token limit
@@ -82,66 +81,6 @@ class AzureOpenAiLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!this.model)
- throw new Error(
- "No OPEN_MODEL_PREF ENV defined. This must the name of a deployment on your Azure account for an LLM chat model like GPT-3.5."
- );
-
- const messages = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- );
- const textResponse = await this.openai
- .getChatCompletions(this.model, messages, {
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- })
- .then((res) => {
- if (!res.hasOwnProperty("choices"))
- throw new Error("AzureOpenAI chat: No results!");
- if (res.choices.length === 0)
- throw new Error("AzureOpenAI chat: No results length!");
- return res.choices[0].message.content;
- })
- .catch((error) => {
- console.log(error);
- throw new Error(
- `AzureOpenAI::getChatCompletions failed with: ${error.message}`
- );
- });
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!this.model)
- throw new Error(
- "No OPEN_MODEL_PREF ENV defined. This must the name of a deployment on your Azure account for an LLM chat model like GPT-3.5."
- );
-
- const messages = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- );
- const stream = await this.openai.streamChatCompletions(
- this.model,
- messages,
- {
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- }
- );
- return stream;
- }
-
async getChatCompletion(messages = [], { temperature = 0.7 }) {
if (!this.model)
throw new Error(
diff --git a/server/utils/AiProviders/gemini/index.js b/server/utils/AiProviders/gemini/index.js
index 354c1899e..b9eb26c3c 100644
--- a/server/utils/AiProviders/gemini/index.js
+++ b/server/utils/AiProviders/gemini/index.js
@@ -1,4 +1,3 @@
-const { chatPrompt } = require("../../chats");
const {
writeResponseChunk,
clientAbortedHandler,
@@ -48,7 +47,7 @@ class GeminiLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
@@ -118,32 +117,6 @@ class GeminiLLM {
return allMessages;
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!this.isValidChatCompletionModel(this.model))
- throw new Error(
- `Gemini chat: ${this.model} is not valid for chat completion!`
- );
-
- const compressedHistory = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- chatHistory,
- },
- rawHistory
- );
-
- const chatThread = this.gemini.startChat({
- history: this.formatMessages(compressedHistory),
- });
- const result = await chatThread.sendMessage(prompt);
- const response = result.response;
- const responseText = response.text();
-
- if (!responseText) throw new Error("Gemini: No response could be parsed.");
-
- return responseText;
- }
-
async getChatCompletion(messages = [], _opts = {}) {
if (!this.isValidChatCompletionModel(this.model))
throw new Error(
@@ -165,30 +138,6 @@ class GeminiLLM {
return responseText;
}
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!this.isValidChatCompletionModel(this.model))
- throw new Error(
- `Gemini chat: ${this.model} is not valid for chat completion!`
- );
-
- const compressedHistory = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- chatHistory,
- },
- rawHistory
- );
-
- const chatThread = this.gemini.startChat({
- history: this.formatMessages(compressedHistory),
- });
- const responseStream = await chatThread.sendMessageStream(prompt);
- if (!responseStream.stream)
- throw new Error("Could not stream response stream from Gemini.");
-
- return responseStream.stream;
- }
-
async streamGetChatCompletion(messages = [], _opts = {}) {
if (!this.isValidChatCompletionModel(this.model))
throw new Error(
diff --git a/server/utils/AiProviders/genericOpenAi/index.js b/server/utils/AiProviders/genericOpenAi/index.js
index cf293c3e7..8c171b679 100644
--- a/server/utils/AiProviders/genericOpenAi/index.js
+++ b/server/utils/AiProviders/genericOpenAi/index.js
@@ -1,5 +1,4 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -53,7 +52,7 @@ class GenericOpenAiLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
// Ensure the user set a value for the token limit
@@ -89,55 +88,6 @@ class GenericOpenAiLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("GenericOpenAI chat: No results!");
- if (result.choices.length === 0)
- throw new Error("GenericOpenAI chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `GenericOpenAI::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- const streamRequest = await this.openai.chat.completions.create({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
const result = await this.openai.chat.completions
.create({
diff --git a/server/utils/AiProviders/groq/index.js b/server/utils/AiProviders/groq/index.js
index add064af4..01d92f006 100644
--- a/server/utils/AiProviders/groq/index.js
+++ b/server/utils/AiProviders/groq/index.js
@@ -1,5 +1,4 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -38,7 +37,7 @@ class GroqLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
@@ -91,65 +90,6 @@ class GroqLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `Groq chat: ${this.model} is not valid for chat completion!`
- );
-
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("GroqAI chat: No results!");
- if (result.choices.length === 0)
- throw new Error("GroqAI chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `GroqAI::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `GroqAI:streamChat: ${this.model} is not valid for chat completion!`
