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shiva raj badu 2025-08-06 14:27:41 +05:45
commit 4d0a88d5e0
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4
Dockerfile
View file

@ -16,7 +16,7 @@ WORKDIR /app
# Set environment variables
ENV APP_DATA_DIRECTORY=/app_data
ENV TEMP_DIRECTORY=/tmp/presenton
ENV PYTHONPATH="${PYTHONPATH}:/app/servers/fastapi"
# ENV PYTHONPATH="${PYTHONPATH}:/app/servers/fastapi"
# Install ollama
@ -24,7 +24,7 @@ RUN curl -fsSL https://ollama.com/install.sh | sh
# Install dependencies for FastAPI
RUN pip install aiohttp aiomysql aiosqlite asyncpg fastapi[standard] \
pathvalidate pdfplumber nltk chromadb sqlmodel \
pathvalidate pdfplumber chromadb sqlmodel \
anthropic google-genai openai fastmcp
RUN pip install docling --extra-index-url https://download.pytorch.org/whl/cpu

4
Dockerfile.dev
View file

@ -24,14 +24,14 @@ RUN ls -a
# Set environment variables
ENV APP_DATA_DIRECTORY=/app_data
ENV TEMP_DIRECTORY=/tmp/presenton
ENV PYTHONPATH="${PYTHONPATH}:/app/servers/fastapi"
# ENV PYTHONPATH="${PYTHONPATH}:/app/servers/fastapi"
# Install ollama
RUN curl -fsSL http://ollama.com/install.sh | sh
# Install dependencies for FastAPI
RUN pip install aiohttp aiomysql aiosqlite asyncpg fastapi[standard] \
pathvalidate pdfplumber nltk chromadb sqlmodel \
pathvalidate pdfplumber chromadb sqlmodel \
anthropic google-genai openai fastmcp
RUN pip install docling --extra-index-url https://download.pytorch.org/whl/cpu

10
servers/fastapi/api/v1/ppt/endpoints/outlines.py
View file

@ -68,7 +68,15 @@ async def stream_outlines(
).to_string()
presentation_outlines_text += chunk
presentation_outlines_json = json.loads(presentation_outlines_text)
try:
presentation_outlines_json = json.loads(presentation_outlines_text)
except Exception as e:
print(e)
raise HTTPException(
status_code=400,
detail="Failed to generate presentation outlines. Please try again.",
)
presentation_outlines = PresentationOutlineModel(
**presentation_outlines_json
)

9
servers/fastapi/api/v1/ppt/endpoints/presentation.py
View file

@ -355,7 +355,14 @@ async def generate_presentation_api(
):
presentation_outlines_text += chunk
presentation_outlines_json = json.loads(presentation_outlines_text)
try:
presentation_outlines_json = json.loads(presentation_outlines_text)
except Exception as e:
print(e)
raise HTTPException(
status_code=400,
detail="Failed to generate presentation outlines. Please try again.",
)
presentation_outlines = PresentationOutlineModel(**presentation_outlines_json)
outlines = presentation_outlines.slides[:n_slides]
total_outlines = len(outlines)

14
servers/fastapi/app_mcp/wrapper/generate_outline.py
View file

@ -1,5 +1,6 @@
import json
import os
from fastapi import HTTPException
from typing import Dict, Any, Optional, List, Annotated
from models.presentation_outline_model import PresentationOutlineModel
from utils.llm_calls.generate_presentation_outlines import generate_ppt_outline
@ -63,8 +64,17 @@ async def generate_outline(
await asyncio.sleep(0)
presentation_outlines_text += chunk
presentation_outlines_json = json.loads(presentation_outlines_text)
presentation_outlines = PresentationOutlineModel(**presentation_outlines_json)
try:
presentation_outlines_json = json.loads(presentation_outlines_text)
presentation_outlines = PresentationOutlineModel(
**presentation_outlines_json
)
except Exception as e:
print(e)
raise HTTPException(
status_code=400,
detail="Failed to generate presentation outlines. Please try again.",
)
# Truncate slides to n_slides
presentation_outlines.slides = presentation_outlines.slides[:n_slides]

