{"slug": "fastapi-for-ai-engineers-part-8-uploading-files-with-fastapi", "title": "FastAPI for AI Engineers - Part 8: Uploading Files with FastAPI", "summary": "A developer's tutorial series on FastAPI for AI engineers covers file uploads, demonstrating how to use FastAPI's File and UploadFile classes with python-multipart. The post shows how to receive, read, and save uploaded files, which are essential for AI applications like document Q&A systems and resume analyzers. It includes code examples and explains the workflow for processing uploaded files in AI pipelines.", "body_md": "In the previous article, we learned how to secure our APIs using JWT Authentication and protect routes from unauthorized access.\n\nNow let's explore another feature used in almost every AI application—**file uploads**.\n\nIf you've built applications like ChatGPT, document Q&A systems, resume analyzers, legal contract reviewers, or medical report analyzers, one thing is common across all of them:\n\n**The user uploads a file.**\n\nWithout file uploads, there is nothing for the AI model to process.\n\nIf you haven't read the previous article, check it out first to continue the series:\n\n[Protecting routes with JWT Tokens](https://dev.to/zeroshotanufastapi-for-ai-engineers-part-7-protecting-routes-with-jwt-tokens-273p)\n\nConsider some popular AI applications:\n\nThe workflow usually looks like this:\n\n```\n  User\n   │\n   ▼\nUpload File\n   │\n   ▼\nFastAPI\n   │\n   ▼\nSave / Read File\n   │\n   ▼\nProcess using AI\n```\n\nFastAPI makes uploading files extremely simple.\n\nFastAPI uses **python-multipart** to process uploaded files.\n\nInstall it using:\n\n```\npip install python-multipart\n```\n\nFastAPI provides two important classes:\n\n`File`\n\n`UploadFile`\n\nLet's import them.\n\n``` python\nfrom fastapi import FastAPI, File, UploadFile\n\napp = FastAPI()\npython\n@app.post(\"/upload\")\ndef upload_file(file: UploadFile):\n\n    return {\n        \"filename\": file.filename\n    }\n```\n\nRun the application.\n\nOpen Swagger UI.\n\nClick **POST /upload**.\n\nYou'll notice FastAPI automatically provides a file picker.\n\nUpload a file.\n\nResponse:\n\n```\n{\n    \"filename\": \"resume.pdf\"\n}\n```\n\nOur API successfully received the uploaded file.\n\nYou might wonder:\n\nWhy didn't we simply use a string or bytes?\n\nFastAPI provides the `UploadFile`\n\nclass because it contains useful information about the uploaded file.\n\nSome commonly used attributes are:\n\n```\nfile.filename\n```\n\nReturns:\n\n```\nresume.pdf\nfile.content_type\n```\n\nReturns:\n\n```\napplication/pdf\nawait file.read()\n```\n\nReads the file contents.\n\nThese attributes become extremely useful when building AI applications.\n\nSuppose we want to know how many bytes were uploaded.\n\n``` python\n@app.post(\"/upload\")\nasync def upload_file(file: UploadFile):\n\n    contents = await file.read()\n\n    return {\n        \"filename\": file.filename,\n        \"size\": len(contents)\n    }\n```\n\nExample response:\n\n```\n{\n    \"filename\": \"contract.pdf\",\n    \"size\": 254321\n}\n```\n\nNotice that we changed the function to:\n\n```\nasync def\n```\n\nThis is because `file.read()`\n\nis an asynchronous operation.\n\nIn many applications, we don't just read the file.\n\nWe save it for later processing.\n\n``` python\n@app.post(\"/upload\")\nasync def upload_file(file: UploadFile):\n\n    contents = await file.read()\n\n    with open(file.filename, \"wb\") as f:\n        f.write(contents)\n\n    return {\n        \"message\": \"File uploaded successfully.