> ## Documentation Index > Fetch the complete documentation index at: https://docs.bigdata.com/llms.txt > Use this file to discover all available pages before exploring further. # Upload and search your content It will only take you a few minutes. This guide walks you through: ✅ Set up authentication (API key)
✅ Create two sample files to upload
✅ Upload private files via the **Content API**
✅ Query bigdata.com with the **Search API**
Private & Secure: No LLM training on your data **Ready to get started?** Run the examples below in your terminal (or open the notebook in Colab). All requests use the REST API with your API key in the `X-API-KEY` header. Open in Colab # Set up authentication Send your API key in the `X-API-KEY` header on every request. See [Authentication](/api-rest/introduction) for details. Replace `YOUR_API_KEY` in the examples with your key. # Create two sample files to upload Create the following two sample files in your local directory. File name `data_science_research-2020-06.txt`: ```text theme={null} RavenPack Data Science researchers recommend the following stocks in June 2020 Microsoft (NASDAQ: MSFT): Microsoft has been heavily investing in AI and cloud computing, which are key growth areas for the company. Datadog (NASDAQ: DDOG): Datadog is a leading provider of monitoring and analytics solutions for cloud-based applications. Oracle (NYSE: ORCL): Oracle is a major player in the enterprise software and cloud computing market. ``` File name `soup_recipes-2020-06.txt`: ```text theme={null} We recommend making chicken noodle soup with homemade chicken stock ``` # Upload private files (Content API) Upload the two files using the [Content API](/api-rest/content_introduction): request a pre-signed URL and document id with **POST /contents/v1/documents**, then **PUT** the file to that URL. Bigdata enriches each document (extraction, structure and annotation of the content) and indexes it, making it available for Search and Research Agent. Use `published_ts` to set the document date (so we can narrow search to June 2020) and `tags` to filter by type later. **1. Request upload URL and upload the first file** ```bash theme={null} # Request a pre-signed URL (replace YOUR_API_KEY with your key) RESP=$(curl -s -X POST 'https://api.bigdata.com/contents/v1/documents' \ -H 'X-API-KEY: YOUR_API_KEY' \ -d '{ "file_name": "data_science_research-2020-06.txt", "published_ts": "2020-06-10T12:00:00Z", "tags": ["Data Science Research"], "share_with_org": false }') # Extract the URL (e.g. with jq) and PUT the file URL=$(echo $RESP | jq -r '.url') curl -X PUT "$URL" --data-binary '@./data_science_research-2020-06.txt' ``` **2. Request upload URL and upload the second file** ```bash theme={null} RESP=$(curl -s -X POST 'https://api.bigdata.com/contents/v1/documents' \ -H 'X-API-KEY: YOUR_API_KEY' \ -d '{ "file_name": "soup_recipes-2020-06.txt", "published_ts": "2020-06-10T12:00:00Z", "tags": ["Cooking recipes"], "share_with_org": false }') URL=$(echo $RESP | jq -r '.url') curl -X PUT "$URL" --data-binary '@./soup_recipes-2020-06.txt' ``` After each PUT, Bigdata enriches and indexes the document. The POST response includes an **id** (content ID); use it with [Get document metadata](/api-reference/documents/get-document-metadata) to poll `status` until it is `completed`. See [Upload your own content](/getting-started/upload_your_own_content) for full details. # Query bigdata.com Run a similarity search for "recommend stock" in June 2020. To search only your uploaded files, filter by category `my_files`. Use **POST /v1/search** with a `query` that has `text` (for similarity) and `filters` for timestamp and document category. To restrict results to your uploaded files, set `category` to `my_files`. **Similarity search in June 2020 (all sources):** ```bash theme={null} curl -X POST 'https://api.bigdata.com/v1/search' \ -H 'Content-Type: application/json' \ -H 'X-API-KEY: YOUR_API_KEY' \ --data '{ "query": { "text": "recommend stock", "filters": { "timestamp": { "start": "2020-06-01T00:00:00.000Z", "end": "2020-06-30T23:59:59.999Z" } }, "max_chunks": 10 } }' ``` **Search only your uploaded files (my\_files):** ```bash theme={null} curl -X POST 'https://api.bigdata.com/v1/search' \ -H 'Content-Type: application/json' \ -H 'X-API-KEY: YOUR_API_KEY' \ --data '{ "query": { "text": "recommend stock", "filters": { "timestamp": { "start": "2020-06-01T00:00:00.000Z", "end": "2020-06-30T23:59:59.999Z" }, "category": { "mode": "INCLUDE", "values": ["my_files"] } }, "max_chunks": 10 } }' ``` **Narrow to the publication window of your files (2 seconds around 2020-06-10 12:00:00):** ```bash theme={null} curl -X POST 'https://api.bigdata.com/v1/search' \ -H 'Content-Type: application/json' \ -H 'X-API-KEY: YOUR_API_KEY' \ --data '{ "query": { "text": "recommend stock", "filters": { "timestamp": { "start": "2020-06-10T11:59:59.000Z", "end": "2020-06-10T12:00:01.000Z" }, "category": { "mode": "INCLUDE", "values": ["my_files"] } }, "max_chunks": 10 } }' ``` You should see your two documents (e.g. `data_science_research-2020-06.txt` and `soup_recipes-2020-06.txt`) in the results. **Filter by tag (e.g. only "Data Science Research"):** Use the `tag` filter with `any_of` to restrict to documents that have a specific tag. See [Search API: tag filter](/api-reference/search/search-documents#body-query-filters-tag). ```bash theme={null} curl -X POST 'https://api.bigdata.com/v1/search' \ -H 'Content-Type: application/json' \ -H 'X-API-KEY: YOUR_API_KEY' \ --data '{ "query": { "text": "recommend stock", "filters": { "timestamp": { "start": "2020-06-01T00:00:00.000Z", "end": "2020-06-30T23:59:59.999Z" }, "category": { "mode": "INCLUDE", "values": ["my_files"] }, "tag": { "any_of": ["Data Science Research"] } }, "max_chunks": 10 } }' ``` # Summary Congratulations! You have uploaded private files with the **Content API** and queried them via the **Search API**. **Related documentation** * [Upload your own content](/getting-started/upload_your_own_content): Full guide to the Content API (upload, list, tags, delete). * [Content API introduction](/api-rest/content_introduction): Connectors vs direct upload, and document operations. * [Search API filters](/getting-started/search/query_filters): * All search filters, including [Tags](/getting-started/search/query_filters#filetag) * Use the [Search API category/source filter](/api-reference/search/search-documents#body-query-filters-category) to restrict your query to your uploaded files only. * [Research Agent search tool filters](/api-reference/research-agent/research-agent#body-tools-configs-one-of-0-search): * Restrict context to just your proprietary content applying [content filters](/api-reference/research-agent/research-agent#body-tools-configs-one-of-0-search-query-filters-content-one-of-0-any-of-items-document-types-items-one-of-4-tags). * Narrow the scope of the agent with [tags](/api-reference/research-agent/research-agent#body-tools-configs-one-of-0-search-query-filters-content-one-of-0-any-of-items-document-types-items-one-of-4-tags). * [Batch files upload](./batch-files-upload): Script for uploading many files. Click on the playgrounds below, use the source selector and filter by **My Files** to test and retrieve your uploaded content. Search across your private content and other sources. In the playground, open the source selector and choose **My Files** to limit results to your uploaded documents. Run research over your private content and real-time data. In the playground, use the source selector and filter by **My Files** to ground answers in your documents.