14
servers/fastapi/services/docling_service.py
View file

@ -1,4 +1,9 @@
from docling.document_converter import DocumentConverter, PdfFormatOption
from docling.document_converter import (
DocumentConverter,
PdfFormatOption,
PowerpointFormatOption,
WordFormatOption,
)
from docling.datamodel.pipeline_options import PdfPipelineOptions
from docling.datamodel.base_models import InputFormat
@ -9,17 +14,18 @@ class DoclingService:
self.pipeline_options.do_ocr = False
self.converter = DocumentConverter(
allowed_formats=[InputFormat.PPTX, InputFormat.PDF, InputFormat.DOCX],
format_options={
InputFormat.DOCX: PdfFormatOption(
InputFormat.DOCX: WordFormatOption(
pipeline_options=self.pipeline_options,
),
InputFormat.PPTX: PdfFormatOption(
InputFormat.PPTX: PowerpointFormatOption(
pipeline_options=self.pipeline_options,
),
InputFormat.PDF: PdfFormatOption(
pipeline_options=self.pipeline_options,
),
}
},
)
def parse_to_markdown(self, file_path: str) -> str:

218
servers/fastapi/services/score_based_chunker.py
View file

@ -1,133 +1,79 @@
import asyncio
from typing import List
import nltk
from models.document_chunk import DocumentChunk
try:
nltk.data.find("tokenizers/punkt", paths=["./nltk"])
except LookupError:
nltk.download("punkt", download_dir="./nltk")
class ScoreBasedChunker:
def extract_sentences(self, text: str, min_sentences: int) -> List[str]:
sentences = self.extract_sentences_markdown(text)
if len(sentences) < min_sentences:
sentences = self.extract_sentences_nltk(text)
if len(sentences) < min_sentences:
sentences = self.extract_sentences_by_stop_words(text)
if len(sentences) < min_sentences:
sentences = self.extract_sentences_by_new_line(text)
if len(sentences) < min_sentences:
raise ValueError(
f"Only {len(sentences)} sentences found, requested {min_sentences}"
)
return sentences
def extract_sentences_markdown(self, text: str) -> List[str]:
def extract_headings(self, text: str) -> List[str]:
lines = text.split("\n")
sentences = []
headings = []
for line in lines:
line = line.strip()
if line:
if line.startswith("#"):
sentences.append(line)
else:
if line.endswith((".", "!", "?")):
sentences.append(line)
else:
sentences.append(line)
return sentences
def extract_sentences_nltk(self, text: str) -> List[str]:
sentences = nltk.sent_tokenize(text)
return sentences
def extract_sentences_by_stop_words(self, text: str) -> List[str]:
sentences = []
current_sentence = ""
for char in text:
current_sentence += char
if char in ".!?":
sentences.append(current_sentence.strip())
current_sentence = ""
if current_sentence.strip():
sentences.append(current_sentence.strip())
return [s for s in sentences if s]
def extract_sentences_by_new_line(self, text: str) -> List[str]:
sentences = text.split("\n")
result = []
for i, sentence in enumerate(sentences):
if i < len(sentences) - 1:
result.append(sentence + "\n")
else:
result.append(sentence)
return result
def score_sentences_for_heading(self, sentences: List[str]) -> List[float]:
sentences_scores = []
if line.startswith("#"):
headings.append(line)
return headings
def score_headings(self, headings: List[str]) -> List[float]:
heading_scores = []
last_heading_index = -1
first_heading_found = False
for i, sentence in enumerate(sentences):
for i, heading in enumerate(headings):
score = 0.0
heading_level = len(heading) - len(heading.lstrip("#"))
if heading_level <= 3:
score += 10.0 - (heading_level - 1) * 2.0
else:
score += 4.0 - (heading_level - 4) * 0.5
if sentence.strip().startswith("#"):
heading_level = len(sentence) - len(sentence.lstrip("#"))
if not first_heading_found:
score += 5.0
first_heading_found = True
if heading_level <= 3:
score += 10.0 - (heading_level - 1) * 2.0
else:
score += 4.0 - (heading_level - 4) * 0.5
if last_heading_index != -1:
distance = i - last_heading_index
distance_bonus = min(5.0, distance * 0.5)
score += distance_bonus
if not first_heading_found:
score += 5.0
first_heading_found = True
last_heading_index = i
heading_scores.append(score)
if last_heading_index != -1:
distance = i - last_heading_index
distance_bonus = min(5.0, distance * 0.5)
score += distance_bonus
return heading_scores
last_heading_index = i
sentences_scores.append(score)
return sentences_scores
def get_chunks(
self, sentences: List[str], sentences_scores: List[float], top_k: int = 10
def get_chunks_from_headings(