- );
-
- const streamRequest = await this.openai.chat.completions.create({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
diff --git a/server/utils/AiProviders/huggingface/index.js b/server/utils/AiProviders/huggingface/index.js
index 22f9c2fd4..6a79880c8 100644
--- a/server/utils/AiProviders/huggingface/index.js
+++ b/server/utils/AiProviders/huggingface/index.js
@@ -1,6 +1,5 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
const { OpenAiEmbedder } = require("../../EmbeddingEngines/openAi");
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -48,7 +47,7 @@ class HuggingFaceLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
@@ -90,55 +89,6 @@ class HuggingFaceLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("HuggingFace chat: No results!");
- if (result.choices.length === 0)
- throw new Error("HuggingFace chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `HuggingFace::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- const streamRequest = await this.openai.chat.completions.create({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
const result = await this.openai.createChatCompletion({
model: this.model,
diff --git a/server/utils/AiProviders/lmStudio/index.js b/server/utils/AiProviders/lmStudio/index.js
index 98cbbcaa5..48f689fbc 100644
--- a/server/utils/AiProviders/lmStudio/index.js
+++ b/server/utils/AiProviders/lmStudio/index.js
@@ -1,4 +1,3 @@
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -49,7 +48,7 @@ class LMStudioLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
// Ensure the user set a value for the token limit
@@ -85,65 +84,6 @@ class LMStudioLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!this.model)
- throw new Error(
- `LMStudio chat: ${this.model} is not valid or defined for chat completion!`
- );
-
- const textResponse = await this.lmstudio.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("LMStudio chat: No results!");
- if (result.choices.length === 0)
- throw new Error("LMStudio chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `LMStudio::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!this.model)
- throw new Error(
- `LMStudio chat: ${this.model} is not valid or defined for chat completion!`
- );
-
- const streamRequest = await this.lmstudio.chat.completions.create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- stream: true,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!this.model)
throw new Error(
diff --git a/server/utils/AiProviders/localAi/index.js b/server/utils/AiProviders/localAi/index.js
index 4a8921af8..504775285 100644
--- a/server/utils/AiProviders/localAi/index.js
+++ b/server/utils/AiProviders/localAi/index.js
@@ -1,4 +1,3 @@
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -41,7 +40,7 @@ class LocalAiLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
// Ensure the user set a value for the token limit
@@ -75,65 +74,6 @@ class LocalAiLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `LocalAI chat: ${this.model} is not valid for chat completion!`
- );
-
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .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((error) => {
- throw new Error(
- `LocalAI::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `LocalAI chat: ${this.model} is not valid for chat completion!`
- );
-
- const streamRequest = await this.openai.chat.completions.create({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
diff --git a/server/utils/AiProviders/mistral/index.js b/server/utils/AiProviders/mistral/index.js
index 7b60f3fed..8410d4cb6 100644
--- a/server/utils/AiProviders/mistral/index.js
+++ b/server/utils/AiProviders/mistral/index.js
@@ -1,4 +1,3 @@
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -42,7 +41,7 @@ class MistralLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
@@ -70,64 +69,6 @@ class MistralLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `Mistral chat: ${this.model} is not valid for chat completion!`
- );
-
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("Mistral chat: No results!");
- if (result.choices.length === 0)
- throw new Error("Mistral chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `Mistral::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `Mistral chat: ${this.model} is not valid for chat completion!`
- );
-
- const streamRequest = await this.openai.chat.completions.create({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
-
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
diff --git a/server/utils/AiProviders/native/index.js b/server/utils/AiProviders/native/index.js
index 07d8918cf..e13b68a2f 100644
--- a/server/utils/AiProviders/native/index.js
+++ b/server/utils/AiProviders/native/index.js
@@ -1,7 +1,6 @@
const fs = require("fs");
const path = require("path");
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
-const { chatPrompt } = require("../../chats");
const {
writeResponseChunk,
clientAbortedHandler,
@@ -94,7 +93,7 @@ class NativeLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
// Ensure the user set a value for the token limit
@@ -123,45 +122,6 @@ class NativeLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- try {
