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107 Commits

Author SHA1 Message Date
github-actions[bot]
8475051a7c chore(release): Update version to v1.4.351 2025-12-18 18:37:22 +00:00
Kayvan Sylvan
9f3122ba35 Merge pull request #1882 from bvandevliet/fix/include-yt-dlp-in-docker-image
Added yt-dlp package to docker image.
2025-12-18 10:34:54 -08:00
Changelog Bot
f61db2cdce chore: incoming 1882 changelog entry 2025-12-18 10:30:23 -08:00
github-actions[bot]
8a2d5f82f1 chore(release): Update version to v1.4.350 2025-12-18 18:29:51 +00:00
Kayvan Sylvan
edaf1a0110 Merge pull request #1884 from ksylvan/kayvan/add-swagger-ui-to-server
Implement interactive Swagger API documentation and automated OpenAPI specification generation.
2025-12-18 10:27:06 -08:00
Changelog Bot
3a4468b970 chore: incoming 1884 changelog entry 2025-12-18 10:05:33 -08:00
Kayvan Sylvan
645190be3a feat: update REST API docs with new fields and examples
### CHANGES

- Add detailed prompt fields table with defaults
- Introduce chat options table with new parameters
- Include complete workflow examples for YouTube summary
- Provide alternative script and CLI comparison for flexibility
2025-12-18 07:30:34 -08:00
Kayvan Sylvan
c06c94f8b8 # CHANGES
- Add Swagger UI at `/swagger/index.html` endpoint
- Generate OpenAPI spec files (JSON and YAML)
- Document chat, patterns, and models endpoints
- Update contributing guide with Swagger annotation instructions
- Add swaggo dependencies to project
- Configure authentication bypass for Swagger documentation
- Add custom YAML handler for OpenAPI spec
- Update REST API documentation with Swagger links
- Add dictionary entries for new tools
2025-12-18 07:12:08 -08:00
Bob Vandevliet
d84bd6f989 Added yt-dlp package to docker image. 2025-12-18 11:16:39 +01:00
Kayvan Sylvan
7ab5e8956c Merge pull request #1880 from ksylvan/kayvan/rest-api-docs 2025-12-17 19:29:28 -08:00
Kayvan Sylvan
99b8b6a972 - Add README table-of-contents link for REST API.
- Document REST API server startup and capabilities.
- Add endpoint overview for chat, patterns, contexts.
- Describe sessions management and model listing endpoints.
- Provide curl examples for key API workflows.
- Explain Ollama compatibility mode endpoints and port.
2025-12-17 19:11:57 -08:00
github-actions[bot]
833b09081e chore(release): Update version to v1.4.349 2025-12-16 08:12:11 +00:00
Kayvan Sylvan
201d1fb791 Merge pull request #1877 from ksylvan/kayvan/modernize-part4-string-and-slice-syntax
modernize: update GitHub Actions and modernize Go code
2025-12-16 00:09:43 -08:00
Changelog Bot
6ecbd044e6 chore: incoming 1877 changelog entry 2025-12-16 00:06:39 -08:00
Kayvan Sylvan
fdadeae1e7 modernize: update GitHub Actions and modernize Go code with latest stdlib features
## CHANGES

- Upgrade GitHub Actions to latest versions (v6, v21)
- Add modernization check step in CI workflow
- Replace strings manipulation with `strings.CutPrefix` and `strings.CutSuffix`
- Replace manual loops with `slices.Contains` for validation
- Use `strings.SplitSeq` for iterator-based string splitting
- Replace `bytes.TrimPrefix` with `bytes.CutPrefix` for clarity
- Use `strings.Builder` instead of string concatenation
- Replace `fmt.Sprintf` with `fmt.Appendf` for efficiency
- Simplify padding calculation with `max` builtin
2025-12-15 23:55:37 -08:00
github-actions[bot]
57c3e36574 chore(release): Update version to v1.4.348 2025-12-16 07:34:45 +00:00
Kayvan Sylvan
1b98a8899f Merge pull request #1876 from ksylvan/kayvan/modernize-part3-typefor-and-range-loops
modernize Go code with TypeFor and range loops
2025-12-15 23:31:44 -08:00
Kayvan Sylvan
a4484d4e01 refactor: modernize Go code with TypeFor and range loops
- Replace reflect.TypeOf with TypeFor generic syntax
- Convert traditional for loops to range-based iterations
- Simplify reflection usage in CLI flag handling
- Update test loops to use range over integers
- Refactor string processing loops in template plugin
2025-12-15 23:29:41 -08:00
github-actions[bot]
005d43674f chore(release): Update version to v1.4.347 2025-12-16 06:51:40 +00:00
Kayvan Sylvan
3a69437790 Merge pull request #1875 from ksylvan/kayvan/modernize-part2-loops
modernize: update benchmarks to use b.Loop and refactor map copying
2025-12-15 22:48:59 -08:00
Changelog Bot
b057f52ca6 chore: incoming 1875 changelog entry 2025-12-15 22:46:45 -08:00
Kayvan Sylvan
dccdfbac8c test: update benchmarks to use b.Loop and refactor map copying
# CHANGES

- update benchmark loops to use cleaner `b.Loop()` syntax
- remove unnecessary `b.ResetTimer()` call in token benchmark
- use `maps.Copy` for merging variables in patterns handler
2025-12-15 22:40:55 -08:00
github-actions[bot]
98038707f1 chore(release): Update version to v1.4.346 2025-12-16 06:30:55 +00:00
Kayvan Sylvan
03b22a70f0 Merge pull request #1874 from ksylvan/kayvan/modernize-part1
refactor: replace interface{} with any across codebase
2025-12-15 22:28:15 -08:00
Kayvan Sylvan
66025d516c refactor: replace interface{} with any across codebase
- Part 1 of incorporating `modernize` tool into Fabric.
- Replace `interface{}` with `any` in slice type declarations
- Update map types from `map[string]interface{}` to `map[string]any`
- Change variadic function parameters to use `...any` instead of `...interface{}`
- Modernize JSON unmarshaling variables to `any` for consistency
- Update struct fields and method signatures to prefer `any` alias
- Ensure all type assertions and conversions use `any` throughout codebase
- Add PR guidelines in docs to encourage focused, reviewable changes
2025-12-15 22:25:18 -08:00
github-actions[bot]
32ef2b73c4 chore(release): Update version to v1.4.345 2025-12-15 06:03:18 +00:00
Kayvan Sylvan
656ca7ee28 Merge pull request #1870 from ksylvan/kayvan/update-web-ui-pdfjs-library
Web UI: upgrade pdfjs and add SSR-safe dynamic PDF worker init
2025-12-14 22:00:41 -08:00
Changelog Bot
0025466e4e chore: incoming 1870 changelog entry 2025-12-14 21:57:06 -08:00
Kayvan Sylvan
4c2b38ca53 feat: upgrade pdfjs and add SSR-safe dynamic PDF worker init
- Upgrade `pdfjs-dist` to v5 with new engine requirement
- Dynamically import PDF.js to avoid SSR import-time crashes
- Configure PDF worker via CDN using runtime PDF.js version
- Update PDF conversion pipeline to use lazy initialization
- Guard chat message localStorage persistence behind browser checks
- Reformat ChatService with consistent imports and typings
- Bump `patch-package` and refresh pnpm lock dependency graph
- Add `skeletonlabs` to VSCode spellcheck dictionary
2025-12-14 16:12:23 -08:00
github-actions[bot]
9c7ce4a974 chore(release): Update version to v1.4.344 2025-12-14 08:14:21 +00:00
Kayvan Sylvan
626c492c63 Merge pull request #1867 from jaredmontoya/update-flake
chore: update flake
2025-12-14 00:11:45 -08:00
Changelog Bot
71fb3fea7e chore: incoming 1867 changelog entry 2025-12-14 00:08:33 -08:00
Kayvan Sylvan
3bc1150da4 Merge branch 'main' into update-flake 2025-12-14 00:07:51 -08:00
github-actions[bot]
827e0aeca7 chore(release): Update version to v1.4.343 2025-12-14 08:05:48 +00:00
Kayvan Sylvan
0a1e01c4ab Merge pull request #1829 from danielmiessler/dependabot/npm_and_yarn/web/npm_and_yarn-3c67cbb9cd
chore(deps): bump js-yaml from 4.1.0 to 4.1.1 in /web in the npm_and_yarn group across 1 directory
2025-12-14 00:03:09 -08:00
Changelog Bot
6003bb2c86 chore: incoming 1829 changelog entry 2025-12-13 23:52:18 -08:00
dependabot[bot]
bb896b1064 chore(deps): bump js-yaml
Bumps the npm_and_yarn group with 1 update in the /web directory: [js-yaml](https://github.com/nodeca/js-yaml).


Updates `js-yaml` from 4.1.0 to 4.1.1
- [Changelog](https://github.com/nodeca/js-yaml/blob/master/CHANGELOG.md)
- [Commits](https://github.com/nodeca/js-yaml/compare/4.1.0...4.1.1)

---
updated-dependencies:
- dependency-name: js-yaml
  dependency-version: 4.1.1
  dependency-type: indirect
  dependency-group: npm_and_yarn
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-13 23:52:18 -08:00
jaredmontoya
d149c62a37 chore: update flake 2025-12-13 20:30:31 +01:00
github-actions[bot]
3d25fbc04c chore(release): Update version to v1.4.342 2025-12-13 08:11:50 +00:00
Kayvan Sylvan
4c822d2c59 Merge pull request #1866 from ksylvan/kayvan/errors-never-to-stdout
fix: write CLI and streaming errors to stderr
2025-12-13 00:09:09 -08:00
Changelog Bot
f1ffd6ee29 chore: incoming 1866 changelog entry 2025-12-13 00:07:08 -08:00
Kayvan Sylvan
deb59bdd21 fix: write CLI and streaming errors to stderr
## CHANGES
- Route CLI execution errors to standard error output
- Print Anthropic stream errors to stderr consistently
- Add os import to support stderr error writes
- Preserve help-output suppression and exit behavior
2025-12-13 00:02:44 -08:00
github-actions[bot]
2a1e8dcf12 chore(release): Update version to v1.4.341 2025-12-11 10:49:47 +00:00
Kayvan Sylvan
b6fd81dd16 Merge pull request #1860 from ksylvan/kayvan/fix-for-setup-reset-required-value-now-does-not-show-validation-error
fix: allow resetting required settings without validation errors
2025-12-11 18:47:16 +08:00
Kayvan Sylvan
5b723c9e92 fix: allow resetting required settings without validation errors
CHANGES
- update `Ask` to detect reset command and bypass validation
- refactor `OnAnswer` to support new `isReset` parameter logic
- invoke `ConfigureCustom` in `Setup` to avoid redundant re-validation
- add unit tests ensuring required fields can be reset
- add incoming 1860 changelog entry
2025-12-11 02:39:35 -08:00
github-actions[bot]
93f8978085 chore(release): Update version to v1.4.340 2025-12-08 00:36:16 +00:00
Kayvan Sylvan
4d91bf837f Merge pull request #1856 from ksylvan/kayvan/claude-haiku-4-5
Add support for new ClaudeHaiku 4.5 models
2025-12-08 08:33:51 +08:00
Changelog Bot
cb29a0d606 chore: incoming 1856 changelog entry 2025-12-08 08:30:17 +08:00
Kayvan Sylvan
b1eb7a82d9 feat: add support for new ClaudeHaiku models in client
### CHANGES

- Add `ModelClaudeHaiku4_5` to supported models
- Add `ModelClaudeHaiku4_5_20251001` to supported models
2025-12-08 08:21:18 +08:00
github-actions[bot]
bc8f5add00 chore(release): Update version to v1.4.339 2025-12-08 00:10:02 +00:00
Kayvan Sylvan
c3f874f985 Merge pull request #1855 from ksylvan/kayvan/ollama_image_handling
feat: add image attachment support for Ollama vision models
2025-12-08 08:07:33 +08:00
Changelog Bot
922df52d0c chore: incoming 1855 changelog entry 2025-12-08 08:00:59 +08:00
Kayvan Sylvan
4badfecadb feat: add multi-modal image support to Ollama client
## CHANGES

- Add base64 and io imports for image handling
- Store httpClient separately in Client struct for reuse
- Convert createChatRequest to return error for validation
- Implement convertMessage to handle multi-content chat messages
- Add loadImageBytes to fetch images from URLs
- Support base64 data URLs for inline images
- Handle HTTP image URLs with context propagation
- Replace debug print with proper debuglog usage
2025-12-08 07:48:36 +08:00
github-actions[bot]
83139a64d5 chore(release): Update version to v1.4.338 2025-12-04 13:34:00 +00:00
Kayvan Sylvan
78fd836532 Merge pull request #1852 from ksylvan/kayvan/add-abacus-provider-for-chatllm-models
Add Abacus vendor for ChatLLM models with static model list
2025-12-04 21:31:34 +08:00
Kayvan Sylvan
894459ddec feat: add static model support and register Abacus provider
CHANGES

- feat: detect modelsURL starting with 'static:' and route
- feat: implement getStaticModels returning curated Abacus model list
- feat: register Abacus provider with ModelsURL 'static:abacus'
- chore: add fmt import for error formatting in provider code
- test: extend provider tests to include Abacus existence
- chore: update .vscode settings add 'kimi' and 'qwen' contributors
2025-12-04 21:22:57 +08:00
github-actions[bot]
920c22c889 chore(release): Update version to v1.4.337 2025-12-04 04:21:35 +00:00
Kayvan Sylvan
a0f931feb0 Merge pull request #1851 from ksylvan/kayvan/add-z-ai-vendor-support
Add Z AI provider and glm model support
2025-12-04 12:19:13 +08:00
Kayvan Sylvan
4b080fd6dd feat: add Z AI provider and glm model support
- Add Z AI provider configuration to ProviderMap
- Include BaseURL for Z AI API endpoint
- Add test case for Z AI provider existence
- Add glm to OpenAI model prefixes list
- Reorder gpt-5 in model prefixes list
- Support new Z AI provider in OpenAI compatible plugins
2025-12-04 12:06:55 +08:00
github-actions[bot]
298abecb3f chore(release): Update version to v1.4.336 2025-12-01 11:37:19 +00:00
Kayvan Sylvan
e2d4aab775 Merge pull request #1848 from zeddy303/fix/localStorage-ssr-issue 2025-12-01 19:34:45 +08:00
Changelog Bot
17cac13584 chore: incoming 1848 changelog entry 2025-12-01 18:41:32 +08:00
zeddy303
e4a004cf88 Fix localStorage SSR error in favorites-store
Use SvelteKit's browser constant instead of typeof localStorage check
to properly handle server-side rendering. Prevents 'localStorage.getItem
is not a function' error when running dev server.
2025-11-29 13:06:54 -07:00
github-actions[bot]
fcb10feadd chore(release): Update version to v1.4.335 2025-11-28 02:17:17 +00:00
Kayvan Sylvan
9560537730 Merge pull request #1847 from ksylvan/kayvan/fix-ollama-model-raw-mode
Improve model name matching for NeedsRaw in Ollama plugin
2025-11-27 18:14:47 -08:00
Kayvan Sylvan
42fabab352 feat: improve model name matching in Ollama plugin
- Add "conceptmap" to VSCode dictionary settings
- Rename `ollamaPrefixes` variable to `ollamaSearchStrings`
- Replace `HasPrefix` with `Contains` for model matching
- Enable substring matching for Ollama model names
- chore: incoming 1847 changelog entry
2025-11-28 10:00:08 +08:00
Kayvan Sylvan
895ca1ad99 Merge branch 'danielmiessler:main' into main 2025-11-26 05:52:48 -08:00
Kayvan Sylvan
2ef7db8bb2 docs: Fix typo in README 2025-11-26 21:51:57 +08:00
github-actions[bot]
8491354a30 chore(release): Update version to v1.4.334 2025-11-26 13:40:22 +00:00
Kayvan Sylvan
1fd5b0d27b Merge pull request #1845 from ksylvan/kayvan/add-claude-opus-4-5-support
Add Claude Opus 4.5 Support
2025-11-26 05:38:02 -08:00
Kayvan Sylvan
7eb67ee82d chore: update Go dependencies and add new Claude Opus 4.5 model support
- Upgrade anthropic-sdk-go from v1.16.0 to v1.19.0
- Bump golang.org/x/text from v0.28.0 to v0.31.0
- Update golang.org/x/crypto from v0.41.0 to v0.45.0
- Upgrade golang.org/x/net from v0.43.0 to v0.47.0
- Bump golang.org/x/sync from v0.16.0 to v0.18.0
- Update golang.org/x/sys from v0.35.0 to v0.38.0
- Add Claude Opus 4.5 model variants to Anthropic client
- chore: incoming 1845 changelog entry
2025-11-26 21:34:54 +08:00
github-actions[bot]
e3df1e1c0a chore(release): Update version to v1.4.333 2025-11-25 22:49:42 +00:00
Kayvan Sylvan
6e939cfff4 Merge pull request #1844 from ksylvan/kayvan/concall-summary-pattern-followup
Correct directory name from `concall_summery` to `concall_summary`
2025-11-25 14:47:21 -08:00
Changelog Bot
9e2a35e150 chore: incoming 1844 changelog entry 2025-11-26 06:43:18 +08:00
Kayvan Sylvan
a3a1e616e7 fix: correct directory name from concall_summery to concall_summary
- Rename pattern directory to fix spelling error
- Add new pattern to explanations documentation
- Update suggest_pattern system with concall_summary references
- Include concall_summary in ANALYSIS category mappings
- Add concall_summary to BUSINESS category listings
- Append concall_summary to SUMMARIZE category references
- Update pattern descriptions JSON with new entry
- Generate pattern extracts for concall_summary functionality
- Add user documentation for earnings call analysis
- Include changelog entry for PR #1833
2025-11-26 06:31:32 +08:00
Kayvan Sylvan
98eddaf5e8 Merge pull request #1833 from junaid18183/main
Added concall_summery
2025-11-25 03:30:24 -08:00
github-actions[bot]
0ae20a8ccd chore(release): Update version to v1.4.332 2025-11-24 14:13:17 +00:00
Kayvan Sylvan
0fbc86be17 Merge pull request #1843 from ksylvan/kayvan/fix-vendor-listing-and-case-sensitivity
Implement case-insensitive vendor and model name matching
2025-11-24 06:10:45 -08:00
Changelog Bot
5b1a4ab306 chore: incoming 1843 changelog entry 2025-11-24 21:48:53 +08:00
Kayvan Sylvan
817e75853e fix: implement case-insensitive vendor and model name matching across the application
## CHANGES

- Add case-insensitive vendor lookup in VendorsManager
- Implement model name normalization in GetChatter method
- Add FilterByVendor method with case-insensitive matching
- Add FindModelNameCaseInsensitive helper for model queries
- Update group/item comparison to use case-insensitive checks
- Store vendors with lowercase keys internally
- Add comprehensive tests for case-insensitive functionality
- Fix vendor filtering for model listing command
2025-11-24 21:36:17 +08:00
github-actions[bot]
659d59028d chore(release): Update version to v1.4.331 2025-11-23 08:15:40 +00:00
Kayvan Sylvan
abbd7d9c53 Merge pull request #1839 from ksylvan/kayvan/github-model-support-and-openai-update
Add GitHub Models Provider and Refactor Fetching Fallback Logic
2025-11-23 00:13:22 -08:00
Kayvan Sylvan
3c728cfacb feat: add GitHub Models provider and refactor model fetching with direct API fallback
- Add GitHub Models to supported OpenAI-compatible providers list
- Implement direct HTTP fallback for non-standard model responses
- Centralize model fetching logic in openai package
- Upgrade openai-go SDK dependency from v1.8.2 to v1.12.0
- Remove redundant model fetching code from openai_compatible package
- Add comprehensive GitHub Models setup documentation (700+ lines)
- Support custom models URL endpoint per provider configuration
- Add unit tests for direct model fetching functionality
- Update internationalization strings for model fetching errors
- Add VSCode dictionary entries for "azureml" and "Jamba"
2025-11-23 15:02:33 +07:00
github-actions[bot]
67778a6159 chore(release): Update version to v1.4.330 2025-11-23 02:45:33 +00:00
Kayvan Sylvan
38e7e31ae1 Merge pull request #1840 from ZackaryWelch/patch-1
Replace deprecated bash function in completion script
2025-11-22 18:42:34 -08:00
Changelog Bot
95e60809fa chore: incoming 1840 changelog entry 2025-11-23 09:40:14 +07:00
Zackary Welch
a09686820d Replace deprecated bash function in completion script
Use `_comp_get_words` if available, which was added in bash 4.12 at the same time `__get_comp_words_by_ref` was deprecated. Latest bash (5.2) has removed  `__get_comp_words_by_ref`, breaking the completion script entirely on Fedora 42+ and other up to date distros.
2025-11-22 09:04:57 -05:00
github-actions[bot]
826ac586ee chore(release): Update version to v1.4.329 2025-11-20 23:24:47 +00:00
Kayvan Sylvan
ec14e42abf Merge pull request #1838 from ksylvan/kayvan/add-internationalized-error-messages-to-youtube-plugin
refactor: implement i18n support for YouTube tool error messages
2025-11-20 15:22:23 -08:00
Kayvan Sylvan
6708c7481b refactor: implement i18n support for YouTube tool error messages
CHANGES
- replace hardcoded error strings with i18n translation calls
- add localization keys for YouTube errors to all locale files
- introduce `extractAndValidateVideoId` helper to reduce code duplication
- update timestamp parsing logic to handle localized error formats
- standardize error handling in `yt-dlp` execution with i18n
- ensure rate limit and bot detection warnings use localized strings
2025-11-21 06:14:18 +07:00
github-actions[bot]
75e11724b4 chore(release): Update version to v1.4.328 2025-11-18 15:17:49 +00:00
Kayvan Sylvan
2dd79a66d7 Merge pull request #1836 from ksylvan/kayvan/update-raw-flag-help-message
docs: clarify `--raw` flag behavior for OpenAI and Anthropic providers
2025-11-18 07:15:01 -08:00
Kayvan Sylvan
b7fa02d91e docs: clarify --raw flag behavior for OpenAI and Anthropic providers
- Update `--raw` flag description across all documentation files
- Clarify flag only affects OpenAI-compatible providers behavior
- Document Anthropic models use smart parameter selection
- Remove outdated reference to system/user role changes
- Update help text in CLI flags definition
- Translate updated description to all supported locales
- Update shell completion descriptions for zsh and fish
- chore: incoming 1836 changelog entry
2025-11-18 04:27:38 -08:00
Juned Memon
15c8a84b25 Added concall_summery 2025-11-17 15:53:25 +05:30
github-actions[bot]
63804d3d52 chore(release): Update version to v1.4.327 2025-11-16 21:12:09 +00:00
Kayvan Sylvan
56f105971f Merge pull request #1832 from ksylvan/kayvan/fix-gemini-panic
Improve channel management in Gemini provider
2025-11-16 13:08:59 -08:00
Kayvan Sylvan
ca96c9c629 fix: improve channel management in Gemini streaming method
- Add deferred channel close at function start
- Return error immediately instead of breaking loop
- Remove redundant channel close statements from loop
- Ensure channel closes on all exit paths consistently
- chore: incoming 1832 changelog entry
2025-11-16 13:06:09 -08:00
Kayvan Sylvan
efb9261b89 Merge pull request #1831 from ksylvan/kayvan/remove-youtube-rss-pattern
Remove `get_youtube_rss` pattern
2025-11-16 12:41:12 -08:00
Kayvan Sylvan
118abdc368 chore: remove get_youtube_rss pattern from multiple files
- Remove `get_youtube_rss` from `pattern_explanations.md`
- Delete `get_youtube_rss` entry in `pattern_descriptions.json`
- Delete `get_youtube_rss` entry in `pattern_extracts.json`
- Remove `get_youtube_rss` from `suggest_pattern/system.md`
- Remove `get_youtube_rss` from `suggest_pattern/user.md`
- chore: incoming 1831 changelog entry
2025-11-16 12:28:09 -08:00
github-actions[bot]
278d488dbf chore(release): Update version to v1.4.326 2025-11-16 19:36:17 +00:00
Kayvan Sylvan
d590c0dd15 Merge pull request #1830 from ksylvan/kayvan/newline-in-output-fix
Ensure final newline in model generated outputs
2025-11-16 11:33:47 -08:00
Kayvan Sylvan
c936f8e77b feat: ensure newline in CreateOutputFile and improve tests
- Add newline to `CreateOutputFile` if missing
- Use `t.Cleanup` for file removal in tests
- Add test for message with trailing newline
- Introduce `printedStream` flag in `Chatter.Send`
- Print newline if stream printed without trailing newline
2025-11-16 11:15:47 -08:00
Kayvan Sylvan
7dacc07f03 chore: update README with recent features and extensions
### CHANGES

- Add v1.4.322 release with concept maps
- Introduce WELLNESS category with psychological analysis
- Upgrade to Claude Sonnet 4.5
- Add Portuguese language variants with BCP 47 support
- Migrate to `openai-go/azure` SDK for Azure
- Add Extensions section to README navigation
2025-11-15 09:34:27 -08:00
github-actions[bot]
4e6a2736ad chore(release): Update version to v1.4.325 2025-11-15 05:25:51 +00:00
Kayvan Sylvan
14c95d7bc1 Merge pull request #1828 from ksylvan/kayvan/fix-empty-input-bug
Fix empty string detection in chatter and AI clients
2025-11-14 21:22:53 -08:00
Changelog Bot
2e7b664e1e chore: incoming 1828 changelog entry 2025-11-14 21:20:52 -08:00
Kayvan Sylvan
729d092754 chore: improve message handling by trimming whitespace in content checks
### CHANGES

- Remove default space in `BuildSession` message content
- Trim whitespace in `anthropic` message content check
- Trim whitespace in `gemini` message content check
2025-11-14 21:13:08 -08:00
103 changed files with 5349 additions and 1526 deletions

View File

@@ -20,18 +20,22 @@ jobs:
contents: read
steps:
- name: Checkout code
uses: actions/checkout@v5
- name: Install Nix
uses: DeterminateSystems/nix-installer-action@main
uses: actions/checkout@v6
- name: Set up Go
uses: actions/setup-go@v5
uses: actions/setup-go@v6
with:
go-version-file: ./go.mod
- name: Run tests
run: go test -v ./...
- name: Check for modernization opportunities
run: |
go run golang.org/x/tools/go/analysis/passes/modernize/cmd/modernize@latest ./...
- name: Install Nix
uses: DeterminateSystems/nix-installer-action@v21
- name: Check Formatting
run: nix flake check

View File

@@ -11,7 +11,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v5
uses: actions/checkout@v6
with:
fetch-depth: 0
@@ -32,7 +32,7 @@ jobs:
- name: Upload Patterns Artifact
if: steps.check-changes.outputs.changes == 'true'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v6
with:
name: patterns
path: patterns.zip

View File

@@ -15,12 +15,12 @@ jobs:
contents: read
steps:
- name: Checkout code
uses: actions/checkout@v5
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
uses: actions/setup-go@v6
with:
go-version-file: ./go.mod
@@ -37,11 +37,11 @@ jobs:
contents: write
steps:
- name: Checkout code
uses: actions/checkout@v5
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
uses: actions/setup-go@v6
with:
go-version-file: ./go.mod
- name: Run GoReleaser

View File

@@ -24,17 +24,17 @@ concurrency:
jobs:
update-version:
if: >
${{ github.repository_owner == 'danielmiessler' }} &&
github.repository_owner == 'danielmiessler' &&
github.event_name == 'push' && github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v5
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Install Nix
uses: DeterminateSystems/nix-installer-action@main
uses: DeterminateSystems/nix-installer-action@v21
- name: Set up Git
run: |

10
.vscode/settings.json vendored
View File

@@ -7,9 +7,11 @@
"Anki",
"anthropics",
"Aoede",
"apikey",
"aplicar",
"atotto",
"Autonoe",
"azureml",
"badfile",
"Behrens",
"blindspots",
@@ -23,6 +25,7 @@
"compadd",
"compdef",
"compinit",
"conceptmap",
"creatordate",
"curcontext",
"custompatterns",
@@ -61,6 +64,7 @@
"gjson",
"GOARCH",
"GODEBUG",
"godoc",
"godotenv",
"GOEXPERIMENT",
"gofmt",
@@ -87,12 +91,14 @@
"horts",
"HTMLURL",
"imagetools",
"Jamba",
"jaredmontoya",
"jessevdk",
"Jina",
"joho",
"kballard",
"Keploy",
"kimi",
"Kore",
"ksylvan",
"Langdock",
@@ -148,6 +154,7 @@
"Pulcherrima",
"pycache",
"pyperclip",
"qwen",
"readystream",
"restapi",
"rmextension",
@@ -161,12 +168,14 @@
"sess",
"sgaunet",
"shellquote",
"skeletonlabs",
"SSEHTTP",
"storer",
"Streamlit",
"stretchr",
"subchunk",
"Sulafat",
"swaggo",
"synctest",
"talkpanel",
"Telos",
@@ -182,6 +191,7 @@
"updatepatterns",
"useb",
"USERPROFILE",
"varnames",
"videoid",
"webp",
"WEBVTT",