self,
text: str,
headings: List[str],
heading_scores: List[float],
top_k: int = 10,
) -> List[DocumentChunk]:
if not sentences_scores:
sentences_scores = self.score_sentences_for_heading(sentences)
if not heading_scores:
heading_scores = self.score_headings(headings)
chunks = []
heading_scores = []
heading_indices = []
for i, score in enumerate(sentences_scores):
for i, score in enumerate(heading_scores):
if score > 0:
heading_scores.append((i, score))
heading_indices.append((i, score))
if len(heading_scores) == 0:
if len(heading_indices) == 0:
return chunks
heading_scores.sort(key=lambda x: (-x[1], x[0]))
heading_indices.sort(key=lambda x: (-x[1], x[0]))
if len(heading_scores) <= top_k:
selected_headings = [idx for idx, _ in heading_scores]
selected_headings.sort()
if len(heading_indices) <= top_k:
selected_indices = [idx for idx, _ in heading_indices]
selected_indices.sort()
else:
score_groups = {}
for idx, score in heading_scores:
for idx, score in heading_indices:
rounded_score = round(score)
if rounded_score not in score_groups:
score_groups[rounded_score] = []
@ -137,62 +83,80 @@ class ScoreBasedChunker:
score_groups.items(), key=lambda x: x[0], reverse=True
)
selected_headings = []
selected_indices = []
for score, headings in sorted_groups:
headings.sort()
remaining_needed = top_k - len(selected_headings)
for score, indices in sorted_groups:
indices.sort()
remaining_needed = top_k - len(selected_indices)
if remaining_needed <= 0:
break
if len(headings) <= remaining_needed:
selected_headings.extend(headings)
if len(indices) <= remaining_needed:
selected_indices.extend(indices)
else:
if remaining_needed == 1:
mid_idx = len(headings) // 2
selected_headings.append(headings[mid_idx])
mid_idx = len(indices) // 2
selected_indices.append(indices[mid_idx])
elif remaining_needed == 2:
selected_headings.append(headings[0])
selected_headings.append(headings[-1])
selected_indices.append(indices[0])
selected_indices.append(indices[-1])
else:
step = (len(headings) - 1) / (remaining_needed - 1)
step = (len(indices) - 1) / (remaining_needed - 1)
for i in range(remaining_needed):
index = int(round(i * step))
if index < len(headings):
selected_headings.append(headings[index])
if index < len(indices):
selected_indices.append(indices[index])
selected_headings.sort()
selected_indices.sort()
for i, heading_idx in enumerate(selected_headings):
heading = sentences[heading_idx]
if i + 1 < len(selected_headings):
next_heading_idx = selected_headings[i + 1]
content_end = next_heading_idx
lines = text.split("\n")
heading_positions = {}
for i, line in enumerate(lines):
line_stripped = line.strip()
if line_stripped.startswith("#"):
for heading_idx, heading in enumerate(headings):
if heading == line_stripped and heading_idx not in heading_positions:
heading_positions[heading_idx] = i
break
for i, heading_idx in enumerate(selected_indices):
if heading_idx not in heading_positions:
continue
heading = headings[heading_idx]
heading_line_idx = heading_positions[heading_idx]
if i + 1 < len(selected_indices):
next_heading_idx = selected_indices[i + 1]
if next_heading_idx in heading_positions:
next_heading_line_idx = heading_positions[next_heading_idx]
content_end = next_heading_line_idx
else:
content_end = len(lines)
else:
content_end = len(sentences)
content_end = len(lines)
content_sentences = sentences[heading_idx + 1 : content_end]
content = " ".join(content_sentences).strip()
content_lines = lines[heading_line_idx + 1 : content_end]
content = "\n".join(content_lines).strip()
chunk = DocumentChunk(
heading=heading,
content=content,
heading_index=heading_idx,
score=sentences_scores[heading_idx],
score=heading_scores[heading_idx],
)
chunks.append(chunk)
return chunks
async def get_n_chunks(self, text: str, n: int) -> List[DocumentChunk]:
sentences = await asyncio.to_thread(self.extract_sentences, text, n)
sentences_scores = await asyncio.to_thread(
self.score_sentences_for_heading, sentences
)
headings = await asyncio.to_thread(self.extract_headings, text)
heading_scores = await asyncio.to_thread(self.score_headings, headings)
chunks = await asyncio.to_thread(
self.get_chunks, sentences, sentences_scores, n
self.get_chunks_from_headings, text, headings, heading_scores, n
)
if len(chunks) < n:
raise ValueError(f"Only {len(chunks)} chunks found, requested {n}")

