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[CHORE] Remove sendChat and streamChat in all LLM providers #1260

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Merged
merged 3 commits into from
May 1, 2024
Merged

[CHORE] Remove sendChat and streamChat in all LLM providers #1260

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0da895c
remove sendChat and streamChat functions/references in all LLM providers
shatfield4 May 1, 2024
392e199
remove unused imports
timothycarambat May 1, 2024
7b5c5c4
Merge branch 'master' of github.com:Mintplex-Labs/anything-llm into 1…
timothycarambat May 1, 2024
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28 changes: 1 addition & 27 deletions server/utils/AiProviders/anthropic/index.js
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
const { v4 } = require("uuid");
const { chatPrompt } = require("../../chats");
const {
writeResponseChunk,
clientAbortedHandler,
Expand Down Expand Up @@ -33,7 +32,7 @@ class AnthropicLLM {
}

streamingEnabled() {
return "streamChat" in this && "streamGetChatCompletion" in this;
return "streamGetChatCompletion" in this;
}

promptWindowLimit() {
Expand Down Expand Up @@ -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(
Expand Down
63 changes: 1 addition & 62 deletions server/utils/AiProviders/azureOpenAi/index.js
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Open in desktop
Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
const { AzureOpenAiEmbedder } = require("../../EmbeddingEngines/azureOpenAi");
const { chatPrompt } = require("../../chats");
const {
writeResponseChunk,
clientAbortedHandler,
Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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(
Expand Down
53 changes: 1 addition & 52 deletions server/utils/AiProviders/gemini/index.js
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
const { chatPrompt } = require("../../chats");
const {
writeResponseChunk,
clientAbortedHandler,
Expand Down Expand Up @@ -48,7 +47,7 @@ class GeminiLLM {
}

streamingEnabled() {
return "streamChat" in this && "streamGetChatCompletion" in this;
return "streamGetChatCompletion" in this;
}

promptWindowLimit() {
Expand Down Expand Up @@ -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(
Expand All @@ -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(
Expand Down
52 changes: 1 addition & 51 deletions server/utils/AiProviders/genericOpenAi/index.js
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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({
Expand Down
62 changes: 1 addition & 61 deletions server/utils/AiProviders/groq/index.js
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
const { chatPrompt } = require("../../chats");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
Expand Down Expand Up @@ -38,7 +37,7 @@ class GroqLLM {
}

streamingEnabled() {
return "streamChat" in this && "streamGetChatCompletion" in this;
return "streamGetChatCompletion" in this;
}

promptWindowLimit() {
Expand Down Expand Up @@ -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(
Expand Down
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