- const messages = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- );
-
- const model = await this.#llamaClient({
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- });
- const response = await model.call(messages);
- return response.content;
- } catch (error) {
- throw new Error(
- `NativeLLM::createChatCompletion failed with: ${error.message}`
- );
- }
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- const model = await this.#llamaClient({
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- });
- const messages = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- );
- const responseStream = await model.stream(messages);
- return responseStream;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
const model = await this.#llamaClient({ temperature });
const response = await model.call(messages);
diff --git a/server/utils/AiProviders/ollama/index.js b/server/utils/AiProviders/ollama/index.js
index a19315254..73269d6d2 100644
--- a/server/utils/AiProviders/ollama/index.js
+++ b/server/utils/AiProviders/ollama/index.js
@@ -1,4 +1,3 @@
-const { chatPrompt } = require("../../chats");
const { StringOutputParser } = require("@langchain/core/output_parsers");
const {
writeResponseChunk,
@@ -74,7 +73,7 @@ class OllamaAILLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
// Ensure the user set a value for the token limit
@@ -108,53 +107,6 @@ class OllamaAILLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- const messages = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- );
-
- const model = this.#ollamaClient({
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- });
- const textResponse = await model
- .pipe(new StringOutputParser())
- .invoke(this.#convertToLangchainPrototypes(messages))
- .catch((e) => {
- throw new Error(
- `Ollama::getChatCompletion failed to communicate with Ollama. ${e.message}`
- );
- });
-
- if (!textResponse || !textResponse.length)
- throw new Error(`Ollama::sendChat text response was empty.`);
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- const messages = await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- );
-
- const model = this.#ollamaClient({
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- });
- const stream = await model
- .pipe(new StringOutputParser())
- .stream(this.#convertToLangchainPrototypes(messages));
- return stream;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
const model = this.#ollamaClient({ temperature });
const textResponse = await model
diff --git a/server/utils/AiProviders/openAi/index.js b/server/utils/AiProviders/openAi/index.js
index d69ec11ee..3a4d997ce 100644
--- a/server/utils/AiProviders/openAi/index.js
+++ b/server/utils/AiProviders/openAi/index.js
@@ -1,5 +1,4 @@
const { OpenAiEmbedder } = require("../../EmbeddingEngines/openAi");
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -41,7 +40,7 @@ class OpenAiLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
@@ -122,65 +121,6 @@ class OpenAiLLM {
return { safe: false, reasons };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `OpenAI chat: ${this.model} is not valid for chat completion!`
- );
-
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("OpenAI chat: No results!");
- if (result.choices.length === 0)
- throw new Error("OpenAI chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `OpenAI::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `OpenAI chat: ${this.model} is not valid for chat completion!`
- );
-
- const streamRequest = await this.openai.chat.completions({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
diff --git a/server/utils/AiProviders/openRouter/index.js b/server/utils/AiProviders/openRouter/index.js
index 8fb078fbc..a83010835 100644
--- a/server/utils/AiProviders/openRouter/index.js
+++ b/server/utils/AiProviders/openRouter/index.js
@@ -1,10 +1,8 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
-const { chatPrompt } = require("../../chats");
const { v4: uuidv4 } = require("uuid");
const {
writeResponseChunk,
clientAbortedHandler,
- handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
const fs = require("fs");
const path = require("path");
@@ -99,7 +97,7 @@ class OpenRouterLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
@@ -131,65 +129,6 @@ class OpenRouterLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `OpenRouter chat: ${this.model} is not valid for chat completion!`
- );
-
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("OpenRouter chat: No results!");
- if (result.choices.length === 0)
- throw new Error("OpenRouter chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `OpenRouter::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `OpenRouter chat: ${this.model} is not valid for chat completion!`
- );
-
- const streamRequest = await this.openai.chat.completions.create({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
@@ -304,143 +243,6 @@ class OpenRouterLLM {
});
}
- // handleStream(response, stream, responseProps) {
- // const timeoutThresholdMs = 500;
- // const { uuid = uuidv4(), sources = [] } = responseProps;
-
- // return new Promise((resolve) => {
- // let fullText = "";
- // let chunk = "";
- // let lastChunkTime = null; // null when first token is still not received.
