forked from open-webui/open-webui
commit
d99114518c
5 changed files with 209 additions and 117 deletions
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@ -1,3 +1,4 @@
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import re
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from typing import List
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from config import CHROMA_CLIENT
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@ -87,3 +88,10 @@ def query_collection(
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pass
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return merge_and_sort_query_results(results, k)
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def rag_template(template: str, context: str, query: str):
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template = re.sub(r"\[context\]", context, template)
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template = re.sub(r"\[query\]", query, template)
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return template
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121
backend/main.py
121
backend/main.py
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@ -12,6 +12,7 @@ from fastapi import HTTPException
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from fastapi.middleware.wsgi import WSGIMiddleware
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from fastapi.middleware.cors import CORSMiddleware
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from starlette.exceptions import HTTPException as StarletteHTTPException
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from starlette.middleware.base import BaseHTTPMiddleware
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from apps.ollama.main import app as ollama_app
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@ -23,6 +24,8 @@ from apps.rag.main import app as rag_app
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from apps.web.main import app as webui_app
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from apps.rag.utils import query_doc, query_collection, rag_template
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from config import WEBUI_NAME, ENV, VERSION, CHANGELOG, FRONTEND_BUILD_DIR
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from constants import ERROR_MESSAGES
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@ -56,6 +59,124 @@ async def on_startup():
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await litellm_app_startup()
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class RAGMiddleware(BaseHTTPMiddleware):
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async def dispatch(self, request: Request, call_next):
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if request.method == "POST" and (
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"/api/chat" in request.url.path or "/chat/completions" in request.url.path
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):
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print(request.url.path)
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# Read the original request body
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body = await request.body()
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# Decode body to string
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body_str = body.decode("utf-8")
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# Parse string to JSON
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data = json.loads(body_str) if body_str else {}
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# Example: Add a new key-value pair or modify existing ones
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# data["modified"] = True # Example modification
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if "docs" in data:
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docs = data["docs"]
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print(docs)
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last_user_message_idx = None
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for i in range(len(data["messages"]) - 1, -1, -1):
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if data["messages"][i]["role"] == "user":
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last_user_message_idx = i
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break
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user_message = data["messages"][last_user_message_idx]
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if isinstance(user_message["content"], list):
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# Handle list content input
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content_type = "list"
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query = ""
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for content_item in user_message["content"]:
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if content_item["type"] == "text":
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query = content_item["text"]
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break
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elif isinstance(user_message["content"], str):
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# Handle text content input
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content_type = "text"
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query = user_message["content"]
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else:
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# Fallback in case the input does not match expected types
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content_type = None
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query = ""
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relevant_contexts = []
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for doc in docs:
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context = None
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try:
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if doc["type"] == "collection":
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context = query_collection(
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collection_names=doc["collection_names"],
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query=query,
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k=rag_app.state.TOP_K,
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embedding_function=rag_app.state.sentence_transformer_ef,
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)
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else:
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context = query_doc(
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collection_name=doc["collection_name"],
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query=query,
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k=rag_app.state.TOP_K,
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embedding_function=rag_app.state.sentence_transformer_ef,
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)
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except Exception as e:
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print(e)
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context = None
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relevant_contexts.append(context)
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context_string = ""
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for context in relevant_contexts:
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if context:
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context_string += " ".join(context["documents"][0]) + "\n"
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ra_content = rag_template(
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template=rag_app.state.RAG_TEMPLATE,
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context=context_string,
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query=query,
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)
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if content_type == "list":
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new_content = []
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for content_item in user_message["content"]:
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if content_item["type"] == "text":
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# Update the text item's content with ra_content
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new_content.append({"type": "text", "text": ra_content})
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else:
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# Keep other types of content as they are
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new_content.append(content_item)
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new_user_message = {**user_message, "content": new_content}
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else:
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new_user_message = {
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**user_message,
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"content": ra_content,
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}
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data["messages"][last_user_message_idx] = new_user_message
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del data["docs"]
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modified_body_bytes = json.dumps(data).encode("utf-8")
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# Create a new request with the modified body
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scope = request.scope
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scope["body"] = modified_body_bytes
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request = Request(scope, receive=lambda: self._receive(modified_body_bytes))
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response = await call_next(request)
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return response
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async def _receive(self, body: bytes):
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return {"type": "http.request", "body": body, "more_body": False}
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app.add_middleware(RAGMiddleware)
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@app.middleware("http")
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async def check_url(request: Request, call_next):
