mirror of
https://github.com/MODSetter/SurfSense.git
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feat: Added Speech to Text support.
- Supports audio & video files. - Will be useful for Youtube vids which dont have transcripts.
This commit is contained in:
parent
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8 changed files with 172 additions and 73 deletions
69
README.md
69
README.md
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@ -27,28 +27,27 @@ https://github.com/user-attachments/assets/bf64a6ca-934b-47ac-9e1b-edac5fe972ec
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## Key Features
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### 1. Latest
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#### 💡 **Idea**:
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### 💡 **Idea**:
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Have your own highly customizable private NotebookLM and Perplexity integrated with external sources.
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#### 📁 **Multiple File Format Uploading Support**
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Save content from your own personal files *(Documents, images and supports **27 file extensions**)* to your own personal knowledge base .
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#### 🔍 **Powerful Search**
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### 📁 **Multiple File Format Uploading Support**
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Save content from your own personal files *(Documents, images, videos and supports **34 file extensions**)* to your own personal knowledge base .
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### 🔍 **Powerful Search**
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Quickly research or find anything in your saved content .
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#### 💬 **Chat with your Saved Content**
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### 💬 **Chat with your Saved Content**
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Interact in Natural Language and get cited answers.
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#### 📄 **Cited Answers**
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### 📄 **Cited Answers**
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Get Cited answers just like Perplexity.
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#### 🔔 **Privacy & Local LLM Support**
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### 🔔 **Privacy & Local LLM Support**
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Works Flawlessly with Ollama local LLMs.
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#### 🏠 **Self Hostable**
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### 🏠 **Self Hostable**
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Open source and easy to deploy locally.
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#### 🎙️ Podcasts
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### 🎙️ Podcasts
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- Blazingly fast podcast generation agent. (Creates a 3-minute podcast in under 20 seconds.)
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- Convert your chat conversations into engaging audio content
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- Support for multiple TTS providers (OpenAI, Azure, Google Vertex AI)
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#### 📊 **Advanced RAG Techniques**
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### 📊 **Advanced RAG Techniques**
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- Supports 150+ LLM's
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- Supports 6000+ Embedding Models.
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- Supports all major Rerankers (Pinecode, Cohere, Flashrank etc)
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@ -56,7 +55,7 @@ Open source and easy to deploy locally.
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- Utilizes Hybrid Search (Semantic + Full Text Search combined with Reciprocal Rank Fusion).
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- RAG as a Service API Backend.
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#### ℹ️ **External Sources**
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### ℹ️ **External Sources**
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- Search Engines (Tavily, LinkUp)
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- Slack
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- Linear
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@ -65,7 +64,39 @@ Open source and easy to deploy locally.
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- GitHub
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- and more to come.....
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#### 🔖 Cross Browser Extension
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### 📄 **Supported File Extensions**
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#### Document
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`.doc`, `.docx`, `.odt`, `.rtf`, `.pdf`, `.xml`
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#### Text & Markup
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`.txt`, `.md`, `.markdown`, `.rst`, `.html`, `.org`
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#### Spreadsheets & Tables
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`.xls`, `.xlsx`, `.csv`, `.tsv`
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#### Audio & Video
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`.mp3`, `.mpga`, `.m4a`, `.wav`, `.mp4`, `.mpeg`, `.webm`
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#### Images
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`.jpg`, `.jpeg`, `.png`, `.bmp`, `.tiff`, `.heic`
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#### Email & eBooks
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`.eml`, `.msg`, `.epub`
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#### PowerPoint Presentations & Other
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`.ppt`, `.pptx`, `.p7s`
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### 🔖 Cross Browser Extension
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- The SurfSense extension can be used to save any webpage you like.
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- Its main usecase is to save any webpages protected beyond authentication.
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@ -209,16 +240,8 @@ Before installation, make sure to complete the [prerequisite setup steps](https:
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## Future Work
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- Add More Connectors.
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- Patch minor bugs.
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- Implement Canvas.