View File

@@ -1,5 +1,291 @@
# Changelog
## v1.4.351 (2025-12-18)
### PR [#1882](https://github.com/danielmiessler/Fabric/pull/1882) by [bvandevliet](https://github.com/bvandevliet): Added yt-dlp package to docker image
- Added yt-dlp package to docker image.
## v1.4.350 (2025-12-18)
### PR [#1880](https://github.com/danielmiessler/Fabric/pull/1880) by [ksylvan](https://github.com/ksylvan): docs: add REST API server section and new endpoint reference
- Add README table-of-contents link for REST API
- Document REST API server startup and capabilities
- Add endpoint overview for chat, patterns, contexts
- Describe sessions management and model listing endpoints
- Provide curl examples for key API workflows
### PR [#1884](https://github.com/danielmiessler/Fabric/pull/1884) by [ksylvan](https://github.com/ksylvan): Implement interactive Swagger API documentation and automated OpenAPI specification generation
- Add Swagger UI at `/swagger/index.html` endpoint
- Generate OpenAPI spec files (JSON and YAML)
- Document chat, patterns, and models endpoints
- Update contributing guide with Swagger annotation instructions
- Configure authentication bypass for Swagger documentation
## v1.4.349 (2025-12-16)
### PR [#1877](https://github.com/danielmiessler/Fabric/pull/1877) by [ksylvan](https://github.com/ksylvan): modernize: update GitHub Actions and modernize Go code
- Modernize GitHub Actions and Go code with latest stdlib features
- Upgrade GitHub Actions to latest versions (v6, v21) and add modernization check step
- Replace strings manipulation with `strings.CutPrefix` and `strings.CutSuffix`
- Replace manual loops with `slices.Contains` for validation and use `strings.SplitSeq` for iterator-based splitting
- Replace `fmt.Sprintf` with `fmt.Appendf` for efficiency and simplify padding calculation with `max` builtin
## v1.4.348 (2025-12-16)
### PR [#1876](https://github.com/danielmiessler/Fabric/pull/1876) by [ksylvan](https://github.com/ksylvan): modernize Go code with TypeFor and range loops
- Replace reflect.TypeOf with TypeFor generic syntax for improved type handling
- Convert traditional for loops to range-based iterations for better code readability
- Simplify reflection usage in CLI flag handling to reduce complexity
- Update test loops to use range over integers for cleaner test code
- Refactor string processing loops in template plugin to use modern Go patterns
## v1.4.347 (2025-12-16)
### PR [#1875](https://github.com/danielmiessler/Fabric/pull/1875) by [ksylvan](https://github.com/ksylvan): modernize: update benchmarks to use b.Loop and refactor map copying
- Updated benchmark loops to use cleaner `b.Loop()` syntax
- Removed unnecessary `b.ResetTimer()` call in token benchmark
- Used `maps.Copy` for merging variables in patterns handler
## v1.4.346 (2025-12-16)
### PR [#1874](https://github.com/danielmiessler/Fabric/pull/1874) by [ksylvan](https://github.com/ksylvan): refactor: replace interface{} with any across codebase
- Part 1 of dealing with #1873 as pointed out by @philoserf
- Replace `interface{}` with `any` in slice type declarations throughout the codebase
- Update map types from `map[string]interface{}` to `map[string]any` for modern Go standards
- Change variadic function parameters to use `...any` instead of `...interface{}`
- Modernize JSON unmarshaling variables to use `any` for consistency
- Update struct fields and method signatures to prefer the `any` alias over legacy interface syntax
## v1.4.345 (2025-12-15)
### PR [#1870](https://github.com/danielmiessler/Fabric/pull/1870) by [ksylvan](https://github.com/ksylvan): Web UI: upgrade pdfjs and add SSR-safe dynamic PDF worker init
- Upgrade `pdfjs-dist` to v5 with new engine requirement
- Dynamically import PDF.js to avoid SSR import-time crashes
- Configure PDF worker via CDN using runtime PDF.js version
- Update PDF conversion pipeline to use lazy initialization
- Guard chat message localStorage persistence behind browser checks
## v1.4.344 (2025-12-14)
### PR [#1867](https://github.com/danielmiessler/Fabric/pull/1867) by [jaredmontoya](https://github.com/jaredmontoya): chore: update flake
- Chore: update flake
- Merge branch 'main' into update-flake
## v1.4.343 (2025-12-14)
### PR [#1829](https://github.com/danielmiessler/Fabric/pull/1829) by [dependabo](https://github.com/apps/dependabot): chore(deps): bump js-yaml from 4.1.0 to 4.1.1 in /web in the npm_and_yarn group across 1 directory
- Updated js-yaml dependency from version 4.1.0 to 4.1.1 in the /web directory
## v1.4.342 (2025-12-13)
### PR [#1866](https://github.com/danielmiessler/Fabric/pull/1866) by [ksylvan](https://github.com/ksylvan): fix: write CLI and streaming errors to stderr
- Fix: write CLI and streaming errors to stderr
- Route CLI execution errors to standard error output
- Print Anthropic stream errors to stderr consistently
- Add os import to support stderr error writes
- Preserve help-output suppression and exit behavior
## v1.4.341 (2025-12-10)
### PR [#1860](https://github.com/danielmiessler/Fabric/pull/1860) by [ksylvan](https://github.com/ksylvan): fix: allow resetting required settings without validation errors
- Fix: allow resetting required settings without validation errors
- Update `Ask` to detect reset command and bypass validation
- Refactor `OnAnswer` to support new `isReset` parameter logic
- Invoke `ConfigureCustom` in `Setup` to avoid redundant re-validation
- Add unit tests ensuring required fields can be reset
## v1.4.340 (2025-12-08)
### PR [#1856](https://github.com/danielmiessler/Fabric/pull/1856) by [ksylvan](https://github.com/ksylvan): Add support for new ClaudeHaiku 4.5 models
- Add support for new ClaudeHaiku models in client
- Add `ModelClaudeHaiku4_5` to supported models
- Add `ModelClaudeHaiku4_5_20251001` to supported models
## v1.4.339 (2025-12-08)
### PR [#1855](https://github.com/danielmiessler/Fabric/pull/1855) by [ksylvan](https://github.com/ksylvan): feat: add image attachment support for Ollama vision models
- Add multi-modal image support to Ollama client
- Implement convertMessage to handle multi-content chat messages
- Add loadImageBytes to fetch images from URLs
- Support base64 data URLs for inline images
- Handle HTTP image URLs with context propagation
## v1.4.338 (2025-12-04)
### PR [#1852](https://github.com/danielmiessler/Fabric/pull/1852) by [ksylvan](https://github.com/ksylvan): Add Abacus vendor for ChatLLM models with static model list
- Add static model support and register Abacus provider
- Detect modelsURL starting with 'static:' and route appropriately
- Implement getStaticModels returning curated Abacus model list
- Register Abacus provider with ModelsURL 'static:abacus'
- Extend provider tests to include Abacus existence
## v1.4.337 (2025-12-04)
### PR [#1851](https://github.com/danielmiessler/Fabric/pull/1851) by [ksylvan](https://github.com/ksylvan): Add Z AI provider and glm model support
- Add Z AI provider configuration to ProviderMap
- Include BaseURL for Z AI API endpoint
- Add test case for Z AI provider existence
- Add glm to OpenAI model prefixes list
- Support new Z AI provider in OpenAI compatible plugins
## v1.4.336 (2025-12-01)
### PR [#1848](https://github.com/danielmiessler/Fabric/pull/1848) by [zeddy303](https://github.com/zeddy303): Fix localStorage SSR error in favorites-store
- Fix localStorage SSR error in favorites-store by using SvelteKit's browser constant instead of typeof localStorage check to properly handle server-side rendering and prevent 'localStorage.getItem is not a function' error when running dev server
## v1.4.335 (2025-11-28)
### PR [#1847](https://github.com/danielmiessler/Fabric/pull/1847) by [ksylvan](https://github.com/ksylvan): Improve model name matching for NeedsRaw in Ollama plugin
- Improved model name matching in Ollama plugin by replacing prefix-based matching with substring matching
- Enhanced NeedsRaw functionality to support more flexible model name detection
- Renamed `ollamaPrefixes` variable to `ollamaSearchStrings` for better code clarity
- Replaced `HasPrefix` function with `Contains` for more comprehensive model matching
- Added "conceptmap" to VSCode dictionary settings
### Direct commits
- Merge branch 'danielmiessler:main' into main
- Docs: Fix typo in README
## v1.4.334 (2025-11-26)
### PR [#1845](https://github.com/danielmiessler/Fabric/pull/1845) by [ksylvan](https://github.com/ksylvan): Add Claude Opus 4.5 Support
- Add Claude Opus 4.5 model variants to Anthropic client
- Upgrade anthropic-sdk-go from v1.16.0 to v1.19.0
- Update golang.org/x/crypto from v0.41.0 to v0.45.0
- Upgrade golang.org/x/net from v0.43.0 to v0.47.0
- Bump golang.org/x/text from v0.28.0 to v0.31.0
## v1.4.333 (2025-11-25)
### PR [#1833](https://github.com/danielmiessler/Fabric/pull/1833) by [junaid18183](https://github.com/junaid18183): Added concall_summary
- Added concall_summery pattern to extract strategic insights from earnings transcripts for investors.
### PR [#1844](https://github.com/danielmiessler/Fabric/pull/1844) by [ksylvan](https://github.com/ksylvan): Correct directory name from `concall_summery` to `concall_summary`
- Fix: correct directory name from `concall_summery` to `concall_summary`
- Rename pattern directory to fix spelling error
- Update suggest_pattern system with concall_summary references
- Add concall_summary to BUSINESS and SUMMARIZE category listings
- Add user documentation for earnings call analysis
## v1.4.332 (2025-11-24)
### PR [#1843](https://github.com/danielmiessler/Fabric/pull/1843) by [ksylvan](https://github.com/ksylvan): Implement case-insensitive vendor and model name matching
- Fix: implement case-insensitive vendor and model name matching across the application
- Add case-insensitive vendor lookup in VendorsManager
- Implement model name normalization in GetChatter method
- Add FilterByVendor method with case-insensitive matching
- Add FindModelNameCaseInsensitive helper for model queries
## v1.4.331 (2025-11-22)
### PR [#1839](https://github.com/danielmiessler/Fabric/pull/1839) by [ksylvan](https://github.com/ksylvan): Add GitHub Models Provider and Refactor Fetching Fallback Logic
- Add GitHub Models provider and refactor model fetching with direct API fallback
- Add GitHub Models to supported OpenAI-compatible providers list
- Implement direct HTTP fallback for non-standard model responses
- Centralize model fetching logic in openai package
- Upgrade openai-go SDK dependency from v1.8.2 to v1.12.0
## v1.4.330 (2025-11-23)
### PR [#1840](https://github.com/danielmiessler/Fabric/pull/1840) by [ZackaryWelch](https://github.com/ZackaryWelch): Replace deprecated bash function in completion script
- Replace deprecated bash function in completion script to use `_comp_get_words` instead of `__get_comp_words_by_ref`, fixing compatibility issues with latest bash versions and preventing script breakage on updated distributions like Fedora 42+
## v1.4.329 (2025-11-20)
### PR [#1838](https://github.com/danielmiessler/fabric/pull/1838) by [ksylvan](https://github.com/ksylvan): refactor: implement i18n support for YouTube tool error messages
- Replace hardcoded error strings with i18n translation calls
- Add localization keys for YouTube errors to all locale files
- Introduce `extractAndValidateVideoId` helper to reduce code duplication
- Update timestamp parsing logic to handle localized error formats
- Standardize error handling in `yt-dlp` execution with i18n
## v1.4.328 (2025-11-18)
### PR [#1836](https://github.com/danielmiessler/Fabric/pull/1836) by [ksylvan](https://github.com/ksylvan): docs: clarify `--raw` flag behavior for OpenAI and Anthropic providers
- Update `--raw` flag description across all documentation files
- Clarify flag only affects OpenAI-compatible providers behavior
- Document Anthropic models use smart parameter selection
- Remove outdated reference to system/user role changes
- Update help text in CLI flags definition
## v1.4.327 (2025-11-16)
### PR [#1831](https://github.com/danielmiessler/Fabric/pull/1831) by [ksylvan](https://github.com/ksylvan): Remove `get_youtube_rss` pattern
- Chore: remove `get_youtube_rss` pattern from multiple files
- Remove `get_youtube_rss` from `pattern_explanations.md`
- Delete `get_youtube_rss` entry in `pattern_descriptions.json`
- Delete `get_youtube_rss` entry in `pattern_extracts.json`
- Remove `get_youtube_rss` from `suggest_pattern/system.md`
### PR [#1832](https://github.com/danielmiessler/Fabric/pull/1832) by [ksylvan](https://github.com/ksylvan): Improve channel management in Gemini provider
- Fix: improve channel management in Gemini streaming method
- Add deferred channel close at function start
- Return error immediately instead of breaking loop
- Remove redundant channel close statements from loop
- Ensure channel closes on all exit paths consistently
## v1.4.326 (2025-11-16)
### PR [#1830](https://github.com/danielmiessler/Fabric/pull/1830) by [ksylvan](https://github.com/ksylvan): Ensure final newline in model generated outputs
- Feat: ensure newline in `CreateOutputFile` and improve tests
- Add newline to `CreateOutputFile` if missing
- Use `t.Cleanup` for file removal in tests
- Add test for message with trailing newline
- Introduce `printedStream` flag in `Chatter.Send`
### Direct commits
- Chore: update README with recent features and extensions
- Add v1.4.322 release with concept maps
- Introduce WELLNESS category with psychological analysis
- Upgrade to Claude Sonnet 4.5
- Add Portuguese language variants with BCP 47 support
- Migrate to `openai-go/azure` SDK for Azure
- Add Extensions section to README navigation
## v1.4.325 (2025-11-15)
### PR [#1828](https://github.com/danielmiessler/Fabric/pull/1828) by [ksylvan](https://github.com/ksylvan): Fix empty string detection in chatter and AI clients
- Chore: improve message handling by trimming whitespace in content checks
- Remove default space in `BuildSession` message content
- Trim whitespace in `anthropic` message content check
- Trim whitespace in `gemini` message content check
## v1.4.324 (2025-11-14)
### PR [#1827](https://github.com/danielmiessler/Fabric/pull/1827) by [ksylvan](https://github.com/ksylvan): Make YouTube API key optional in setup