2
servers/fastapi/utils/get_dynamic_models.py
View file

@ -7,7 +7,7 @@ from models.presentation_structure_model import PresentationStructureModel
def get_presentation_outline_model_with_n_slides(n_slides: int):
class PresentationOutlineModelWithNSlides(PresentationOutlineModel):
slides: List[str] = Field(
description="Markdown content for each slide",
description="Markdown content for each slide in about 100 to 200 words",
min_items=n_slides,
max_items=n_slides,
)

2
servers/nextjs/app/(presentation-generator)/documents-preview/components/DocumentPreviewPage.tsx
View file

@ -154,7 +154,7 @@ const DocumentsPreviewPage: React.FC = () => {
);
dispatch(setPresentationId(createResponse.id));
router.push("/outline");
router.replace("/outline");
} catch (error: any) {
console.error("Error in radar presentation creation:", error);
toast.error("Error", {

3
servers/nextjs/app/(presentation-generator)/outline/components/GenerateButton.tsx
View file

@ -1,12 +1,10 @@
import React from "react";
import { Button } from "@/components/ui/button";
import { SlideOutline } from "@/store/slices/presentationGeneration";
import { LoadingState, StreamState, LayoutGroup } from "../types/index";
interface GenerateButtonProps {
loadingState: LoadingState;
streamState: StreamState;
outlines: SlideOutline[] | null;
selectedLayoutGroup: LayoutGroup | null;
onSubmit: () => void;
}
@ -14,7 +12,6 @@ interface GenerateButtonProps {
const GenerateButton: React.FC<GenerateButtonProps> = ({
loadingState,
streamState,
outlines,
selectedLayoutGroup,
onSubmit
}) => {

1
servers/nextjs/app/(presentation-generator)/outline/components/OutlinePage.tsx
View file

@ -85,7 +85,6 @@ const OutlinePage: React.FC = () => {
<GenerateButton
loadingState={loadingState}
streamState={streamState}
outlines={outlines}
selectedLayoutGroup={selectedLayoutGroup}
onSubmit={handleSubmit}
/>