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start_time = int(time.time())
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@ -252,7 +252,7 @@ export const queryCollection = async (
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token: string,
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collection_names: string,
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query: string,
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k: number
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k: number | null = null
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) => {
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let error = null;
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@ -232,53 +232,6 @@
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const sendPrompt = async (prompt, parentId) => {
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const _chatId = JSON.parse(JSON.stringify($chatId));
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const docs = messages
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.filter((message) => message?.files ?? null)
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.map((message) =>
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message.files.filter((item) => item.type === 'doc' || item.type === 'collection')
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)
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.flat(1);
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console.log(docs);
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if (docs.length > 0) {
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processing = 'Reading';
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const query = history.messages[parentId].content;
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let relevantContexts = await Promise.all(
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docs.map(async (doc) => {
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if (doc.type === 'collection') {
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return await queryCollection(localStorage.token, doc.collection_names, query).catch(
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(error) => {
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console.log(error);
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return null;
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}
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);
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} else {
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return await queryDoc(localStorage.token, doc.collection_name, query).catch((error) => {
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console.log(error);
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return null;
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});
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}
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})
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);
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relevantContexts = relevantContexts.filter((context) => context);
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const contextString = relevantContexts.reduce((a, context, i, arr) => {
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return `${a}${context.documents.join(' ')}\n`;
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}, '');
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console.log(contextString);
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history.messages[parentId].raContent = await RAGTemplate(
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localStorage.token,
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contextString,
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query
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);
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history.messages[parentId].contexts = relevantContexts;
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await tick();
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processing = '';
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}
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await Promise.all(
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selectedModels.map(async (modelId) => {
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const model = $models.filter((m) => m.id === modelId).at(0);
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@ -342,15 +295,25 @@
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...messages
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]
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.filter((message) => message)
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.map((message, idx, arr) => ({
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role: message.role,
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content: arr.length - 2 !== idx ? message.content : message?.raContent ?? message.content,
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...(message.files && {
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images: message.files
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.filter((file) => file.type === 'image')
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.map((file) => file.url.slice(file.url.indexOf(',') + 1))
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})
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}));
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.map((message, idx, arr) => {
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// Prepare the base message object
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const baseMessage = {
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role: message.role,
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content: arr.length - 2 !== idx ? message.content : message?.raContent ?? message.content
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};
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// Extract and format image URLs if any exist
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const imageUrls = message.files
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?.filter((file) => file.type === 'image')
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.map((file) => file.url.slice(file.url.indexOf(',') + 1));
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// Add images array only if it contains elements
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if (imageUrls && imageUrls.length > 0) {
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baseMessage.images = imageUrls;
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}
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return baseMessage;
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});
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let lastImageIndex = -1;
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@ -368,6 +331,13 @@
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}
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});
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const docs = messages
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.filter((message) => message?.files ?? null)
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.map((message) =>
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message.files.filter((item) => item.type === 'doc' || item.type === 'collection')
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)
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.flat(1);
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const [res, controller] = await generateChatCompletion(localStorage.token, {
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model: model,
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messages: messagesBody,
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@ -375,7 +345,8 @@
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...($settings.options ?? {})
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},
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format: $settings.requestFormat ?? undefined,
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keep_alive: $settings.keepAlive ?? undefined
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keep_alive: $settings.keepAlive ?? undefined,
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docs: docs.length > 0 ? docs : undefined
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});
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if (res && res.ok) {
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@ -535,6 +506,15 @@
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const responseMessage = history.messages[responseMessageId];
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scrollToBottom();
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const docs = messages
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.filter((message) => message?.files ?? null)
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.map((message) =>
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message.files.filter((item) => item.type === 'doc' || item.type === 'collection')
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)
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.flat(1);
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console.log(docs);
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const res = await generateOpenAIChatCompletion(
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localStorage.token,
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{
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@ -583,7 +563,8 @@
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top_p: $settings?.options?.top_p ?? undefined,
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num_ctx: $settings?.options?.num_ctx ?? undefined,
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frequency_penalty: $settings?.options?.repeat_penalty ?? undefined,
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max_tokens: $settings?.options?.num_predict ?? undefined
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max_tokens: $settings?.options?.num_predict ?? undefined,
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docs: docs.length > 0 ? docs : undefined
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},
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model.source === 'litellm' ? `${LITELLM_API_BASE_URL}/v1` : `${OPENAI_API_BASE_URL}`