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- Complete Hybrid Search. **[Done]**
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- Add support for file uploads QA. **[Done]**
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- Shift to WebSockets for Streaming responses. **[Deprecated in favor of AI SDK Stream Protocol]**
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- Based on feedback, I will work on making it compatible with local models. **[Done]**
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- Cross Browser Extension **[Done]**
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- Critical Notifications **[Done | PAUSED]**
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- Saving Chats **[Done]**
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- Basic keyword search page for saved sessions **[Done]**
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- Multi & Single Document Chat **[Done]**
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- Document Chat **[REIMPLEMENT]**
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- Document Podcasts
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@ -18,6 +18,9 @@ LONG_CONTEXT_LLM="gemini/gemini-2.0-flash"
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#LiteLLM TTS Provider: https://docs.litellm.ai/docs/text_to_speech#supported-providers
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TTS_SERVICE="openai/tts-1"
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#LiteLLM STT Provider: https://docs.litellm.ai/docs/audio_transcription#supported-providers
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STT_SERVICE="openai/whisper-1"
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# Chosen LiteLLM Providers Keys
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OPENAI_API_KEY="sk-proj-iA"
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GEMINI_API_KEY="AIzaSyB6-1641124124124124124124124124124"
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@ -35,3 +38,5 @@ LANGSMITH_PROJECT="surfsense"
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FAST_LLM_API_BASE=""
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STRATEGIC_LLM_API_BASE=""
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LONG_CONTEXT_LLM_API_BASE=""
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TTS_SERVICE_API_BASE=""
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STT_SERVICE_API_BASE=""
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@ -135,14 +135,23 @@ async def create_merged_podcast_audio(state: State, config: RunnableConfig) -> D
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filename = f"{temp_dir}/{session_id}_{index}.mp3"
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try:
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# Generate speech using litellm
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response = await aspeech(
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model=app_config.TTS_SERVICE,
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voice=voice,
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input=dialog,
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max_retries=2,
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timeout=600,
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)
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if app_config.TTS_SERVICE_API_BASE:
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response = await aspeech(
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model=app_config.TTS_SERVICE,
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api_base=app_config.TTS_SERVICE_API_BASE,
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voice=voice,
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input=dialog,
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max_retries=2,
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timeout=600,
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)
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else:
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response = await aspeech(
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model=app_config.TTS_SERVICE,
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voice=voice,
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input=dialog,
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max_retries=2,
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timeout=600,
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)
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# Save the audio to a file - use proper streaming method
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with open(filename, 'wb') as f:
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@ -6,7 +6,7 @@ from chonkie import AutoEmbeddings, CodeChunker, RecursiveChunker
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from dotenv import load_dotenv
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from langchain_community.chat_models import ChatLiteLLM
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from rerankers import Reranker
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from litellm import speech
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# Get the base directory of the project
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BASE_DIR = Path(__file__).resolve().parent.parent.parent
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@ -97,6 +97,12 @@ class Config:
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# Litellm TTS Configuration
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TTS_SERVICE = os.getenv("TTS_SERVICE")
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TTS_SERVICE_API_BASE = os.getenv("TTS_SERVICE_API_BASE")
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# Litellm STT Configuration
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STT_SERVICE = os.getenv("STT_SERVICE")
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STT_SERVICE_API_BASE = os.getenv("STT_SERVICE_API_BASE")
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# Validation Checks
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# Check embedding dimension
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@ -1,3 +1,4 @@
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from litellm import atranscription
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from fastapi import APIRouter, Depends, BackgroundTasks, UploadFile, Form, HTTPException
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy.future import select
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@ -7,6 +8,7 @@ from app.schemas import DocumentsCreate, DocumentUpdate, DocumentRead
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from app.users import current_active_user
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from app.utils.check_ownership import check_ownership
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from app.tasks.background_tasks import add_received_markdown_file_document, add_extension_received_document, add_received_file_document, add_crawled_url_document, add_youtube_video_document
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from app.config import config as app_config
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# Force asyncio to use standard event loop before unstructured imports
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import asyncio
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try:
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@ -17,9 +19,9 @@ import os
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os.environ["UNSTRUCTURED_HAS_PATCHED_LOOP"] = "1"
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router = APIRouter()
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@router.post("/documents/")
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async def create_documents(
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request: DocumentsCreate,
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detail=f"Failed to process documents: {str(e)}"
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)
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@router.post("/documents/fileupload")
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async def create_documents(
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files: list[UploadFile],
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markdown_content,
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search_space_id
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)
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# Check if the file is an audio file
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elif filename.lower().endswith(('.mp3', '.mp4', '.mpeg', '.mpga', '.m4a', '.wav', '.webm')):
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# Open the audio file for transcription
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with open(file_path, "rb") as audio_file:
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# Use LiteLLM for audio transcription
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if app_config.STT_SERVICE_API_BASE:
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transcription_response = await atranscription(
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model=app_config.STT_SERVICE,
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file=audio_file,
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api_base=app_config.STT_SERVICE_API_BASE
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)
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else:
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transcription_response = await atranscription(
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model=app_config.STT_SERVICE,
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file=audio_file
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)
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# Extract the transcribed text
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transcribed_text = transcription_response.get("text", "")