15
servers/nextjs/app/(presentation-generator)/outline/hooks/useOutlineManagement.ts
View file

@ -1,9 +1,9 @@
import { useCallback } from "react";
import { useDispatch } from "react-redux";
import { arrayMove } from "@dnd-kit/sortable";
import { setOutlines, SlideOutline } from "@/store/slices/presentationGeneration";
import { setOutlines } from "@/store/slices/presentationGeneration";
export const useOutlineManagement = (outlines: SlideOutline[] | null) => {
export const useOutlineManagement = (outlines: string[] | null) => {
const dispatch = useDispatch();
const handleDragEnd = useCallback((event: any) => {
@ -12,8 +12,8 @@ export const useOutlineManagement = (outlines: SlideOutline[] | null) => {
if (!active || !over || !outlines) return;
if (active.id !== over.id) {
const oldIndex = outlines.findIndex((item) => item.title === active.id);
const newIndex = outlines.findIndex((item) => item.title === over.id);
const oldIndex = outlines.findIndex((item) => item === active.id);
const newIndex = outlines.findIndex((item) => item === over.id);
const reorderedArray = arrayMove(outlines, oldIndex, newIndex);
dispatch(setOutlines(reorderedArray));
}
@ -22,12 +22,7 @@ export const useOutlineManagement = (outlines: SlideOutline[] | null) => {
const handleAddSlide = useCallback(() => {
if (!outlines) return;
const newSlide: SlideOutline = {
title: "Outline title",
body: "Outline body",
};
const updatedOutlines = [...outlines, newSlide];
const updatedOutlines = [...outlines, "Outline title"];
dispatch(setOutlines(updatedOutlines));
}, [outlines, dispatch]);

6
servers/nextjs/app/(presentation-generator)/outline/hooks/useOutlineStreaming.ts
View file

@ -85,11 +85,11 @@ export const useOutlineStreaming = (presentationId: string | null) => {
} catch (error) {
setStreamState({ isStreaming: false, isLoading: false });
toast.error("Failed to initialize connection");
}finally{
setStreamState({ isStreaming: false, isLoading: false });
}
};
initializeStream();
initializeStream();
return () => {
if (eventSource) {
eventSource.close();

6
servers/nextjs/app/(presentation-generator)/outline/hooks/usePresentationGeneration.ts
View file

@ -2,7 +2,7 @@ import { useState, useCallback } from "react";
import { useDispatch } from "react-redux";
import { useRouter } from "next/navigation";
import { toast } from "sonner";
import { clearPresentationData, SlideOutline } from "@/store/slices/presentationGeneration";
import { clearPresentationData } from "@/store/slices/presentationGeneration";
import { PresentationGenerationApi } from "../../services/api/presentation-generation";
import { LayoutGroup, LoadingState, TABS } from "../types/index";
@ -15,7 +15,7 @@ const DEFAULT_LOADING_STATE: LoadingState = {
export const usePresentationGeneration = (
presentationId: string | null,
outlines: SlideOutline[] | null,
outlines: string[] | null,
selectedLayoutGroup: LayoutGroup | null,
setActiveTab: (tab: string) => void
) => {
@ -84,7 +84,7 @@ export const usePresentationGeneration = (
if (response) {
dispatch(clearPresentationData());
router.push(`/presentation?id=${presentationId}&stream=true`);
router.replace(`/presentation?id=${presentationId}&stream=true`);
}
} catch (error: any) {
console.error('Error In Presentation Generation(prepare).', error);

7
servers/nextjs/app/(presentation-generator)/pdf-maker/PdfMakerPage.tsx
View file