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);
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@ -245,53 +245,6 @@
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const sendPrompt = async (prompt, parentId) => {
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const _chatId = JSON.parse(JSON.stringify($chatId));
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const docs = messages
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.filter((message) => message?.files ?? null)
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.map((message) =>
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message.files.filter((item) => item.type === 'doc' || item.type === 'collection')
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)
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.flat(1);
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console.log(docs);
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if (docs.length > 0) {
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processing = 'Reading';
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const query = history.messages[parentId].content;
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let relevantContexts = await Promise.all(
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docs.map(async (doc) => {
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if (doc.type === 'collection') {
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return await queryCollection(localStorage.token, doc.collection_names, query).catch(
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(error) => {
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console.log(error);
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return null;
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}
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);
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} else {
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return await queryDoc(localStorage.token, doc.collection_name, query).catch((error) => {
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console.log(error);
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return null;
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});
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}
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})
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);
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relevantContexts = relevantContexts.filter((context) => context);
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const contextString = relevantContexts.reduce((a, context, i, arr) => {
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return `${a}${context.documents.join(' ')}\n`;
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}, '');
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console.log(contextString);
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history.messages[parentId].raContent = await RAGTemplate(
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localStorage.token,
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contextString,
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query
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);
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history.messages[parentId].contexts = relevantContexts;
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await tick();
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processing = '';
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}
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await Promise.all(
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selectedModels.map(async (modelId) => {
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const model = $models.filter((m) => m.id === modelId).at(0);
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|
@ -355,15 +308,25 @@
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...messages
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]
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.filter((message) => message)
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.map((message, idx, arr) => ({
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role: message.role,
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content: arr.length - 2 !== idx ? message.content : message?.raContent ?? message.content,
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...(message.files && {
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images: message.files
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.filter((file) => file.type === 'image')
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.map((file) => file.url.slice(file.url.indexOf(',') + 1))
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})
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}));
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.map((message, idx, arr) => {
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// Prepare the base message object
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const baseMessage = {
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role: message.role,
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content: arr.length - 2 !== idx ? message.content : message?.raContent ?? message.content
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};
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// Extract and format image URLs if any exist
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const imageUrls = message.files
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?.filter((file) => file.type === 'image')
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.map((file) => file.url.slice(file.url.indexOf(',') + 1));
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// Add images array only if it contains elements
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if (imageUrls && imageUrls.length > 0) {
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baseMessage.images = imageUrls;
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}
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return baseMessage;
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});
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let lastImageIndex = -1;
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|
@ -381,6 +344,13 @@
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}
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});
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const docs = messages
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.filter((message) => message?.files ?? null)
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.map((message) =>
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message.files.filter((item) => item.type === 'doc' || item.type === 'collection')
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)
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.flat(1);
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const [res, controller] = await generateChatCompletion(localStorage.token, {
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model: model,
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messages: messagesBody,
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|
@ -388,7 +358,8 @@
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...($settings.options ?? {})
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},
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format: $settings.requestFormat ?? undefined,
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keep_alive: $settings.keepAlive ?? undefined
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keep_alive: $settings.keepAlive ?? undefined,
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docs: docs.length > 0 ? docs : undefined
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});
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if (res && res.ok) {
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|
@ -548,6 +519,15 @@
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const responseMessage = history.messages[responseMessageId];
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scrollToBottom();
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const docs = messages
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.filter((message) => message?.files ?? null)
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.map((message) =>
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message.files.filter((item) => item.type === 'doc' || item.type === 'collection')
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)
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.flat(1);
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console.log(docs);
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const res = await generateOpenAIChatCompletion(
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localStorage.token,
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{
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|
@ -596,7 +576,8 @@
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top_p: $settings?.options?.top_p ?? undefined,
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num_ctx: $settings?.options?.num_ctx ?? undefined,
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frequency_penalty: $settings?.options?.repeat_penalty ?? undefined,
|
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max_tokens: $settings?.options?.num_predict ?? undefined
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max_tokens: $settings?.options?.num_predict ?? undefined,
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docs: docs.length > 0 ? docs : undefined
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},
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model.source === 'litellm' ? `${LITELLM_API_BASE_URL}/v1` : `${OPENAI_API_BASE_URL}`
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);
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|
@ -710,6 +691,7 @@
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await setChatTitle(_chatId, userPrompt);
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}
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};
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const stopResponse = () => {
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stopResponseFlag = true;
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console.log('stopResponse');
|
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|
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