\"\n    }\ncontents = await file.read()\n```\n\nReads the uploaded file into memory.\n\n```\nwith open(file.filename, \"wb\")\n```\n\nCreates a new file.\n\nThe `\"wb\"`\n\nmode means:\n\nBinary mode is important because PDFs, images, Word documents, and many other files are not plain text.\n\n```\nf.write(contents)\n```\n\nWrites the uploaded data to disk.\n\nSuppose a user uploads a legal contract.\n\n```\n   contract.pdf\n        │\n        ▼\nFastAPI Upload Endpoint\n        │\n        ▼\n     Save PDF\n        │\n        ▼\n    Extract Text\n        │\n        ▼\nCreate Embeddings\n        │\n        ▼\nStore in Vector Database\n        │\n        ▼\n   Ask Questions\n```\n\nThis is the same workflow followed by many Retrieval-Augmented Generation (RAG) applications.\n\nSimilarly,\n\nResume Analyzer:\n\n```\nResume.pdf\n      │\n      ▼\nExtract Text\n      │\n      ▼\nSkill Extraction\n      │\n      ▼\n  ATS Score\n```\n\nMedical Report Analyzer:\n\n```\nBlood_Report.pdf\n        │\n        ▼\nOCR / Text Extraction\n        │\n        ▼\n  LLM Analysis\n        │\n        ▼\n  Health Summary\n```\n\nFile uploads are the entry point for almost every document-based AI application.\n\nFastAPI also allows uploading files as raw bytes.\n\n``` python\n@app.post(\"/upload\")\nasync def upload(file: bytes = File()):\n\n    return {\n        \"size\": len(file)\n    }\n```\n\nAlthough this works, it is rarely used for large files.\n\n`UploadFile`\n\nis generally preferred because:\n\nFor most production applications, **UploadFile** is the recommended choice.\n\n``` python\nfrom fastapi import FastAPI, UploadFile\n\napp = FastAPI()\n\n@app.post(\"/upload\")\nasync def upload_file(file: UploadFile):\n\n    contents = await file.read()\n\n    with open(file.filename, \"wb\") as f:\n        f.write(contents)\n\n    return {\n        \"filename\": file.filename,\n        \"content_type\": file.content_type,\n        \"size\": len(contents),\n        \"message\": \"Upload Successful\"\n    }\nUser Uploads File\n        │\n        ▼\nFastAPI Receives Upload\n        │\n        ▼\nUploadFile Object Created\n        │\n        ▼\n    Read File\n        │\n        ▼\n    Save File\n        │\n        ▼\nAI Processing Begins\n```\n\nUploading files is one of the most important capabilities of modern AI backends.\n\nWhether you're building a chatbot over PDFs, a resume analyzer, a legal contract assistant, or a medical report analyzer, every application begins with accepting user files.\n\nToday we learned how to:\n\n`UploadFile`\n\nobjectIt's been some time since I've uploaded. We will continue with our FastAPI series in the upcoming posts.", "url": "https://wpnews.pro/news/fastapi-for-ai-engineers-part-8-uploading-files-with-fastapi", "canonical_source": "https://dev.to/zeroshotanu/fastapi-for-ai-engineers-part-8-uploading-files-with-fastapi-4f9b", "published_at": "2026-08-31 15:37:39+00:00", "updated_at": "2026-08-31 15:52:41.608906+00:00", "lang": "en", "topics": ["developer-tools"], "entities": ["FastAPI", "python-multipart"], "alternates": {"html": "https://wpnews.pro/news/fastapi-for-ai-engineers-part-8-uploading-files-with-fastapi", "markdown": "https://wpnews.pro/news/fastapi-for-ai-engineers-part-8-uploading-files-with-fastapi.md", "text": "https://wpnews.pro/news/fastapi-for-ai-engineers-part-8-uploading-files-with-fastapi.txt", "jsonld": "https://wpnews.pro/news/fastapi-for-ai-engineers-part-8-uploading-files-with-fastapi.jsonld"}}