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# Add metadata about the transcription
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transcribed_text = f"# Transcription of {filename}\n\n{transcribed_text}"
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# Clean up the temp file
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try:
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os.unlink(file_path)
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except:
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pass
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# Process transcription as markdown document
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await add_received_markdown_file_document(
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session,
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filename,
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transcribed_text,
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search_space_id
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)
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else:
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# Use synchronous unstructured API to avoid event loop issues
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from langchain_unstructured import UnstructuredLoader
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import logging
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logging.error(f"Error processing file in background: {str(e)}")
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@router.get("/documents/", response_model=List[DocumentRead])
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async def read_documents(
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skip: int = 0,
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user: User = Depends(current_active_user)
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):
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try:
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query = select(Document).join(SearchSpace).filter(SearchSpace.user_id == user.id)
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query = select(Document).join(SearchSpace).filter(
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SearchSpace.user_id == user.id)
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# Filter by search_space_id if provided
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if search_space_id is not None:
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detail=f"Failed to fetch documents: {str(e)}"
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)
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@router.get("/documents/{document_id}", response_model=DocumentRead)
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async def read_document(
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document_id: int,
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detail=f"Failed to fetch document: {str(e)}"
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)
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@router.put("/documents/{document_id}", response_model=DocumentRead)
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async def update_document(
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document_id: int,
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detail=f"Failed to update document: {str(e)}"
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)
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@router.delete("/documents/{document_id}", response_model=dict)
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async def delete_document(
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document_id: int,
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import logging
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logging.error(f"Error processing extension document: {str(e)}")
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async def process_crawled_url_with_new_session(
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url: str,
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search_space_id: int
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import logging
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logging.error(f"Error processing crawled URL: {str(e)}")
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async def process_file_in_background_with_new_session(
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file_path: str,
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filename: str,
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async with async_session_maker() as session:
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await process_file_in_background(file_path, filename, search_space_id, session)
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async def process_youtube_video_with_new_session(
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url: str,
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search_space_id: int
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except Exception as e:
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import logging
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logging.error(f"Error processing YouTube video: {str(e)}")
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'text/html': ['.html'],
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'image/jpeg': ['.jpeg', '.jpg'],
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'image/png': ['.png'],
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'text/markdown': ['.md'],
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'text/markdown': ['.md', '.markdown'],
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'application/vnd.ms-outlook': ['.msg'],
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'application/vnd.oasis.opendocument.text': ['.odt'],
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'text/x-org': ['.org'],
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'application/vnd.ms-excel': ['.xls'],
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'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet': ['.xlsx'],
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'application/xml': ['.xml'],
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'audio/mpeg': ['.mp3', '.mpeg', '.mpga'],
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'audio/mp4': ['.mp4', '.m4a'],
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'audio/wav': ['.wav'],
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'audio/webm': ['.webm'],
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}
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const supportedExtensions = Array.from(new Set(Object.values(acceptedFileTypes).flat())).sort()
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| UNSTRUCTURED_API_KEY | API key for Unstructured.io service for document parsing |
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| FIRECRAWL_API_KEY | API key for Firecrawl service for web crawling |
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| TTS_SERVICE | Text-to-Speech API provider for Podcasts (e.g., `openai/tts-1`, `azure/neural`, `vertex_ai/`). See [supported providers](https://docs.litellm.ai/docs/text_to_speech#supported-providers) |
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| STT_SERVICE | Speech-to-Text API provider for Podcasts (e.g., `openai/whisper-1`). See [supported providers](https://docs.litellm.ai/docs/audio_transcription#supported-providers) |
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Include API keys for the LLM providers you're using. For example:
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| FAST_LLM_API_BASE | Custom API base URL for the fast LLM |
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| STRATEGIC_LLM_API_BASE | Custom API base URL for the strategic LLM |
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| LONG_CONTEXT_LLM_API_BASE | Custom API base URL for the long context LLM |
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| TTS_SERVICE_API_BASE | Custom API base URL for the Text-to-Speech (TTS) service |
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| STT_SERVICE_API_BASE | Custom API base URL for the Speech-to-Text (STT) service |
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For other LLM providers, refer to the [LiteLLM documentation](https://docs.litellm.ai/docs/providers).
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| UNSTRUCTURED_API_KEY | API key for Unstructured.io service |
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| FIRECRAWL_API_KEY | API key for Firecrawl service (if using crawler) |
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| TTS_SERVICE | Text-to-Speech API provider for Podcasts (e.g., `openai/tts-1`, `azure/neural`, `vertex_ai/`). See [supported providers](https://docs.litellm.ai/docs/text_to_speech#supported-providers) |
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| STT_SERVICE | Speech-to-Text API provider for Podcasts (e.g., `openai/whisper-1`). See [supported providers](https://docs.litellm.ai/docs/audio_transcription#supported-providers) |
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**Important**: Since LLM calls are routed through LiteLLM, include API keys for the LLM providers you're using:
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| FAST_LLM_API_BASE | Custom API base URL for the fast LLM |
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| STRATEGIC_LLM_API_BASE | Custom API base URL for the strategic LLM |
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| LONG_CONTEXT_LLM_API_BASE | Custom API base URL for the long context LLM |
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| TTS_SERVICE_API_BASE | Custom API base URL for the Text-to-Speech (TTS) service |
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| STT_SERVICE_API_BASE | Custom API base URL for the Speech-to-Text (STT) service |
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### 2. Install Dependencies
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