View File

@@ -38,6 +38,7 @@
[Philosophy](#philosophy) •
[Installation](#installation) •
[Usage](#usage) •
[REST API](#rest-api-server) •
[Examples](#examples) •
[Just Use the Patterns](#just-use-the-patterns) •
[Custom Patterns](#custom-patterns) •
@@ -73,6 +74,14 @@ Below are the **new features and capabilities** we've added (newest first):
### Recent Major Features
- [v1.4.338](https://github.com/danielmiessler/fabric/releases/tag/v1.4.338) (Dec 4, 2025) — Add Abacus vendor support for Chat-LLM
models (see [RouteLLM APIs](https://abacus.ai/app/route-llm-apis)).
- [v1.4.337](https://github.com/danielmiessler/fabric/releases/tag/v1.4.337) (Dec 4, 2025) — Add "Z AI" vendor support. See the [Z AI overview](https://docs.z.ai/guides/overview/overview) page for more details.
- [v1.4.334](https://github.com/danielmiessler/fabric/releases/tag/v1.4.334) (Nov 26, 2025) — **Claude Opus 4.5**: Updates the Anthropic SDK to the latest and adds the new [Claude Opus 4.5](https://www.anthropic.com/news/claude-opus-4-5) to the available models.
- [v1.4.331](https://github.com/danielmiessler/fabric/releases/tag/v1.4.331) (Nov 23, 2025) — **Support for GitHub Models**: Adds support for using GitHub Models.
- [v1.4.322](https://github.com/danielmiessler/fabric/releases/tag/v1.4.322) (Nov 5, 2025) — **Interactive HTML Concept Maps and Claude Sonnet 4.5**: Adds `create_conceptmap` pattern for visual knowledge representation using Vis.js, introduces WELLNESS category with psychological analysis patterns, and upgrades to Claude Sonnet 4.5
- [v1.4.317](https://github.com/danielmiessler/fabric/releases/tag/v1.4.317) (Sep 21, 2025) — **Portuguese Language Variants**: Adds BCP 47 locale normalization with support for Brazilian Portuguese (pt-BR) and European Portuguese (pt-PT) with intelligent fallback chains
- [v1.4.314](https://github.com/danielmiessler/fabric/releases/tag/v1.4.314) (Sep 17, 2025) — **Azure OpenAI Migration**: Migrates to official `openai-go/azure` SDK with improved authentication and default API version support
- [v1.4.311](https://github.com/danielmiessler/fabric/releases/tag/v1.4.311) (Sep 13, 2025) — **More internationalization support**: Adds de (German), fa (Persian / Farsi), fr (French), it (Italian),
ja (Japanese), pt (Portuguese), zh (Chinese)
- [v1.4.309](https://github.com/danielmiessler/fabric/releases/tag/v1.4.309) (Sep 9, 2025) — **Comprehensive internationalization support**: Includes English and Spanish locale files.
@@ -161,6 +170,8 @@ Keep in mind that many of these were recorded when Fabric was Python-based, so r
- [Fish Completion](#fish-completion)
- [Usage](#usage)
- [Debug Levels](#debug-levels)
- [Extensions](#extensions)
- [REST API Server](#rest-api-server)
- [Our approach to prompting](#our-approach-to-prompting)
- [Examples](#examples)
- [Just use the Patterns](#just-use-the-patterns)
@@ -290,7 +301,7 @@ docker run --rm -it -v $HOME/.fabric-config:/root/.config/fabric kayvan/fabric:l
# Use Fabric with your patterns
docker run --rm -it -v $HOME/.fabric-config:/root/.config/fabric kayvan/fabric:latest -p summarize
# Run the REST API server
# Run the REST API server (see REST API Server section)
docker run --rm -it -p 8080:8080 -v $HOME/.fabric-config:/root/.config/fabric kayvan/fabric:latest --serve
```
@@ -619,9 +630,10 @@ Application Options:
-T, --topp= Set top P (default: 0.9)
-s, --stream Stream
-P, --presencepenalty= Set presence penalty (default: 0.0)
-r, --raw Use the defaults of the model without sending chat options (like
temperature etc.) and use the user role instead of the system role for
patterns.
-r, --raw Use the defaults of the model without sending chat options
(temperature, top_p, etc.). Only affects OpenAI-compatible providers.
Anthropic models always use smart parameter selection to comply with
model-specific requirements.
-F, --frequencypenalty= Set frequency penalty (default: 0.0)
-l, --listpatterns List all patterns
-L, --listmodels List all available models
@@ -711,6 +723,25 @@ Fabric supports extensions that can be called within patterns. See the [Extensio
**Important:** Extensions only work within pattern files, not via direct stdin. See the guide for details and examples.
## REST API Server
Fabric includes a built-in REST API server that exposes all core functionality over HTTP. Start the server with:
```bash
fabric --serve
```
The server provides endpoints for:
- Chat completions with streaming responses
- Pattern management (create, read, update, delete)
- Context and session management
- Model and vendor listing
- YouTube transcript extraction
- Configuration management
For complete endpoint documentation, authentication setup, and usage examples, see [REST API Documentation](docs/rest-api.md).
## Our approach to prompting
Fabric _Patterns_ are different than most prompts you'll see.

View File

@@ -109,11 +109,11 @@ func ScanDirectory(rootDir string, maxDepth int, instructions string, ignoreList
}
// Create final data structure
var data []interface{}
var data []any
data = append(data, rootItem)
// Add report
reportItem := map[string]interface{}{
reportItem := map[string]any{
"type": "report",
"directories": dirCount,
"files": fileCount,
@@ -121,7 +121,7 @@ func ScanDirectory(rootDir string, maxDepth int, instructions string, ignoreList
data = append(data, reportItem)
// Add instructions
instructionsItem := map[string]interface{}{
instructionsItem := map[string]any{
"type": "instructions",
"name": "code_change_instructions",
"details": instructions,

View File

@@ -12,7 +12,7 @@ import (
func main() {
err := cli.Cli(version)
if err != nil && !flags.WroteHelp(err) {
fmt.Printf("%s\n", err)
fmt.Fprintf(os.Stderr, "%s\n", err)
os.Exit(1)
}
}

View File

@@ -1,3 +1,3 @@
package main
var version = "v1.4.324"
var version = "v1.4.351"

Binary file not shown.

View File

@@ -574,8 +574,8 @@ func (g *Generator) extractChanges(pr *github.PR) []string {
}
if len(changes) == 0 && pr.Body != "" {
lines := strings.Split(pr.Body, "\n")
for _, line := range lines {
lines := strings.SplitSeq(pr.Body, "\n")
for line := range lines {
line = strings.TrimSpace(line)
if strings.HasPrefix(line, "- ") || strings.HasPrefix(line, "* ") {
change := strings.TrimPrefix(strings.TrimPrefix(line, "- "), "* ")

View File

@@ -159,7 +159,7 @@ func (g *Generator) CreateNewChangelogEntry(version string) error {
for _, file := range files {
// Extract PR number from filename (e.g., "1640.txt" -> 1640)
filename := filepath.Base(file)
if prNumStr := strings.TrimSuffix(filename, ".txt"); prNumStr != filename {
if prNumStr, ok := strings.CutSuffix(filename, ".txt"); ok {
if prNum, err := strconv.Atoi(prNumStr); err == nil {
processedPRs[prNum] = true
prNumbers = append(prNumbers, prNum)

View File

@@ -333,7 +333,7 @@ func (c *Client) FetchAllMergedPRsGraphQL(since time.Time) ([]*PR, error) {
for {
// Prepare variables
variables := map[string]interface{}{
variables := map[string]any{
"owner": graphql.String(c.owner),
"repo": graphql.String(c.repo),
"after": (*graphql.String)(after),

View File

@@ -81,7 +81,7 @@ _fabric() {
'(-T --topp)'{-T,--topp}'[Set top P (default: 0.9)]:topp:' \
'(-s --stream)'{-s,--stream}'[Stream]' \
'(-P --presencepenalty)'{-P,--presencepenalty}'[Set presence penalty (default: 0.0)]:presence penalty:' \
'(-r --raw)'{-r,--raw}'[Use the defaults of the model without sending chat options]' \
'(-r --raw)'{-r,--raw}'[Use the defaults of the model without sending chat options. Only affects OpenAI-compatible providers. Anthropic models always use smart parameter selection to comply with model-specific requirements.]' \
'(-F --frequencypenalty)'{-F,--frequencypenalty}'[Set frequency penalty (default: 0.0)]:frequency penalty:' \
'(-l --listpatterns)'{-l,--listpatterns}'[List all patterns]' \
'(-L --listmodels)'{-L,--listmodels}'[List all available models]' \

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@@ -10,7 +10,11 @@
_fabric() {
local cur prev words cword
_get_comp_words_by_ref -n : cur prev words cword
if declare -F _comp_get_words &>/dev/null; then
_comp_get_words cur prev words cword
else
_get_comp_words_by_ref cur prev words cword
fi
# Define all possible options/flags
local opts="--pattern -p --variable -v --context -C --session --attachment -a --setup -S --temperature -t --topp -T --stream -s --presencepenalty -P --raw -r --frequencypenalty -F --listpatterns -l --listmodels -L --listcontexts -x --listsessions -X --updatepatterns -U --copy -c --model -m --vendor -V --modelContextLength --output -o --output-session --latest -n --changeDefaultModel -d --youtube -y --playlist --transcript --transcript-with-timestamps --comments --metadata --yt-dlp-args --language -g --scrape_url -u --scrape_question -q --seed -e --thinking --wipecontext -w --wipesession -W --printcontext --printsession --readability --input-has-vars --no-variable-replacement --dry-run --serve --serveOllama --address --api-key --config --search --search-location --image-file --image-size --image-quality --image-compression --image-background --suppress-think --think-start-tag --think-end-tag --disable-responses-api --transcribe-file --transcribe-model --split-media-file --voice --list-gemini-voices --notification --notification-command --debug --version --listextensions --addextension --rmextension --strategy --liststrategies --listvendors --shell-complete-list --help -h"

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@@ -105,7 +105,7 @@ function __fabric_register_completions
# Boolean flags (no arguments)
complete -c $cmd -s S -l setup -d "Run setup for all reconfigurable parts of fabric"
complete -c $cmd -s s -l stream -d "Stream"
complete -c $cmd -s r -l raw -d "Use the defaults of the model without sending chat options"
complete -c $cmd -s r -l raw -d "Use the defaults of the model without sending chat options. Only affects OpenAI-compatible providers. Anthropic models always use smart parameter selection to comply with model-specific requirements."
complete -c $cmd -s l -l listpatterns -d "List all patterns"
complete -c $cmd -s L -l listmodels -d "List all available models"
complete -c $cmd -s x -l listcontexts -d "List all contexts"

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@@ -0,0 +1,84 @@
# IDENTITY and PURPOSE
You are an equity research analyst specializing in earnings and conference call analysis. Your role involves carefully examining transcripts to extract actionable insights that can inform investment decisions. You need to focus on several key areas, including management commentary, analyst questions, financial and operational insights, risks and red flags, hidden signals, and an executive summary. Your task is to distill complex information into clear, concise bullet points, capturing strategic themes, growth drivers, and potential concerns. It is crucial to interpret the tone, identify contradictions, and highlight any subtle cues that may indicate future strategic shifts or risks.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
* Analyze the transcript to extract management commentary, focusing on strategic themes, growth drivers, margin commentary, guidance, tone analysis, and any contradictions or vague areas.
* Extract a summary of the content in exactly **25 words**, including who is presenting and the content being discussed; place this under a **SUMMARY** section.
* For each analyst's question, determine the underlying concern, summarize managements exact answer, evaluate if the answers address the question fully, and identify anything the management avoided or deflected.
* Gather financial and operational insights, including commentary on demand, pricing, capacity, market share, cost inflation, raw material trends, and supply-chain issues.
* Identify risks and red flags by noting any negative commentary, early warning signs, unusual wording, delayed responses, repeated disclaimers, and areas where management seemed less confident.
* Detect hidden signals such as forward-looking hints, unasked but important questions, and subtle cues about strategy shifts or stress.
* Create an executive summary in bullet points, listing the 10 most important takeaways, 3 surprises, and 3 things to track in the next quarter.
# OUTPUT STRUCTURE
* MANAGEMENT COMMENTARY
* Key strategic themes
* Growth drivers discussed
* Margin commentary
* Guidance (explicit + implicit)
* Tone analysis (positive/neutral/negative)
* Any contradictions or vague areas
* ANALYST QUESTIONS (Q&A)
* For each analyst (use bullets, one analyst per bullet-group):
* Underlying concern (what the question REALLY asked)
* Managements exact answer (concise)
* Answer completeness (Yes/No — short explanation)
* Items management avoided or deflected
* FINANCIAL & OPERATIONAL INSIGHTS
* Demand, pricing, capacity, market share commentary
* Cost inflation, raw material trends, supply-chain issues
* Segment-wise performance and commentary (if applicable)
* RISKS & RED FLAGS
* Negative commentary or early-warning signs
* Unusual wording, delayed responses, repeated disclaimers
* Areas where management was less confident
* HIDDEN SIGNALS
* Forward-looking hints and tone shifts
* Important topics not asked by analysts but relevant
* Subtle cues of strategy change, stress, or opportunity
* EXECUTIVE SUMMARY
* 10 most important takeaways (bullet points)
* 3 surprises (bullet points)
* 3 things to track next quarter (bullet points)
* SUMMARY (exactly 25 words)
* A single 25-word sentence summarizing who presented and what was discussed
# OUTPUT INSTRUCTIONS
* Only output Markdown.
* Provide everything in clear, crisp bullet points.
* Use bulleted lists only; do not use numbered lists.
* Begin the output with the **SUMMARY** (exactly 25 words), then the sections in the order shown under **OUTPUT STRUCTURE**.
* For **ANALYST QUESTIONS (Q&A)**, keep each analysts Q&A grouped and separated by a blank line for readability.
* For **EXECUTIVE SUMMARY**, present the 10 takeaways first, then the 3 surprises, then the 3 things to track.
* Keep each bullet concise — prefer single-sentence bullets.
* Do not include warnings, meta-comments, or process notes in the final output.
* Do not repeat ideas, insights, quotes, habits, facts, or references across bullets.
* When interpreting tone or identifying a hidden signal, be explicit about the textual clue supporting that interpretation (briefly, within the same bullet).
* If any numeric figure or explicit guidance is cited in the transcript, reproduce it verbatim in the relevant bullet and mark it as **(quoted)**.
* If information is missing or management declined to answer, state that clearly within the relevant bullet.
* Ensure fidelity: do not invent facts not in the transcript. If you infer, label it as an inference.
* Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:

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@@ -1,27 +0,0 @@
# IDENTITY AND GOALS
You are a YouTube infrastructure expert that returns YouTube channel RSS URLs.
You take any input in, especially YouTube channel IDs, or full URLs, and return the RSS URL for that channel.
# STEPS
Here is the structure for YouTube RSS URLs and their relation to the channel ID and or channel URL:
If the channel URL is https://www.youtube.com/channel/UCnCikd0s4i9KoDtaHPlK-JA, the RSS URL is https://www.youtube.com/feeds/videos.xml?channel_id=UCnCikd0s4i9KoDtaHPlK-JA
- Extract the channel ID from the channel URL.
- Construct the RSS URL using the channel ID.
- Output the RSS URL.
# OUTPUT
- Output only the RSS URL and nothing else.
- Don't complain, just do it.
# INPUT
(INPUT)

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@@ -46,117 +46,117 @@
42. **clean_text**: Fix broken or malformatted text by correcting line breaks, punctuation, capitalization, and paragraphs without altering content or spelling.
43. **coding_master**: Explain a coding concept to a beginner, providing examples, and formatting code in markdown with specific output sections like ideas, recommendations, facts, and insights.
44. **compare_and_contrast**: Compare and contrast a list of items in a markdown table, with items on the left and topics on top.
45. **convert_to_markdown**: Convert content to clean, complete Markdown format, preserving all original structure, formatting, links, and code blocks without alterations.
46. **create_5_sentence_summary**: Create concise summaries or answers to input at 5 different levels of depth, from 5 words to 1 word.
47. **create_academic_paper**: Generate a high-quality academic paper in LaTeX format with clear concepts, structured content, and a professional layout.
48. **create_ai_jobs_analysis**: Analyze job categories' susceptibility to automation, identify resilient roles, and provide strategies for personal adaptation to AI-driven changes in the workforce.
49. **create_aphorisms**: Find and generate a list of brief, witty statements.
50. **create_art_prompt**: Generates a detailed, compelling visual description of a concept, including stylistic references and direct AI instructions for creating art.
51. **create_better_frame**: Identifies and analyzes different frames of interpreting reality, emphasizing the power of positive, productive lenses in shaping outcomes.
52. **create_coding_feature**: Generates secure and composable code features using modern technology and best practices from project specifications.
53. **create_coding_project**: Generate wireframes and starter code for any coding ideas that you have.
54. **create_command**: Helps determine the correct parameters and switches for penetration testing tools based on a brief description of the objective.
55. **create_conceptmap**: Transforms unstructured text or markdown content into an interactive HTML concept map using Vis.js by extracting key concepts and their logical relationships.
56. **create_cyber_summary**: Summarizes cybersecurity threats, vulnerabilities, incidents, and malware with a 25-word summary and categorized bullet points, after thoroughly analyzing and mapping the provided input.
57. **create_design_document**: Creates a detailed design document for a system using the C4 model, addressing business and security postures, and including a system context diagram.
58. **create_diy**: Creates structured "Do It Yourself" tutorial patterns by analyzing prompts, organizing requirements, and providing step-by-step instructions in Markdown format.
59. **create_excalidraw_visualization**: Creates complex Excalidraw diagrams to visualize relationships between concepts and ideas in structured format.
60. **create_flash_cards**: Creates flashcards for key concepts, definitions, and terms with question-answer format for educational purposes.
61. **create_formal_email**: Crafts professional, clear, and respectful emails by analyzing context, tone, and purpose, ensuring proper structure and formatting.
62. **create_git_diff_commit**: Generates Git commands and commit messages for reflecting changes in a repository, using conventional commits and providing concise shell commands for updates.
63. **create_graph_from_input**: Generates a CSV file with progress-over-time data for a security program, focusing on relevant metrics and KPIs.
64. **create_hormozi_offer**: Creates a customized business offer based on principles from Alex Hormozi's book, "$100M Offers."
65. **create_idea_compass**: Organizes and structures ideas by exploring their definition, evidence, sources, and related themes or consequences.
66. **create_investigation_visualization**: Creates detailed Graphviz visualizations of complex input, highlighting key aspects and providing clear, well-annotated diagrams for investigative analysis and conclusions.
67. **create_keynote**: Creates TED-style keynote presentations with a clear narrative, structured slides, and speaker notes, emphasizing impactful takeaways and cohesive flow.
68. **create_loe_document**: Creates detailed Level of Effort documents for estimating work effort, resources, and costs for tasks or projects.
69. **create_logo**: Creates simple, minimalist company logos without text, generating AI prompts for vector graphic logos based on input.
70. **create_markmap_visualization**: Transforms complex ideas into clear visualizations using MarkMap syntax, simplifying concepts into diagrams with relationships, boxes, arrows, and labels.
71. **create_mermaid_visualization**: Creates detailed, standalone visualizations of concepts using Mermaid (Markdown) syntax, ensuring clarity and coherence in diagrams.
72. **create_mermaid_visualization_for_github**: Creates standalone, detailed visualizations using Mermaid (Markdown) syntax to effectively explain complex concepts, ensuring clarity and precision.
73. **create_micro_summary**: Summarizes content into a concise, 20-word summary with main points and takeaways, formatted in Markdown.
74. **create_mnemonic_phrases**: Creates memorable mnemonic sentences from given words to aid in memory retention and learning.
75. **create_network_threat_landscape**: Analyzes open ports and services from a network scan and generates a comprehensive, insightful, and detailed security threat report in Markdown.
76. **create_newsletter_entry**: Condenses provided article text into a concise, objective, newsletter-style summary with a title in the style of Frontend Weekly.
77. **create_npc**: Generates a detailed D&D 5E NPC, including background, flaws, stats, appearance, personality, goals, and more in Markdown format.
78. **create_pattern**: Extracts, organizes, and formats LLM/AI prompts into structured sections, detailing the AI's role, instructions, output format, and any provided examples for clarity and accuracy.
79. **create_prd**: Creates a precise Product Requirements Document (PRD) in Markdown based on input.
80. **create_prediction_block**: Extracts and formats predictions from input into a structured Markdown block for a blog post.
81. **create_quiz**: Creates a three-phase reading plan based on an author or topic to help the user become significantly knowledgeable, including core, extended, and supplementary readings.
82. **create_reading_plan**: Generates review questions based on learning objectives from the input, adapted to the specified student level, and outputs them in a clear markdown format.
83. **create_recursive_outline**: Breaks down complex tasks or projects into manageable, hierarchical components with recursive outlining for clarity and simplicity.
84. **create_report_finding**: Creates a detailed, structured security finding report in markdown, including sections on Description, Risk, Recommendations, References, One-Sentence-Summary, and Quotes.
85. **create_rpg_summary**: Summarizes an in-person RPG session with key events, combat details, player stats, and role-playing highlights in a structured format.
86. **create_security_update**: Creates concise security updates for newsletters, covering stories, threats, advisories, vulnerabilities, and a summary of key issues.
87. **create_show_intro**: Creates compelling short intros for podcasts, summarizing key topics and themes discussed in the episode.
88. **create_sigma_rules**: Extracts Tactics, Techniques, and Procedures (TTPs) from security news and converts them into Sigma detection rules for host-based detections.
89. **create_story_about_people_interaction**: Analyze two personas, compare their dynamics, and craft a realistic, character-driven story from those insights.
90. **create_story_about_person**: Creates compelling, realistic short stories based on psychological profiles, showing how characters navigate everyday problems using strategies consistent with their personality traits.
91. **create_story_explanation**: Summarizes complex content in a clear, approachable story format that makes the concepts easy to understand.
92. **create_stride_threat_model**: Create a STRIDE-based threat model for a system design, identifying assets, trust boundaries, data flows, and prioritizing threats with mitigations.
93. **create_summary**: Summarizes content into a 20-word sentence, 10 main points (16 words max), and 5 key takeaways in Markdown format.
94. **create_tags**: Identifies at least 5 tags from text content for mind mapping tools, including authors and existing tags if present.
95. **create_threat_scenarios**: Identifies likely attack methods for any system by providing a narrative-based threat model, balancing risk and opportunity.
96. **create_ttrc_graph**: Creates a CSV file showing the progress of Time to Remediate Critical Vulnerabilities over time using given data.
97. **create_ttrc_narrative**: Creates a persuasive narrative highlighting progress in reducing the Time to Remediate Critical Vulnerabilities metric over time.
98. **create_upgrade_pack**: Extracts world model and task algorithm updates from content, providing beliefs about how the world works and task performance.
99. **create_user_story**: Writes concise and clear technical user stories for new features in complex software programs, formatted for all stakeholders.
100. **create_video_chapters**: Extracts interesting topics and timestamps from a transcript, providing concise summaries of key moments.
101. **create_visualization**: Transforms complex ideas into visualizations using intricate ASCII art, simplifying concepts where necessary.
102. **dialog_with_socrates**: Engages in deep, meaningful dialogues to explore and challenge beliefs using the Socratic method.
103. **enrich_blog_post**: Enhances Markdown blog files by applying instructions to improve structure, visuals, and readability for HTML rendering.
104. **explain_code**: Explains code, security tool output, configuration text, and answers questions based on the provided input.
105. **explain_docs**: Improves and restructures tool documentation into clear, concise instructions, including overviews, usage, use cases, and key features.
106. **explain_math**: Helps you understand mathematical concepts in a clear and engaging way.
107. **explain_project**: Summarizes project documentation into clear, concise sections covering the project, problem, solution, installation, usage, and examples.
108. **explain_terms**: Produces a glossary of advanced terms from content, providing a definition, analogy, and explanation of why each term matters.
109. **export_data_as_csv**: Extracts and outputs all data structures from the input in properly formatted CSV data.
110. **extract_algorithm_update_recommendations**: Extracts concise, practical algorithm update recommendations from the input and outputs them in a bulleted list.
111. **extract_article_wisdom**: Extracts surprising, insightful, and interesting information from content, categorizing it into sections like summary, ideas, quotes, facts, references, and recommendations.
112. **extract_book_ideas**: Extracts and outputs 50 to 100 of the most surprising, insightful, and interesting ideas from a book's content.
113. **extract_book_recommendations**: Extracts and outputs 50 to 100 practical, actionable recommendations from a book's content.
114. **extract_business_ideas**: Extracts top business ideas from content and elaborates on the best 10 with unique differentiators.
115. **extract_characters**: Identify all characters (human and non-human), resolve their aliases and pronouns into canonical names, and produce detailed descriptions of each character's role, motivations, and interactions ranked by narrative importance.
116. **extract_controversial_ideas**: Extracts and outputs controversial statements and supporting quotes from the input in a structured Markdown list.
117. **extract_core_message**: Extracts and outputs a clear, concise sentence that articulates the core message of a given text or body of work.
118. **extract_ctf_writeup**: Extracts a short writeup from a warstory-like text about a cyber security engagement.
119. **extract_domains**: Extracts domains and URLs from content to identify sources used for articles, newsletters, and other publications.
120. **extract_extraordinary_claims**: Extracts and outputs a list of extraordinary claims from conversations, focusing on scientifically disputed or false statements.
121. **extract_ideas**: Extracts and outputs all the key ideas from input, presented as 15-word bullet points in Markdown.
122. **extract_insights**: Extracts and outputs the most powerful and insightful ideas from text, formatted as 16-word bullet points in the INSIGHTS section, also IDEAS section.
123. **extract_insights_dm**: Extracts and outputs all valuable insights and a concise summary of the content, including key points and topics discussed.
124. **extract_instructions**: Extracts clear, actionable step-by-step instructions and main objectives from instructional video transcripts, organizing them into a concise list.
125. **extract_jokes**: Extracts jokes from text content, presenting each joke with its punchline in separate bullet points.
126. **extract_latest_video**: Extracts the latest video URL from a YouTube RSS feed and outputs the URL only.
127. **extract_main_activities**: Extracts key events and activities from transcripts or logs, providing a summary of what happened.
128. **extract_main_idea**: Extracts the main idea and key recommendation from the input, summarizing them in 15-word sentences.
129. **extract_mcp_servers**: Identify and summarize Model Context Protocol (MCP) servers referenced in the input along with their key details.
130. **extract_most_redeeming_thing**: Extracts the most redeeming aspect from an input, summarizing it in a single 15-word sentence.
131. **extract_patterns**: Extracts and analyzes recurring, surprising, and insightful patterns from input, providing detailed analysis and advice for builders.
132. **extract_poc**: Extracts proof of concept URLs and validation methods from security reports, providing the URL and command to run.
133. **extract_predictions**: Extracts predictions from input, including specific details such as date, confidence level, and verification method.
134. **extract_primary_problem**: Extracts the primary problem with the world as presented in a given text or body of work.
135. **extract_primary_solution**: Extracts the primary solution for the world as presented in a given text or body of work.
136. **extract_product_features**: Extracts and outputs a list of product features from the provided input in a bulleted format.
137. **extract_questions**: Extracts and outputs all questions asked by the interviewer in a conversation or interview.
138. **extract_recipe**: Extracts and outputs a recipe with a short meal description, ingredients with measurements, and preparation steps.
139. **extract_recommendations**: Extracts and outputs concise, practical recommendations from a given piece of content in a bulleted list.
140. **extract_references**: Extracts and outputs a bulleted list of references to art, stories, books, literature, and other sources from content.
141. **extract_skills**: Extracts and classifies skills from a job description into a table, separating each skill and classifying it as either hard or soft.
142. **extract_song_meaning**: Analyzes a song to provide a summary of its meaning, supported by detailed evidence from lyrics, artist commentary, and fan analysis.
143. **extract_sponsors**: Extracts and lists official sponsors and potential sponsors from a provided transcript.
144. **extract_videoid**: Extracts and outputs the video ID from any given URL.
145. **extract_wisdom**: Extracts surprising, insightful, and interesting information from text on topics like human flourishing, AI, learning, and more.
146. **extract_wisdom_agents**: Extracts valuable insights, ideas, quotes, and references from content, emphasizing topics like human flourishing, AI, learning, and technology.
147. **extract_wisdom_dm**: Extracts all valuable, insightful, and thought-provoking information from content, focusing on topics like human flourishing, AI, learning, and technology.
148. **extract_wisdom_nometa**: Extracts insights, ideas, quotes, habits, facts, references, and recommendations from content, focusing on human flourishing, AI, technology, and related topics.
149. **find_female_life_partner**: Analyzes criteria for finding a female life partner and provides clear, direct, and poetic descriptions.
150. **find_hidden_message**: Extracts overt and hidden political messages, justifications, audience actions, and a cynical analysis from content.
151. **find_logical_fallacies**: Identifies and analyzes fallacies in arguments, classifying them as formal or informal with detailed reasoning.
152. **fix_typos**: Proofreads and corrects typos, spelling, grammar, and punctuation errors in text.
153. **generate_code_rules**: Compile best-practice coding rules and guardrails for AI-assisted development workflows from the provided content.
154. **get_wow_per_minute**: Determines the wow-factor of content per minute based on surprise, novelty, insight, value, and wisdom, measuring how rewarding the content is for the viewer.
155. **get_youtube_rss**: Returns the RSS URL for a given YouTube channel based on the channel ID or URL.
45. **concall_summary**: Analyzes earnings and conference call transcripts to extract management commentary, analyst Q&A, financial insights, risks, and executive summaries.
46. **convert_to_markdown**: Convert content to clean, complete Markdown format, preserving all original structure, formatting, links, and code blocks without alterations.
47. **create_5_sentence_summary**: Create concise summaries or answers to input at 5 different levels of depth, from 5 words to 1 word.
48. **create_academic_paper**: Generate a high-quality academic paper in LaTeX format with clear concepts, structured content, and a professional layout.
49. **create_ai_jobs_analysis**: Analyze job categories' susceptibility to automation, identify resilient roles, and provide strategies for personal adaptation to AI-driven changes in the workforce.
50. **create_aphorisms**: Find and generate a list of brief, witty statements.
51. **create_art_prompt**: Generates a detailed, compelling visual description of a concept, including stylistic references and direct AI instructions for creating art.
52. **create_better_frame**: Identifies and analyzes different frames of interpreting reality, emphasizing the power of positive, productive lenses in shaping outcomes.
53. **create_coding_feature**: Generates secure and composable code features using modern technology and best practices from project specifications.
54. **create_coding_project**: Generate wireframes and starter code for any coding ideas that you have.
55. **create_command**: Helps determine the correct parameters and switches for penetration testing tools based on a brief description of the objective.
56. **create_conceptmap**: Transforms unstructured text or markdown content into an interactive HTML concept map using Vis.js by extracting key concepts and their logical relationships.
57. **create_cyber_summary**: Summarizes cybersecurity threats, vulnerabilities, incidents, and malware with a 25-word summary and categorized bullet points, after thoroughly analyzing and mapping the provided input.
58. **create_design_document**: Creates a detailed design document for a system using the C4 model, addressing business and security postures, and including a system context diagram.
59. **create_diy**: Creates structured "Do It Yourself" tutorial patterns by analyzing prompts, organizing requirements, and providing step-by-step instructions in Markdown format.
60. **create_excalidraw_visualization**: Creates complex Excalidraw diagrams to visualize relationships between concepts and ideas in structured format.