@ -3,18 +3,15 @@ import React, { useEffect, useState } from "react";
import { useDispatch, useSelector } from "react-redux";
import { RootState } from "@/store/store";
import { Skeleton } from "@/components/ui/skeleton";
import { toast } from "sonner";
import { Button } from "@/components/ui/button";
import { AlertCircle } from "lucide-react";
import { useGroupLayouts } from "../hooks/useGroupLayouts";
import { setPresentationData } from "@/store/slices/presentationGeneration";
import { DashboardApi } from "../services/api/dashboard";
const PresentationPage = ({ presentation_id }: { presentation_id: string }) => {
const { renderSlideContent, loading } = useGroupLayouts();
const [contentLoading, setContentLoading] = useState(true);

8
servers/nextjs/app/(presentation-generator)/presentation/hooks/usePresentationStreaming.ts
View file

@ -6,7 +6,10 @@ import {
setStreaming,
} from "@/store/slices/presentationGeneration";
import { jsonrepair } from "jsonrepair";
<<<<<<< HEAD
import { RootState } from "@/store/store";
=======
>>>>>>> main
import { toast } from "sonner";
export const usePresentationStreaming = (
@ -97,7 +100,10 @@ export const usePresentationStreaming = (
data.detail ||
"Failed to connect to the server. Please try again.",
});
break;
setLoading(false);
dispatch(setStreaming(false));
setError(true);
break;
}
});

1
servers/nextjs/app/(presentation-generator)/upload/components/UploadPage.tsx
View file

@ -131,6 +131,7 @@ const UploadPage = () => {
config,
files: responses,
}));
dispatch(clearOutlines());
router.push("/documents-preview");
};

