mirror of
https://github.com/Significant-Gravitas/AutoGPT.git
synced 2026-02-09 14:25:25 -05:00
c1a1767034
- Add generate_block_docs.py script that introspects block code to
generate markdown
- Support manual content preservation via <!-- MANUAL: --> markers
- Add migrate_block_docs.py to preserve existing manual content from git
HEAD
- Add CI workflow (docs-block-sync.yml) to fail if docs drift from code
- Add Claude PR review workflow (docs-claude-review.yml) for doc changes
- Add manual LLM enhancement workflow (docs-enhance.yml)
- Add GitBook configuration (.gitbook.yaml, SUMMARY.md)
- Fix non-deterministic category ordering (categories is a set)
- Add comprehensive test suite (32 tests)
- Generate docs for 444 blocks with 66 preserved manual sections
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
<!-- Clearly explain the need for these changes: -->
### Changes 🏗️
<!-- Concisely describe all of the changes made in this pull request:
-->
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Extensively test code generation for the docs pages
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Introduces an automated documentation pipeline for blocks and
integrates it into CI.
>
> - Adds `scripts/generate_block_docs.py` (+ tests) to introspect blocks
and generate `docs/integrations/**`, preserving `<!-- MANUAL: -->`
sections
> - New CI workflows: **docs-block-sync** (fails if docs drift),
**docs-claude-review** (AI review for block/docs PRs), and
**docs-enhance** (optional LLM improvements)
> - Updates existing Claude workflows to use `CLAUDE_CODE_OAUTH_TOKEN`
instead of `ANTHROPIC_API_KEY`
> - Improves numerous block descriptions/typos and links across backend
blocks to standardize docs output
> - Commits initial generated docs including
`docs/integrations/README.md` and many provider/category pages
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
631e53e0f6. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
3.2 KiB
3.2 KiB
Exa Search
Blocks for searching the web using Exa's advanced neural and keyword search API.
Exa Search
What it is
Searches the web using Exa's advanced search API
How it works
This block uses Exa's advanced search API to find web content. Unlike traditional search engines, Exa offers neural search that understands semantic meaning, making it excellent for finding specific types of content. You can choose between keyword search (traditional), neural search (semantic understanding), or fast search.
The block supports powerful filtering by domain, date ranges, content categories (companies, research papers, news, etc.), and text patterns. Results include URLs, titles, and optionally full content extraction.
Inputs
| Input | Description | Type | Required |
|---|---|---|---|
| query | The search query | str | Yes |
| type | Type of search | "keyword" | "neural" | "fast" | "auto" | No |
| category | Category to search within: company, research paper, news, pdf, github, tweet, personal site, linkedin profile, financial report | "company" | "research paper" | "news" | "pdf" | "github" | "tweet" | "personal site" | "linkedin profile" | "financial report" | No |
| user_location | The two-letter ISO country code of the user (e.g., 'US') | str | No |
| number_of_results | Number of results to return | int | No |
| include_domains | Domains to include in search | List[str] | No |
| exclude_domains | Domains to exclude from search | List[str] | No |
| start_crawl_date | Start date for crawled content | str (date-time) | No |
| end_crawl_date | End date for crawled content | str (date-time) | No |
| start_published_date | Start date for published content | str (date-time) | No |
| end_published_date | End date for published content | str (date-time) | No |
| include_text | Text patterns to include | List[str] | No |
| exclude_text | Text patterns to exclude | List[str] | No |
| contents | Content retrieval settings | ContentSettings | No |
| moderation | Enable content moderation to filter unsafe content from search results | bool | No |
Outputs
| Output | Description | Type |
|---|---|---|
| error | Error message if the request failed | str |
| results | List of search results | List[ExaSearchResults] |
| result | Single search result | ExaSearchResults |
| context | A formatted string of the search results ready for LLMs. | str |
| search_type | For auto searches, indicates which search type was selected. | str |
| resolved_search_type | The search type that was actually used for this request (neural or keyword) | str |
| cost_dollars | Cost breakdown for the request | CostDollars |
Possible use case
Competitive Research: Search for companies in a specific industry, filtered by recent news or funding announcements.
Content Curation: Find relevant articles and research papers on specific topics for newsletters or content aggregation.
Lead Generation: Search for companies matching specific criteria (industry, size, recent activity) for sales prospecting.