61. **create_flash_cards**: Creates flashcards for key concepts, definitions, and terms with question-answer format for educational purposes.
62. **create_formal_email**: Crafts professional, clear, and respectful emails by analyzing context, tone, and purpose, ensuring proper structure and formatting.
63. **create_git_diff_commit**: Generates Git commands and commit messages for reflecting changes in a repository, using conventional commits and providing concise shell commands for updates.
64. **create_graph_from_input**: Generates a CSV file with progress-over-time data for a security program, focusing on relevant metrics and KPIs.
65. **create_hormozi_offer**: Creates a customized business offer based on principles from Alex Hormozi's book, "$100M Offers."
66. **create_idea_compass**: Organizes and structures ideas by exploring their definition, evidence, sources, and related themes or consequences.
67. **create_investigation_visualization**: Creates detailed Graphviz visualizations of complex input, highlighting key aspects and providing clear, well-annotated diagrams for investigative analysis and conclusions.
68. **create_keynote**: Creates TED-style keynote presentations with a clear narrative, structured slides, and speaker notes, emphasizing impactful takeaways and cohesive flow.
69. **create_loe_document**: Creates detailed Level of Effort documents for estimating work effort, resources, and costs for tasks or projects.
70. **create_logo**: Creates simple, minimalist company logos without text, generating AI prompts for vector graphic logos based on input.
71. **create_markmap_visualization**: Transforms complex ideas into clear visualizations using MarkMap syntax, simplifying concepts into diagrams with relationships, boxes, arrows, and labels.
72. **create_mermaid_visualization**: Creates detailed, standalone visualizations of concepts using Mermaid (Markdown) syntax, ensuring clarity and coherence in diagrams.
73. **create_mermaid_visualization_for_github**: Creates standalone, detailed visualizations using Mermaid (Markdown) syntax to effectively explain complex concepts, ensuring clarity and precision.
74. **create_micro_summary**: Summarizes content into a concise, 20-word summary with main points and takeaways, formatted in Markdown.
75. **create_mnemonic_phrases**: Creates memorable mnemonic sentences from given words to aid in memory retention and learning.
76. **create_network_threat_landscape**: Analyzes open ports and services from a network scan and generates a comprehensive, insightful, and detailed security threat report in Markdown.
77. **create_newsletter_entry**: Condenses provided article text into a concise, objective, newsletter-style summary with a title in the style of Frontend Weekly.
78. **create_npc**: Generates a detailed D&D 5E NPC, including background, flaws, stats, appearance, personality, goals, and more in Markdown format.
79. **create_pattern**: Extracts, organizes, and formats LLM/AI prompts into structured sections, detailing the AI's role, instructions, output format, and any provided examples for clarity and accuracy.
80. **create_prd**: Creates a precise Product Requirements Document (PRD) in Markdown based on input.
81. **create_prediction_block**: Extracts and formats predictions from input into a structured Markdown block for a blog post.
82. **create_quiz**: Creates a three-phase reading plan based on an author or topic to help the user become significantly knowledgeable, including core, extended, and supplementary readings.
83. **create_reading_plan**: Generates review questions based on learning objectives from the input, adapted to the specified student level, and outputs them in a clear markdown format.
84. **create_recursive_outline**: Breaks down complex tasks or projects into manageable, hierarchical components with recursive outlining for clarity and simplicity.
85. **create_report_finding**: Creates a detailed, structured security finding report in markdown, including sections on Description, Risk, Recommendations, References, One-Sentence-Summary, and Quotes.
86. **create_rpg_summary**: Summarizes an in-person RPG session with key events, combat details, player stats, and role-playing highlights in a structured format.
87. **create_security_update**: Creates concise security updates for newsletters, covering stories, threats, advisories, vulnerabilities, and a summary of key issues.
88. **create_show_intro**: Creates compelling short intros for podcasts, summarizing key topics and themes discussed in the episode.
89. **create_sigma_rules**: Extracts Tactics, Techniques, and Procedures (TTPs) from security news and converts them into Sigma detection rules for host-based detections.
90. **create_story_about_people_interaction**: Analyze two personas, compare their dynamics, and craft a realistic, character-driven story from those insights.
91. **create_story_about_person**: Creates compelling, realistic short stories based on psychological profiles, showing how characters navigate everyday problems using strategies consistent with their personality traits.
92. **create_story_explanation**: Summarizes complex content in a clear, approachable story format that makes the concepts easy to understand.
93. **create_stride_threat_model**: Create a STRIDE-based threat model for a system design, identifying assets, trust boundaries, data flows, and prioritizing threats with mitigations.
94. **create_summary**: Summarizes content into a 20-word sentence, 10 main points (16 words max), and 5 key takeaways in Markdown format.
95. **create_tags**: Identifies at least 5 tags from text content for mind mapping tools, including authors and existing tags if present.
96. **create_threat_scenarios**: Identifies likely attack methods for any system by providing a narrative-based threat model, balancing risk and opportunity.
97. **create_ttrc_graph**: Creates a CSV file showing the progress of Time to Remediate Critical Vulnerabilities over time using given data.
98. **create_ttrc_narrative**: Creates a persuasive narrative highlighting progress in reducing the Time to Remediate Critical Vulnerabilities metric over time.
99. **create_upgrade_pack**: Extracts world model and task algorithm updates from content, providing beliefs about how the world works and task performance.
100. **create_user_story**: Writes concise and clear technical user stories for new features in complex software programs, formatted for all stakeholders.
101. **create_video_chapters**: Extracts interesting topics and timestamps from a transcript, providing concise summaries of key moments.
102. **create_visualization**: Transforms complex ideas into visualizations using intricate ASCII art, simplifying concepts where necessary.
103. **dialog_with_socrates**: Engages in deep, meaningful dialogues to explore and challenge beliefs using the Socratic method.
104. **enrich_blog_post**: Enhances Markdown blog files by applying instructions to improve structure, visuals, and readability for HTML rendering.
105. **explain_code**: Explains code, security tool output, configuration text, and answers questions based on the provided input.
106. **explain_docs**: Improves and restructures tool documentation into clear, concise instructions, including overviews, usage, use cases, and key features.
107. **explain_math**: Helps you understand mathematical concepts in a clear and engaging way.
108. **explain_project**: Summarizes project documentation into clear, concise sections covering the project, problem, solution, installation, usage, and examples.
109. **explain_terms**: Produces a glossary of advanced terms from content, providing a definition, analogy, and explanation of why each term matters.
110. **export_data_as_csv**: Extracts and outputs all data structures from the input in properly formatted CSV data.
111. **extract_algorithm_update_recommendations**: Extracts concise, practical algorithm update recommendations from the input and outputs them in a bulleted list.
112. **extract_article_wisdom**: Extracts surprising, insightful, and interesting information from content, categorizing it into sections like summary, ideas, quotes, facts, references, and recommendations.
113. **extract_book_ideas**: Extracts and outputs 50 to 100 of the most surprising, insightful, and interesting ideas from a book's content.
114. **extract_book_recommendations**: Extracts and outputs 50 to 100 practical, actionable recommendations from a book's content.
115. **extract_business_ideas**: Extracts top business ideas from content and elaborates on the best 10 with unique differentiators.
116. **extract_characters**: Identify all characters (human and non-human), resolve their aliases and pronouns into canonical names, and produce detailed descriptions of each character's role, motivations, and interactions ranked by narrative importance.
117. **extract_controversial_ideas**: Extracts and outputs controversial statements and supporting quotes from the input in a structured Markdown list.
118. **extract_core_message**: Extracts and outputs a clear, concise sentence that articulates the core message of a given text or body of work.
119. **extract_ctf_writeup**: Extracts a short writeup from a warstory-like text about a cyber security engagement.
120. **extract_domains**: Extracts domains and URLs from content to identify sources used for articles, newsletters, and other publications.
121. **extract_extraordinary_claims**: Extracts and outputs a list of extraordinary claims from conversations, focusing on scientifically disputed or false statements.
122. **extract_ideas**: Extracts and outputs all the key ideas from input, presented as 15-word bullet points in Markdown.
123. **extract_insights**: Extracts and outputs the most powerful and insightful ideas from text, formatted as 16-word bullet points in the INSIGHTS section, also IDEAS section.
124. **extract_insights_dm**: Extracts and outputs all valuable insights and a concise summary of the content, including key points and topics discussed.
125. **extract_instructions**: Extracts clear, actionable step-by-step instructions and main objectives from instructional video transcripts, organizing them into a concise list.
126. **extract_jokes**: Extracts jokes from text content, presenting each joke with its punchline in separate bullet points.
127. **extract_latest_video**: Extracts the latest video URL from a YouTube RSS feed and outputs the URL only.
128. **extract_main_activities**: Extracts key events and activities from transcripts or logs, providing a summary of what happened.
129. **extract_main_idea**: Extracts the main idea and key recommendation from the input, summarizing them in 15-word sentences.
130. **extract_mcp_servers**: Identify and summarize Model Context Protocol (MCP) servers referenced in the input along with their key details.
131. **extract_most_redeeming_thing**: Extracts the most redeeming aspect from an input, summarizing it in a single 15-word sentence.
132. **extract_patterns**: Extracts and analyzes recurring, surprising, and insightful patterns from input, providing detailed analysis and advice for builders.
133. **extract_poc**: Extracts proof of concept URLs and validation methods from security reports, providing the URL and command to run.
134. **extract_predictions**: Extracts predictions from input, including specific details such as date, confidence level, and verification method.
135. **extract_primary_problem**: Extracts the primary problem with the world as presented in a given text or body of work.
136. **extract_primary_solution**: Extracts the primary solution for the world as presented in a given text or body of work.
137. **extract_product_features**: Extracts and outputs a list of product features from the provided input in a bulleted format.
138. **extract_questions**: Extracts and outputs all questions asked by the interviewer in a conversation or interview.
139. **extract_recipe**: Extracts and outputs a recipe with a short meal description, ingredients with measurements, and preparation steps.
140. **extract_recommendations**: Extracts and outputs concise, practical recommendations from a given piece of content in a bulleted list.
141. **extract_references**: Extracts and outputs a bulleted list of references to art, stories, books, literature, and other sources from content.
142. **extract_skills**: Extracts and classifies skills from a job description into a table, separating each skill and classifying it as either hard or soft.
143. **extract_song_meaning**: Analyzes a song to provide a summary of its meaning, supported by detailed evidence from lyrics, artist commentary, and fan analysis.
144. **extract_sponsors**: Extracts and lists official sponsors and potential sponsors from a provided transcript.
145. **extract_videoid**: Extracts and outputs the video ID from any given URL.
146. **extract_wisdom**: Extracts surprising, insightful, and interesting information from text on topics like human flourishing, AI, learning, and more.
147. **extract_wisdom_agents**: Extracts valuable insights, ideas, quotes, and references from content, emphasizing topics like human flourishing, AI, learning, and technology.
148. **extract_wisdom_dm**: Extracts all valuable, insightful, and thought-provoking information from content, focusing on topics like human flourishing, AI, learning, and technology.
149. **extract_wisdom_nometa**: Extracts insights, ideas, quotes, habits, facts, references, and recommendations from content, focusing on human flourishing, AI, technology, and related topics.
150. **find_female_life_partner**: Analyzes criteria for finding a female life partner and provides clear, direct, and poetic descriptions.
151. **find_hidden_message**: Extracts overt and hidden political messages, justifications, audience actions, and a cynical analysis from content.
152. **find_logical_fallacies**: Identifies and analyzes fallacies in arguments, classifying them as formal or informal with detailed reasoning.
153. **fix_typos**: Proofreads and corrects typos, spelling, grammar, and punctuation errors in text.
154. **generate_code_rules**: Compile best-practice coding rules and guardrails for AI-assisted development workflows from the provided content.
155. **get_wow_per_minute**: Determines the wow-factor of content per minute based on surprise, novelty, insight, value, and wisdom, measuring how rewarding the content is for the viewer.
156. **heal_person**: Develops a comprehensive plan for spiritual and mental healing based on psychological profiles, providing personalized recommendations for mental health improvement and overall life enhancement.
157. **humanize**: Rewrites AI-generated text to sound natural, conversational, and easy to understand, maintaining clarity and simplicity.
158. **identify_dsrp_distinctions**: Encourages creative, systems-based thinking by exploring distinctions, boundaries, and their implications, drawing on insights from prominent systems thinkers.

View File

@@ -73,21 +73,21 @@ Match the request to one or more of these primary categories:
**AI**: ai, create_ai_jobs_analysis, create_art_prompt, create_pattern, create_prediction_block, extract_mcp_servers, extract_wisdom_agents, generate_code_rules, improve_prompt, judge_output, rate_ai_response, rate_ai_result, raw_query, suggest_pattern, summarize_prompt
**ANALYSIS**: ai, analyze_answers, analyze_bill, analyze_bill_short, analyze_candidates, analyze_cfp_submission, analyze_claims, analyze_comments, analyze_debate, analyze_email_headers, analyze_incident, analyze_interviewer_techniques, analyze_logs, analyze_malware, analyze_military_strategy, analyze_mistakes, analyze_paper, analyze_paper_simple, analyze_patent, analyze_personality, analyze_presentation, analyze_product_feedback, analyze_proposition, analyze_prose, analyze_prose_json, analyze_prose_pinker, analyze_risk, analyze_sales_call, analyze_spiritual_text, analyze_tech_impact, analyze_terraform_plan, analyze_threat_report, analyze_threat_report_cmds, analyze_threat_report_trends, apply_ul_tags, check_agreement, compare_and_contrast, create_ai_jobs_analysis, create_idea_compass, create_investigation_visualization, create_prediction_block, create_recursive_outline, create_story_about_people_interaction, create_tags, dialog_with_socrates, extract_main_idea, extract_predictions, find_hidden_message, find_logical_fallacies, get_wow_per_minute, identify_dsrp_distinctions, identify_dsrp_perspectives, identify_dsrp_relationships, identify_dsrp_systems, identify_job_stories, label_and_rate, model_as_sherlock_freud, predict_person_actions, prepare_7s_strategy, provide_guidance, rate_content, rate_value, recommend_artists, recommend_talkpanel_topics, review_design, summarize_board_meeting, t_analyze_challenge_handling, t_check_dunning_kruger, t_check_metrics, t_describe_life_outlook, t_extract_intro_sentences, t_extract_panel_topics, t_find_blindspots, t_find_negative_thinking, t_red_team_thinking, t_threat_model_plans, t_year_in_review, write_hackerone_report
**ANALYSIS**: ai, analyze_answers, analyze_bill, analyze_bill_short, analyze_candidates, analyze_cfp_submission, analyze_claims, analyze_comments, analyze_debate, analyze_email_headers, analyze_incident, analyze_interviewer_techniques, analyze_logs, analyze_malware, analyze_military_strategy, analyze_mistakes, analyze_paper, analyze_paper_simple, analyze_patent, analyze_personality, analyze_presentation, analyze_product_feedback, analyze_proposition, analyze_prose, analyze_prose_json, analyze_prose_pinker, analyze_risk, analyze_sales_call, analyze_spiritual_text, analyze_tech_impact, analyze_terraform_plan, analyze_threat_report, analyze_threat_report_cmds, analyze_threat_report_trends, apply_ul_tags, check_agreement, compare_and_contrast, concall_summary, create_ai_jobs_analysis, create_idea_compass, create_investigation_visualization, create_prediction_block, create_recursive_outline, create_story_about_people_interaction, create_tags, dialog_with_socrates, extract_main_idea, extract_predictions, find_hidden_message, find_logical_fallacies, get_wow_per_minute, identify_dsrp_distinctions, identify_dsrp_perspectives, identify_dsrp_relationships, identify_dsrp_systems, identify_job_stories, label_and_rate, model_as_sherlock_freud, predict_person_actions, prepare_7s_strategy, provide_guidance, rate_content, rate_value, recommend_artists, recommend_talkpanel_topics, review_design, summarize_board_meeting, t_analyze_challenge_handling, t_check_dunning_kruger, t_check_metrics, t_describe_life_outlook, t_extract_intro_sentences, t_extract_panel_topics, t_find_blindspots, t_find_negative_thinking, t_red_team_thinking, t_threat_model_plans, t_year_in_review, write_hackerone_report
**BILL**: analyze_bill, analyze_bill_short
**BUSINESS**: check_agreement, create_ai_jobs_analysis, create_formal_email, create_hormozi_offer, create_loe_document, create_logo, create_newsletter_entry, create_prd, explain_project, extract_business_ideas, extract_characters, extract_product_features, extract_skills, extract_sponsors, identify_job_stories, prepare_7s_strategy, rate_value, t_check_metrics, t_create_h3_career, t_visualize_mission_goals_projects, t_year_in_review, transcribe_minutes
**BUSINESS**: check_agreement, concall_summary, create_ai_jobs_analysis, create_formal_email, create_hormozi_offer, create_loe_document, create_logo, create_newsletter_entry, create_prd, explain_project, extract_business_ideas, extract_characters, extract_product_features, extract_skills, extract_sponsors, identify_job_stories, prepare_7s_strategy, rate_value, t_check_metrics, t_create_h3_career, t_visualize_mission_goals_projects, t_year_in_review, transcribe_minutes
**CLASSIFICATION**: apply_ul_tags
**CONVERSION**: clean_text, convert_to_markdown, create_graph_from_input, export_data_as_csv, extract_videoid, get_youtube_rss, humanize, md_callout, sanitize_broken_html_to_markdown, to_flashcards, transcribe_minutes, translate, tweet, write_latex
**CONVERSION**: clean_text, convert_to_markdown, create_graph_from_input, export_data_as_csv, extract_videoid, humanize, md_callout, sanitize_broken_html_to_markdown, to_flashcards, transcribe_minutes, translate, tweet, write_latex
**CR THINKING**: capture_thinkers_work, create_idea_compass, create_markmap_visualization, dialog_with_socrates, extract_alpha, extract_controversial_ideas, extract_extraordinary_claims, extract_predictions, extract_primary_problem, extract_wisdom_nometa, find_hidden_message, find_logical_fallacies, summarize_debate, t_analyze_challenge_handling, t_check_dunning_kruger, t_find_blindspots, t_find_negative_thinking, t_find_neglected_goals, t_red_team_thinking
**CREATIVITY**: create_mnemonic_phrases, write_essay
**DEVELOPMENT**: agility_story, analyze_logs, analyze_prose_json, answer_interview_question, ask_secure_by_design_questions, ask_uncle_duke, coding_master, create_coding_feature, create_coding_project, create_command, create_design_document, create_git_diff_commit, create_loe_document, create_mermaid_visualization, create_mermaid_visualization_for_github, create_pattern, create_prd, create_sigma_rules, create_user_story, explain_code, explain_docs, explain_project, export_data_as_csv, extract_algorithm_update_recommendations, extract_mcp_servers, extract_poc, extract_product_features, generate_code_rules, get_youtube_rss, identify_job_stories, improve_prompt, official_pattern_template, recommend_pipeline_upgrades, refine_design_document, review_code, review_design, sanitize_broken_html_to_markdown, suggest_pattern, summarize_git_changes, summarize_git_diff, summarize_pull-requests, write_nuclei_template_rule, write_pull-request, write_semgrep_rule
**DEVELOPMENT**: agility_story, analyze_logs, analyze_prose_json, answer_interview_question, ask_secure_by_design_questions, ask_uncle_duke, coding_master, create_coding_feature, create_coding_project, create_command, create_design_document, create_git_diff_commit, create_loe_document, create_mermaid_visualization, create_mermaid_visualization_for_github, create_pattern, create_prd, create_sigma_rules, create_user_story, explain_code, explain_docs, explain_project, export_data_as_csv, extract_algorithm_update_recommendations, extract_mcp_servers, extract_poc, extract_product_features, generate_code_rules, identify_job_stories, improve_prompt, official_pattern_template, recommend_pipeline_upgrades, refine_design_document, review_code, review_design, sanitize_broken_html_to_markdown, suggest_pattern, summarize_git_changes, summarize_git_diff, summarize_pull-requests, write_nuclei_template_rule, write_pull-request, write_semgrep_rule
**DEVOPS**: analyze_terraform_plan
@@ -109,7 +109,7 @@ Match the request to one or more of these primary categories:
**STRATEGY**: analyze_military_strategy, create_better_frame, prepare_7s_strategy, t_analyze_challenge_handling, t_find_blindspots, t_find_negative_thinking, t_find_neglected_goals, t_red_team_thinking, t_threat_model_plans, t_visualize_mission_goals_projects
**SUMMARIZE**: capture_thinkers_work, create_5_sentence_summary, create_micro_summary, create_newsletter_entry, create_show_intro, create_summary, extract_core_message, extract_latest_video, extract_main_idea, summarize, summarize_board_meeting, summarize_debate, summarize_git_changes, summarize_git_diff, summarize_lecture, summarize_legislation, summarize_meeting, summarize_micro, summarize_newsletter, summarize_paper, summarize_pull-requests, summarize_rpg_session, youtube_summary
**SUMMARIZE**: capture_thinkers_work, concall_summary, create_5_sentence_summary, create_micro_summary, create_newsletter_entry, create_show_intro, create_summary, extract_core_message, extract_latest_video, extract_main_idea, summarize, summarize_board_meeting, summarize_debate, summarize_git_changes, summarize_git_diff, summarize_lecture, summarize_legislation, summarize_meeting, summarize_micro, summarize_newsletter, summarize_paper, summarize_pull-requests, summarize_rpg_session, youtube_summary
**VISUALIZE**: create_conceptmap, create_excalidraw_visualization, create_graph_from_input, create_idea_compass, create_investigation_visualization, create_keynote, create_logo, create_markmap_visualization, create_mermaid_visualization, create_mermaid_visualization_for_github, create_video_chapters, create_visualization, enrich_blog_post, t_visualize_mission_goals_projects

View File

@@ -196,6 +196,10 @@ Review contract to identify stipulations, issues, and changes for negotiation.
Create comparisons table, highlighting key differences and similarities.
### concall_summary
Analyze earnings call transcripts to extract management insights, financial metrics, and investment implications.
### create_ai_jobs_analysis
Identify automation risks and career resilience strategies.
@@ -942,10 +946,6 @@ Convert content to markdown, preserving original content and structure.
Extract data and convert to CSV, preserving data integrity.
### get_youtube_rss
Generate RSS feed URLs for YouTube channels.
### sanitize_broken_html_to_markdown
Clean/convert malformed HTML to markdown.

View File

@@ -51,6 +51,29 @@ docs: update installation instructions
## Pull Request Process
### Pull Request Guidelines
**Keep pull requests focused and minimal.**
PRs that touch a large number of files (50+) without clear functional justification will likely be rejected without detailed review.
#### Why we enforce this
- **Reviewability**: Large PRs are effectively un-reviewable. Studies show reviewer effectiveness drops significantly after ~200-400 lines of code. A 93-file "cleanup" PR cannot receive meaningful review.
- **Git history**: Sweeping changes pollute `git blame`, making it harder to trace when and why functional changes were made.
- **Merge conflicts**: Large PRs increase the likelihood of conflicts with other contributors' work.
- **Risk**: More changed lines means more opportunities for subtle bugs, even in "safe" refactors.
#### What to do instead
If you have a large change in mind, break it into logical, independently-mergeable slices. For example:
- ✅ "Replace `interface{}` with `any` across codebase" (single mechanical change, easy to verify)
- ✅ "Migrate to `strings.CutPrefix` in `internal/cli`" (scoped to one package)
- ❌ "Modernize codebase with multiple idiom updates" (too broad, impossible to review)
For sweeping refactors or style changes, **open an issue first** to discuss the approach with maintainers before investing time in the work.
### Changelog Generation (REQUIRED)
After opening your PR, generate a changelog entry:
@@ -142,6 +165,79 @@ Example output here
- Include usage examples
- Keep documentation current
### REST API Documentation
When adding or modifying REST API endpoints, you must update the Swagger documentation:
**1. Add Swagger annotations to your handler:**
```go
// HandlerName godoc
// @Summary Short description of what this endpoint does
// @Description Detailed description of the endpoint's functionality
// @Tags category-name
// @Accept json
// @Produce json
// @Param name path string true "Parameter description"
// @Param body body RequestType true "Request body description"
// @Success 200 {object} ResponseType "Success description"
// @Failure 400 {object} map[string]string "Bad request"
// @Failure 500 {object} map[string]string "Server error"
// @Security ApiKeyAuth
// @Router /endpoint/path [get]
func (h *Handler) HandlerName(c *gin.Context) {
// Implementation
}
```
**2. Regenerate Swagger documentation:**
```bash
# Install swag CLI if you haven't already
go install github.com/swaggo/swag/cmd/swag@latest
# Generate updated documentation
swag init -g internal/server/serve.go -o docs
```
**3. Commit the generated files:**
The following files will be updated and should be committed:
- `docs/swagger.json`
- `docs/swagger.yaml`
- `docs/docs.go`
**4. Test your changes:**
Start the server and verify your endpoint appears in Swagger UI:
```bash
go run ./cmd/fabric --serve
# Open http://localhost:8080/swagger/index.html
```
**Examples to follow:**
- Chat endpoint: `internal/server/chat.go:58-68`
- Patterns endpoint: `internal/server/patterns.go:36-45`
- Models endpoint: `internal/server/models.go:20-28`
**Common annotation tags:**
- `@Summary` - One-line description (required)
- `@Description` - Detailed explanation
- `@Tags` - Logical grouping (e.g., "patterns", "chat", "models")
- `@Accept` - Input content type (e.g., "json")
- `@Produce` - Output content type (e.g., "json", "text/event-stream")
- `@Param` - Request parameters (path, query, body)
- `@Success` - Successful response (include status code and type)
- `@Failure` - Error responses
- `@Security` - Authentication requirement (use "ApiKeyAuth" for API key)
- `@Router` - Endpoint path and HTTP method
For complete Swagger annotation syntax, see the [swaggo documentation](https://github.com/swaggo/swag#declarative-comments-format)
## Getting Help
- Check existing issues first

700
docs/GitHub-Models-Setup.md Normal file
View File

@@ -0,0 +1,700 @@
# GitHub Models Setup Guide for Fabric
This guide will walk you through setting up and using GitHub Models with Fabric CLI. GitHub Models provides free access to multiple AI models from OpenAI, Meta, Microsoft, DeepSeek, xAI, and other providers using only your GitHub credentials.
## Table of Contents
- [What are GitHub Models?](#what-are-github-models)
- [Getting Your GitHub Models API Key](#getting-your-github-models-api-key)
- [Configuring Fabric for GitHub Models](#configuring-fabric-for-github-models)
- [Testing Your Setup](#testing-your-setup)
- [Available Models](#available-models)
- [Rate Limits & Free Tier](#rate-limits--free-tier)
- [Troubleshooting](#troubleshooting)
- [Advanced Usage](#advanced-usage)
---
## What are GitHub Models?
**GitHub Models** is a free AI inference API platform that allows you to access multiple AI models using only your GitHub account. It's powered by Azure AI infrastructure and provides:
- **Unified Access**: Single API endpoint for models from multiple providers
- **No Extra API Keys**: Uses GitHub Personal Access Tokens (no separate OpenAI, Anthropic, etc. keys needed)
- **Free Tier**: Rate-limited free access perfect for prototyping and personal projects
- **Web Playground**: Test models directly at [github.com/marketplace/models](https://github.com/marketplace/models)
- **Compatible Format**: Works with OpenAI SDK standards
### Why Use GitHub Models with Fabric?
- **No Cost for Testing**: Free tier allows 50-150 requests/day depending on model
- **Multiple Providers**: Access OpenAI, Meta Llama, Microsoft Phi, DeepSeek, and more
- **Easy Setup**: Just one GitHub token instead of managing multiple API keys
- **Great for Learning**: Experiment with different models without financial commitment
---
## Getting Your GitHub Models API Key
GitHub Models uses **Personal Access Tokens (PAT)** instead of separate API keys.
### Step-by-Step Instructions
1. **Sign in to GitHub** at [github.com](https://github.com)
2. **Navigate to Token Settings:**
- Click your profile picture (upper-right corner)
- Click **Settings**
- Scroll down the left sidebar to **Developer settings** (at the bottom)
- Click **Personal access tokens****Fine-grained tokens** (recommended)
3. **Generate New Token:**
- Click **Generate new token**
- Give it a descriptive name: `Fabric CLI - GitHub Models`
- Set expiration (recommended: 90 days or custom)
- **Repository access**: Select "Public Repositories (read-only)" or "All repositories" (your choice)
- **Permissions**:
- Scroll down to **Account permissions**
- Find **AI Models** and set to **Read-only**
- This grants the `models:read` scope
- Click **Generate token** at the bottom
4. **Save Your Token:**
- **IMPORTANT**: Copy the token immediately (starts with `github_pat_` or `ghp_`)
- You won't be able to see it again!
- Store it securely - this will be your `GITHUB_TOKEN`
### Security Best Practices
- ✅ Use fine-grained tokens with minimal permissions
- ✅ Set an expiration date (rotate tokens regularly)
- ✅ Never commit tokens to Git repositories
- ✅ Store in environment variables or secure credential managers
- ❌ Don't share tokens in chat, email, or screenshots
---
## Configuring Fabric for GitHub Models
### Method 1: Using Fabric Setup (Recommended)
This is the easiest and safest method:
1. **Run Fabric Setup:**
```bash
fabric --setup
```
2. **Select GitHub from the Menu:**
- You'll see a numbered list of AI vendors
- Find `[8] GitHub (configured)` or similar
- Enter the number (e.g., `8`) and press Enter
3. **Enter Your GitHub Token:**
- When prompted for "API Key", paste your GitHub Personal Access Token
- The token you created earlier (starts with `github_pat_` or `ghp_`)
- Press Enter
4. **Verify Base URL (Optional):**
- You'll be asked for "API Base URL"
- Press Enter to use the default: `https://models.github.ai/inference`
- Or customize if needed (advanced use only)
5. **Save and Exit:**
- The setup wizard will save your configuration
- You should see "GitHub (configured)" next time
### Method 2: Manual Configuration (Advanced)
If you prefer to manually edit the configuration file:
1. **Edit Environment File:**
```bash
nano ~/.config/fabric/.env
```
2. **Add GitHub Configuration:**
```bash
# GitHub Models API Key (your Personal Access Token)
GITHUB_API_KEY=github_pat_YOUR_TOKEN_HERE
# GitHub Models API Base URL (default, usually don't need to change)
GITHUB_API_BASE_URL=https://models.github.ai/inference
```
Save and exit (Ctrl+X, then Y, then Enter)
**Note**: The environment variable is `GITHUB_API_KEY`, not `GITHUB_TOKEN`.
### Verify Configuration
Check that your configuration is properly set:
```bash
grep GITHUB_API_KEY ~/.config/fabric/.env
```
You should see:
```text
GITHUB_API_KEY=github_pat_...
```
Or run setup again to verify:
```bash
fabric --setup
```
Look for `[8] GitHub (configured)` in the list.
---
## Testing Your Setup
### 1. List Available Models
Verify that Fabric can connect to GitHub Models and fetch the model list:
```bash
fabric --listmodels | grep GitHub
```
**Expected Output:**
```text
Available models:
...
$ fabric -L | grep GitHub
[65] GitHub|ai21-labs/ai21-jamba-1.5-large
[66] GitHub|cohere/cohere-command-a
[67] GitHub|cohere/cohere-command-r-08-2024
[68] GitHub|cohere/cohere-command-r-plus-08-2024
[69] GitHub|deepseek/deepseek-r1
[70] GitHub|deepseek/deepseek-r1-0528
[71] GitHub|deepseek/deepseek-v3-0324
[72] GitHub|meta/llama-3.2-11b-vision-instruct
[73] GitHub|meta/llama-3.2-90b-vision-instruct
... (and more)
```
### 2. Simple Chat Test
Test a basic chat completion with a small, fast model:
```bash
# Use gpt-4o-mini (fast and has generous rate limits)
fabric --vendor GitHub -m openai/gpt-4o-mini 'Why is th
e sky blue?'
```
**Expected**: You should see a response explaining Rayleigh scattering.
**Tip**: Model names from `--listmodels` can be used directly (e.g., `openai/gpt-4o-mini`, `openai/gpt-4o`, `meta/llama-4-maverick-17b-128e-instruct-fp8`).
### 3. Test with a Pattern
Use one of Fabric's built-in patterns:
```bash
echo "Artificial intelligence is transforming how we work and live." | \
fabric --pattern summarize --vendor GitHub --model "openai/gpt-4o-mini"
```
### 4. Test Streaming
Verify streaming responses work:
```bash
echo "Count from 1 to 100" | \
fabric --vendor GitHub --model "openai/gpt-4o-mini" --stream
```
You should see the response appear progressively, word by word.
### 5. Test with Different Models
Try a Meta Llama model:
```bash
# Use a Llama model
echo "Explain quantum computing" | \
fabric --vendor GitHub --model "meta/Meta-Llama-3.1-8B-Instruct"
```
### Quick Validation Checklist
- [x] `--listmodels` shows GitHub models
- [x] Basic chat completion works