-
- // // Establish listener to early-abort a streaming response
- // // in case things go sideways or the user does not like the response.
- // // We preserve the generated text but continue as if chat was completed
- // // to preserve previously generated content.
- // const handleAbort = () => clientAbortedHandler(resolve, fullText);
- // response.on("close", handleAbort);
-
- // // NOTICE: Not all OpenRouter models will return a stop reason
- // // which keeps the connection open and so the model never finalizes the stream
- // // like the traditional OpenAI response schema does. So in the case the response stream
- // // never reaches a formal close state we maintain an interval timer that if we go >=timeoutThresholdMs with
- // // no new chunks then we kill the stream and assume it to be complete. OpenRouter is quite fast
- // // so this threshold should permit most responses, but we can adjust `timeoutThresholdMs` if
- // // we find it is too aggressive.
- // const timeoutCheck = setInterval(() => {
- // if (lastChunkTime === null) return;
-
- // const now = Number(new Date());
- // const diffMs = now - lastChunkTime;
- // if (diffMs >= timeoutThresholdMs) {
- // console.log(
- // `OpenRouter stream did not self-close and has been stale for >${timeoutThresholdMs}ms. Closing response stream.`
- // );
- // writeResponseChunk(response, {
- // uuid,
- // sources,
- // type: "textResponseChunk",
- // textResponse: "",
- // close: true,
- // error: false,
- // });
- // clearInterval(timeoutCheck);
- // response.removeListener("close", handleAbort);
- // resolve(fullText);
- // }
- // }, 500);
-
- // stream.data.on("data", (data) => {
- // const lines = data
- // ?.toString()
- // ?.split("\n")
- // .filter((line) => line.trim() !== "");
-
- // for (const line of lines) {
- // let validJSON = false;
- // const message = chunk + line.replace(/^data: /, "");
-
- // // JSON chunk is incomplete and has not ended yet
- // // so we need to stitch it together. You would think JSON
- // // chunks would only come complete - but they don't!
- // try {
- // JSON.parse(message);
- // validJSON = true;
- // } catch { }
-
- // if (!validJSON) {
- // // It can be possible that the chunk decoding is running away
- // // and the message chunk fails to append due to string length.
- // // In this case abort the chunk and reset so we can continue.