57
servers/nextjs/store/slices/presentationGeneration.ts
View file

@ -1,11 +1,6 @@
import { Slide } from "@/app/(presentation-generator)/types/slide";
import { createSlice, PayloadAction } from "@reduxjs/toolkit";
export interface PresentationData {
id: string;
language: string;
@ -137,7 +132,7 @@ const presentationGenerationSlice = createSlice({
action.payload.slide;
}
},
// Update slide content at specific data path (for Tiptap text editing)
updateSlideContent: (
state,
@ -154,12 +149,12 @@ const presentationGenerationSlice = createSlice({
) {
const slide = state.presentationData.slides[action.payload.slideIndex];
const { dataPath, content } = action.payload;
// Helper function to set nested property value
const setNestedValue = (obj: any, path: string, value: string) => {
const keys = path.split(/[.\[\]]+/).filter(Boolean);
let current = obj;
// Navigate to the parent object
for (let i = 0; i < keys.length - 1; i++) {
const key = keys[i];
@ -178,7 +173,7 @@ const presentationGenerationSlice = createSlice({
current = current[index];
}
}
// Set the final value
const finalKey = keys[keys.length - 1];
if (isNaN(Number(finalKey))) {
@ -187,7 +182,7 @@ const presentationGenerationSlice = createSlice({
current[Number(finalKey)] = value;
}
};
// Update the slide content
if (dataPath && slide.content) {
setNestedValue(slide.content, dataPath, content);
@ -198,8 +193,8 @@ const presentationGenerationSlice = createSlice({
addNewSlide: (state, action: PayloadAction<{ slideData: any; index: number }>) => {
if (state.presentationData?.slides) {
// Insert the new slide at the specified index + 1 (after current slide)
state.presentationData.slides.splice(action.payload.index +1, 0, action.payload.slideData);
state.presentationData.slides.splice(action.payload.index + 1, 0, action.payload.slideData);
// Update indices for all slides to ensure they remain sequential
state.presentationData.slides = state.presentationData.slides.map(
(slide: any, idx: number) => ({
@ -227,12 +222,12 @@ const presentationGenerationSlice = createSlice({
) {
const slide = state.presentationData.slides[action.payload.slideIndex];
const { dataPath, imageUrl, prompt } = action.payload;
// Helper function to set nested property value for images
const setNestedImageValue = (obj: any, path: string, url: string, promptText?: string) => {
const keys = path.split(/[.\[\]]+/).filter(Boolean);
let current = obj;
// Navigate to the parent object
for (let i = 0; i < keys.length - 1; i++) {
const key = keys[i];
@ -249,33 +244,33 @@ const presentationGenerationSlice = createSlice({
current = current[index];
}
}
// Set the image properties
const finalKey = keys[keys.length - 1];
const target = isNaN(Number(finalKey)) ? current[finalKey] : current[Number(finalKey)];
// Preserve existing properties if the target already exists
const updatedValue = {
...(target && typeof target === 'object' ? target : {}),
__image_url__: url,
__image_prompt__: promptText || (target?.__image_prompt__) || ''
};
if (isNaN(Number(finalKey))) {
current[finalKey] = updatedValue;
} else {
current[Number(finalKey)] = updatedValue;
}
// Add debugging
console.log('Redux: Updated slide image at path:', path, 'with URL:', url);
};
// Update the slide image
if (dataPath && slide.content) {
setNestedImageValue(slide.content, dataPath, imageUrl, prompt);
}
// Also update the images array if it exists
if (slide.images && Array.isArray(slide.images)) {
const imageIndex = parseInt(dataPath.split('[')[1]?.split(']')[0]) || 0;
@ -293,7 +288,7 @@ const presentationGenerationSlice = createSlice({
itemIndex: number;
properties: any;
}>
) => {
) => {
if (
state.presentationData &&
state.presentationData.slides &&
@ -305,8 +300,8 @@ const presentationGenerationSlice = createSlice({
...slide.properties,
[itemIndex]: properties
};
}
}
},
// Update slide icon at specific data path
@ -326,12 +321,12 @@ const presentationGenerationSlice = createSlice({
) {
const slide = state.presentationData.slides[action.payload.slideIndex];
const { dataPath, iconUrl, query } = action.payload;
// Helper function to set nested property value for icons
const setNestedIconValue = (obj: any, path: string, url: string, queryText?: string) => {
const keys = path.split(/[.\[\]]+/).filter(Boolean);
let current = obj;
// Navigate to the parent object
for (let i = 0; i < keys.length - 1; i++) {
const key = keys[i];
@ -348,33 +343,33 @@ const presentationGenerationSlice = createSlice({
current = current[index];
}
}
// Set the icon properties
const finalKey = keys[keys.length - 1];
const target = isNaN(Number(finalKey)) ? current[finalKey] : current[Number(finalKey)];
// Preserve existing properties if the target already exists
const updatedValue = {
...(target && typeof target === 'object' ? target : {}),
__icon_url__: url,
__icon_query__: queryText || (target?.__icon_query__) || ''
};
if (isNaN(Number(finalKey))) {
current[finalKey] = updatedValue;
} else {
current[Number(finalKey)] = updatedValue;
}
// Add debugging
console.log('Redux: Updated slide icon at path:', path, 'with URL:', url);
};
// Update the slide icon
if (dataPath && slide.content) {
setNestedIconValue(slide.content, dataPath, iconUrl, query);
}
// Also update the icons array if it exists
if (slide.icons && Array.isArray(slide.icons)) {
const iconIndex = parseInt(dataPath.split('[')[1]?.split(']')[0]) || 0;

24
start.js
View file

@ -103,19 +103,19 @@ const startServers = async () => {
console.error("FastAPI process failed to start:", err);
});
const appmcpProcess = spawn(
"python",
["mcp_server.py", "--port", appmcpPort.toString()],
{
cwd: fastapiDir,
stdio: "inherit",
env: process.env,
},
);
// const appmcpProcess = spawn(
// "python",
// ["mcp_server.py", "--port", appmcpPort.toString()],
// {
// cwd: fastapiDir,
// stdio: "inherit",
// env: process.env,
// },
// );
appmcpProcess.on("error", (err) => {
console.error("App MCP process failed to start:", err);
});
// appmcpProcess.on("error", (err) => {
// console.error("App MCP process failed to start:", err);
// });
const nextjsProcess = spawn(
"npm",