- [x] Patterns work with GitHub vendor
- [x] Streaming responses work
- [x] Can switch between different models
---
## Available Models
GitHub Models provides access to models from multiple providers. Models use the format: `{publisher}/{model-name}`
### OpenAI Models
| Model ID | Description | Tier | Best For |
|----------|-------------|------|----------|
| `openai/gpt-4.1` | Latest flagship GPT-4 | High | Complex tasks, reasoning |
| `openai/gpt-4o` | Optimized GPT-4 | High | General purpose, fast |
| `openai/gpt-4o-mini` | Compact, cost-effective | Low | Quick tasks, high volume |
| `openai/o1` | Advanced reasoning | High | Complex problem solving |
| `openai/o3` | Next-gen reasoning | High | Cutting-edge reasoning |
### Meta Llama Models
| Model ID | Description | Tier | Best For |
|----------|-------------|------|----------|
| `meta/llama-3.1-405b` | Largest Llama model | High | Complex tasks, accuracy |
| `meta/llama-3.1-70b` | Mid-size Llama | Low | Balanced performance |
| `meta/llama-3.1-8b` | Compact Llama | Low | Fast, efficient tasks |
### Microsoft Phi Models
| Model ID | Description | Tier | Best For |
|----------|-------------|------|----------|
| `microsoft/phi-4` | Latest Phi generation | Low | Efficient reasoning |
| `microsoft/phi-3-medium` | Mid-size variant | Low | General tasks |
| `microsoft/phi-3-mini` | Smallest Phi | Low | Quick, simple tasks |
### DeepSeek Models
| Model ID | Description | Tier | Special |
|----------|-------------|------|---------|
| `deepseek/deepseek-r1` | Reasoning model | Very Limited | 8 requests/day |
| `deepseek/deepseek-r1-0528` | Updated version | Very Limited | 8 requests/day |
### xAI Models
| Model ID | Description | Tier | Special |
|----------|-------------|------|---------|
| `xai/grok-3` | Latest Grok | Very Limited | 15 requests/day |
| `xai/grok-3-mini` | Smaller Grok | Very Limited | 15 requests/day |
### Getting the Full List
To see all currently available models:
```bash
fabric --listmodels | grep GitHub
```
Or for a formatted list with details, you can query the GitHub Models API directly:
```bash
curl -H "Authorization: Bearer $GITHUB_TOKEN" \
-H "X-GitHub-Api-Version: 2022-11-28" \
https://models.github.ai/catalog/models | jq '.[] | {id, publisher, tier: .rate_limit_tier}'
```
---
## Rate Limits & Free Tier
GitHub Models has tiered rate limits based on model complexity. Understanding these helps you use the free tier effectively.
### Low Tier Models (Recommended for High Volume)
**Models**: `gpt-4o-mini`, `llama-3.1-*`, `phi-*`
- **Requests per minute**: 15
- **Requests per day**: 150
- **Tokens per request**: 8,000 input / 4,000 output
- **Concurrent requests**: 5
**Best practices**: Use these for most Fabric patterns and daily tasks.
### High Tier Models (Use Sparingly)
**Models**: `gpt-4.1`, `gpt-4o`, `o1`, `o3`, `llama-3.1-405b`
- **Requests per minute**: 10
- **Requests per day**: 50
- **Tokens per request**: 8,000 input / 4,000 output
- **Concurrent requests**: 2
**Best practices**: Save for complex tasks, important queries, or when you need maximum quality.
### Very Limited Models
**Models**: `deepseek-r1`, `grok-3`
- **Requests per minute**: 1
- **Requests per day**: 8-15 (varies by model)
- **Tokens per request**: 4,000 input / 4,000 output
- **Concurrent requests**: 1
**Best practices**: Use only for special experiments or when you specifically need these models.
### Rate Limit Reset Times
- **Per-minute limits**: Reset every 60 seconds
- **Daily limits**: Reset at midnight UTC
- **Per-user**: Limits are tied to your GitHub account, not the token
### Enhanced Limits with GitHub Copilot
If you have a GitHub Copilot subscription, you get higher limits:
- **Copilot Business**: 2× daily request limits
- **Copilot Enterprise**: 3× daily limits + higher token limits
### What Happens When You Hit Limits?
You'll receive an HTTP 429 error with a message like:
```text
Rate limit exceeded. Try again in X seconds.
```
Fabric will display this error. Wait for the reset time and try again.
### Tips for Staying Within Limits
1. **Use low-tier models** for most tasks (`gpt-4o-mini`, `llama-3.1-8b`)
2. **Batch your requests** - process multiple items together when possible
3. **Cache results** - save responses for repeated queries
4. **Monitor usage** - keep track of daily request counts
5. **Set per-pattern models** - configure specific models for specific patterns (see Advanced Usage)
---
## Troubleshooting
### Error: "Authentication failed" or "Unauthorized"
**Cause**: Invalid or missing GitHub token
**Solutions**:
1. Verify token is in `.env` file:
```bash
grep GITHUB_API_KEY ~/.config/fabric/.env
```
2. Check token has `models:read` permission:
- Go to GitHub Settings → Developer settings → Personal access tokens
- Click on your token
- Verify "AI Models: Read-only" is checked
3. Re-run setup to reconfigure:
```bash
fabric --setup
# Select GitHub (number 8 or similar)
# Enter your token again
```
4. Generate a new token if needed (tokens expire)
### Error: "Rate limit exceeded"
**Cause**: Too many requests in a short time period
**Solutions**:
1. Check which tier your model is in (see [Rate Limits](#rate-limits--free-tier))
2. Wait for the reset (check error message for wait time)
3. Switch to a lower-tier model:
```bash
# Instead of gpt-4.1 (high tier)
fabric --vendor GitHub --model openai/gpt-4.1 ...
# Use gpt-4o-mini (low tier)
fabric --vendor GitHub --model openai/gpt-4o-mini ...
```
### Error: "Model not found" or "Invalid model"
**Cause**: Model name format incorrect or model not available
**Solutions**:
1. Use correct format: `{publisher}/{model-name}`, e.g., `openai/gpt-4o-mini`
```bash
# ❌ Wrong
fabric --vendor GitHub --model gpt-4o-mini
# ✅ Correct
fabric --vendor GitHub --model openai/gpt-4o-mini
```
2. List available models to verify name:
```bash
fabric --listmodels --vendor GitHub | grep -i "gpt-4"
```
### Error: "Cannot list models" or Empty model list
**Cause**: API endpoint issue or authentication problem
**Solutions**:
1. Test direct API access:
```bash
curl -H "Authorization: Bearer $GITHUB_TOKEN" \
-H "X-GitHub-Api-Version: 2022-11-28" \
https://models.github.ai/catalog/models
```
2. If curl works but Fabric doesn't, rebuild Fabric:
```bash
cd /path/to/fabric
go build ./cmd/fabric
```
3. Check for network/firewall issues blocking `models.github.ai`
### Error: "Response format not supported"
**Cause**: This should be fixed in the latest version with direct fetch fallback
**Solutions**:
1. Update to the latest Fabric version with PR #1839 merged
2. Verify you're on a version that includes the `FetchModelsDirectly` fallback
### Models are slow to respond
**Cause**: High tier models have limited concurrency, or GitHub Models API congestion
**Solutions**:
1. Switch to faster models:
- `openai/gpt-4o-mini` instead of `gpt-4.1`
- `meta/llama-3.1-8b` instead of `llama-3.1-405b`
2. Check your internet connection
3. Try again later (API may be experiencing high traffic)
### Token expires or becomes invalid
**Cause**: Tokens have expiration dates or can be revoked
**Solutions**:
1. Generate a new token (see [Getting Your GitHub Models API Key](#getting-your-github-models-api-key))
2. Update `.env` file with new token
3. Set longer expiration when creating tokens (e.g., 90 days)
---
## Advanced Usage
### Using Specific Models with Patterns
You can specify which model to use with any pattern:
```bash
# Use GPT-4.1 with the analyze_claims pattern
cat article.txt | fabric --pattern analyze_claims \
--vendor GitHub --model openai/gpt-4.1
# Use Llama for summarization
cat document.txt | fabric --pattern summarize \
--vendor GitHub --model meta/llama-3.1-70b
```
### Per-Pattern Model Mapping
Set default models for specific patterns using environment variables:
Edit `~/.config/fabric/.env`:
```bash
# Use GPT-4.1 for complex analysis
FABRIC_MODEL_analyze_claims=GitHub|openai/gpt-4.1
FABRIC_MODEL_extract_wisdom=GitHub|openai/gpt-4.1
# Use GPT-4o-mini for simple tasks
FABRIC_MODEL_summarize=GitHub|openai/gpt-4o-mini
FABRIC_MODEL_extract_article_wisdom=GitHub|openai/gpt-4o-mini
# Use Llama for code tasks
FABRIC_MODEL_explain_code=GitHub|meta/llama-3.1-70b
```
Now when you run:
```bash
cat article.txt | fabric --pattern analyze_claims
```
It will automatically use `GitHub|openai/gpt-4.1` without needing to specify the vendor and model.
### Comparing Responses Across Providers
Compare how different models respond to the same input:
```bash
# OpenAI GPT-4o-mini
echo "Explain quantum computing" | \
fabric --vendor GitHub --model openai/gpt-4o-mini > response_openai.txt
# Meta Llama
echo "Explain quantum computing" | \
fabric --vendor GitHub --model meta/llama-3.1-70b > response_llama.txt
# Microsoft Phi
echo "Explain quantum computing" | \
fabric --vendor GitHub --model microsoft/phi-4 > response_phi.txt
# Compare
diff response_openai.txt response_llama.txt
```
### Testing Different Models for a Pattern
Find the best model for your use case:
```bash
# Create a test script
cat > test_models.sh << 'EOF'
#!/bin/bash
INPUT="Explain the concept of recursion in programming"
PATTERN="explain_code"
for MODEL in "openai/gpt-4o-mini" "meta/llama-3.1-8b" "microsoft/phi-4"; do
echo "=== Testing $MODEL ==="
echo "$INPUT" | fabric --pattern "$PATTERN" --vendor GitHub --model "$MODEL"
echo ""
done
EOF
chmod +x test_models.sh
./test_models.sh
```
### Quick Test Without Setup
If you want to quickly test without running full setup, you can set the environment variable directly:
```bash
# Temporary test (this session only)
export GITHUB_API_KEY=github_pat_YOUR_TOKEN_HERE
# Test immediately
fabric --listmodels --vendor GitHub
```
This is useful for quick tests, but we recommend using `fabric --setup` for permanent configuration.
### Streaming for Long Responses
For long-form content, use streaming to see results as they generate:
```bash
cat long_article.txt | \
fabric --pattern summarize \
--vendor GitHub --model openai/gpt-4o-mini \
--stream
```
### Saving Token Usage
Monitor your usage to stay within rate limits:
```bash
# Create a simple usage tracker
echo "$(date): Used gpt-4.1 for analyze_claims" >> ~/.config/fabric/usage.log
# Check daily usage
grep "$(date +%Y-%m-%d)" ~/.config/fabric/usage.log | wc -l
```
### Environment-Based Configuration
Create different profiles for different use cases:
```bash
# Development profile (uses free GitHub Models)
cat > ~/.config/fabric/.env.dev << EOF
GITHUB_TOKEN=github_pat_dev_token_here
DEFAULT_VENDOR=GitHub
DEFAULT_MODEL=openai/gpt-4o-mini
EOF
# Production profile (uses paid OpenAI)
cat > ~/.config/fabric/.env.prod << EOF
OPENAI_API_KEY=sk-prod-key-here
DEFAULT_VENDOR=OpenAI
DEFAULT_MODEL=gpt-4
EOF
# Switch profiles
ln -sf ~/.config/fabric/.env.dev ~/.config/fabric/.env
```
---
## Additional Resources
### Official Documentation
- [GitHub Models Quickstart](https://docs.github.com/en/github-models/quickstart)
- [GitHub Models API Reference](https://docs.github.com/en/rest/models)
- [GitHub Models Marketplace](https://github.com/marketplace/models)
### Fabric Documentation
- [Fabric README](../README.md)
- [Contexts and Sessions Tutorial](./contexts-and-sessions-tutorial.md)
- [Using Speech-to-Text](./Using-Speech-To-Text.md)
### Community
- [Fabric GitHub Repository](https://github.com/danielmiessler/fabric)
- [Fabric Issues](https://github.com/danielmiessler/fabric/issues)
- [Fabric Discussions](https://github.com/danielmiessler/fabric/discussions)
---
## Summary
GitHub Models provides an excellent way to experiment with AI models through Fabric without managing multiple API keys or incurring costs. Key points:
✅ **Free to start**: No credit card required, 50-150 requests/day
✅ **Multiple providers**: OpenAI, Meta, Microsoft, DeepSeek, xAI
✅ **Simple setup**: Just one GitHub token via `fabric --setup`
✅ **Great for learning**: Try different models and patterns
✅ **Production path**: Can upgrade to paid tier when ready
### Quick Start Commands
```bash
# 1. Get GitHub token with models:read scope from:
# https://github.com/settings/tokens
# 2. Configure Fabric
fabric --setup
# Select [8] GitHub
# Paste your token when prompted
# 3. List available models
fabric --listmodels --vendor GitHub | grep gpt-4o
# 4. Try it out with gpt-4o-mini
echo "What is AI?" | fabric --vendor GitHub --model "gpt-4o-mini"
```
**Recommended starting point**: Use `gpt-4o-mini` for most patterns - it's fast, capable, and has generous rate limits (150 requests/day).
**Available Models**: `gpt-4o`, `gpt-4o-mini`, `Meta-Llama-3.1-8B-Instruct`, `Meta-Llama-3.1-70B-Instruct`, `Mistral-large-2407`, and more. Use `--listmodels` to see the complete list.
Happy prompting! 🚀

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@@ -0,0 +1,431 @@
// Package docs Code generated by swaggo/swag. DO NOT EDIT
package docs
import "github.com/swaggo/swag"
const docTemplate = `{
"schemes": {{ marshal .Schemes }},
"swagger": "2.0",
"info": {
"description": "{{escape .Description}}",
"title": "{{.Title}}",
"contact": {
"name": "Fabric Support",
"url": "https://github.com/danielmiessler/fabric"
},
"license": {
"name": "MIT",
"url": "https://opensource.org/licenses/MIT"
},
"version": "{{.Version}}"
},
"host": "{{.Host}}",
"basePath": "{{.BasePath}}",
"paths": {
"/chat": {
"post": {
"security": [
{
"ApiKeyAuth": []
}
],
"description": "Stream AI responses using Server-Sent Events (SSE)",
"consumes": [
"application/json"
],
"produces": [
"text/event-stream"
],
"tags": [
"chat"
],
"summary": "Stream chat completions",
"parameters": [
{
"description": "Chat request with prompts and options",
"name": "request",
"in": "body",
"required": true,
"schema": {
"$ref": "#/definitions/restapi.ChatRequest"
}
}
],
"responses": {
"200": {
"description": "Streaming response",
"schema": {
"$ref": "#/definitions/restapi.StreamResponse"
}
},
"400": {
"description": "Bad Request",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
}
}
},
"/models/names": {
"get": {
"security": [
{
"ApiKeyAuth": []
}
],
"description": "Get a list of all available AI models grouped by vendor",
"produces": [
"application/json"
],
"tags": [
"models"
],
"summary": "List all available models",
"responses": {
"200": {
"description": "Returns models (array) and vendors (map)",
"schema": {
"type": "object",
"additionalProperties": true
}
},
"500": {
"description": "Internal Server Error",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
}
}
},
"/patterns/{name}": {
"get": {
"security": [
{
"ApiKeyAuth": []
}
],
"description": "Retrieve a pattern by name",
"consumes": [
"application/json"
],
"produces": [
"application/json"
],
"tags": [
"patterns"
],
"summary": "Get a pattern",
"parameters": [
{
"type": "string",
"description": "Pattern name",
"name": "name",
"in": "path",
"required": true
}
],
"responses": {
"200": {
"description": "OK",
"schema": {
"$ref": "#/definitions/fsdb.Pattern"
}
},
"500": {
"description": "Internal Server Error",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
}
}
},
"/patterns/{name}/apply": {
"post": {
"security": [
{
"ApiKeyAuth": []
}
],
"description": "Apply a pattern with variable substitution",
"consumes": [
"application/json"
],
"produces": [
"application/json"
],
"tags": [
"patterns"
],
"summary": "Apply pattern with variables",
"parameters": [
{
"type": "string",
"description": "Pattern name",
"name": "name",
"in": "path",
"required": true
},
{
"description": "Pattern application request",
"name": "request",
"in": "body",
"required": true,
"schema": {
"$ref": "#/definitions/restapi.PatternApplyRequest"
}
}
],
"responses": {
"200": {
"description": "OK",
"schema": {
"$ref": "#/definitions/fsdb.Pattern"
}
},
"400": {
"description": "Bad Request",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
},
"500": {
"description": "Internal Server Error",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
}
}
}
},
"definitions": {
"domain.ThinkingLevel": {
"type": "string",
"enum": [
"off",
"low",
"medium",
"high"
],
"x-enum-varnames": [
"ThinkingOff",
"ThinkingLow",
"ThinkingMedium",
"ThinkingHigh"
]
},
"fsdb.Pattern": {
"type": "object",
"properties": {
"description": {
"type": "string"
},
"name": {
"type": "string"
},
"pattern": {
"type": "string"
}
}
},
"restapi.ChatRequest": {
"type": "object",
"properties": {
"audioFormat": {
"type": "string"
},
"audioOutput": {
"type": "boolean"
},
"frequencyPenalty": {
"type": "number",
"format": "float64"
},
"imageBackground": {
"type": "string"
},
"imageCompression": {
"type": "integer"
},
"imageFile": {
"type": "string"
},
"imageQuality": {
"type": "string"
},
"imageSize": {
"type": "string"
},
"language": {
"description": "Add Language field to bind from request",
"type": "string"
},
"maxTokens": {
"type": "integer"
},
"model": {
"type": "string"
},
"modelContextLength": {
"type": "integer"
},
"notification": {
"type": "boolean"
},
"notificationCommand": {
"type": "string"
},
"presencePenalty": {
"type": "number",
"format": "float64"
},
"prompts": {
"type": "array",
"items": {
"$ref": "#/definitions/restapi.PromptRequest"
}
},
"raw": {
"type": "boolean"
},
"search": {
"type": "boolean"
},
"searchLocation": {
"type": "string"
},
"seed": {
"type": "integer"
},
"suppressThink": {
"type": "boolean"
},
"temperature": {
"type": "number",
"format": "float64"
},
"thinkEndTag": {
"type": "string"
},
"thinkStartTag": {
"type": "string"
},
"thinking": {
"$ref": "#/definitions/domain.ThinkingLevel"
},
"topP": {
"type": "number",
"format": "float64"
},
"voice": {
"type": "string"
}
}
},
"restapi.PatternApplyRequest": {
"type": "object",
"properties": {
"input": {
"type": "string"
},
"variables": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
},
"restapi.PromptRequest": {
"type": "object",
"properties": {
"contextName": {
"type": "string"
},
"model": {
"type": "string"
},
"patternName": {
"type": "string"
},
"strategyName": {
"description": "Optional strategy name",
"type": "string"
},
"userInput": {
"type": "string"
},
"variables": {
"description": "Pattern variables",
"type": "object",
"additionalProperties": {
"type": "string"
}
},
"vendor": {
"type": "string"
}
}
},
"restapi.StreamResponse": {
"type": "object",
"properties": {
"content": {
"description": "The actual content",
"type": "string"
},
"format": {
"description": "\"markdown\", \"mermaid\", \"plain\"",
"type": "string"
},
"type": {
"description": "\"content\", \"error\", \"complete\"",
"type": "string"
}
}
}
},
"securityDefinitions": {
"ApiKeyAuth": {
"type": "apiKey",
"name": "X-API-Key",
"in": "header"
}
}
}`
// SwaggerInfo holds exported Swagger Info so clients can modify it
var SwaggerInfo = &swag.Spec{
Version: "1.0",
Host: "localhost:8080",
BasePath: "/",
Schemes: []string{},
Title: "Fabric REST API",
Description: "REST API for Fabric AI augmentation framework. Provides endpoints for chat completions, pattern management, contexts, sessions, and more.",
InfoInstanceName: "swagger",
SwaggerTemplate: docTemplate,
LeftDelim: "{{",
RightDelim: "}}",
}
func init() {
swag.Register(SwaggerInfo.InstanceName(), SwaggerInfo)
}

487
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@@ -0,0 +1,487 @@
# Fabric REST API
Fabric's REST API provides HTTP access to all core functionality: chat completions, pattern management, contexts, sessions, and more.
## Quick Start
Start the server:
```bash
fabric --serve
```
The server runs on `http://localhost:8080` by default.
Test it:
```bash
curl http://localhost:8080/patterns/names
```
## Interactive API Documentation
Fabric includes Swagger/OpenAPI documentation with an interactive UI:
- **Swagger UI**: [http://localhost:8080/swagger/index.html](http://localhost:8080/swagger/index.html)
- **OpenAPI JSON**: [http://localhost:8080/swagger/doc.json](http://localhost:8080/swagger/doc.json)
- **OpenAPI YAML**: [http://localhost:8080/swagger/swagger.yaml](http://localhost:8080/swagger/swagger.yaml)
The Swagger UI lets you:
- Browse all available endpoints
- View request/response schemas
- Test API calls directly in your browser
- See authentication requirements
**Note:** Swagger documentation endpoints are publicly accessible even when API key authentication is enabled. Only the actual API endpoints require authentication
## Server Options
| Flag | Description | Default |
| ------ | ------------- | --------- |
| `--serve` | Start the REST API server | - |
| `--address` | Server address and port | `:8080` |
| `--api-key` | Enable API key authentication | (none) |
Example with custom configuration:
```bash
fabric --serve --address :9090 --api-key my_secret_key
```
## Authentication
When you set an API key with `--api-key`, all requests must include:
```http
X-API-Key: your-api-key-here
```
Example:
```bash
curl -H "X-API-Key: my_secret_key" http://localhost:8080/patterns/names
```
Without an API key, the server accepts all requests and logs a warning.
## Endpoints
### Chat Completions
Stream AI responses using Server-Sent Events (SSE).
**Endpoint:** `POST /chat`
**Request:**
```json
{
"prompts": [
{
"userInput": "Explain quantum computing",
"vendor": "openai",
"model": "gpt-4o",
"patternName": "explain",
"contextName": "",
"strategyName": "",
"variables": {}
}
],
"language": "en",
"temperature": 0.7,
"topP": 0.9,
"frequencyPenalty": 0,
"presencePenalty": 0,
"thinking": 0
}
```
**Prompt Fields:**
| Field | Required | Default | Description |
| ------- | ---------- | --------- | ------------- |
| `userInput` | **Yes** | - | Your message or question |
| `vendor` | **Yes** | - | AI provider: `openai`, `anthropic`, `gemini`, `ollama`, etc. |
| `model` | **Yes** | - | Model name: `gpt-4o`, `claude-sonnet-4.5`, `gemini-2.0-flash-exp`, etc. |
| `patternName` | No | `""` | Pattern to apply (from `~/.config/fabric/patterns/`) |
| `contextName` | No | `""` | Context to prepend (from `~/.config/fabric/contexts/`) |
| `strategyName` | No | `""` | Strategy to use (from `~/.config/fabric/strategies/`) |
| `variables` | No | `{}` | Variable substitutions for patterns (e.g., `{"role": "expert"}`) |
**Chat Options:**
| Field | Required | Default | Description |
| ------- | ---------- | --------- | ------------- |
| `language` | No | `"en"` | Language code for responses |
| `temperature` | No | `0.7` | Randomness (0.0-1.0) |
| `topP` | No | `0.9` | Nucleus sampling (0.0-1.0) |
| `frequencyPenalty` | No | `0.0` | Reduce repetition (-2.0 to 2.0) |
| `presencePenalty` | No | `0.0` | Encourage new topics (-2.0 to 2.0) |
| `thinking` | No | `0` | Reasoning level (0=off, or numeric for tokens) |
**Response:**
Server-Sent Events stream with `Content-Type: text/readystream`. Each line contains JSON:
```json
{"type": "content", "format": "markdown", "content": "Quantum computing uses..."}
{"type": "content", "format": "markdown", "content": " quantum mechanics..."}
{"type": "complete", "format": "markdown", "content": ""}
```
**Types:**
- `content` - Response chunk
- `error` - Error message
- `complete` - Stream finished
**Formats:**
- `markdown` - Standard text
- `mermaid` - Mermaid diagram
- `plain` - Plain text
**Example:**
```bash
curl -X POST http://localhost:8080/chat \
-H "Content-Type: application/json" \
-d '{
"prompts": [{
"userInput": "What is Fabric?",
"vendor": "openai",
"model": "gpt-4o",
"patternName": "explain"
}]
}'
```
### Patterns
Manage reusable AI prompts.
| Method | Endpoint | Description |
| -------- | ---------- | ------------- |
| `GET` | `/patterns/names` | List all pattern names |
| `GET` | `/patterns/:name` | Get pattern content |
| `GET` | `/patterns/exists/:name` | Check if pattern exists |
| `POST` | `/patterns/:name` | Create or update pattern |
| `DELETE` | `/patterns/:name` | Delete pattern |
| `PUT` | `/patterns/rename/:oldName/:newName` | Rename pattern |
| `POST` | `/patterns/:name/apply` | Apply pattern with variables |
**Example - Get pattern:**
```bash
curl http://localhost:8080/patterns/summarize
```
**Example - Apply pattern with variables:**
```bash
curl -X POST http://localhost:8080/patterns/translate/apply \
-H "Content-Type: application/json" \
-d '{
"input": "Hello world",
"variables": {"lang_code": "es"}
}'
```
**Example - Create pattern:**
```bash
curl -X POST http://localhost:8080/patterns/my_custom_pattern \
-H "Content-Type: text/plain" \
-d "You are an expert in explaining complex topics simply..."
```
### Contexts
Manage context snippets that prepend to prompts.
| Method | Endpoint | Description |
| -------- | ---------- | ------------- |
| `GET` | `/contexts/names` | List all context names |
| `GET` | `/contexts/:name` | Get context content |
| `GET` | `/contexts/exists/:name` | Check if context exists |
| `POST` | `/contexts/:name` | Create or update context |
| `DELETE` | `/contexts/:name` | Delete context |
| `PUT` | `/contexts/rename/:oldName/:newName` | Rename context |
### Sessions
Manage chat conversation history.
| Method | Endpoint | Description |
| -------- | ---------- | ------------- |
| `GET` | `/sessions/names` | List all session names |
| `GET` | `/sessions/:name` | Get session messages (JSON array) |
| `GET` | `/sessions/exists/:name` | Check if session exists |
| `POST` | `/sessions/:name` | Save session messages |
| `DELETE` | `/sessions/:name` | Delete session |
| `PUT` | `/sessions/rename/:oldName/:newName` | Rename session |
### Models
List available AI models.
**Endpoint:** `GET /models/names`
**Response:**
```json
{
"models": ["gpt-4o", "gpt-4o-mini", "claude-sonnet-4.5", "gemini-2.0-flash-exp"],
"vendors": {
"openai": ["gpt-4o", "gpt-4o-mini"],
"anthropic": ["claude-sonnet-4.5", "claude-opus-4.5"],
"gemini": ["gemini-2.0-flash-exp", "gemini-2.0-flash-thinking-exp"]
}
}
```
### Strategies
List available prompt strategies (Chain of Thought, etc.).
**Endpoint:** `GET /strategies`
**Response:**
```json
[
{
"name": "chain_of_thought",
"description": "Think step by step",
"prompt": "Let's think through this step by step..."
}
]
```
### YouTube Transcripts
Extract transcripts from YouTube videos.
**Endpoint:** `POST /youtube/transcript`
**Request:**
```json
{
"url": "https://youtube.com/watch?v=dQw4w9WgXcQ",
"timestamps": false
}
```
**Response:**
```json
{
"title": "Video Title",
"transcript": "Full transcript text..."
}
```
**Example:**
```bash
curl -X POST http://localhost:8080/youtube/transcript \
-H "Content-Type: application/json" \
-d '{"url": "https://youtube.com/watch?v=dQw4w9WgXcQ", "timestamps": true}'
```
### Configuration
Manage API keys and environment settings.
**Get configuration:**
`GET /config`
Returns API keys and URLs for all configured vendors.
**Update configuration:**
`POST /config/update`
```json
{
"OPENAI_API_KEY": "sk-...",
"ANTHROPIC_API_KEY": "sk-ant-..."
}
```
Updates `~/.config/fabric/.env` with new values.
## Complete Workflow Examples
### Example: Summarize a YouTube Video
This example shows how to extract a YouTube transcript and summarize it using the `youtube_summary` pattern. This requires two API calls:
#### Step 1: Extract the transcript
```bash
curl -X POST http://localhost:8080/youtube/transcript \
-H "Content-Type: application/json" \
-d '{
"url": "https://youtube.com/watch?v=dQw4w9WgXcQ",
"timestamps": false
}' > transcript.json
```
Response:
```json
{
"title": "Rick Astley - Never Gonna Give You Up (Official Video)",
"transcript": "We're no strangers to love. You know the rules and so do I..."
}
```
#### Step 2: Summarize the transcript
Extract the transcript text and send it to the chat endpoint with the `youtube_summary` pattern:
```bash
# Extract transcript text from JSON
TRANSCRIPT=$(cat transcript.json | jq -r '.transcript')
# Send to chat endpoint with pattern
curl -X POST http://localhost:8080/chat \
-H "Content-Type: application/json" \
-d "{
\"prompts\": [{
\"userInput\": \"$TRANSCRIPT\",
\"vendor\": \"openai\",
\"model\": \"gpt-4o\",
\"patternName\": \"youtube_summary\"
}]
}"
```
#### Combined one-liner (using jq)
```bash
curl -s -X POST http://localhost:8080/youtube/transcript \
-H "Content-Type: application/json" \
-d '{"url": "https://youtube.com/watch?v=dQw4w9WgXcQ", "timestamps": false}' | \
jq -r '.transcript' | \
xargs -I {} curl -X POST http://localhost:8080/chat \
-H "Content-Type: application/json" \
-d "{\"prompts\":[{\"userInput\":\"{}\",\"vendor\":\"openai\",\"model\":\"gpt-4o\",\"patternName\":\"youtube_summary\"}]}"
```
#### Alternative: Using a script
```bash
#!/bin/bash
YOUTUBE_URL="https://youtube.com/watch?v=dQw4w9WgXcQ"
API_BASE="http://localhost:8080"
# Step 1: Get transcript
echo "Extracting transcript..."
TRANSCRIPT=$(curl -s -X POST "$API_BASE/youtube/transcript" \
-H "Content-Type: application/json" \
-d "{\"url\":\"$YOUTUBE_URL\",\"timestamps\":false}" | jq -r '.transcript')
# Step 2: Summarize with pattern
echo "Generating summary..."
curl -X POST "$API_BASE/chat" \
-H "Content-Type: application/json" \
-d "{
\"prompts\": [{
\"userInput\": $(echo "$TRANSCRIPT" | jq -Rs .),
\"vendor\": \"openai\",
\"model\": \"gpt-4o\",
\"patternName\": \"youtube_summary\"
}]
}"
```
#### Comparison with CLI
The CLI combines these steps automatically:
```bash
# CLI version (single command)
fabric -y "https://youtube.com/watch?v=dQw4w9WgXcQ" --pattern youtube_summary
```
The API provides more flexibility by separating transcript extraction and summarization, allowing you to:
- Extract the transcript once and process it multiple ways
- Apply different patterns to the same transcript
- Store the transcript for later use
- Use different models or vendors for summarization
## Docker Usage
Run the server in Docker:
```bash
# Setup (first time)
mkdir -p $HOME/.fabric-config
docker run --rm -it \
-v $HOME/.fabric-config:/root/.config/fabric \
kayvan/fabric:latest --setup
# Start server
docker run --rm -it \
-p 8080:8080 \
-v $HOME/.fabric-config:/root/.config/fabric \
kayvan/fabric:latest --serve
# With authentication
docker run --rm -it \
-p 8080:8080 \
-v $HOME/.fabric-config:/root/.config/fabric \
kayvan/fabric:latest --serve --api-key my_secret_key
```
## Ollama Compatibility Mode
Fabric can emulate Ollama's API endpoints:
```bash
fabric --serveOllama --address :11434
```
This mode provides:
- `GET /api/tags` - Lists patterns as models
- `GET /api/version` - Server version
- `POST /api/chat` - Ollama-compatible chat endpoint
## Error Handling
All endpoints return standard HTTP status codes:
- `200 OK` - Success
- `400 Bad Request` - Invalid input
- `401 Unauthorized` - Missing or invalid API key
- `404 Not Found` - Resource not found
- `500 Internal Server Error` - Server error
Error responses include JSON with details:
```json
{
"error": "Pattern not found: nonexistent"
}
```
## Rate Limiting
The server does not implement rate limiting. When deploying publicly, use a reverse proxy (nginx, Caddy) with rate limiting enabled.
## CORS
The server sets CORS headers for local development:
```http
Access-Control-Allow-Origin: http://localhost:5173
```
For production, configure CORS through a reverse proxy.

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@@ -0,0 +1,407 @@
{
"swagger": "2.0",
"info": {
"description": "REST API for Fabric AI augmentation framework. Provides endpoints for chat completions, pattern management, contexts, sessions, and more.",
"title": "Fabric REST API",
"contact": {
"name": "Fabric Support",
"url": "https://github.com/danielmiessler/fabric"
},
"license": {
"name": "MIT",
"url": "https://opensource.org/licenses/MIT"
},
"version": "1.0"
},
"host": "localhost:8080",
"basePath": "/",
"paths": {
"/chat": {
"post": {
"security": [
{
"ApiKeyAuth": []
}
],
"description": "Stream AI responses using Server-Sent Events (SSE)",
"consumes": [
"application/json"
],
"produces": [
"text/event-stream"
],
"tags": [
"chat"
],
"summary": "Stream chat completions",
"parameters": [
{
"description": "Chat request with prompts and options",
"name": "request",
"in": "body",
"required": true,
"schema": {
"$ref": "#/definitions/restapi.ChatRequest"
}
}
],
"responses": {
"200": {
"description": "Streaming response",
"schema": {
"$ref": "#/definitions/restapi.StreamResponse"
}
},
"400": {
"description": "Bad Request",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
}
}
},
"/models/names": {
"get": {
"security": [
{
"ApiKeyAuth": []
}
],
"description": "Get a list of all available AI models grouped by vendor",
"produces": [
"application/json"
],
"tags": [
"models"
],
"summary": "List all available models",
"responses": {
"200": {
"description": "Returns models (array) and vendors (map)",
"schema": {
"type": "object",
"additionalProperties": true
}
},
"500": {
"description": "Internal Server Error",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
}
}
},
"/patterns/{name}": {
"get": {
"security": [
{
"ApiKeyAuth": []
}
],
"description": "Retrieve a pattern by name",
"consumes": [
"application/json"
],
"produces": [
"application/json"
],
"tags": [
"patterns"
],
"summary": "Get a pattern",
"parameters": [
{
"type": "string",
"description": "Pattern name",
"name": "name",
"in": "path",
"required": true
}
],
"responses": {
"200": {
"description": "OK",
"schema": {
"$ref": "#/definitions/fsdb.Pattern"
}
},
"500": {
"description": "Internal Server Error",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
}
}
},
"/patterns/{name}/apply": {
"post": {
"security": [
{
"ApiKeyAuth": []
}
],
"description": "Apply a pattern with variable substitution",
"consumes": [
"application/json"
],
"produces": [
"application/json"
],
"tags": [
"patterns"
],
"summary": "Apply pattern with variables",
"parameters": [
{
"type": "string",
"description": "Pattern name",
"name": "name",
"in": "path",
"required": true
},
{
"description": "Pattern application request",
"name": "request",
"in": "body",
"required": true,
"schema": {
"$ref": "#/definitions/restapi.PatternApplyRequest"
}
}
],
"responses": {
"200": {
"description": "OK",
"schema": {
"$ref": "#/definitions/fsdb.Pattern"
}
},
"400": {
"description": "Bad Request",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
},
"500": {
"description": "Internal Server Error",
"schema": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
}
}
}
},
"definitions": {
"domain.ThinkingLevel": {
"type": "string",
"enum": [
"off",
"low",
"medium",
"high"
],
"x-enum-varnames": [
"ThinkingOff",
"ThinkingLow",
"ThinkingMedium",
"ThinkingHigh"
]
},
"fsdb.Pattern": {
"type": "object",
"properties": {
"description": {
"type": "string"
},
"name": {
"type": "string"
},
"pattern": {
"type": "string"
}
}
},
"restapi.ChatRequest": {
"type": "object",
"properties": {
"audioFormat": {
"type": "string"
},
"audioOutput": {
"type": "boolean"
},
"frequencyPenalty": {
"type": "number",
"format": "float64"
},
"imageBackground": {
"type": "string"
},
"imageCompression": {
"type": "integer"
},
"imageFile": {
"type": "string"
},
"imageQuality": {
"type": "string"
},
"imageSize": {
"type": "string"
},
"language": {
"description": "Add Language field to bind from request",
"type": "string"
},
"maxTokens": {
"type": "integer"
},
"model": {
"type": "string"
},
"modelContextLength": {
"type": "integer"
},
"notification": {
"type": "boolean"
},
"notificationCommand": {
"type": "string"
},
"presencePenalty": {
"type": "number",
"format": "float64"
},
"prompts": {
"type": "array",
"items": {
"$ref": "#/definitions/restapi.PromptRequest"
}
},
"raw": {
"type": "boolean"
},
"search": {
"type": "boolean"
},
"searchLocation": {
"type": "string"
},
"seed": {
"type": "integer"
},
"suppressThink": {
"type": "boolean"
},
"temperature": {
"type": "number",
"format": "float64"
},
"thinkEndTag": {
"type": "string"
},
"thinkStartTag": {
"type": "string"
},
"thinking": {
"$ref": "#/definitions/domain.ThinkingLevel"
},
"topP": {
"type": "number",
"format": "float64"
},
"voice": {
"type": "string"
}
}
},
"restapi.PatternApplyRequest": {
"type": "object",
"properties": {
"input": {
"type": "string"
},
"variables": {
"type": "object",