- // // ref: https://github.com/Mintplex-Labs/anything-llm/issues/416
- // try {
- // chunk += message;
- // } catch (e) {
- // console.error(`Chunk appending error`, e);
- // chunk = "";
- // }
- // continue;
- // } else {
- // chunk = "";
- // }
-
- // if (message == "[DONE]") {
- // lastChunkTime = Number(new Date());
- // writeResponseChunk(response, {
- // uuid,
- // sources,
- // type: "textResponseChunk",
- // textResponse: "",
- // close: true,
- // error: false,
- // });
- // clearInterval(timeoutCheck);
- // response.removeListener("close", handleAbort);
- // resolve(fullText);
- // } else {
- // let finishReason = null;
- // let token = "";
- // try {
- // const json = JSON.parse(message);
- // token = json?.choices?.[0]?.delta?.content;
- // finishReason = json?.choices?.[0]?.finish_reason || null;
- // } catch {
- // continue;
- // }
-
- // if (token) {
- // fullText += token;
- // lastChunkTime = Number(new Date());
- // writeResponseChunk(response, {
- // uuid,
- // sources: [],
- // type: "textResponseChunk",
- // textResponse: token,
- // close: false,
- // error: false,
- // });
- // }
-
- // if (finishReason !== null) {
- // lastChunkTime = Number(new Date());
- // writeResponseChunk(response, {
- // uuid,
- // sources,
- // type: "textResponseChunk",
- // textResponse: "",
- // close: true,
- // error: false,
- // });
- // clearInterval(timeoutCheck);
- // response.removeListener("close", handleAbort);
- // resolve(fullText);
- // }
- // }
- // }
- // });
- // });
- // }
-
// Simple wrapper for dynamic embedder & normalize interface for all LLM implementations
async embedTextInput(textInput) {
return await this.embedder.embedTextInput(textInput);
diff --git a/server/utils/AiProviders/perplexity/index.js b/server/utils/AiProviders/perplexity/index.js
index 71b74e9e3..a17ec43f5 100644
--- a/server/utils/AiProviders/perplexity/index.js
+++ b/server/utils/AiProviders/perplexity/index.js
@@ -1,5 +1,4 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -50,7 +49,7 @@ class PerplexityLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
promptWindowLimit() {
@@ -81,65 +80,6 @@ class PerplexityLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `Perplexity chat: ${this.model} is not valid for chat completion!`
- );
-
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("Perplexity chat: No results!");
- if (result.choices.length === 0)
- throw new Error("Perplexity chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `Perplexity::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `Perplexity chat: ${this.model} is not valid for chat completion!`
- );
-
- const streamRequest = await this.openai.chat.completions.create({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
diff --git a/server/utils/AiProviders/togetherAi/index.js b/server/utils/AiProviders/togetherAi/index.js
index 6d91e9a98..577a4b742 100644
--- a/server/utils/AiProviders/togetherAi/index.js
+++ b/server/utils/AiProviders/togetherAi/index.js
@@ -1,4 +1,3 @@
-const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
@@ -49,7 +48,7 @@ class TogetherAiLLM {
}
streamingEnabled() {
- return "streamChat" in this && "streamGetChatCompletion" in this;
+ return "streamGetChatCompletion" in this;
}
// Ensure the user set a value for the token limit
@@ -82,65 +81,6 @@ class TogetherAiLLM {
return { safe: true, reasons: [] };
}
- async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `Together AI chat: ${this.model} is not valid for chat completion!`
- );
-
- const textResponse = await this.openai.chat.completions
- .create({
- model: this.model,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- })
- .then((result) => {
- if (!result.hasOwnProperty("choices"))
- throw new Error("Together AI chat: No results!");
- if (result.choices.length === 0)
- throw new Error("Together AI chat: No results length!");
- return result.choices[0].message.content;
- })
- .catch((error) => {
- throw new Error(
- `TogetherAI::createChatCompletion failed with: ${error.message}`
- );
- });
-
- return textResponse;
- }
-
- async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
- if (!(await this.isValidChatCompletionModel(this.model)))
- throw new Error(
- `TogetherAI chat: ${this.model} is not valid for chat completion!`
- );
-
- const streamRequest = await this.openai.chat.completions.create({
- model: this.model,
- stream: true,
- temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
- n: 1,
- messages: await this.compressMessages(
- {
- systemPrompt: chatPrompt(workspace),
- userPrompt: prompt,
- chatHistory,
- },
- rawHistory
- ),
- });
- return streamRequest;
- }
-
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(