"additionalProperties": {
"type": "string"
}
}
}
},
"restapi.PromptRequest": {
"type": "object",
"properties": {
"contextName": {
"type": "string"
},
"model": {
"type": "string"
},
"patternName": {
"type": "string"
},
"strategyName": {
"description": "Optional strategy name",
"type": "string"
},
"userInput": {
"type": "string"
},
"variables": {
"description": "Pattern variables",
"type": "object",
"additionalProperties": {
"type": "string"
}
},
"vendor": {
"type": "string"
}
}
},
"restapi.StreamResponse": {
"type": "object",
"properties": {
"content": {
"description": "The actual content",
"type": "string"
},
"format": {
"description": "\"markdown\", \"mermaid\", \"plain\"",
"type": "string"
},
"type": {
"description": "\"content\", \"error\", \"complete\"",
"type": "string"
}
}
}
},
"securityDefinitions": {
"ApiKeyAuth": {
"type": "apiKey",
"name": "X-API-Key",
"in": "header"
}
}
}

270
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@@ -0,0 +1,270 @@
basePath: /
definitions:
domain.ThinkingLevel:
enum:
- "off"
- low
- medium
- high
type: string
x-enum-varnames:
- ThinkingOff
- ThinkingLow
- ThinkingMedium
- ThinkingHigh
fsdb.Pattern:
properties:
description:
type: string
name:
type: string
pattern:
type: string
type: object
restapi.ChatRequest:
properties:
audioFormat:
type: string
audioOutput:
type: boolean
frequencyPenalty:
format: float64
type: number
imageBackground:
type: string
imageCompression:
type: integer
imageFile:
type: string
imageQuality:
type: string
imageSize:
type: string
language:
description: Add Language field to bind from request
type: string
maxTokens:
type: integer
model:
type: string
modelContextLength:
type: integer
notification:
type: boolean
notificationCommand:
type: string
presencePenalty:
format: float64
type: number
prompts:
items:
$ref: '#/definitions/restapi.PromptRequest'
type: array
raw:
type: boolean
search:
type: boolean
searchLocation:
type: string
seed:
type: integer
suppressThink:
type: boolean
temperature:
format: float64
type: number
thinkEndTag:
type: string
thinkStartTag:
type: string
thinking:
$ref: '#/definitions/domain.ThinkingLevel'
topP:
format: float64
type: number
voice:
type: string
type: object
restapi.PatternApplyRequest:
properties:
input:
type: string
variables:
additionalProperties:
type: string
type: object
type: object
restapi.PromptRequest:
properties:
contextName:
type: string
model:
type: string
patternName:
type: string
strategyName:
description: Optional strategy name
type: string
userInput:
type: string
variables:
additionalProperties:
type: string
description: Pattern variables
type: object
vendor:
type: string
type: object
restapi.StreamResponse:
properties:
content:
description: The actual content
type: string
format:
description: '"markdown", "mermaid", "plain"'
type: string
type:
description: '"content", "error", "complete"'
type: string
type: object
host: localhost:8080
info:
contact:
name: Fabric Support
url: https://github.com/danielmiessler/fabric
description: REST API for Fabric AI augmentation framework. Provides endpoints for
chat completions, pattern management, contexts, sessions, and more.
license:
name: MIT
url: https://opensource.org/licenses/MIT
title: Fabric REST API
version: "1.0"
paths:
/chat:
post:
consumes:
- application/json
description: Stream AI responses using Server-Sent Events (SSE)
parameters:
- description: Chat request with prompts and options
in: body
name: request
required: true
schema:
$ref: '#/definitions/restapi.ChatRequest'
produces:
- text/event-stream
responses:
"200":
description: Streaming response
schema:
$ref: '#/definitions/restapi.StreamResponse'
"400":
description: Bad Request
schema:
additionalProperties:
type: string
type: object
security:
- ApiKeyAuth: []
summary: Stream chat completions
tags:
- chat
/models/names:
get:
description: Get a list of all available AI models grouped by vendor
produces:
- application/json
responses:
"200":
description: Returns models (array) and vendors (map)
schema:
additionalProperties: true
type: object
"500":
description: Internal Server Error
schema:
additionalProperties:
type: string
type: object
security:
- ApiKeyAuth: []
summary: List all available models
tags:
- models
/patterns/{name}:
get:
consumes:
- application/json
description: Retrieve a pattern by name
parameters:
- description: Pattern name
in: path
name: name
required: true
type: string
produces:
- application/json
responses:
"200":
description: OK
schema:
$ref: '#/definitions/fsdb.Pattern'
"500":
description: Internal Server Error
schema:
additionalProperties:
type: string
type: object
security:
- ApiKeyAuth: []
summary: Get a pattern
tags:
- patterns
/patterns/{name}/apply:
post:
consumes:
- application/json
description: Apply a pattern with variable substitution
parameters:
- description: Pattern name
in: path
name: name
required: true
type: string
- description: Pattern application request
in: body
name: request
required: true
schema:
$ref: '#/definitions/restapi.PatternApplyRequest'
produces:
- application/json
responses:
"200":
description: OK
schema:
$ref: '#/definitions/fsdb.Pattern'
"400":
description: Bad Request
schema:
additionalProperties:
type: string
type: object
"500":
description: Internal Server Error
schema:
additionalProperties:
type: string
type: object
security:
- ApiKeyAuth: []
summary: Apply pattern with variables
tags:
- patterns
securityDefinitions:
ApiKeyAuth:
in: header
name: X-API-Key
type: apiKey
swagger: "2.0"

24
flake.lock generated
View File

@@ -5,11 +5,11 @@
"systems": "systems"
},
"locked": {
"lastModified": 1694529238,
"narHash": "sha256-zsNZZGTGnMOf9YpHKJqMSsa0dXbfmxeoJ7xHlrt+xmY=",
"lastModified": 1731533236,
"narHash": "sha256-l0KFg5HjrsfsO/JpG+r7fRrqm12kzFHyUHqHCVpMMbI=",
"owner": "numtide",
"repo": "flake-utils",
"rev": "ff7b65b44d01cf9ba6a71320833626af21126384",
"rev": "11707dc2f618dd54ca8739b309ec4fc024de578b",
"type": "github"
},
"original": {
@@ -26,11 +26,11 @@
]
},
"locked": {
"lastModified": 1742209644,
"narHash": "sha256-jMy1XqXqD0/tJprEbUmKilTkvbDY/C0ZGSsJJH4TNCE=",
"lastModified": 1763982521,
"narHash": "sha256-ur4QIAHwgFc0vXiaxn5No/FuZicxBr2p0gmT54xZkUQ=",
"owner": "nix-community",
"repo": "gomod2nix",
"rev": "8f3534eb8f6c5c3fce799376dc3b91bae6b11884",
"rev": "02e63a239d6eabd595db56852535992c898eba72",
"type": "github"
},
"original": {
@@ -41,11 +41,11 @@
},
"nixpkgs": {
"locked": {
"lastModified": 1745234285,
"narHash": "sha256-GfpyMzxwkfgRVN0cTGQSkTC0OHhEkv3Jf6Tcjm//qZ0=",
"lastModified": 1765472234,
"narHash": "sha256-9VvC20PJPsleGMewwcWYKGzDIyjckEz8uWmT0vCDYK0=",
"owner": "nixos",
"repo": "nixpkgs",
"rev": "c11863f1e964833214b767f4a369c6e6a7aba141",
"rev": "2fbfb1d73d239d2402a8fe03963e37aab15abe8b",
"type": "github"
},
"original": {
@@ -100,11 +100,11 @@
]
},
"locked": {
"lastModified": 1744961264,
"narHash": "sha256-aRmUh0AMwcbdjJHnytg1e5h5ECcaWtIFQa6d9gI85AI=",
"lastModified": 1762938485,
"narHash": "sha256-AlEObg0syDl+Spi4LsZIBrjw+snSVU4T8MOeuZJUJjM=",
"owner": "numtide",
"repo": "treefmt-nix",
"rev": "8d404a69efe76146368885110f29a2ca3700bee6",
"rev": "5b4ee75aeefd1e2d5a1cc43cf6ba65eba75e83e4",
"type": "github"
},
"original": {

56
go.mod
View File

@@ -3,14 +3,14 @@ module github.com/danielmiessler/fabric
go 1.25.1
require (
github.com/anthropics/anthropic-sdk-go v1.16.0
github.com/anthropics/anthropic-sdk-go v1.19.0
github.com/atotto/clipboard v0.1.4
github.com/aws/aws-sdk-go-v2 v1.39.0
github.com/aws/aws-sdk-go-v2/config v1.31.8
github.com/aws/aws-sdk-go-v2/service/bedrock v1.46.1
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.40.1
github.com/gabriel-vasile/mimetype v1.4.9
github.com/gin-gonic/gin v1.10.1
github.com/gabriel-vasile/mimetype v1.4.12
github.com/gin-gonic/gin v1.11.0
github.com/go-git/go-git/v5 v5.16.2
github.com/go-shiori/go-readability v0.0.0-20250217085726-9f5bf5ca7612
github.com/google/go-github/v66 v66.0.0
@@ -21,15 +21,18 @@ require (
github.com/mattn/go-sqlite3 v1.14.28
github.com/nicksnyder/go-i18n/v2 v2.6.0
github.com/ollama/ollama v0.11.7
github.com/openai/openai-go v1.8.2
github.com/openai/openai-go v1.12.0
github.com/otiai10/copy v1.14.1
github.com/pkg/errors v0.9.1
github.com/samber/lo v1.50.0
github.com/sgaunet/perplexity-go/v2 v2.8.0
github.com/spf13/cobra v1.9.1
github.com/stretchr/testify v1.11.1
github.com/swaggo/files v1.0.1
github.com/swaggo/gin-swagger v1.6.1
github.com/swaggo/swag v1.16.6
golang.org/x/oauth2 v0.30.0
golang.org/x/text v0.28.0
golang.org/x/text v0.32.0
google.golang.org/api v0.247.0
gopkg.in/yaml.v3 v3.0.1
)
@@ -37,8 +40,27 @@ require (
require (
github.com/Azure/azure-sdk-for-go/sdk/azcore v1.19.1 // indirect
github.com/Azure/azure-sdk-for-go/sdk/internal v1.11.2 // indirect
github.com/KyleBanks/depth v1.2.1 // indirect
github.com/bytedance/gopkg v0.1.3 // indirect
github.com/go-openapi/jsonpointer v0.22.4 // indirect
github.com/go-openapi/jsonreference v0.21.4 // indirect
github.com/go-openapi/spec v0.22.2 // indirect
github.com/go-openapi/swag/conv v0.25.4 // indirect
github.com/go-openapi/swag/jsonname v0.25.4 // indirect
github.com/go-openapi/swag/jsonutils v0.25.4 // indirect
github.com/go-openapi/swag/loading v0.25.4 // indirect
github.com/go-openapi/swag/stringutils v0.25.4 // indirect
github.com/go-openapi/swag/typeutils v0.25.4 // indirect
github.com/go-openapi/swag/yamlutils v0.25.4 // indirect
github.com/goccy/go-yaml v1.19.1 // indirect
github.com/google/go-cmp v0.7.0 // indirect
github.com/gorilla/websocket v1.5.3 // indirect
github.com/quic-go/qpack v0.6.0 // indirect
github.com/quic-go/quic-go v0.57.1 // indirect
go.uber.org/mock v0.6.0 // indirect
go.yaml.in/yaml/v3 v3.0.4 // indirect
golang.org/x/mod v0.31.0 // indirect
golang.org/x/tools v0.40.0 // indirect
)
require (
@@ -63,10 +85,10 @@ require (
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.34.4 // indirect
github.com/aws/aws-sdk-go-v2/service/sts v1.38.4 // indirect
github.com/aws/smithy-go v1.23.0 // indirect
github.com/bytedance/sonic v1.13.3 // indirect
github.com/bytedance/sonic/loader v0.2.4 // indirect
github.com/bytedance/sonic v1.14.2 // indirect
github.com/bytedance/sonic/loader v0.4.0 // indirect
github.com/cloudflare/circl v1.6.1 // indirect
github.com/cloudwego/base64x v0.1.5 // indirect
github.com/cloudwego/base64x v0.1.6 // indirect
github.com/coder/websocket v1.8.13 // indirect
github.com/cyphar/filepath-securejoin v0.4.1 // indirect
github.com/davecgh/go-spew v1.1.2-0.20180830191138-d8f796af33cc // indirect
@@ -79,7 +101,7 @@ require (
github.com/go-logr/stdr v1.2.2 // indirect
github.com/go-playground/locales v0.14.1 // indirect
github.com/go-playground/universal-translator v0.18.1 // indirect
github.com/go-playground/validator/v10 v10.26.0 // indirect
github.com/go-playground/validator/v10 v10.29.0 // indirect
github.com/go-shiori/dom v0.0.0-20230515143342-73569d674e1c // indirect
github.com/goccy/go-json v0.10.5 // indirect
github.com/gogs/chardet v0.0.0-20211120154057-b7413eaefb8f // indirect
@@ -93,7 +115,7 @@ require (
github.com/jbenet/go-context v0.0.0-20150711004518-d14ea06fba99 // indirect
github.com/json-iterator/go v1.1.12 // indirect
github.com/kevinburke/ssh_config v1.2.0 // indirect
github.com/klauspost/cpuid/v2 v2.2.10 // indirect
github.com/klauspost/cpuid/v2 v2.3.0 // indirect
github.com/leodido/go-urn v1.4.0 // indirect
github.com/mattn/go-isatty v0.0.20 // indirect
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect
@@ -110,23 +132,23 @@ require (
github.com/tidwall/pretty v1.2.1 // indirect
github.com/tidwall/sjson v1.2.5 // indirect
github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
github.com/ugorji/go/codec v1.2.14 // indirect
github.com/ugorji/go/codec v1.3.1 // indirect
github.com/xanzy/ssh-agent v0.3.3 // indirect
go.opentelemetry.io/auto/sdk v1.1.0 // indirect
go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp v0.61.0 // indirect
go.opentelemetry.io/otel v1.36.0 // indirect
go.opentelemetry.io/otel/metric v1.36.0 // indirect
go.opentelemetry.io/otel/trace v1.36.0 // indirect
golang.org/x/arch v0.18.0 // indirect
golang.org/x/crypto v0.41.0 // indirect
golang.org/x/arch v0.23.0 // indirect
golang.org/x/crypto v0.46.0 // indirect
golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b // indirect
golang.org/x/net v0.43.0 // indirect
golang.org/x/sync v0.16.0 // indirect
golang.org/x/sys v0.35.0 // indirect
golang.org/x/net v0.48.0 // indirect
golang.org/x/sync v0.19.0 // indirect
golang.org/x/sys v0.39.0 // indirect
google.golang.org/genai v1.17.0
google.golang.org/genproto/googleapis/api v0.0.0-20250818200422-3122310a409c // indirect
google.golang.org/genproto/googleapis/rpc v0.0.0-20250818200422-3122310a409c // indirect
google.golang.org/grpc v1.74.2 // indirect
google.golang.org/protobuf v1.36.7 // indirect
google.golang.org/protobuf v1.36.11 // indirect
gopkg.in/warnings.v0 v0.1.2 // indirect
)

137
go.sum
View File

@@ -18,6 +18,8 @@ github.com/AzureAD/microsoft-authentication-library-for-go v1.4.2 h1:oygO0locgZJ
github.com/AzureAD/microsoft-authentication-library-for-go v1.4.2/go.mod h1:wP83P5OoQ5p6ip3ScPr0BAq0BvuPAvacpEuSzyouqAI=
github.com/BurntSushi/toml v1.5.0 h1:W5quZX/G/csjUnuI8SUYlsHs9M38FC7znL0lIO+DvMg=
github.com/BurntSushi/toml v1.5.0/go.mod h1:ukJfTF/6rtPPRCnwkur4qwRxa8vTRFBF0uk2lLoLwho=
github.com/KyleBanks/depth v1.2.1 h1:5h8fQADFrWtarTdtDudMmGsC7GPbOAu6RVB3ffsVFHc=
github.com/KyleBanks/depth v1.2.1/go.mod h1:jzSb9d0L43HxTQfT+oSA1EEp2q+ne2uh6XgeJcm8brE=
github.com/Microsoft/go-winio v0.5.2/go.mod h1:WpS1mjBmmwHBEWmogvA2mj8546UReBk4v8QkMxJ6pZY=
github.com/Microsoft/go-winio v0.6.2 h1:F2VQgta7ecxGYO8k3ZZz3RS8fVIXVxONVUPlNERoyfY=
github.com/Microsoft/go-winio v0.6.2/go.mod h1:yd8OoFMLzJbo9gZq8j5qaps8bJ9aShtEA8Ipt1oGCvU=
@@ -27,8 +29,8 @@ github.com/andybalholm/cascadia v1.3.3 h1:AG2YHrzJIm4BZ19iwJ/DAua6Btl3IwJX+VI4kk
github.com/andybalholm/cascadia v1.3.3/go.mod h1:xNd9bqTn98Ln4DwST8/nG+H0yuB8Hmgu1YHNnWw0GeA=
github.com/anmitsu/go-shlex v0.0.0-20200514113438-38f4b401e2be h1:9AeTilPcZAjCFIImctFaOjnTIavg87rW78vTPkQqLI8=
github.com/anmitsu/go-shlex v0.0.0-20200514113438-38f4b401e2be/go.mod h1:ySMOLuWl6zY27l47sB3qLNK6tF2fkHG55UZxx8oIVo4=
github.com/anthropics/anthropic-sdk-go v1.16.0 h1:nRkOFDqYXsHteoIhjdJr/5dsiKbFF3rflSv8ax50y8o=
github.com/anthropics/anthropic-sdk-go v1.16.0/go.mod h1:WTz31rIUHUHqai2UslPpw5CwXrQP3geYBioRV4WOLvE=
github.com/anthropics/anthropic-sdk-go v1.19.0 h1:mO6E+ffSzLRvR/YUH9KJC0uGw0uV8GjISIuzem//3KE=
github.com/anthropics/anthropic-sdk-go v1.19.0/go.mod h1:WTz31rIUHUHqai2UslPpw5CwXrQP3geYBioRV4WOLvE=
github.com/araddon/dateparse v0.0.0-20210429162001-6b43995a97de h1:FxWPpzIjnTlhPwqqXc4/vE0f7GvRjuAsbW+HOIe8KnA=
github.com/araddon/dateparse v0.0.0-20210429162001-6b43995a97de/go.mod h1:DCaWoUhZrYW9p1lxo/cm8EmUOOzAPSEZNGF2DK1dJgw=
github.com/armon/go-socks5 v0.0.0-20160902184237-e75332964ef5 h1:0CwZNZbxp69SHPdPJAN/hZIm0C4OItdklCFmMRWYpio=
@@ -67,16 +69,16 @@ github.com/aws/aws-sdk-go-v2/service/sts v1.38.4 h1:PR00NXRYgY4FWHqOGx3fC3lhVKjs
github.com/aws/aws-sdk-go-v2/service/sts v1.38.4/go.mod h1:Z+Gd23v97pX9zK97+tX4ppAgqCt3Z2dIXB02CtBncK8=
github.com/aws/smithy-go v1.23.0 h1:8n6I3gXzWJB2DxBDnfxgBaSX6oe0d/t10qGz7OKqMCE=
github.com/aws/smithy-go v1.23.0/go.mod h1:t1ufH5HMublsJYulve2RKmHDC15xu1f26kHCp/HgceI=
github.com/bytedance/sonic v1.13.3 h1:MS8gmaH16Gtirygw7jV91pDCN33NyMrPbN7qiYhEsF0=
github.com/bytedance/sonic v1.13.3/go.mod h1:o68xyaF9u2gvVBuGHPlUVCy+ZfmNNO5ETf1+KgkJhz4=
github.com/bytedance/sonic/loader v0.1.1/go.mod h1:ncP89zfokxS5LZrJxl5z0UJcsk4M4yY2JpfqGeCtNLU=
github.com/bytedance/sonic/loader v0.2.4 h1:ZWCw4stuXUsn1/+zQDqeE7JKP+QO47tz7QCNan80NzY=
github.com/bytedance/sonic/loader v0.2.4/go.mod h1:N8A3vUdtUebEY2/VQC0MyhYeKUFosQU6FxH2JmUe6VI=
github.com/bytedance/gopkg v0.1.3 h1:TPBSwH8RsouGCBcMBktLt1AymVo2TVsBVCY4b6TnZ/M=
github.com/bytedance/gopkg v0.1.3/go.mod h1:576VvJ+eJgyCzdjS+c4+77QF3p7ubbtiKARP3TxducM=
github.com/bytedance/sonic v1.14.2 h1:k1twIoe97C1DtYUo+fZQy865IuHia4PR5RPiuGPPIIE=
github.com/bytedance/sonic v1.14.2/go.mod h1:T80iDELeHiHKSc0C9tubFygiuXoGzrkjKzX2quAx980=
github.com/bytedance/sonic/loader v0.4.0 h1:olZ7lEqcxtZygCK9EKYKADnpQoYkRQxaeY2NYzevs+o=
github.com/bytedance/sonic/loader v0.4.0/go.mod h1:AR4NYCk5DdzZizZ5djGqQ92eEhCCcdf5x77udYiSJRo=
github.com/cloudflare/circl v1.6.1 h1:zqIqSPIndyBh1bjLVVDHMPpVKqp8Su/V+6MeDzzQBQ0=
github.com/cloudflare/circl v1.6.1/go.mod h1:uddAzsPgqdMAYatqJ0lsjX1oECcQLIlRpzZh3pJrofs=
github.com/cloudwego/base64x v0.1.5 h1:XPciSp1xaq2VCSt6lF0phncD4koWyULpl5bUxbfCyP4=
github.com/cloudwego/base64x v0.1.5/go.mod h1:0zlkT4Wn5C6NdauXdJRhSKRlJvmclQ1hhJgA0rcu/8w=
github.com/cloudwego/iasm v0.2.0/go.mod h1:8rXZaNYT2n95jn+zTI1sDr+IgcD2GVs0nlbbQPiEFhY=
github.com/cloudwego/base64x v0.1.6 h1:t11wG9AECkCDk5fMSoxmufanudBtJ+/HemLstXDLI2M=
github.com/cloudwego/base64x v0.1.6/go.mod h1:OFcloc187FXDaYHvrNIjxSe8ncn0OOM8gEHfghB2IPU=
github.com/coder/websocket v1.8.13 h1:f3QZdXy7uGVz+4uCJy2nTZyM0yTBj8yANEHhqlXZ9FE=
github.com/coder/websocket v1.8.13/go.mod h1:LNVeNrXQZfe5qhS9ALED3uA+l5pPqvwXg3CKoDBB2gs=
github.com/cpuguy83/go-md2man/v2 v2.0.6/go.mod h1:oOW0eioCTA6cOiMLiUPZOpcVxMig6NIQQ7OS05n1F4g=
@@ -92,12 +94,14 @@ github.com/emirpasic/gods v1.18.1 h1:FXtiHYKDGKCW2KzwZKx0iC0PQmdlorYgdFG9jPXJ1Bc
github.com/emirpasic/gods v1.18.1/go.mod h1:8tpGGwCnJ5H4r6BWwaV6OrWmMoPhUl5jm/FMNAnJvWQ=
github.com/felixge/httpsnoop v1.0.4 h1:NFTV2Zj1bL4mc9sqWACXbQFVBBg2W3GPvqp8/ESS2Wg=
github.com/felixge/httpsnoop v1.0.4/go.mod h1:m8KPJKqk1gH5J9DgRY2ASl2lWCfGKXixSwevea8zH2U=
github.com/gabriel-vasile/mimetype v1.4.9 h1:5k+WDwEsD9eTLL8Tz3L0VnmVh9QxGjRmjBvAG7U/oYY=
github.com/gabriel-vasile/mimetype v1.4.9/go.mod h1:WnSQhFKJuBlRyLiKohA/2DtIlPFAbguNaG7QCHcyGok=
github.com/gabriel-vasile/mimetype v1.4.12 h1:e9hWvmLYvtp846tLHam2o++qitpguFiYCKbn0w9jyqw=
github.com/gabriel-vasile/mimetype v1.4.12/go.mod h1:d+9Oxyo1wTzWdyVUPMmXFvp4F9tea18J8ufA774AB3s=
github.com/gin-contrib/gzip v0.0.6 h1:NjcunTcGAj5CO1gn4N8jHOSIeRFHIbn51z6K+xaN4d4=
github.com/gin-contrib/gzip v0.0.6/go.mod h1:QOJlmV2xmayAjkNS2Y8NQsMneuRShOU/kjovCXNuzzk=
github.com/gin-contrib/sse v1.1.0 h1:n0w2GMuUpWDVp7qSpvze6fAu9iRxJY4Hmj6AmBOU05w=
github.com/gin-contrib/sse v1.1.0/go.mod h1:hxRZ5gVpWMT7Z0B0gSNYqqsSCNIJMjzvm6fqCz9vjwM=
github.com/gin-gonic/gin v1.10.1 h1:T0ujvqyCSqRopADpgPgiTT63DUQVSfojyME59Ei63pQ=
github.com/gin-gonic/gin v1.10.1/go.mod h1:4PMNQiOhvDRa013RKVbsiNwoyezlm2rm0uX/T7kzp5Y=
github.com/gin-gonic/gin v1.11.0 h1:OW/6PLjyusp2PPXtyxKHU0RbX6I/l28FTdDlae5ueWk=
github.com/gin-gonic/gin v1.11.0/go.mod h1:+iq/FyxlGzII0KHiBGjuNn4UNENUlKbGlNmc+W50Dls=
github.com/gliderlabs/ssh v0.3.8 h1:a4YXD1V7xMF9g5nTkdfnja3Sxy1PVDCj1Zg4Wb8vY6c=
github.com/gliderlabs/ssh v0.3.8/go.mod h1:xYoytBv1sV0aL3CavoDuJIQNURXkkfPA/wxQ1pL1fAU=
github.com/go-git/gcfg v1.5.1-0.20230307220236-3a3c6141e376 h1:+zs/tPmkDkHx3U66DAb0lQFJrpS6731Oaa12ikc+DiI=
@@ -113,20 +117,49 @@ github.com/go-logr/logr v1.4.3 h1:CjnDlHq8ikf6E492q6eKboGOC0T8CDaOvkHCIg8idEI=
github.com/go-logr/logr v1.4.3/go.mod h1:9T104GzyrTigFIr8wt5mBrctHMim0Nb2HLGrmQ40KvY=
github.com/go-logr/stdr v1.2.2 h1:hSWxHoqTgW2S2qGc0LTAI563KZ5YKYRhT3MFKZMbjag=
github.com/go-logr/stdr v1.2.2/go.mod h1:mMo/vtBO5dYbehREoey6XUKy/eSumjCCveDpRre4VKE=
github.com/go-openapi/jsonpointer v0.22.4 h1:dZtK82WlNpVLDW2jlA1YCiVJFVqkED1MegOUy9kR5T4=
github.com/go-openapi/jsonpointer v0.22.4/go.mod h1:elX9+UgznpFhgBuaMQ7iu4lvvX1nvNsesQ3oxmYTw80=
github.com/go-openapi/jsonreference v0.21.4 h1:24qaE2y9bx/q3uRK/qN+TDwbok1NhbSmGjjySRCHtC8=
github.com/go-openapi/jsonreference v0.21.4/go.mod h1:rIENPTjDbLpzQmQWCj5kKj3ZlmEh+EFVbz3RTUh30/4=
github.com/go-openapi/spec v0.22.2 h1:KEU4Fb+Lp1qg0V4MxrSCPv403ZjBl8Lx1a83gIPU8Qc=
github.com/go-openapi/spec v0.22.2/go.mod h1:iIImLODL2loCh3Vnox8TY2YWYJZjMAKYyLH2Mu8lOZs=
github.com/go-openapi/swag v0.19.15 h1:D2NRCBzS9/pEY3gP9Nl8aDqGUcPFrwG2p+CNFrLyrCM=
github.com/go-openapi/swag/conv v0.25.4 h1:/Dd7p0LZXczgUcC/Ikm1+YqVzkEeCc9LnOWjfkpkfe4=
github.com/go-openapi/swag/conv v0.25.4/go.mod h1:3LXfie/lwoAv0NHoEuY1hjoFAYkvlqI/Bn5EQDD3PPU=
github.com/go-openapi/swag/jsonname v0.25.4 h1:bZH0+MsS03MbnwBXYhuTttMOqk+5KcQ9869Vye1bNHI=
github.com/go-openapi/swag/jsonname v0.25.4/go.mod h1:GPVEk9CWVhNvWhZgrnvRA6utbAltopbKwDu8mXNUMag=
github.com/go-openapi/swag/jsonutils v0.25.4 h1:VSchfbGhD4UTf4vCdR2F4TLBdLwHyUDTd1/q4i+jGZA=
github.com/go-openapi/swag/jsonutils v0.25.4/go.mod h1:7OYGXpvVFPn4PpaSdPHJBtF0iGnbEaTk8AvBkoWnaAY=
github.com/go-openapi/swag/jsonutils/fixtures_test v0.25.4 h1:IACsSvBhiNJwlDix7wq39SS2Fh7lUOCJRmx/4SN4sVo=
github.com/go-openapi/swag/jsonutils/fixtures_test v0.25.4/go.mod h1:Mt0Ost9l3cUzVv4OEZG+WSeoHwjWLnarzMePNDAOBiM=
github.com/go-openapi/swag/loading v0.25.4 h1:jN4MvLj0X6yhCDduRsxDDw1aHe+ZWoLjW+9ZQWIKn2s=
github.com/go-openapi/swag/loading v0.25.4/go.mod h1:rpUM1ZiyEP9+mNLIQUdMiD7dCETXvkkC30z53i+ftTE=
github.com/go-openapi/swag/stringutils v0.25.4 h1:O6dU1Rd8bej4HPA3/CLPciNBBDwZj9HiEpdVsb8B5A8=
github.com/go-openapi/swag/stringutils v0.25.4/go.mod h1:GTsRvhJW5xM5gkgiFe0fV3PUlFm0dr8vki6/VSRaZK0=
github.com/go-openapi/swag/typeutils v0.25.4 h1:1/fbZOUN472NTc39zpa+YGHn3jzHWhv42wAJSN91wRw=
github.com/go-openapi/swag/typeutils v0.25.4/go.mod h1:Ou7g//Wx8tTLS9vG0UmzfCsjZjKhpjxayRKTHXf2pTE=
github.com/go-openapi/swag/yamlutils v0.25.4 h1:6jdaeSItEUb7ioS9lFoCZ65Cne1/RZtPBZ9A56h92Sw=
github.com/go-openapi/swag/yamlutils v0.25.4/go.mod h1:MNzq1ulQu+yd8Kl7wPOut/YHAAU/H6hL91fF+E2RFwc=
github.com/go-openapi/testify/enable/yaml/v2 v2.0.2 h1:0+Y41Pz1NkbTHz8NngxTuAXxEodtNSI1WG1c/m5Akw4=
github.com/go-openapi/testify/enable/yaml/v2 v2.0.2/go.mod h1:kme83333GCtJQHXQ8UKX3IBZu6z8T5Dvy5+CW3NLUUg=
github.com/go-openapi/testify/v2 v2.0.2 h1:X999g3jeLcoY8qctY/c/Z8iBHTbwLz7R2WXd6Ub6wls=
github.com/go-openapi/testify/v2 v2.0.2/go.mod h1:HCPmvFFnheKK2BuwSA0TbbdxJ3I16pjwMkYkP4Ywn54=
github.com/go-playground/assert/v2 v2.2.0 h1:JvknZsQTYeFEAhQwI4qEt9cyV5ONwRHC+lYKSsYSR8s=
github.com/go-playground/assert/v2 v2.2.0/go.mod h1:VDjEfimB/XKnb+ZQfWdccd7VUvScMdVu0Titje2rxJ4=
github.com/go-playground/locales v0.14.1 h1:EWaQ/wswjilfKLTECiXz7Rh+3BjFhfDFKv/oXslEjJA=
github.com/go-playground/locales v0.14.1/go.mod h1:hxrqLVvrK65+Rwrd5Fc6F2O76J/NuW9t0sjnWqG1slY=
github.com/go-playground/universal-translator v0.18.1 h1:Bcnm0ZwsGyWbCzImXv+pAJnYK9S473LQFuzCbDbfSFY=
github.com/go-playground/universal-translator v0.18.1/go.mod h1:xekY+UJKNuX9WP91TpwSH2VMlDf28Uj24BCp08ZFTUY=
github.com/go-playground/validator/v10 v10.26.0 h1:SP05Nqhjcvz81uJaRfEV0YBSSSGMc/iMaVtFbr3Sw2k=
github.com/go-playground/validator/v10 v10.26.0/go.mod h1:I5QpIEbmr8On7W0TktmJAumgzX4CA1XNl4ZmDuVHKKo=
github.com/go-playground/validator/v10 v10.29.0 h1:lQlF5VNJWNlRbRZNeOIkWElR+1LL/OuHcc0Kp14w1xk=
github.com/go-playground/validator/v10 v10.29.0/go.mod h1:D6QxqeMlgIPuT02L66f2ccrZ7AGgHkzKmmTMZhk/Kc4=
github.com/go-shiori/dom v0.0.0-20230515143342-73569d674e1c h1:wpkoddUomPfHiOziHZixGO5ZBS73cKqVzZipfrLmO1w=
github.com/go-shiori/dom v0.0.0-20230515143342-73569d674e1c/go.mod h1:oVDCh3qjJMLVUSILBRwrm+Bc6RNXGZYtoh9xdvf1ffM=
github.com/go-shiori/go-readability v0.0.0-20250217085726-9f5bf5ca7612 h1:BYLNYdZaepitbZreRIa9xeCQZocWmy/wj4cGIH0qyw0=
github.com/go-shiori/go-readability v0.0.0-20250217085726-9f5bf5ca7612/go.mod h1:wgqthQa8SAYs0yyljVeCOQlZ027VW5CmLsbi9jWC08c=
github.com/goccy/go-json v0.10.5 h1:Fq85nIqj+gXn/S5ahsiTlK3TmC85qgirsdTP/+DeaC4=
github.com/goccy/go-json v0.10.5/go.mod h1:oq7eo15ShAhp70Anwd5lgX2pLfOS3QCiwU/PULtXL6M=
github.com/goccy/go-yaml v1.19.1 h1:3rG3+v8pkhRqoQ/88NYNMHYVGYztCOCIZ7UQhu7H+NE=
github.com/goccy/go-yaml v1.19.1/go.mod h1:XBurs7gK8ATbW4ZPGKgcbrY1Br56PdM69F7LkFRi1kA=
github.com/gogs/chardet v0.0.0-20211120154057-b7413eaefb8f h1:3BSP1Tbs2djlpprl7wCLuiqMaUh5SJkkzI2gDs+FgLs=
github.com/gogs/chardet v0.0.0-20211120154057-b7413eaefb8f/go.mod h1:Pcatq5tYkCW2Q6yrR2VRHlbHpZ/R4/7qyL1TCF7vl14=
github.com/golang-jwt/jwt/v5 v5.2.2 h1:Rl4B7itRWVtYIHFrSNd7vhTiz9UpLdi6gZhZ3wEeDy8=
@@ -170,10 +203,8 @@ github.com/kballard/go-shellquote v0.0.0-20180428030007-95032a82bc51 h1:Z9n2FFNU
github.com/kballard/go-shellquote v0.0.0-20180428030007-95032a82bc51/go.mod h1:CzGEWj7cYgsdH8dAjBGEr58BoE7ScuLd+fwFZ44+/x8=
github.com/kevinburke/ssh_config v1.2.0 h1:x584FjTGwHzMwvHx18PXxbBVzfnxogHaAReU4gf13a4=
github.com/kevinburke/ssh_config v1.2.0/go.mod h1:CT57kijsi8u/K/BOFA39wgDQJ9CxiF4nAY/ojJ6r6mM=
github.com/klauspost/cpuid/v2 v2.0.9/go.mod h1:FInQzS24/EEf25PyTYn52gqo7WaD8xa0213Md/qVLRg=
github.com/klauspost/cpuid/v2 v2.2.10 h1:tBs3QSyvjDyFTq3uoc/9xFpCuOsJQFNPiAhYdw2skhE=
github.com/klauspost/cpuid/v2 v2.2.10/go.mod h1:hqwkgyIinND0mEev00jJYCxPNVRVXFQeu1XKlok6oO0=
github.com/knz/go-libedit v1.10.1/go.mod h1:MZTVkCWyz0oBc7JOWP3wNAzd002ZbM/5hgShxwh4x8M=
github.com/klauspost/cpuid/v2 v2.3.0 h1:S4CRMLnYUhGeDFDqkGriYKdfoFlDnMtqTiI/sFzhA9Y=
github.com/klauspost/cpuid/v2 v2.3.0/go.mod h1:hqwkgyIinND0mEev00jJYCxPNVRVXFQeu1XKlok6oO0=
github.com/kr/pretty v0.1.0/go.mod h1:dAy3ld7l9f0ibDNOQOHHMYYIIbhfbHSm3C4ZsoJORNo=
github.com/kr/pretty v0.3.1 h1:flRD4NNwYAUpkphVc1HcthR4KEIFJ65n8Mw5qdRn3LE=
github.com/kr/pretty v0.3.1/go.mod h1:hoEshYVHaxMs3cyo3Yncou5ZscifuDolrwPKZanG3xk=
@@ -201,8 +232,8 @@ github.com/ollama/ollama v0.11.7 h1:CuYjaJ/YEnvLDpJocJbbVdpdVFyGA/OP6lKFyzZD4dI=
github.com/ollama/ollama v0.11.7/go.mod h1:9+1//yWPsDE2u+l1a5mpaKrYw4VdnSsRU3ioq5BvMms=
github.com/onsi/gomega v1.34.1 h1:EUMJIKUjM8sKjYbtxQI9A4z2o+rruxnzNvpknOXie6k=
github.com/onsi/gomega v1.34.1/go.mod h1:kU1QgUvBDLXBJq618Xvm2LUX6rSAfRaFRTcdOeDLwwY=
github.com/openai/openai-go v1.8.2 h1:UqSkJ1vCOPUpz9Ka5tS0324EJFEuOvMc+lA/EarJWP8=
github.com/openai/openai-go v1.8.2/go.mod h1:g461MYGXEXBVdV5SaR/5tNzNbSfwTBBefwc+LlDCK0Y=
github.com/openai/openai-go v1.12.0 h1:NBQCnXzqOTv5wsgNC36PrFEiskGfO5wccfCWDo9S1U0=
github.com/openai/openai-go v1.12.0/go.mod h1:g461MYGXEXBVdV5SaR/5tNzNbSfwTBBefwc+LlDCK0Y=
github.com/otiai10/copy v1.14.1 h1:5/7E6qsUMBaH5AnQ0sSLzzTg1oTECmcCmT6lvF45Na8=
github.com/otiai10/copy v1.14.1/go.mod h1:oQwrEDDOci3IM8dJF0d8+jnbfPDllW6vUjNc3DoZm9I=
github.com/otiai10/mint v1.6.3 h1:87qsV/aw1F5as1eH1zS/yqHY85ANKVMgkDrf9rcxbQs=
@@ -218,6 +249,10 @@ github.com/pkg/errors v0.9.1/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINE
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/pmezard/go-difflib v1.0.1-0.20181226105442-5d4384ee4fb2 h1:Jamvg5psRIccs7FGNTlIRMkT8wgtp5eCXdBlqhYGL6U=
github.com/pmezard/go-difflib v1.0.1-0.20181226105442-5d4384ee4fb2/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/quic-go/qpack v0.6.0 h1:g7W+BMYynC1LbYLSqRt8PBg5Tgwxn214ZZR34VIOjz8=
github.com/quic-go/qpack v0.6.0/go.mod h1:lUpLKChi8njB4ty2bFLX2x4gzDqXwUpaO1DP9qMDZII=
github.com/quic-go/quic-go v0.57.1 h1:25KAAR9QR8KZrCZRThWMKVAwGoiHIrNbT72ULHTuI10=
github.com/quic-go/quic-go v0.57.1/go.mod h1:ly4QBAjHA2VhdnxhojRsCUOeJwKYg+taDlos92xb1+s=
github.com/rivo/uniseg v0.1.0/go.mod h1:J6wj4VEh+S6ZtnVlnTBMWIodfgj8LQOQFoIToxlJtxc=
github.com/rogpeppe/go-internal v1.14.1 h1:UQB4HGPB6osV0SQTLymcB4TgvyWu6ZyliaW0tI/otEQ=
github.com/rogpeppe/go-internal v1.14.1/go.mod h1:MaRKkUm5W0goXpeCfT7UZI6fk/L7L7so1lCWt35ZSgc=
@@ -239,15 +274,23 @@ github.com/spf13/pflag v1.0.6/go.mod h1:McXfInJRrz4CZXVZOBLb0bTZqETkiAhM9Iw0y3An
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
github.com/stretchr/objx v0.4.0/go.mod h1:YvHI0jy2hoMjB+UWwv71VJQ9isScKT/TqJzVSSt89Yw=
github.com/stretchr/objx v0.5.0/go.mod h1:Yh+to48EsGEfYuaHDzXPcE3xhTkx73EhmCGUpEOglKo=
github.com/stretchr/objx v0.5.2/go.mod h1:FRsXN1f5AsAjCGJKqEizvkpNtU+EGNCLh3NxZ/8L+MA=
github.com/stretchr/testify v1.2.2/go.mod h1:a8OnRcib4nhh0OaRAV+Yts87kKdq0PP7pXfy6kDkUVs=
github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
github.com/stretchr/testify v1.4.0/go.mod h1:j7eGeouHqKxXV5pUuKE4zz7dFj8WfuZ+81PSLYec5m4=
github.com/stretchr/testify v1.7.0/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
github.com/stretchr/testify v1.7.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
github.com/stretchr/testify v1.8.0/go.mod h1:yNjHg4UonilssWZ8iaSj1OCr/vHnekPRkoO+kdMU+MU=
github.com/stretchr/testify v1.8.1/go.mod h1:w2LPCIKwWwSfY2zedu0+kehJoqGctiVI29o6fzry7u4=
github.com/stretchr/testify v1.8.4/go.mod h1:sz/lmYIOXD/1dqDmKjjqLyZ2RngseejIcXlSw2iwfAo=
github.com/stretchr/testify v1.10.0/go.mod h1:r2ic/lqez/lEtzL7wO/rwa5dbSLXVDPFyf8C91i36aY=
github.com/stretchr/testify v1.11.1 h1:7s2iGBzp5EwR7/aIZr8ao5+dra3wiQyKjjFuvgVKu7U=
github.com/stretchr/testify v1.11.1/go.mod h1:wZwfW3scLgRK+23gO65QZefKpKQRnfz6sD981Nm4B6U=
github.com/swaggo/files v1.0.1 h1:J1bVJ4XHZNq0I46UU90611i9/YzdrF7x92oX1ig5IdE=
github.com/swaggo/files v1.0.1/go.mod h1:0qXmMNH6sXNf+73t65aKeB+ApmgxdnkQzVTAj2uaMUg=
github.com/swaggo/gin-swagger v1.6.1 h1:Ri06G4gc9N4t4k8hekMigJ9zKTFSlqj/9paAQCQs7cY=
github.com/swaggo/gin-swagger v1.6.1/go.mod h1:LQ+hJStHakCWRiK/YNYtJOu4mR2FP+pxLnILT/qNiTw=
github.com/swaggo/swag v1.16.6 h1:qBNcx53ZaX+M5dxVyTrgQ0PJ/ACK+NzhwcbieTt+9yI=
github.com/swaggo/swag v1.16.6/go.mod h1:ngP2etMK5a0P3QBizic5MEwpRmluJZPHjXcMoj4Xesg=
github.com/tidwall/gjson v1.14.2/go.mod h1:/wbyibRr2FHMks5tjHJ5F8dMZh3AcwJEMf5vlfC0lxk=
github.com/tidwall/gjson v1.18.0 h1:FIDeeyB800efLX89e5a8Y0BNH+LOngJyGrIWxG2FKQY=
github.com/tidwall/gjson v1.18.0/go.mod h1:/wbyibRr2FHMks5tjHJ5F8dMZh3AcwJEMf5vlfC0lxk=
@@ -260,8 +303,8 @@ github.com/tidwall/sjson v1.2.5 h1:kLy8mja+1c9jlljvWTlSazM7cKDRfJuR/bOJhcY5NcY=
github.com/tidwall/sjson v1.2.5/go.mod h1:Fvgq9kS/6ociJEDnK0Fk1cpYF4FIW6ZF7LAe+6jwd28=
github.com/twitchyliquid64/golang-asm v0.15.1 h1:SU5vSMR7hnwNxj24w34ZyCi/FmDZTkS4MhqMhdFk5YI=
github.com/twitchyliquid64/golang-asm v0.15.1/go.mod h1:a1lVb/DtPvCB8fslRZhAngC2+aY1QWCk3Cedj/Gdt08=
github.com/ugorji/go/codec v1.2.14 h1:yOQvXCBc3Ij46LRkRoh4Yd5qK6LVOgi0bYOXfb7ifjw=
github.com/ugorji/go/codec v1.2.14/go.mod h1:UNopzCgEMSXjBc6AOMqYvWC1ktqTAfzJZUZgYf6w6lg=
github.com/ugorji/go/codec v1.3.1 h1:waO7eEiFDwidsBN6agj1vJQ4AG7lh2yqXyOXqhgQuyY=
github.com/ugorji/go/codec v1.3.1/go.mod h1:pRBVtBSKl77K30Bv8R2P+cLSGaTtex6fsA2Wjqmfxj4=
github.com/xanzy/ssh-agent v0.3.3 h1:+/15pJfg/RsTxqYcX6fHqOXZwwMP+2VyYWJeWM2qQFM=
github.com/xanzy/ssh-agent v0.3.3/go.mod h1:6dzNDKs0J9rVPHPhaGCukekBHKqfl+L3KghI1Bc68Uw=
github.com/yuin/goldmark v1.4.13/go.mod h1:6yULJ656Px+3vBD8DxQVa3kxgyrAnzto9xy5taEt/CY=
@@ -279,8 +322,12 @@ go.opentelemetry.io/otel/sdk/metric v1.36.0 h1:r0ntwwGosWGaa0CrSt8cuNuTcccMXERFw
go.opentelemetry.io/otel/sdk/metric v1.36.0/go.mod h1:qTNOhFDfKRwX0yXOqJYegL5WRaW376QbB7P4Pb0qva4=
go.opentelemetry.io/otel/trace v1.36.0 h1:ahxWNuqZjpdiFAyrIoQ4GIiAIhxAunQR6MUoKrsNd4w=
go.opentelemetry.io/otel/trace v1.36.0/go.mod h1:gQ+OnDZzrybY4k4seLzPAWNwVBBVlF2szhehOBB/tGA=
golang.org/x/arch v0.18.0 h1:WN9poc33zL4AzGxqf8VtpKUnGvMi8O9lhNyBMF/85qc=
golang.org/x/arch v0.18.0/go.mod h1:bdwinDaKcfZUGpH09BB7ZmOfhalA8lQdzl62l8gGWsk=
go.uber.org/mock v0.6.0 h1:hyF9dfmbgIX5EfOdasqLsWD6xqpNZlXblLB/Dbnwv3Y=
go.uber.org/mock v0.6.0/go.mod h1:KiVJ4BqZJaMj4svdfmHM0AUx4NJYO8ZNpPnZn1Z+BBU=
go.yaml.in/yaml/v3 v3.0.4 h1:tfq32ie2Jv2UxXFdLJdh3jXuOzWiL1fo0bu/FbuKpbc=
go.yaml.in/yaml/v3 v3.0.4/go.mod h1:DhzuOOF2ATzADvBadXxruRBLzYTpT36CKvDb3+aBEFg=
golang.org/x/arch v0.23.0 h1:lKF64A2jF6Zd8L0knGltUnegD62JMFBiCPBmQpToHhg=
golang.org/x/arch v0.23.0/go.mod h1:dNHoOeKiyja7GTvF9NJS1l3Z2yntpQNzgrjh1cU103A=
golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACkg1iLfiJU5Ep61QUkGW8qpdssI0+w=
golang.org/x/crypto v0.0.0-20210921155107-089bfa567519/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
golang.org/x/crypto v0.0.0-20220622213112-05595931fe9d/go.mod h1:IxCIyHEi3zRg3s0A5j5BB6A9Jmi73HwBIUl50j+osU4=
@@ -288,8 +335,8 @@ golang.org/x/crypto v0.13.0/go.mod h1:y6Z2r+Rw4iayiXXAIxJIDAJ1zMW4yaTpebo8fPOliY
golang.org/x/crypto v0.19.0/go.mod h1:Iy9bg/ha4yyC70EfRS8jz+B6ybOBKMaSxLj6P6oBDfU=
golang.org/x/crypto v0.23.0/go.mod h1:CKFgDieR+mRhux2Lsu27y0fO304Db0wZe70UKqHu0v8=
golang.org/x/crypto v0.31.0/go.mod h1:kDsLvtWBEx7MV9tJOj9bnXsPbxwJQ6csT/x4KIN4Ssk=
golang.org/x/crypto v0.41.0 h1:WKYxWedPGCTVVl5+WHSSrOBT0O8lx32+zxmHxijgXp4=
golang.org/x/crypto v0.41.0/go.mod h1:pO5AFd7FA68rFak7rOAGVuygIISepHftHnr8dr6+sUc=
golang.org/x/crypto v0.46.0 h1:cKRW/pmt1pKAfetfu+RCEvjvZkA9RimPbh7bhFjGVBU=
golang.org/x/crypto v0.46.0/go.mod h1:Evb/oLKmMraqjZ2iQTwDwvCtJkczlDuTmdJXoZVzqU0=
golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b h1:QoALfVG9rhQ/M7vYDScfPdWjGL9dlsVVM5VGh7aKoAA=
golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b/go.mod h1:U6Lno4MTRCDY+Ba7aCcauB9T60gsv5s4ralQzP72ZoQ=
golang.org/x/mod v0.6.0-dev.0.20220419223038-86c51ed26bb4/go.mod h1:jJ57K6gSWd91VN4djpZkiMVwK6gcyfeH4XE8wZrZaV4=
@@ -297,18 +344,21 @@ golang.org/x/mod v0.8.0/go.mod h1:iBbtSCu2XBx23ZKBPSOrRkjjQPZFPuis4dIYUhu/chs=
golang.org/x/mod v0.12.0/go.mod h1:iBbtSCu2XBx23ZKBPSOrRkjjQPZFPuis4dIYUhu/chs=
golang.org/x/mod v0.15.0/go.mod h1:hTbmBsO62+eylJbnUtE2MGJUyE7QWk4xUqPFrRgJ+7c=
golang.org/x/mod v0.17.0/go.mod h1:hTbmBsO62+eylJbnUtE2MGJUyE7QWk4xUqPFrRgJ+7c=
golang.org/x/mod v0.31.0 h1:HaW9xtz0+kOcWKwli0ZXy79Ix+UW/vOfmWI5QVd2tgI=
golang.org/x/mod v0.31.0/go.mod h1:43JraMp9cGx1Rx3AqioxrbrhNsLl2l/iNAvuBkrezpg=
golang.org/x/net v0.0.0-20190620200207-3b0461eec859/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
golang.org/x/net v0.0.0-20210226172049-e18ecbb05110/go.mod h1:m0MpNAwzfU5UDzcl9v0D8zg8gWTRqZa9RBIspLL5mdg=
golang.org/x/net v0.0.0-20211112202133-69e39bad7dc2/go.mod h1:9nx3DQGgdP8bBQD5qxJ1jj9UTztislL4KSBs9R2vV5Y=
golang.org/x/net v0.0.0-20220722155237-a158d28d115b/go.mod h1:XRhObCWvk6IyKnWLug+ECip1KBveYUHfp+8e9klMJ9c=
golang.org/x/net v0.6.0/go.mod h1:2Tu9+aMcznHK/AK1HMvgo6xiTLG5rD5rZLDS+rp2Bjs=
golang.org/x/net v0.7.0/go.mod h1:2Tu9+aMcznHK/AK1HMvgo6xiTLG5rD5rZLDS+rp2Bjs=
golang.org/x/net v0.10.0/go.mod h1:0qNGK6F8kojg2nk9dLZ2mShWaEBan6FAoqfSigmmuDg=
golang.org/x/net v0.15.0/go.mod h1:idbUs1IY1+zTqbi8yxTbhexhEEk5ur9LInksu6HrEpk=
golang.org/x/net v0.21.0/go.mod h1:bIjVDfnllIU7BJ2DNgfnXvpSvtn8VRwhlsaeUTyUS44=
golang.org/x/net v0.25.0/go.mod h1:JkAGAh7GEvH74S6FOH42FLoXpXbE/aqXSrIQjXgsiwM=
golang.org/x/net v0.33.0/go.mod h1:HXLR5J+9DxmrqMwG9qjGCxZ+zKXxBru04zlTvWlWuN4=
golang.org/x/net v0.43.0 h1:lat02VYK2j4aLzMzecihNvTlJNQUq316m2Mr9rnM6YE=
golang.org/x/net v0.43.0/go.mod h1:vhO1fvI4dGsIjh73sWfUVjj3N7CA9WkKJNQm2svM6Jg=
golang.org/x/net v0.48.0 h1:zyQRTTrjc33Lhh0fBgT/H3oZq9WuvRR5gPC70xpDiQU=
golang.org/x/net v0.48.0/go.mod h1:+ndRgGjkh8FGtu1w1FGbEC31if4VrNVMuKTgcAAnQRY=
golang.org/x/oauth2 v0.30.0 h1:dnDm7JmhM45NNpd8FDDeLhK6FwqbOf4MLCM9zb1BOHI=
golang.org/x/oauth2 v0.30.0/go.mod h1:B++QgG3ZKulg6sRPGD/mqlHQs5rB3Ml9erfeDY7xKlU=
golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
@@ -318,8 +368,8 @@ golang.org/x/sync v0.3.0/go.mod h1:FU7BRWz2tNW+3quACPkgCx/L+uEAv1htQ0V83Z9Rj+Y=
golang.org/x/sync v0.6.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
golang.org/x/sync v0.7.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
golang.org/x/sync v0.10.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
golang.org/x/sync v0.16.0 h1:ycBJEhp9p4vXvUZNszeOq0kGTPghopOL8q0fq3vstxw=
golang.org/x/sync v0.16.0/go.mod h1:1dzgHSNfp02xaA81J2MS99Qcpr2w7fw1gpm99rleRqA=
golang.org/x/sync v0.19.0 h1:vV+1eWNmZ5geRlYjzm2adRgW2/mcpevXNg50YZtPCE4=
golang.org/x/sync v0.19.0/go.mod h1:9KTHXmSnoGruLpwFjVSX0lNNA75CykiMECbovNTZqGI=
golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20191026070338-33540a1f6037/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
@@ -336,8 +386,8 @@ golang.org/x/sys v0.12.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.17.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
golang.org/x/sys v0.20.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
golang.org/x/sys v0.28.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
golang.org/x/sys v0.35.0 h1:vz1N37gP5bs89s7He8XuIYXpyY0+QlsKmzipCbUtyxI=
golang.org/x/sys v0.35.0/go.mod h1:BJP2sWEmIv4KK5OTEluFJCKSidICx8ciO85XgH3Ak8k=
golang.org/x/sys v0.39.0 h1:CvCKL8MeisomCi6qNZ+wbb0DN9E5AATixKsvNtMoMFk=
golang.org/x/sys v0.39.0/go.mod h1:OgkHotnGiDImocRcuBABYBEXf8A9a87e/uXjp9XT3ks=
golang.org/x/telemetry v0.0.0-20240228155512-f48c80bd79b2/go.mod h1:TeRTkGYfJXctD9OcfyVLyj2J3IxLnKwHJR8f4D8a3YE=
golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
golang.org/x/term v0.0.0-20210927222741-03fcf44c2211/go.mod h1:jbD1KX2456YbFQfuXm/mYQcufACuNUgVhRMnK/tPxf8=
@@ -347,8 +397,8 @@ golang.org/x/term v0.12.0/go.mod h1:owVbMEjm3cBLCHdkQu9b1opXd4ETQWc3BhuQGKgXgvU=
golang.org/x/term v0.17.0/go.mod h1:lLRBjIVuehSbZlaOtGMbcMncT+aqLLLmKrsjNrUguwk=
golang.org/x/term v0.20.0/go.mod h1:8UkIAJTvZgivsXaD6/pH6U9ecQzZ45awqEOzuCvwpFY=
golang.org/x/term v0.27.0/go.mod h1:iMsnZpn0cago0GOrHO2+Y7u7JPn5AylBrcoWkElMTSM=
golang.org/x/term v0.34.0 h1:O/2T7POpk0ZZ7MAzMeWFSg6S5IpWd/RXDlM9hgM3DR4=
golang.org/x/term v0.34.0/go.mod h1:5jC53AEywhIVebHgPVeg0mj8OD3VO9OzclacVrqpaAw=
golang.org/x/term v0.38.0 h1:PQ5pkm/rLO6HnxFR7N2lJHOZX6Kez5Y1gDSJla6jo7Q=
golang.org/x/term v0.38.0/go.mod h1:bSEAKrOT1W+VSu9TSCMtoGEOUcKxOKgl3LE5QEF/xVg=
golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
@@ -359,14 +409,18 @@ golang.org/x/text v0.13.0/go.mod h1:TvPlkZtksWOMsz7fbANvkp4WM8x/WCo/om8BMLbz+aE=
golang.org/x/text v0.14.0/go.mod h1:18ZOQIKpY8NJVqYksKHtTdi31H5itFRjB5/qKTNYzSU=
golang.org/x/text v0.15.0/go.mod h1:18ZOQIKpY8NJVqYksKHtTdi31H5itFRjB5/qKTNYzSU=
golang.org/x/text v0.21.0/go.mod h1:4IBbMaMmOPCJ8SecivzSH54+73PCFmPWxNTLm+vZkEQ=
golang.org/x/text v0.28.0 h1:rhazDwis8INMIwQ4tpjLDzUhx6RlXqZNPEM0huQojng=
golang.org/x/text v0.28.0/go.mod h1:U8nCwOR8jO/marOQ0QbDiOngZVEBB7MAiitBuMjXiNU=
golang.org/x/text v0.32.0 h1:ZD01bjUt1FQ9WJ0ClOL5vxgxOI/sVCNgX1YtKwcY0mU=
golang.org/x/text v0.32.0/go.mod h1:o/rUWzghvpD5TXrTIBuJU77MTaN0ljMWE47kxGJQ7jY=
golang.org/x/time v0.12.0 h1:ScB/8o8olJvc+CQPWrK3fPZNfh7qgwCrY0zJmoEQLSE=
golang.org/x/time v0.12.0/go.mod h1:CDIdPxbZBQxdj6cxyCIdrNogrJKMJ7pr37NYpMcMDSg=
golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20191119224855-298f0cb1881e/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.1.12/go.mod h1:hNGJHUnrk76NpqgfD5Aqm5Crs+Hm0VOH/i9J2+nxYbc=
golang.org/x/tools v0.6.0/go.mod h1:Xwgl3UAJ/d3gWutnCtw505GrjyAbvKui8lOU390QaIU=
golang.org/x/tools v0.13.0/go.mod h1:HvlwmtVNQAhOuCjW7xxvovg8wbNq7LwfXh/k7wXUl58=
golang.org/x/tools v0.21.1-0.20240508182429-e35e4ccd0d2d/go.mod h1:aiJjzUbINMkxbQROHiO6hDPo2LHcIPhhQsa9DLh0yGk=
golang.org/x/tools v0.40.0 h1:yLkxfA+Qnul4cs9QA3KnlFu0lVmd8JJfoq+E41uSutA=
golang.org/x/tools v0.40.0/go.mod h1:Ik/tzLRlbscWpqqMRjyWYDisX8bG13FrdXp3o4Sr9lc=
golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
google.golang.org/api v0.247.0 h1:tSd/e0QrUlLsrwMKmkbQhYVa109qIintOls2Wh6bngc=
@@ -381,8 +435,8 @@ google.golang.org/genproto/googleapis/rpc v0.0.0-20250818200422-3122310a409c h1:
google.golang.org/genproto/googleapis/rpc v0.0.0-20250818200422-3122310a409c/go.mod h1:gw1tLEfykwDz2ET4a12jcXt4couGAm7IwsVaTy0Sflo=
google.golang.org/grpc v1.74.2 h1:WoosgB65DlWVC9FqI82dGsZhWFNBSLjQ84bjROOpMu4=
google.golang.org/grpc v1.74.2/go.mod h1:CtQ+BGjaAIXHs/5YS3i473GqwBBa1zGQNevxdeBEXrM=
google.golang.org/protobuf v1.36.7 h1:IgrO7UwFQGJdRNXH/sQux4R1Dj1WAKcLElzeeRaXV2A=
google.golang.org/protobuf v1.36.7/go.mod h1:jduwjTPXsFjZGTmRluh+L6NjiWu7pchiJ2/5YcXBHnY=
google.golang.org/protobuf v1.36.11 h1:fV6ZwhNocDyBLK0dj+fg8ektcVegBBuEolpbTQyBNVE=
google.golang.org/protobuf v1.36.11/go.mod h1:HTf+CrKn2C3g5S8VImy6tdcUvCska2kB7j23XfzDpco=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20190902080502-41f04d3bba15/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c h1:Hei/4ADfdWqJk1ZMxUNpqntNwaWcugrBjAiHlqqRiVk=
@@ -394,4 +448,3 @@ gopkg.in/yaml.v2 v2.4.0/go.mod h1:RDklbk79AGWmwhnvt/jBztapEOGDOx6ZbXqjP6csGnQ=
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
nullprogram.com/x/optparse v1.0.0/go.mod h1:KdyPE+Igbe0jQUrVfMqDMeJQIJZEuyV7pjYmp6pbG50=

View File

@@ -8,6 +8,7 @@ import (
"os"
"path/filepath"
"reflect"
"slices"
"strconv"
"strings"
@@ -35,7 +36,7 @@ type Flags struct {
TopP float64 `short:"T" long:"topp" yaml:"topp" description:"Set top P" default:"0.9"`
Stream bool `short:"s" long:"stream" yaml:"stream" description:"Stream"`
PresencePenalty float64 `short:"P" long:"presencepenalty" yaml:"presencepenalty" description:"Set presence penalty" default:"0.0"`
Raw bool `short:"r" long:"raw" yaml:"raw" description:"Use the defaults of the model without sending chat options (like temperature etc.) and use the user role instead of the system role for patterns."`
Raw bool `short:"r" long:"raw" yaml:"raw" description:"Use the defaults of the model without sending chat options (temperature, top_p, etc.). Only affects OpenAI-compatible providers. Anthropic models always use smart parameter selection to comply with model-specific requirements."`
FrequencyPenalty float64 `short:"F" long:"frequencypenalty" yaml:"frequencypenalty" description:"Set frequency penalty" default:"0.0"`
ListPatterns bool `short:"l" long:"listpatterns" description:"List all patterns"`
ListAllModels bool `short:"L" long:"listmodels" description:"List all available models"`
@@ -115,7 +116,7 @@ func Init() (ret *Flags, err error) {
// Create mapping from flag names (both short and long) to yaml tag names
flagToYamlTag := make(map[string]string)
t := reflect.TypeOf(Flags{})
t := reflect.TypeFor[Flags]()
for i := 0; i < t.NumField(); i++ {
field := t.Field(i)
yamlTag := field.Tag.Get("yaml")
@@ -224,14 +225,14 @@ func Init() (ret *Flags, err error) {
}
func parseDebugLevel(args []string) int {
for i := 0; i < len(args); i++ {
for i := range args {
arg := args[i]
if arg == "--debug" && i+1 < len(args) {
if lvl, err := strconv.Atoi(args[i+1]); err == nil {
return lvl
}
} else if strings.HasPrefix(arg, "--debug=") {
if lvl, err := strconv.Atoi(strings.TrimPrefix(arg, "--debug=")); err == nil {
} else if after, ok := strings.CutPrefix(arg, "--debug="); ok {
if lvl, err := strconv.Atoi(after); err == nil {
return lvl
}
}
@@ -241,8 +242,8 @@ func parseDebugLevel(args []string) int {
func extractFlag(arg string) string {
var flag string
if strings.HasPrefix(arg, "--") {
flag = strings.TrimPrefix(arg, "--")
if after, ok := strings.CutPrefix(arg, "--"); ok {
flag = after
if i := strings.Index(flag, "="); i > 0 {
flag = flag[:i]
}
@@ -348,10 +349,8 @@ func validateImageFile(imagePath string) error {
ext := strings.ToLower(filepath.Ext(imagePath))
validExtensions := []string{".png", ".jpeg", ".jpg", ".webp"}
for _, validExt := range validExtensions {
if ext == validExt {
return nil // Valid extension found
}
if slices.Contains(validExtensions, ext) {
return nil // Valid extension found
}
return fmt.Errorf("%s", fmt.Sprintf(i18n.T("invalid_image_file_extension"), ext))
@@ -370,13 +369,7 @@ func validateImageParameters(imagePath, size, quality, background string, compre
// Validate size
if size != "" {
validSizes := []string{"1024x1024", "1536x1024", "1024x1536", "auto"}
valid := false
for _, validSize := range validSizes {
if size == validSize {
valid = true
break
}
}
valid := slices.Contains(validSizes, size)
if !valid {
return fmt.Errorf("%s", fmt.Sprintf(i18n.T("invalid_image_size"), size))
}
@@ -385,13 +378,7 @@ func validateImageParameters(imagePath, size, quality, background string, compre
// Validate quality
if quality != "" {
validQualities := []string{"low", "medium", "high", "auto"}
valid := false
for _, validQuality := range validQualities {
if quality == validQuality {
valid = true
break
}
}
valid := slices.Contains(validQualities, quality)
if !valid {
return fmt.Errorf("%s", fmt.Sprintf(i18n.T("invalid_image_quality"), quality))
}
@@ -400,13 +387,7 @@ func validateImageParameters(imagePath, size, quality, background string, compre
// Validate background
if background != "" {
validBackgrounds := []string{"opaque", "transparent"}
valid := false
for _, validBackground := range validBackgrounds {
if background == validBackground {
valid = true
break
}
}
valid := slices.Contains(validBackgrounds, background)
if !valid {
return fmt.Errorf("%s", fmt.Sprintf(i18n.T("invalid_image_background"), background))
}

View File

@@ -137,8 +137,7 @@ func (h *TranslatedHelpWriter) getTranslatedDescription(flagName string) string
// getOriginalDescription retrieves the original description from struct tags
func (h *TranslatedHelpWriter) getOriginalDescription(flagName string) string {
flags := &Flags{}
flagsType := reflect.TypeOf(flags).Elem()
flagsType := reflect.TypeFor[Flags]()
for i := 0; i < flagsType.NumField(); i++ {
field := flagsType.Field(i)
@@ -184,10 +183,10 @@ func detectLanguageFromArgs() string {
if i+1 < len(args) {
return args[i+1]
}
} else if strings.HasPrefix(arg, "--language=") {
return strings.TrimPrefix(arg, "--language=")
} else if strings.HasPrefix(arg, "-g=") {
return strings.TrimPrefix(arg, "-g=")
} else if after, ok := strings.CutPrefix(arg, "--language="); ok {
return after
} else if after, ok := strings.CutPrefix(arg, "-g="); ok {
return after
} else if runtime.GOOS == "windows" && strings.HasPrefix(arg, "/g:") {
return strings.TrimPrefix(arg, "/g:")
} else if runtime.GOOS == "windows" && strings.HasPrefix(arg, "/g=") {
@@ -218,8 +217,7 @@ func detectLanguageFromEnv() string {
// writeAllFlags writes all flags with translated descriptions
func (h *TranslatedHelpWriter) writeAllFlags() {
// Use direct reflection on the Flags struct to get all flag definitions
flags := &Flags{}
flagsType := reflect.TypeOf(flags).Elem()
flagsType := reflect.TypeFor[Flags]()
for i := 0; i < flagsType.NumField(); i++ {
field := flagsType.Field(i)
@@ -274,10 +272,7 @@ func (h *TranslatedHelpWriter) writeAllFlags() {
// Pad to align descriptions
flagStr := flagLine.String()
padding := 34 - len(flagStr)
if padding < 2 {
padding = 2
}
padding := max(34-len(flagStr), 2)
fmt.Fprintf(h.writer, "%s%s%s", flagStr, strings.Repeat(" ", padding), description)

View File

@@ -39,6 +39,11 @@ func handleListingCommands(currentFlags *Flags, fabricDb *fsdb.Db, registry *cor
if models, err = registry.VendorManager.GetModels(); err != nil {
return true, err
}
if currentFlags.Vendor != "" {
models = models.FilterByVendor(currentFlags.Vendor)
}
if currentFlags.ShellCompleteOutput {
models.Print(true)
} else {

View File

@@ -4,6 +4,7 @@ import (
"fmt"
"os"
"path/filepath"
"slices"
"strings"
"github.com/atotto/clipboard"
@@ -29,6 +30,9 @@ func CreateOutputFile(message string, fileName string) (err error) {
return
}
defer file.Close()
if !strings.HasSuffix(message, "\n") {
message += "\n"
}
if _, err = file.WriteString(message); err != nil {
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("error_writing_to_file"), err))
} else {
@@ -63,10 +67,5 @@ func CreateAudioOutputFile(audioData []byte, fileName string) (err error) {
func IsAudioFormat(fileName string) bool {
ext := strings.ToLower(filepath.Ext(fileName))
audioExts := []string{".wav", ".mp3", ".m4a", ".aac", ".ogg", ".flac"}
for _, audioExt := range audioExts {
if ext == audioExt {
return true
}
}
return false
return slices.Contains(audioExts, ext)
}

View File

@@ -24,5 +24,34 @@ func TestCreateOutputFile(t *testing.T) {
t.Fatalf("CreateOutputFile() error = %v", err)
}
defer os.Remove(fileName)
t.Cleanup(func() { os.Remove(fileName) })
data, err := os.ReadFile(fileName)
if err != nil {
t.Fatalf("failed to read output file: %v", err)
}
expected := message + "\n"
if string(data) != expected {
t.Fatalf("expected file contents %q, got %q", expected, data)
}
}
func TestCreateOutputFileMessageWithTrailingNewline(t *testing.T) {
fileName := "test_output_with_newline.txt"
message := "test message with newline\n"
if err := CreateOutputFile(message, fileName); err != nil {
t.Fatalf("CreateOutputFile() error = %v", err)
}
t.Cleanup(func() { os.Remove(fileName) })
data, err := os.ReadFile(fileName)
if err != nil {
t.Fatalf("failed to read output file: %v", err)
}
if string(data) != message {
t.Fatalf("expected file contents %q, got %q", message, data)
}
}

View File

@@ -17,8 +17,9 @@ func handleTranscription(flags *Flags, registry *core.PluginRegistry) (message s
if vendorName == "" {
vendorName = "OpenAI"
}
vendor, ok := registry.VendorManager.VendorsByName[vendorName]
if !ok {
vendor := registry.VendorManager.FindByName(vendorName)
if vendor == nil {
return "", fmt.Errorf("%s", fmt.Sprintf(i18n.T("vendor_not_configured"), vendorName))
}
tr, ok := vendor.(transcriber)

View File

@@ -32,11 +32,9 @@ type Chatter struct {
// Send processes a chat request and applies file changes for create_coding_feature pattern
func (o *Chatter) Send(request *domain.ChatRequest, opts *domain.ChatOptions) (session *fsdb.Session, err error) {
modelToUse := opts.Model
if modelToUse == "" {
modelToUse = o.model
}
if o.vendor.NeedsRawMode(modelToUse) {
// Use o.model (normalized) for NeedsRawMode check instead of opts.Model
// This ensures case-insensitive model names work correctly (e.g., "GPT-5" → "gpt-5")
if o.vendor.NeedsRawMode(o.model) {
opts.Raw = true
}
if session, err = o.BuildSession(request, opts.Raw); err != nil {
@@ -57,6 +55,10 @@ func (o *Chatter) Send(request *domain.ChatRequest, opts *domain.ChatOptions) (s
if opts.Model == "" {
opts.Model = o.model
} else {
// Ensure opts.Model uses the normalized name from o.model if they refer to the same model
// This handles cases where user provides "GPT-5" but we've normalized it to "gpt-5"
opts.Model = o.model
}
if opts.ModelContextLength == 0 {
@@ -69,6 +71,7 @@ func (o *Chatter) Send(request *domain.ChatRequest, opts *domain.ChatOptions) (s
responseChan := make(chan string)
errChan := make(chan error, 1)
done := make(chan struct{})
printedStream := false
go func() {
defer close(done)
@@ -81,9 +84,14 @@ func (o *Chatter) Send(request *domain.ChatRequest, opts *domain.ChatOptions) (s
message += response
if !opts.SuppressThink {
fmt.Print(response)
printedStream = true
}
}
if printedStream && !opts.SuppressThink && !strings.HasSuffix(message, "\n") {
fmt.Println()
}
// Wait for goroutine to finish
<-done
@@ -175,7 +183,7 @@ func (o *Chatter) BuildSession(request *domain.ChatRequest, raw bool) (session *
if request.Message == nil {
request.Message = &chat.ChatCompletionMessage{
Role: chat.ChatMessageRoleUser,
Content: " ",
Content: "",
}
}

View File

@@ -222,9 +222,8 @@ func (o *PluginRegistry) Setup() (err error) {
}
}
if _, ok := o.VendorManager.VendorsByName[plugin.GetName()]; !ok {
var vendor ai.Vendor
if vendor, ok = plugin.(ai.Vendor); ok {
if o.VendorManager.FindByName(plugin.GetName()) == nil {
if vendor, ok := plugin.(ai.Vendor); ok {
o.VendorManager.AddVendors(vendor)
}
}
@@ -330,11 +329,22 @@ func (o *PluginRegistry) GetChatter(model string, modelContextLength int, vendor
if models, err = vendorManager.GetModels(); err != nil {
return
}
// Normalize model name to match actual available model (case-insensitive)
// This must be done BEFORE checking vendor availability
actualModelName := models.FindModelNameCaseInsensitive(model)
if actualModelName != "" {
model = actualModelName // Use normalized name for all subsequent checks
}
if vendorName != "" {
// ensure vendor exists and provides model
ret.vendor = vendorManager.FindByName(vendorName)
availableVendors := models.FindGroupsByItem(model)
if ret.vendor == nil || !lo.Contains(availableVendors, vendorName) {
vendorAvailable := lo.ContainsBy(availableVendors, func(name string) bool {
return strings.EqualFold(name, vendorName)
})
if ret.vendor == nil || !vendorAvailable {
err = fmt.Errorf("model %s not available for vendor %s", model, vendorName)
return
}
@@ -345,6 +355,7 @@ func (o *PluginRegistry) GetChatter(model string, modelContextLength int, vendor
}
ret.vendor = vendorManager.FindByName(models.FindGroupsByItemFirst(model))
}
ret.model = model
}

View File

@@ -5,6 +5,7 @@ import (
"fmt"
"os"
"path/filepath"
"slices"
"strings"
)
@@ -146,14 +147,7 @@ func fixInvalidEscapes(jsonStr string) string {
// Check for escape sequences only inside strings
if inQuotes && ch == '\\' && i+1 < len(jsonStr) {
nextChar := jsonStr[i+1]
isValid := false
for _, validEscape := range validEscapes {
if nextChar == validEscape {
isValid = true
break
}
}
isValid := slices.Contains(validEscapes, nextChar)
if !isValid {
// Invalid escape sequence - add an extra backslash

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "Anbieter %s unterstützt keine Audio-Transkription",
"transcription_model_required": "Transkriptionsmodell ist erforderlich (verwende --transcribe-model)",
"youtube_not_configured": "YouTube ist nicht konfiguriert, bitte führe das Setup-Verfahren aus",
"youtube_api_key_required": "YouTube API-Schlüssel für Kommentare und Metadaten erforderlich. Führe 'fabric --setup' aus, um zu konfigurieren",
"youtube_ytdlp_not_found": "yt-dlp wurde nicht in PATH gefunden. Bitte installiere yt-dlp, um die YouTube-Transkript-Funktionalität zu nutzen",
"youtube_invalid_url": "ungültige YouTube-URL, kann keine Video- oder Playlist-ID abrufen: '%s'",
"youtube_url_is_playlist_not_video": "URL ist eine Playlist, kein Video",
"youtube_no_video_id_found": "keine Video-ID in URL gefunden",
"youtube_rate_limit_exceeded": "YouTube-Ratenlimit überschritten. Versuche es später erneut oder verwende andere yt-dlp-Argumente wie '--sleep-requests 1', um Anfragen zu verlangsamen.",
"youtube_auth_required_bot_detection": "YouTube erfordert Authentifizierung (Bot-Erkennung). Verwende --yt-dlp-args='--cookies-from-browser BROWSER' wobei BROWSER chrome, firefox, brave usw. sein kann.",
"youtube_ytdlp_stderr_error": "Fehler beim Lesen von yt-dlp stderr",
"youtube_invalid_ytdlp_arguments": "ungültige yt-dlp-Argumente: %v",
"youtube_failed_create_temp_dir": "temporäres Verzeichnis konnte nicht erstellt werden: %v",
"youtube_no_transcript_content": "kein Transkriptinhalt in VTT-Datei gefunden",
"youtube_no_vtt_files_found": "keine VTT-Dateien im Verzeichnis gefunden",
"youtube_failed_walk_directory": "Verzeichnis konnte nicht durchlaufen werden: %v",
"youtube_error_getting_video_details": "Fehler beim Abrufen der Videodetails: %v",
"youtube_invalid_duration_string": "ungültige Dauer-Zeichenfolge: %s",
"youtube_error_getting_metadata": "Fehler beim Abrufen der Video-Metadaten: %v",
"youtube_error_parsing_duration": "Fehler beim Parsen der Videodauer: %v",
"youtube_error_getting_comments": "Fehler beim Abrufen der Kommentare: %v",
"youtube_error_saving_csv": "Fehler beim Speichern der Videos in CSV: %v",
"youtube_no_video_found_with_id": "kein Video mit ID gefunden: %s",
"youtube_invalid_timestamp_format": "ungültiges Zeitstempel-Format: %s",
"youtube_empty_seconds_string": "leere Sekunden-Zeichenfolge",
"youtube_invalid_seconds_format": "ungültiges Sekundenformat %q: %w",
"error_fetching_playlist_videos": "Fehler beim Abrufen der Playlist-Videos: %w",
"openai_api_base_url_not_configured": "API-Basis-URL für Anbieter %s nicht konfiguriert",
"openai_failed_to_create_models_url": "Modell-URL konnte nicht erstellt werden: %w",
"openai_unexpected_status_code_with_body": "unerwarteter Statuscode: %d von Anbieter %s, Antwort: %s",
"openai_unexpected_status_code_read_error_partial": "unerwarteter Statuscode: %d von Anbieter %s (Fehler beim Lesen: %v), teilweise Antwort: %s",
"openai_unexpected_status_code_read_error": "unerwarteter Statuscode: %d von Anbieter %s (Fehler beim Lesen der Antwort: %v)",
"openai_unable_to_parse_models_response": "Modell-Antwort konnte nicht geparst werden; rohe Antwort: %s",
"scraping_not_configured": "Scraping-Funktionalität ist nicht konfiguriert. Bitte richte Jina ein, um Scraping zu aktivieren",
"could_not_determine_home_dir": "konnte Benutzer-Home-Verzeichnis nicht bestimmen: %w",
"could_not_stat_env_file": "konnte .env-Datei nicht überprüfen: %w",
@@ -53,7 +82,7 @@
"set_top_p": "Top P festlegen",
"stream_help": "Streaming",
"set_presence_penalty": "Präsenzstrafe festlegen",
"use_model_defaults_raw_help": "Verwende die Standardwerte des Modells ohne Senden von Chat-Optionen (wie Temperatur usw.) und verwende die Benutzerrolle anstelle der Systemrolle für Muster.",
"use_model_defaults_raw_help": "Verwende die Standardwerte des Modells, ohne Chat-Optionen (temperature, top_p usw.) zu senden. Gilt nur für OpenAI-kompatible Anbieter. Anthropic-Modelle verwenden stets eine intelligente Parameterauswahl, um modell-spezifische Anforderungen einzuhalten.",
"set_frequency_penalty": "Häufigkeitsstrafe festlegen",
"list_all_patterns": "Alle Muster auflisten",
"list_all_available_models": "Alle verfügbaren Modelle auflisten",

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "vendor %s does not support audio transcription",
"transcription_model_required": "transcription model is required (use --transcribe-model)",
"youtube_not_configured": "YouTube is not configured, please run the setup procedure",
"youtube_api_key_required": "YouTube API key required for comments and metadata. Run 'fabric --setup' to configure",
"youtube_ytdlp_not_found": "yt-dlp not found in PATH. Please install yt-dlp to use YouTube transcript functionality",
"youtube_invalid_url": "invalid YouTube URL, can't get video or playlist ID: '%s'",
"youtube_url_is_playlist_not_video": "URL is a playlist, not a video",
"youtube_no_video_id_found": "no video ID found in URL",
"youtube_rate_limit_exceeded": "YouTube rate limit exceeded. Try again later or use different yt-dlp arguments like '--sleep-requests 1' to slow down requests.",
"youtube_auth_required_bot_detection": "YouTube requires authentication (bot detection). Use --yt-dlp-args='--cookies-from-browser BROWSER' where BROWSER is chrome, firefox, brave, etc.",
"youtube_ytdlp_stderr_error": "Error reading yt-dlp stderr",
"youtube_invalid_ytdlp_arguments": "invalid yt-dlp arguments: %v",
"youtube_failed_create_temp_dir": "failed to create temp directory: %v",
"youtube_no_transcript_content": "no transcript content found in VTT file",
"youtube_no_vtt_files_found": "no VTT files found in directory",
"youtube_failed_walk_directory": "failed to walk directory: %v",
"youtube_error_getting_video_details": "error getting video details: %v",
"youtube_invalid_duration_string": "invalid duration string: %s",
"youtube_error_getting_metadata": "error getting video metadata: %v",
"youtube_error_parsing_duration": "error parsing video duration: %v",
"youtube_error_getting_comments": "error getting comments: %v",
"youtube_error_saving_csv": "error saving videos to CSV: %v",
"youtube_no_video_found_with_id": "no video found with ID: %s",
"youtube_invalid_timestamp_format": "invalid timestamp format: %s",
"youtube_empty_seconds_string": "empty seconds string",
"youtube_invalid_seconds_format": "invalid seconds format %q: %w",
"error_fetching_playlist_videos": "error fetching playlist videos: %w",
"openai_api_base_url_not_configured": "API base URL not configured for provider %s",
"openai_failed_to_create_models_url": "failed to create models URL: %w",
"openai_unexpected_status_code_with_body": "unexpected status code: %d from provider %s, response body: %s",
"openai_unexpected_status_code_read_error_partial": "unexpected status code: %d from provider %s (error reading body: %v), partial response: %s",
"openai_unexpected_status_code_read_error": "unexpected status code: %d from provider %s (failed to read response body: %v)",
"openai_unable_to_parse_models_response": "unable to parse models response; raw response: %s",
"scraping_not_configured": "scraping functionality is not configured. Please set up Jina to enable scraping",
"could_not_determine_home_dir": "could not determine user home directory: %w",
"could_not_stat_env_file": "could not stat .env file: %w",
@@ -53,7 +82,7 @@
"set_top_p": "Set top P",
"stream_help": "Stream",
"set_presence_penalty": "Set presence penalty",
"use_model_defaults_raw_help": "Use the defaults of the model without sending chat options (like temperature etc.) and use the user role instead of the system role for patterns.",
"use_model_defaults_raw_help": "Use the defaults of the model without sending chat options (temperature, top_p, etc.). Only affects OpenAI-compatible providers. Anthropic models always use smart parameter selection to comply with model-specific requirements.",
"set_frequency_penalty": "Set frequency penalty",
"list_all_patterns": "List all patterns",
"list_all_available_models": "List all available models",

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "el proveedor %s no admite transcripción de audio",
"transcription_model_required": "se requiere un modelo de transcripción (usa --transcribe-model)",
"youtube_not_configured": "YouTube no está configurado, por favor ejecuta el procedimiento de configuración",
"youtube_api_key_required": "Se requiere clave de API de YouTube para comentarios y metadatos. Ejecuta 'fabric --setup' para configurar",
"youtube_ytdlp_not_found": "yt-dlp no encontrado en PATH. Por favor instala yt-dlp para usar la funcionalidad de transcripción de YouTube",
"youtube_invalid_url": "URL de YouTube inválida, no se puede obtener ID de video o lista de reproducción: '%s'",
"youtube_url_is_playlist_not_video": "La URL es una lista de reproducción, no un video",
"youtube_no_video_id_found": "no se encontró ID de video en la URL",
"youtube_rate_limit_exceeded": "Límite de tasa de YouTube excedido. Intenta de nuevo más tarde o usa diferentes argumentos de yt-dlp como '--sleep-requests 1' para ralentizar las solicitudes.",
"youtube_auth_required_bot_detection": "YouTube requiere autenticación (detección de bot). Usa --yt-dlp-args='--cookies-from-browser BROWSER' donde BROWSER puede ser chrome, firefox, brave, etc.",
"youtube_ytdlp_stderr_error": "Error al leer stderr de yt-dlp",
"youtube_invalid_ytdlp_arguments": "argumentos de yt-dlp inválidos: %v",
"youtube_failed_create_temp_dir": "falló al crear directorio temporal: %v",
"youtube_no_transcript_content": "no se encontró contenido de transcripción en el archivo VTT",
"youtube_no_vtt_files_found": "no se encontraron archivos VTT en el directorio",
"youtube_failed_walk_directory": "falló al recorrer el directorio: %v",
"youtube_error_getting_video_details": "error al obtener detalles del video: %v",
"youtube_invalid_duration_string": "cadena de duración inválida: %s",
"youtube_error_getting_metadata": "error al obtener metadatos del video: %v",
"youtube_error_parsing_duration": "error al analizar la duración del video: %v",
"youtube_error_getting_comments": "error al obtener comentarios: %v",
"youtube_error_saving_csv": "error al guardar videos en CSV: %v",
"youtube_no_video_found_with_id": "no se encontró video con ID: %s",
"youtube_invalid_timestamp_format": "formato de marca de tiempo inválido: %s",
"youtube_empty_seconds_string": "cadena de segundos vacía",
"youtube_invalid_seconds_format": "formato de segundos inválido %q: %w",
"error_fetching_playlist_videos": "error al obtener videos de la lista de reproducción: %w",
"openai_api_base_url_not_configured": "URL base de API no configurada para el proveedor %s",
"openai_failed_to_create_models_url": "error al crear URL de modelos: %w",
"openai_unexpected_status_code_with_body": "código de estado inesperado: %d del proveedor %s, cuerpo de respuesta: %s",
"openai_unexpected_status_code_read_error_partial": "código de estado inesperado: %d del proveedor %s (error al leer cuerpo: %v), respuesta parcial: %s",
"openai_unexpected_status_code_read_error": "código de estado inesperado: %d del proveedor %s (error al leer cuerpo de respuesta: %v)",
"openai_unable_to_parse_models_response": "no se pudo analizar la respuesta de modelos; respuesta cruda: %s",
"scraping_not_configured": "la funcionalidad de extracción no está configurada. Por favor configura Jina para habilitar la extracción",
"could_not_determine_home_dir": "no se pudo determinar el directorio home del usuario: %w",
"could_not_stat_env_file": "no se pudo verificar el archivo .env: %w",
@@ -53,7 +82,7 @@
"set_top_p": "Establecer top P",
"stream_help": "Transmitir",
"set_presence_penalty": "Establecer penalización de presencia",
"use_model_defaults_raw_help": "Usar los valores predeterminados del modelo sin enviar opciones de chat (como temperatura, etc.) y usar el rol de usuario en lugar del rol del sistema para patrones.",
"use_model_defaults_raw_help": "Utiliza los valores predeterminados del modelo sin enviar opciones de chat (temperature, top_p, etc.). Solo afecta a los proveedores compatibles con OpenAI. Los modelos de Anthropic siempre usan una selección inteligente de parámetros para cumplir los requisitos específicos del modelo.",
"set_frequency_penalty": "Establecer penalización de frecuencia",
"list_all_patterns": "Listar todos los patrones",
"list_all_available_models": "Listar todos los modelos disponibles",

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "تامین‌کننده %s از رونویسی صوتی پشتیبانی نمی‌کند",
"transcription_model_required": "مدل رونویسی الزامی است (از --transcribe-model استفاده کنید)",
"youtube_not_configured": "یوتیوب پیکربندی نشده است، لطفاً روند تنظیمات را اجرا کنید",
"youtube_api_key_required": "کلید API یوتیوب برای دریافت نظرات و متادیتا الزامی است. برای پیکربندی 'fabric --setup' را اجرا کنید",
"youtube_ytdlp_not_found": "yt-dlp در PATH یافت نشد. لطفاً yt-dlp را نصب کنید تا از قابلیت رونویسی یوتیوب استفاده کنید",
"youtube_invalid_url": "URL یوتیوب نامعتبر است، نمی‌توان ID ویدیو یا فهرست پخش را دریافت کرد: '%s'",
"youtube_url_is_playlist_not_video": "URL یک فهرست پخش است، نه یک ویدیو",
"youtube_no_video_id_found": "هیچ ID ویدیویی در URL یافت نشد",
"youtube_rate_limit_exceeded": "محدودیت نرخ یوتیوب فراتر رفته است. بعداً دوباره امتحان کنید یا از آرگومان‌های مختلف yt-dlp مانند '--sleep-requests 1' برای کاهش سرعت درخواست‌ها استفاده کنید.",
"youtube_auth_required_bot_detection": "یوتیوب احراز هویت می‌خواهد (تشخیص ربات). از --yt-dlp-args='--cookies-from-browser BROWSER' استفاده کنید که BROWSER می‌تواند chrome، firefox، brave و غیره باشد.",
"youtube_ytdlp_stderr_error": "خطا در خواندن stderr yt-dlp",
"youtube_invalid_ytdlp_arguments": "آرگومان‌های yt-dlp نامعتبر: %v",
"youtube_failed_create_temp_dir": "ایجاد دایرکتوری موقت ناموفق بود: %v",
"youtube_no_transcript_content": "محتوای رونوشتی در فایل VTT یافت نشد",
"youtube_no_vtt_files_found": "فایل‌های VTT در دایرکتوری یافت نشدند",
"youtube_failed_walk_directory": "پیمایش دایرکتوری ناموفق بود: %v",
"youtube_error_getting_video_details": "خطا در دریافت جزئیات ویدیو: %v",
"youtube_invalid_duration_string": "رشته مدت زمان نامعتبر: %s",
"youtube_error_getting_metadata": "خطا در دریافت متادیتای ویدیو: %v",
"youtube_error_parsing_duration": "خطا در تجزیه مدت زمان ویدیو: %v",
"youtube_error_getting_comments": "خطا در دریافت نظرات: %v",
"youtube_error_saving_csv": "خطا در ذخیره ویدیوها در CSV: %v",
"youtube_no_video_found_with_id": "هیچ ویدیویی با ID یافت نشد: %s",
"youtube_invalid_timestamp_format": "فرمت مهر زمانی نامعتبر: %s",
"youtube_empty_seconds_string": "رشته ثانیه خالی",
"youtube_invalid_seconds_format": "فرمت ثانیه نامعتبر %q: %w",
"error_fetching_playlist_videos": "خطا در دریافت ویدیوهای فهرست پخش: %w",
"openai_api_base_url_not_configured": "URL پایه API برای ارائه‌دهنده %s پیکربندی نشده است",
"openai_failed_to_create_models_url": "ایجاد URL مدل‌ها ناموفق بود: %w",
"openai_unexpected_status_code_with_body": "کد وضعیت غیرمنتظره: %d از ارائه‌دهنده %s، پاسخ: %s",
"openai_unexpected_status_code_read_error_partial": "کد وضعیت غیرمنتظره: %d از ارائه‌دهنده %s (خطا در خواندن: %v)، پاسخ جزئی: %s",
"openai_unexpected_status_code_read_error": "کد وضعیت غیرمنتظره: %d از ارائه‌دهنده %s (خطا در خواندن پاسخ: %v)",
"openai_unable_to_parse_models_response": "تجزیه پاسخ مدل‌ها ناموفق بود; پاسخ خام: %s",
"scraping_not_configured": "قابلیت استخراج داده پیکربندی نشده است. لطفاً Jina را برای فعال‌سازی استخراج تنظیم کنید",
"could_not_determine_home_dir": "نتوانست دایرکتوری خانه کاربر را تعیین کند: %w",
"could_not_stat_env_file": "نتوانست وضعیت فایل .env را بررسی کند: %w",
@@ -53,7 +82,7 @@
"set_top_p": "تنظیم top P",
"stream_help": "پخش زنده",
"set_presence_penalty": "تنظیم جریمه حضور",
"use_model_defaults_raw_help": "استفاده از پیش‌فرض‌های مدل بدون ارسال گزینه‌های گفتگو (مثل دما و غیره) و استفاده از نقش کاربر به جای نقش سیستم برای الگوها.",
"use_model_defaults_raw_help": "از مقادیر پیش‌فرض مدل بدون ارسال گزینه‌های چت (temperature، top_p و غیره) استفاده می‌کند. فقط بر ارائه‌دهندگان سازگار با OpenAI تأثیر می‌گذارد. مدل‌های Anthropic همواره برای رعایت نیازهای خاص هر مدل از انتخاب هوشمند پارامتر استفاده می‌کنند.",
"set_frequency_penalty": "تنظیم جریمه فرکانس",
"list_all_patterns": "فهرست تمام الگوها",
"list_all_available_models": "فهرست تمام مدل‌های موجود",

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "le fournisseur %s ne prend pas en charge la transcription audio",
"transcription_model_required": "un modèle de transcription est requis (utilisez --transcribe-model)",
"youtube_not_configured": "YouTube n'est pas configuré, veuillez exécuter la procédure de configuration",
"youtube_api_key_required": "Clé API YouTube requise pour les commentaires et métadonnées. Exécutez 'fabric --setup' pour configurer",
"youtube_ytdlp_not_found": "yt-dlp introuvable dans PATH. Veuillez installer yt-dlp pour utiliser la fonctionnalité de transcription YouTube",
"youtube_invalid_url": "URL YouTube invalide, impossible d'obtenir l'ID de vidéo ou de liste de lecture : '%s'",
"youtube_url_is_playlist_not_video": "L'URL est une liste de lecture, pas une vidéo",
"youtube_no_video_id_found": "aucun ID de vidéo trouvé dans l'URL",
"youtube_rate_limit_exceeded": "Limite de taux YouTube dépassée. Réessayez plus tard ou utilisez différents arguments yt-dlp comme '--sleep-requests 1' pour ralentir les requêtes.",
"youtube_auth_required_bot_detection": "YouTube nécessite une authentification (détection de bot). Utilisez --yt-dlp-args='--cookies-from-browser BROWSER' où BROWSER peut être chrome, firefox, brave, etc.",
"youtube_ytdlp_stderr_error": "Erreur lors de la lecture du stderr de yt-dlp",
"youtube_invalid_ytdlp_arguments": "arguments yt-dlp invalides : %v",
"youtube_failed_create_temp_dir": "échec de création du répertoire temporaire : %v",
"youtube_no_transcript_content": "aucun contenu de transcription trouvé dans le fichier VTT",
"youtube_no_vtt_files_found": "aucun fichier VTT trouvé dans le répertoire",
"youtube_failed_walk_directory": "échec du parcours du répertoire : %v",
"youtube_error_getting_video_details": "erreur lors de l'obtention des détails de la vidéo : %v",
"youtube_invalid_duration_string": "chaîne de durée invalide : %s",
"youtube_error_getting_metadata": "erreur lors de l'obtention des métadonnées de la vidéo : %v",
"youtube_error_parsing_duration": "erreur lors de l'analyse de la durée de la vidéo : %v",
"youtube_error_getting_comments": "erreur lors de l'obtention des commentaires : %v",
"youtube_error_saving_csv": "erreur lors de l'enregistrement des vidéos en CSV : %v",
"youtube_no_video_found_with_id": "aucune vidéo trouvée avec l'ID : %s",
"youtube_invalid_timestamp_format": "format d'horodatage invalide : %s",
"youtube_empty_seconds_string": "chaîne de secondes vide",
"youtube_invalid_seconds_format": "format de secondes invalide %q : %w",
"error_fetching_playlist_videos": "erreur lors de la récupération des vidéos de la liste de lecture : %w",
"openai_api_base_url_not_configured": "URL de base de l'API non configurée pour le fournisseur %s",
"openai_failed_to_create_models_url": "échec de création de l'URL des modèles : %w",
"openai_unexpected_status_code_with_body": "code d'état inattendu : %d du fournisseur %s, corps de réponse : %s",
"openai_unexpected_status_code_read_error_partial": "code d'état inattendu : %d du fournisseur %s (erreur de lecture : %v), réponse partielle : %s",
"openai_unexpected_status_code_read_error": "code d'état inattendu : %d du fournisseur %s (échec de lecture du corps de réponse : %v)",
"openai_unable_to_parse_models_response": "impossible d'analyser la réponse des modèles ; réponse brute : %s",
"scraping_not_configured": "la fonctionnalité de scraping n'est pas configurée. Veuillez configurer Jina pour activer le scraping",
"could_not_determine_home_dir": "impossible de déterminer le répertoire home de l'utilisateur : %w",
"could_not_stat_env_file": "impossible de vérifier le fichier .env : %w",
@@ -53,7 +82,7 @@
"set_top_p": "Définir le top P",
"stream_help": "Streaming",
"set_presence_penalty": "Définir la pénalité de présence",
"use_model_defaults_raw_help": "Utiliser les valeurs par défaut du modèle sans envoyer d'options de chat (comme la température, etc.) et utiliser le rôle utilisateur au lieu du rôle système pour les motifs.",
"use_model_defaults_raw_help": "Utilise les valeurs par défaut du modèle sans envoyer doptions de discussion (temperature, top_p, etc.). Naffecte que les fournisseurs compatibles avec OpenAI. Les modèles Anthropic utilisent toujours une sélection intelligente des paramètres pour respecter les exigences propres à chaque modèle.",
"set_frequency_penalty": "Définir la pénalité de fréquence",
"list_all_patterns": "Lister tous les motifs",
"list_all_available_models": "Lister tous les modèles disponibles",

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "il fornitore %s non supporta la trascrizione audio",
"transcription_model_required": "è richiesto un modello di trascrizione (usa --transcribe-model)",
"youtube_not_configured": "YouTube non è configurato, per favore esegui la procedura di configurazione",
"youtube_api_key_required": "Chiave API YouTube richiesta per commenti e metadati. Esegui 'fabric --setup' per configurare",
"youtube_ytdlp_not_found": "yt-dlp non trovato in PATH. Per favore installa yt-dlp per usare la funzionalità di trascrizione YouTube",
"youtube_invalid_url": "URL YouTube non valido, impossibile ottenere l'ID del video o della playlist: '%s'",
"youtube_url_is_playlist_not_video": "L'URL è una playlist, non un video",
"youtube_no_video_id_found": "nessun ID video trovato nell'URL",
"youtube_rate_limit_exceeded": "Limite di richieste YouTube superato. Riprova più tardi o usa argomenti yt-dlp diversi come '--sleep-requests 1' per rallentare le richieste.",
"youtube_auth_required_bot_detection": "YouTube richiede autenticazione (rilevamento bot). Usa --yt-dlp-args='--cookies-from-browser BROWSER' dove BROWSER può essere chrome, firefox, brave, ecc.",
"youtube_ytdlp_stderr_error": "Errore durante la lettura dello stderr di yt-dlp",
"youtube_invalid_ytdlp_arguments": "argomenti yt-dlp non validi: %v",
"youtube_failed_create_temp_dir": "impossibile creare la directory temporanea: %v",
"youtube_no_transcript_content": "nessun contenuto di trascrizione trovato nel file VTT",
"youtube_no_vtt_files_found": "nessun file VTT trovato nella directory",
"youtube_failed_walk_directory": "impossibile esplorare la directory: %v",
"youtube_error_getting_video_details": "errore nell'ottenere i dettagli del video: %v",
"youtube_invalid_duration_string": "stringa di durata non valida: %s",
"youtube_error_getting_metadata": "errore nell'ottenere i metadati del video: %v",
"youtube_error_parsing_duration": "errore nell'analizzare la durata del video: %v",
"youtube_error_getting_comments": "errore nell'ottenere i commenti: %v",
"youtube_error_saving_csv": "errore nel salvare i video in CSV: %v",
"youtube_no_video_found_with_id": "nessun video trovato con ID: %s",
"youtube_invalid_timestamp_format": "formato timestamp non valido: %s",
"youtube_empty_seconds_string": "stringa di secondi vuota",
"youtube_invalid_seconds_format": "formato secondi non valido %q: %w",
"error_fetching_playlist_videos": "errore nel recupero dei video della playlist: %w",
"openai_api_base_url_not_configured": "URL base API non configurato per il provider %s",
"openai_failed_to_create_models_url": "impossibile creare URL modelli: %w",
"openai_unexpected_status_code_with_body": "codice di stato imprevisto: %d dal provider %s, corpo risposta: %s",
"openai_unexpected_status_code_read_error_partial": "codice di stato imprevisto: %d dal provider %s (errore lettura corpo: %v), risposta parziale: %s",
"openai_unexpected_status_code_read_error": "codice di stato imprevisto: %d dal provider %s (errore lettura corpo risposta: %v)",
"openai_unable_to_parse_models_response": "impossibile analizzare risposta modelli; risposta grezza: %s",
"scraping_not_configured": "la funzionalità di scraping non è configurata. Per favore configura Jina per abilitare lo scraping",
"could_not_determine_home_dir": "impossibile determinare la directory home dell'utente: %w",
"could_not_stat_env_file": "impossibile verificare il file .env: %w",
@@ -53,7 +82,7 @@
"set_top_p": "Imposta top P",
"stream_help": "Streaming",
"set_presence_penalty": "Imposta penalità di presenza",
"use_model_defaults_raw_help": "Usa i valori predefiniti del modello senza inviare opzioni di chat (come temperatura, ecc.) e usa il ruolo utente invece del ruolo sistema per i pattern.",
"use_model_defaults_raw_help": "Usa i valori predefiniti del modello senza inviare opzioni della chat (temperature, top_p, ecc.). Si applica solo ai provider compatibili con OpenAI. I modelli Anthropic utilizzano sempre una selezione intelligente dei parametri per rispettare i requisiti specifici del modello.",
"set_frequency_penalty": "Imposta penalità di frequenza",
"list_all_patterns": "Elenca tutti i pattern",
"list_all_available_models": "Elenca tutti i modelli disponibili",

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "ベンダー %s は音声転写をサポートしていません",
"transcription_model_required": "転写モデルが必要です(--transcribe-model を使用)",
"youtube_not_configured": "YouTubeが設定されていません。セットアップ手順を実行してください",
"youtube_api_key_required": "コメントとメタデータにはYouTube APIキーが必要です。設定するには 'fabric --setup' を実行してください",
"youtube_ytdlp_not_found": "PATHにyt-dlpが見つかりません。YouTubeトランスクリプト機能を使用するにはyt-dlpをインストールしてください",
"youtube_invalid_url": "無効なYouTube URL、動画またはプレイリストIDを取得できません: '%s'",
"youtube_url_is_playlist_not_video": "URLはプレイリストであり、動画ではありません",
"youtube_no_video_id_found": "URLに動画IDが見つかりません",
"youtube_rate_limit_exceeded": "YouTubeのレート制限を超えました。後でもう一度試すか、'--sleep-requests 1'のような異なるyt-dlp引数を使用してリクエストを遅くしてください。",
"youtube_auth_required_bot_detection": "YouTubeは認証を必要としていますボット検出。--yt-dlp-args='--cookies-from-browser BROWSER'を使用してください。BROWSERはchrome、firefox、braveなどです。",
"youtube_ytdlp_stderr_error": "yt-dlp stderrの読み取りエラー",
"youtube_invalid_ytdlp_arguments": "無効なyt-dlp引数: %v",
"youtube_failed_create_temp_dir": "一時ディレクトリの作成に失敗しました: %v",
"youtube_no_transcript_content": "VTTファイルにトランスクリプトコンテンツが見つかりません",
"youtube_no_vtt_files_found": "ディレクトリにVTTファイルが見つかりません",
"youtube_failed_walk_directory": "ディレクトリの走査に失敗しました: %v",
"youtube_error_getting_video_details": "動画の詳細取得エラー: %v",
"youtube_invalid_duration_string": "無効な長さ文字列: %s",
"youtube_error_getting_metadata": "動画のメタデータ取得エラー: %v",
"youtube_error_parsing_duration": "動画の長さ解析エラー: %v",
"youtube_error_getting_comments": "コメント取得エラー: %v",
"youtube_error_saving_csv": "動画のCSV保存エラー: %v",
"youtube_no_video_found_with_id": "IDの動画が見つかりません: %s",
"youtube_invalid_timestamp_format": "無効なタイムスタンプ形式: %s",
"youtube_empty_seconds_string": "空の秒文字列",
"youtube_invalid_seconds_format": "無効な秒形式 %q: %w",
"error_fetching_playlist_videos": "プレイリスト動画の取得エラー: %w",
"openai_api_base_url_not_configured": "プロバイダー %s のAPIベースURLが設定されていません",
"openai_failed_to_create_models_url": "モデルURLの作成に失敗しました: %w",
"openai_unexpected_status_code_with_body": "予期しないステータスコード: プロバイダー %s から %d、レスポンス本文: %s",
"openai_unexpected_status_code_read_error_partial": "予期しないステータスコード: プロバイダー %s から %d (本文読み取りエラー: %v)、部分的なレスポンス: %s",
"openai_unexpected_status_code_read_error": "予期しないステータスコード: プロバイダー %s から %d (レスポンス本文の読み取りに失敗: %v)",
"openai_unable_to_parse_models_response": "モデルレスポンスの解析に失敗しました; 生のレスポンス: %s",
"scraping_not_configured": "スクレイピング機能が設定されていません。スクレイピングを有効にするためにJinaを設定してください",
"could_not_determine_home_dir": "ユーザーのホームディレクトリを特定できませんでした: %w",
"could_not_stat_env_file": ".envファイルの状態を確認できませんでした: %w",
@@ -53,7 +82,7 @@
"set_top_p": "Top Pを設定",
"stream_help": "ストリーミング",
"set_presence_penalty": "プレゼンスペナルティを設定",
"use_model_defaults_raw_help": "チャットオプション(温度など)を送信せずにモデルのデフォルトを使用し、パターンにシステムロールではなくユーザーロールを使用します。",
"use_model_defaults_raw_help": "チャットオプション(temperature、top_p など)を送信せずにモデルのデフォルトを使用します。OpenAI 互換プロバイダーにのみ適用されます。Anthropic モデルは常に、モデル固有の要件に準拠するためにスマートなパラメーター選択を使用します。",
"set_frequency_penalty": "頻度ペナルティを設定",
"list_all_patterns": "すべてのパターンを一覧表示",
"list_all_available_models": "すべての利用可能なモデルを一覧表示",

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "o fornecedor %s não suporta transcrição de áudio",
"transcription_model_required": "modelo de transcrição é necessário (use --transcribe-model)",
"youtube_not_configured": "YouTube não está configurado, por favor execute o procedimento de configuração",
"youtube_api_key_required": "Chave de API do YouTube necessária para comentários e metadados. Execute 'fabric --setup' para configurar",
"youtube_ytdlp_not_found": "yt-dlp não encontrado no PATH. Por favor instale o yt-dlp para usar a funcionalidade de transcrição do YouTube",
"youtube_invalid_url": "URL do YouTube inválida, não é possível obter o ID do vídeo ou da playlist: '%s'",
"youtube_url_is_playlist_not_video": "A URL é uma playlist, não um vídeo",
"youtube_no_video_id_found": "nenhum ID de vídeo encontrado na URL",
"youtube_rate_limit_exceeded": "Limite de taxa do YouTube excedido. Tente novamente mais tarde ou use argumentos diferentes do yt-dlp como '--sleep-requests 1' para desacelerar as requisições.",
"youtube_auth_required_bot_detection": "YouTube requer autenticação (detecção de bot). Use --yt-dlp-args='--cookies-from-browser BROWSER' onde BROWSER pode ser chrome, firefox, brave, etc.",
"youtube_ytdlp_stderr_error": "Erro ao ler stderr do yt-dlp",
"youtube_invalid_ytdlp_arguments": "argumentos do yt-dlp inválidos: %v",
"youtube_failed_create_temp_dir": "falha ao criar diretório temporário: %v",
"youtube_no_transcript_content": "nenhum conteúdo de transcrição encontrado no arquivo VTT",
"youtube_no_vtt_files_found": "nenhum arquivo VTT encontrado no diretório",
"youtube_failed_walk_directory": "falha ao percorrer o diretório: %v",
"youtube_error_getting_video_details": "erro ao obter detalhes do vídeo: %v",
"youtube_invalid_duration_string": "string de duração inválida: %s",
"youtube_error_getting_metadata": "erro ao obter metadados do vídeo: %v",
"youtube_error_parsing_duration": "erro ao analisar a duração do vídeo: %v",
"youtube_error_getting_comments": "erro ao obter comentários: %v",
"youtube_error_saving_csv": "erro ao salvar vídeos em CSV: %v",
"youtube_no_video_found_with_id": "nenhum vídeo encontrado com o ID: %s",
"youtube_invalid_timestamp_format": "formato de timestamp inválido: %s",
"youtube_empty_seconds_string": "string de segundos vazia",
"youtube_invalid_seconds_format": "formato de segundos inválido %q: %w",
"error_fetching_playlist_videos": "erro ao buscar vídeos da playlist: %w",
"openai_api_base_url_not_configured": "URL base da API não configurada para o provedor %s",
"openai_failed_to_create_models_url": "falha ao criar URL de modelos: %w",
"openai_unexpected_status_code_with_body": "código de status inesperado: %d do provedor %s, corpo da resposta: %s",
"openai_unexpected_status_code_read_error_partial": "código de status inesperado: %d do provedor %s (erro ao ler corpo: %v), resposta parcial: %s",
"openai_unexpected_status_code_read_error": "código de status inesperado: %d do provedor %s (falha ao ler corpo da resposta: %v)",
"openai_unable_to_parse_models_response": "não foi possível analisar a resposta de modelos; resposta bruta: %s",
"scraping_not_configured": "funcionalidade de scraping não está configurada. Por favor configure o Jina para ativar o scraping",
"could_not_determine_home_dir": "não foi possível determinar o diretório home do usuário: %w",
"could_not_stat_env_file": "não foi possível verificar o arquivo .env: %w",
@@ -53,7 +82,7 @@
"set_top_p": "Definir top P",
"stream_help": "Streaming",
"set_presence_penalty": "Definir penalidade de presença",
"use_model_defaults_raw_help": "Usar as configurações padrão do modelo sem enviar opções de chat (como temperatura, etc.) e usar o papel de usuário em vez do papel de sistema para padrões.",
"use_model_defaults_raw_help": "Usa os padrões do modelo sem enviar opções de chat (temperature, top_p etc.). Afeta apenas provedores compatíveis com o OpenAI. Os modelos da Anthropic sempre utilizam seleção inteligente de parâmetros para cumprir os requisitos específicos de cada modelo.",
"set_frequency_penalty": "Definir penalidade de frequência",
"list_all_patterns": "Listar todos os padrões/patterns",
"list_all_available_models": "Listar todos os modelos disponíveis",
@@ -133,4 +162,4 @@
"no_description_available": "Nenhuma descrição disponível",
"i18n_download_failed": "Falha ao baixar tradução para o idioma '%s': %v",
"i18n_load_failed": "Falha ao carregar arquivo de tradução: %v"
}
}

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "o fornecedor %s não suporta transcrição de áudio",
"transcription_model_required": "modelo de transcrição é necessário (use --transcribe-model)",
"youtube_not_configured": "YouTube não está configurado, por favor execute o procedimento de configuração",
"youtube_api_key_required": "Chave de API do YouTube necessária para comentários e metadados. Execute 'fabric --setup' para configurar",
"youtube_ytdlp_not_found": "yt-dlp não encontrado no PATH. Por favor instale o yt-dlp para usar a funcionalidade de transcrição do YouTube",
"youtube_invalid_url": "URL do YouTube inválido, não é possível obter o ID do vídeo ou da lista de reprodução: '%s'",
"youtube_url_is_playlist_not_video": "O URL é uma lista de reprodução, não um vídeo",
"youtube_no_video_id_found": "nenhum ID de vídeo encontrado no URL",
"youtube_rate_limit_exceeded": "Limite de taxa do YouTube excedido. Tente novamente mais tarde ou utilize argumentos diferentes do yt-dlp como '--sleep-requests 1' para desacelerar os pedidos.",
"youtube_auth_required_bot_detection": "YouTube requer autenticação (deteção de bot). Use --yt-dlp-args='--cookies-from-browser BROWSER' onde BROWSER pode ser chrome, firefox, brave, etc.",
"youtube_ytdlp_stderr_error": "Erro ao ler stderr do yt-dlp",
"youtube_invalid_ytdlp_arguments": "argumentos do yt-dlp inválidos: %v",
"youtube_failed_create_temp_dir": "falha ao criar diretório temporário: %v",
"youtube_no_transcript_content": "nenhum conteúdo de transcrição encontrado no ficheiro VTT",
"youtube_no_vtt_files_found": "nenhum ficheiro VTT encontrado no diretório",
"youtube_failed_walk_directory": "falha ao percorrer o diretório: %v",
"youtube_error_getting_video_details": "erro ao obter detalhes do vídeo: %v",
"youtube_invalid_duration_string": "cadeia de duração inválida: %s",
"youtube_error_getting_metadata": "erro ao obter metadados do vídeo: %v",
"youtube_error_parsing_duration": "erro ao analisar a duração do vídeo: %v",
"youtube_error_getting_comments": "erro ao obter comentários: %v",
"youtube_error_saving_csv": "erro ao guardar vídeos em CSV: %v",
"youtube_no_video_found_with_id": "nenhum vídeo encontrado com o ID: %s",
"youtube_invalid_timestamp_format": "formato de timestamp inválido: %s",
"youtube_empty_seconds_string": "cadeia de segundos vazia",
"youtube_invalid_seconds_format": "formato de segundos inválido %q: %w",
"error_fetching_playlist_videos": "erro ao obter vídeos da playlist: %w",
"openai_api_base_url_not_configured": "URL base da API não configurado para o fornecedor %s",
"openai_failed_to_create_models_url": "falha ao criar URL de modelos: %w",
"openai_unexpected_status_code_with_body": "código de estado inesperado: %d do fornecedor %s, corpo da resposta: %s",
"openai_unexpected_status_code_read_error_partial": "código de estado inesperado: %d do fornecedor %s (erro ao ler corpo: %v), resposta parcial: %s",
"openai_unexpected_status_code_read_error": "código de estado inesperado: %d do fornecedor %s (falha ao ler corpo da resposta: %v)",
"openai_unable_to_parse_models_response": "não foi possível analisar a resposta de modelos; resposta bruta: %s",
"scraping_not_configured": "funcionalidade de scraping não está configurada. Por favor configure o Jina para ativar o scraping",
"could_not_determine_home_dir": "não foi possível determinar o diretório home do utilizador: %w",
"could_not_stat_env_file": "não foi possível verificar o ficheiro .env: %w",
@@ -53,7 +82,7 @@
"set_top_p": "Definir top P",
"stream_help": "Streaming",
"set_presence_penalty": "Definir penalidade de presença",
"use_model_defaults_raw_help": "Usar as predefinições do modelo sem enviar opções de chat (como temperatura, etc.) e usar o papel de utilizador em vez do papel de sistema para padrões.",
"use_model_defaults_raw_help": "Utiliza os valores predefinidos do modelo sem enviar opções de chat (temperature, top_p, etc.). Só afeta fornecedores compatíveis com o OpenAI. Os modelos Anthropic usam sempre uma seleção inteligente de parâmetros para cumprir os requisitos específicos do modelo.",
"set_frequency_penalty": "Definir penalidade de frequência",
"list_all_patterns": "Listar todos os padrões",
"list_all_available_models": "Listar todos os modelos disponíveis",

View File

@@ -4,7 +4,36 @@
"vendor_no_transcription_support": "供应商 %s 不支持音频转录",
"transcription_model_required": "需要转录模型(使用 --transcribe-model",
"youtube_not_configured": "YouTube 未配置,请运行设置程序",
"youtube_api_key_required": "评论和元数据需要 YouTube API 密钥。运行 'fabric --setup' 进行配置",
"youtube_ytdlp_not_found": "在 PATH 中未找到 yt-dlp。请安装 yt-dlp 以使用 YouTube 转录功能",
"youtube_invalid_url": "无效的 YouTube URL无法获取视频或播放列表 ID'%s'",
"youtube_url_is_playlist_not_video": "URL 是播放列表,而不是视频",
"youtube_no_video_id_found": "在 URL 中未找到视频 ID",
"youtube_rate_limit_exceeded": "超过 YouTube 速率限制。请稍后重试,或使用不同的 yt-dlp 参数(如 '--sleep-requests 1')来减慢请求速度。",
"youtube_auth_required_bot_detection": "YouTube 需要身份验证(机器人检测)。使用 --yt-dlp-args='--cookies-from-browser BROWSER',其中 BROWSER 可以是 chrome、firefox、brave 等。",
"youtube_ytdlp_stderr_error": "读取 yt-dlp stderr 时出错",
"youtube_invalid_ytdlp_arguments": "无效的 yt-dlp 参数:%v",
"youtube_failed_create_temp_dir": "创建临时目录失败:%v",
"youtube_no_transcript_content": "在 VTT 文件中未找到转录内容",
"youtube_no_vtt_files_found": "在目录中未找到 VTT 文件",
"youtube_failed_walk_directory": "遍历目录失败:%v",
"youtube_error_getting_video_details": "获取视频详情时出错:%v",
"youtube_invalid_duration_string": "无效的时长字符串:%s",
"youtube_error_getting_metadata": "获取视频元数据时出错:%v",
"youtube_error_parsing_duration": "解析视频时长时出错:%v",
"youtube_error_getting_comments": "获取评论时出错:%v",
"youtube_error_saving_csv": "将视频保存为 CSV 时出错:%v",
"youtube_no_video_found_with_id": "未找到 ID 为 %s 的视频",
"youtube_invalid_timestamp_format": "无效的时间戳格式:%s",
"youtube_empty_seconds_string": "秒数字符串为空",
"youtube_invalid_seconds_format": "无效的秒数格式 %q%w",
"error_fetching_playlist_videos": "获取播放列表视频时出错: %w",
"openai_api_base_url_not_configured": "未为提供商 %s 配置 API 基础 URL",
"openai_failed_to_create_models_url": "创建模型 URL 失败:%w",
"openai_unexpected_status_code_with_body": "意外的状态码:来自提供商 %s 的 %d响应主体%s",
"openai_unexpected_status_code_read_error_partial": "意外的状态码:来自提供商 %s 的 %d读取主体错误%v部分响应%s",
"openai_unexpected_status_code_read_error": "意外的状态码:来自提供商 %s 的 %d读取响应主体失败%v)",
"openai_unable_to_parse_models_response": "无法解析模型响应;原始响应:%s",
"scraping_not_configured": "抓取功能未配置。请设置 Jina 以启用抓取功能",
"could_not_determine_home_dir": "无法确定用户主目录: %w",
"could_not_stat_env_file": "无法获取 .env 文件状态: %w",
@@ -53,7 +82,7 @@
"set_top_p": "设置 top P",
"stream_help": "流式传输",
"set_presence_penalty": "设置存在惩罚",
"use_model_defaults_raw_help": "使用模型默认设置,不发送聊天选项(如温度等),对于模式使用用户角色而非系统角色。",
"use_model_defaults_raw_help": "在不发送聊天选项temperature、top_p 等)的情况下使用模型默认值。仅影响兼容 OpenAI 的提供商。Anthropic 模型始终使用智能参数选择以满足特定模型的要求。",
"set_frequency_penalty": "设置频率惩罚",
"list_all_patterns": "列出所有模式",
"list_all_available_models": "列出所有可用模型",

View File

@@ -51,7 +51,7 @@ func LevelFromInt(i int) Level {
}
// Debug writes a debug message if the global level permits.
func Debug(l Level, format string, a ...interface{}) {
func Debug(l Level, format string, a ...any) {
mu.RLock()
current := level
w := output
@@ -63,7 +63,7 @@ func Debug(l Level, format string, a ...interface{}) {
// Log writes a message unconditionally to stderr.
// This is for important messages that should always be shown regardless of debug level.
func Log(format string, a ...interface{}) {
func Log(format string, a ...any) {
mu.RLock()
w := output
mu.RUnlock()

View File

@@ -4,6 +4,7 @@ import (
"context"
"fmt"
"net/http"
"os"
"strconv"
"strings"
@@ -50,6 +51,10 @@ func NewClient() (ret *Client) {
string(anthropic.ModelClaudeOpus4_1_20250805),
string(anthropic.ModelClaudeSonnet4_5),
string(anthropic.ModelClaudeSonnet4_5_20250929),
string(anthropic.ModelClaudeOpus4_5_20251101),
string(anthropic.ModelClaudeOpus4_5),
string(anthropic.ModelClaudeHaiku4_5),
string(anthropic.ModelClaudeHaiku4_5_20251001),
}
ret.modelBetas = map[string][]string{
@@ -212,7 +217,7 @@ func (an *Client) SendStream(
}
if stream.Err() != nil {
fmt.Printf("Messages stream error: %v\n", stream.Err())
fmt.Fprintf(os.Stderr, "Messages stream error: %v\n", stream.Err())
}
close(channel)
return
@@ -356,7 +361,7 @@ func (an *Client) toMessages(msgs []*chat.ChatCompletionMessage) (ret []anthropi
lastRoleWasUser := false
for _, msg := range msgs {
if msg.Content == "" {
if strings.TrimSpace(msg.Content) == "" {
continue // Skip empty messages
}

View File

@@ -52,7 +52,7 @@ func createExpiredToken(accessToken, refreshToken string) *util.OAuthToken {
}
// mockTokenServer creates a mock OAuth token server for testing
func mockTokenServer(_ *testing.T, responses map[string]interface{}) *httptest.Server {
func mockTokenServer(_ *testing.T, responses map[string]any) *httptest.Server {
return httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.URL.Path != "/v1/oauth/token" {
http.NotFound(w, r)
@@ -80,7 +80,7 @@ func mockTokenServer(_ *testing.T, responses map[string]interface{}) *httptest.S
w.Header().Set("Content-Type", "application/json")
if errorResp, ok := response.(map[string]interface{}); ok && errorResp["error"] != nil {
if errorResp, ok := response.(map[string]any); ok && errorResp["error"] != nil {
w.WriteHeader(http.StatusBadRequest)
}
@@ -114,8 +114,8 @@ func TestGeneratePKCE(t *testing.T) {
func TestExchangeToken_Success(t *testing.T) {
// Create mock server
server := mockTokenServer(t, map[string]interface{}{
"authorization_code": map[string]interface{}{
server := mockTokenServer(t, map[string]any{
"authorization_code": map[string]any{
"access_token": "test_access_token",
"refresh_token": "test_refresh_token",
"expires_in": 3600,
@@ -161,8 +161,8 @@ func TestRefreshToken_Success(t *testing.T) {
os.WriteFile(tokenPath, data, 0600)
// Create mock server for refresh
server := mockTokenServer(t, map[string]interface{}{
"refresh_token": map[string]interface{}{
server := mockTokenServer(t, map[string]any{
"refresh_token": map[string]any{
"access_token": "new_access_token",
"refresh_token": "new_refresh_token",
"expires_in": 3600,
@@ -416,7 +416,7 @@ func TestGetValidTokenWithValidToken(t *testing.T) {
// Benchmark tests
func BenchmarkGeneratePKCE(b *testing.B) {
for i := 0; i < b.N; i++ {
for b.Loop() {
_, _, err := generatePKCE()
if err != nil {
b.Fatal(err)
@@ -427,8 +427,7 @@ func BenchmarkGeneratePKCE(b *testing.B) {
func BenchmarkTokenIsExpired(b *testing.B) {
token := createTestToken("access", "refresh", 3600)
b.ResetTimer()
for i := 0; i < b.N; i++ {
for b.Loop() {
token.IsExpired(5)
}
}

View File

@@ -131,6 +131,8 @@ func (o *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions, channel chan string) (err error) {
ctx := context.Background()
defer close(channel)
var client *genai.Client
if client, err = genai.NewClient(ctx, &genai.ClientConfig{
APIKey: o.ApiKey.Value,
@@ -153,8 +155,7 @@ func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
for response, err := range stream {
if err != nil {
channel <- fmt.Sprintf("Error: %v\n", err)
close(channel)
break
return err
}
text := o.extractTextFromResponse(response)
@@ -162,7 +163,6 @@ func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
channel <- text
}
}
close(channel)
return
}
@@ -456,7 +456,7 @@ func (o *Client) convertMessages(msgs []*chat.ChatCompletionMessage) []*genai.Co
content.Role = "user"
}
if msg.Content != "" {
if strings.TrimSpace(msg.Content) != "" {
content.Parts = append(content.Parts, &genai.Part{Text: msg.Content})
}

View File

@@ -3,6 +3,7 @@ package gemini
import (
"fmt"
"sort"
"strings"
)
// GeminiVoice represents a Gemini TTS voice with its characteristics
@@ -126,16 +127,17 @@ func ListGeminiVoices(shellCompleteMode bool) string {
if shellCompleteMode {
// For shell completion, just return voice names
names := GetGeminiVoiceNames()
result := ""
var result strings.Builder
for _, name := range names {
result += name + "\n"
result.WriteString(name + "\n")
}
return result
return result.String()
}
// For human-readable output
voices := GetGeminiVoices()
result := "Available Gemini Text-to-Speech voices:\n\n"
var result strings.Builder
result.WriteString("Available Gemini Text-to-Speech voices:\n\n")
// Group by characteristics for better readability
groups := map[string][]GeminiVoice{
@@ -186,22 +188,22 @@ func ListGeminiVoices(shellCompleteMode bool) string {
// Output grouped voices
for groupName, groupVoices := range groups {
if len(groupVoices) > 0 {
result += fmt.Sprintf("%s:\n", groupName)
result.WriteString(fmt.Sprintf("%s:\n", groupName))
for _, voice := range groupVoices {
defaultStr := ""
if voice.Name == "Kore" {
defaultStr = " (default)"
}
result += fmt.Sprintf(" %-15s - %s%s\n", voice.Name, voice.Description, defaultStr)
result.WriteString(fmt.Sprintf(" %-15s - %s%s\n", voice.Name, voice.Description, defaultStr))
}
result += "\n"
result.WriteString("\n")
}
}
result += "Use --voice <voice_name> to select a specific voice.\n"
result += "Example: fabric --voice Charon -m gemini-2.5-flash-preview-tts -o output.wav \"Hello world\"\n"
result.WriteString("Use --voice <voice_name> to select a specific voice.\n")
result.WriteString("Example: fabric --voice Charon -m gemini-2.5-flash-preview-tts -o output.wav \"Hello world\"\n")
return result
return result.String()
}
// NOTE: This implementation maintains a curated list based on official Google documentation.

View File

@@ -90,7 +90,7 @@ func (c *Client) ListModels() ([]string, error) {
func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions, channel chan string) (err error) {
url := fmt.Sprintf("%s/chat/completions", c.ApiUrl.Value)
payload := map[string]interface{}{
payload := map[string]any{
"messages": msgs,
"model": opts.Model,
"stream": true, // Enable streaming
@@ -140,27 +140,27 @@ func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
continue
}
if bytes.HasPrefix(line, []byte("data: ")) {
line = bytes.TrimPrefix(line, []byte("data: "))
if after, ok := bytes.CutPrefix(line, []byte("data: ")); ok {
line = after
}
if string(line) == "[DONE]" {
break
}
var result map[string]interface{}
var result map[string]any
if err = json.Unmarshal(line, &result); err != nil {
continue
}
var choices []interface{}
var choices []any
var ok bool
if choices, ok = result["choices"].([]interface{}); !ok || len(choices) == 0 {
if choices, ok = result["choices"].([]any); !ok || len(choices) == 0 {
continue
}
var delta map[string]interface{}
if delta, ok = choices[0].(map[string]interface{})["delta"].(map[string]interface{}); !ok {
var delta map[string]any
if delta, ok = choices[0].(map[string]any)["delta"].(map[string]any); !ok {
continue
}
@@ -176,7 +176,7 @@ func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions) (content string, err error) {
url := fmt.Sprintf("%s/chat/completions", c.ApiUrl.Value)
payload := map[string]interface{}{
payload := map[string]any{
"messages": msgs,
"model": opts.Model,
// Add other options from opts if supported by LM Studio
@@ -208,21 +208,21 @@ func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
return
}
var result map[string]interface{}
var result map[string]any
if err = json.NewDecoder(resp.Body).Decode(&result); err != nil {
err = fmt.Errorf("failed to decode response: %w", err)
return
}
var choices []interface{}
var choices []any
var ok bool
if choices, ok = result["choices"].([]interface{}); !ok || len(choices) == 0 {
if choices, ok = result["choices"].([]any); !ok || len(choices) == 0 {
err = fmt.Errorf("invalid response format: missing or empty choices")
return
}
var message map[string]interface{}
if message, ok = choices[0].(map[string]interface{})["message"].(map[string]interface{}); !ok {
var message map[string]any
if message, ok = choices[0].(map[string]any)["message"].(map[string]any); !ok {
err = fmt.Errorf("invalid response format: missing message in first choice")
return
}
@@ -238,7 +238,7 @@ func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
func (c *Client) Complete(ctx context.Context, prompt string, opts *domain.ChatOptions) (text string, err error) {
url := fmt.Sprintf("%s/completions", c.ApiUrl.Value)
payload := map[string]interface{}{
payload := map[string]any{
"prompt": prompt,
"model": opts.Model,
// Add other options from opts if supported by LM Studio
@@ -270,20 +270,20 @@ func (c *Client) Complete(ctx context.Context, prompt string, opts *domain.ChatO
return
}
var result map[string]interface{}
var result map[string]any
if err = json.NewDecoder(resp.Body).Decode(&result); err != nil {
err = fmt.Errorf("failed to decode response: %w", err)
return
}
var choices []interface{}
var choices []any
var ok bool
if choices, ok = result["choices"].([]interface{}); !ok || len(choices) == 0 {
if choices, ok = result["choices"].([]any); !ok || len(choices) == 0 {
err = fmt.Errorf("invalid response format: missing or empty choices")
return
}
if text, ok = choices[0].(map[string]interface{})["text"].(string); !ok {
if text, ok = choices[0].(map[string]any)["text"].(string); !ok {
err = fmt.Errorf("invalid response format: missing or non-string text in first choice")
return
}
@@ -294,7 +294,7 @@ func (c *Client) Complete(ctx context.Context, prompt string, opts *domain.ChatO
func (c *Client) GetEmbeddings(ctx context.Context, input string, opts *domain.ChatOptions) (embeddings []float64, err error) {
url := fmt.Sprintf("%s/embeddings", c.ApiUrl.Value)
payload := map[string]interface{}{
payload := map[string]any{
"input": input,
"model": opts.Model,
// Add other options from opts if supported by LM Studio

View File

@@ -17,6 +17,35 @@ type VendorsModels struct {
*util.GroupsItemsSelectorString
}
// FilterByVendor returns a new VendorsModels containing only the specified vendor's models.
// Vendor matching is case-insensitive (e.g., "OpenAI", "openai", and "OPENAI" all match).
// If the vendor is not found, an empty VendorsModels is returned.
func (o *VendorsModels) FilterByVendor(vendor string) *VendorsModels {
filtered := NewVendorsModels()
for _, groupItems := range o.GroupsItems {
if strings.EqualFold(groupItems.Group, vendor) {
filtered.AddGroupItems(groupItems.Group, groupItems.Items...)
break
}
}
return filtered
}
// FindModelNameCaseInsensitive returns the actual model name from available models,
// matching case-insensitively. Returns empty string if not found.
// For example, if the available models contain "gpt-4o" and user queries "GPT-4O",
// this returns "gpt-4o" (the actual model name that should be sent to the API).
func (o *VendorsModels) FindModelNameCaseInsensitive(modelQuery string) string {
for _, groupItems := range o.GroupsItems {
for _, item := range groupItems.Items {
if strings.EqualFold(item, modelQuery) {
return item
}
}
}
return ""
}
// PrintWithVendor prints models including their vendor on each line.
// When shellCompleteList is true, output is suitable for shell completion.
// Default vendor and model are highlighted with an asterisk.

View File

@@ -19,19 +19,19 @@ func TestNewVendorsModels(t *testing.T) {
func TestFindVendorsByModelFirst(t *testing.T) {
vendors := NewVendorsModels()
vendors.AddGroupItems("vendor1", []string{"model1", "model2"}...)
vendors.AddGroupItems("Vendor1", []string{"Model1", "model2"}...)
vendor := vendors.FindGroupsByItemFirst("model1")
if vendor != "vendor1" {
t.Fatalf("FindVendorsByModelFirst() = %v, want %v", vendor, "vendor1")
if vendor != "Vendor1" {
t.Fatalf("FindVendorsByModelFirst() = %v, want %v", vendor, "Vendor1")
}
}
func TestFindVendorsByModel(t *testing.T) {
vendors := NewVendorsModels()
vendors.AddGroupItems("vendor1", []string{"model1", "model2"}...)
foundVendors := vendors.FindGroupsByItem("model1")
if len(foundVendors) != 1 || foundVendors[0] != "vendor1" {
t.Fatalf("FindVendorsByModel() = %v, want %v", foundVendors, []string{"vendor1"})
vendors.AddGroupItems("Vendor1", []string{"Model1", "model2"}...)
foundVendors := vendors.FindGroupsByItem("MODEL1")
if len(foundVendors) != 1 || foundVendors[0] != "Vendor1" {
t.Fatalf("FindVendorsByModel() = %v, want %v", foundVendors, []string{"Vendor1"})
}
}
@@ -54,3 +54,51 @@ func TestPrintWithVendorMarksDefault(t *testing.T) {
t.Fatalf("default model not marked: %s", out)
}
}
func TestFilterByVendorCaseInsensitive(t *testing.T) {
vendors := NewVendorsModels()
vendors.AddGroupItems("vendor1", []string{"model1"}...)
vendors.AddGroupItems("vendor2", []string{"model2"}...)
filtered := vendors.FilterByVendor("VENDOR2")
if len(filtered.GroupsItems) != 1 {
t.Fatalf("expected 1 vendor group, got %d", len(filtered.GroupsItems))
}
if filtered.GroupsItems[0].Group != "vendor2" {
t.Fatalf("expected vendor2, got %s", filtered.GroupsItems[0].Group)
}
if len(filtered.GroupsItems[0].Items) != 1 || filtered.GroupsItems[0].Items[0] != "model2" {
t.Fatalf("unexpected models for vendor2: %v", filtered.GroupsItems[0].Items)
}
}
func TestFindModelNameCaseInsensitive(t *testing.T) {
vendors := NewVendorsModels()
vendors.AddGroupItems("OpenAI", []string{"gpt-4o", "gpt-5"}...)
vendors.AddGroupItems("Anthropic", []string{"claude-3-opus"}...)
tests := []struct {
name string
query string
expectedModel string
}{
{"exact match lowercase", "gpt-4o", "gpt-4o"},
{"uppercase query", "GPT-4O", "gpt-4o"},
{"mixed case query", "GpT-5", "gpt-5"},
{"exact match with hyphens", "claude-3-opus", "claude-3-opus"},
{"uppercase with hyphens", "CLAUDE-3-OPUS", "claude-3-opus"},
{"non-existent model", "gpt-999", ""},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := vendors.FindModelNameCaseInsensitive(tt.query)
if result != tt.expectedModel {
t.Errorf("FindModelNameCaseInsensitive(%q) = %q, want %q", tt.query, result, tt.expectedModel)
}
})
}
}

View File

@@ -2,7 +2,9 @@ package ollama
import (
"context"
"encoding/base64"
"fmt"
"io"
"net/http"
"net/url"
"os"
@@ -10,11 +12,10 @@ import (
"time"
"github.com/danielmiessler/fabric/internal/chat"
ollamaapi "github.com/ollama/ollama/api"
"github.com/samber/lo"
"github.com/danielmiessler/fabric/internal/domain"
debuglog "github.com/danielmiessler/fabric/internal/log"
"github.com/danielmiessler/fabric/internal/plugins"
ollamaapi "github.com/ollama/ollama/api"
)
const defaultBaseUrl = "http://localhost:11434"
@@ -48,6 +49,7 @@ type Client struct {
apiUrl *url.URL
client *ollamaapi.Client
ApiHttpTimeout *plugins.SetupQuestion
httpClient *http.Client
}
type transport_sec struct {
@@ -84,7 +86,8 @@ func (o *Client) configure() (err error) {
}
}
o.client = ollamaapi.NewClient(o.apiUrl, &http.Client{Timeout: timeout, Transport: &transport_sec{underlyingTransport: http.DefaultTransport, ApiKey: o.ApiKey}})
o.httpClient = &http.Client{Timeout: timeout, Transport: &transport_sec{underlyingTransport: http.DefaultTransport, ApiKey: o.ApiKey}}
o.client = ollamaapi.NewClient(o.apiUrl, o.httpClient)
return
}
@@ -104,15 +107,18 @@ func (o *Client) ListModels() (ret []string, err error) {
}
func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions, channel chan string) (err error) {
req := o.createChatRequest(msgs, opts)
ctx := context.Background()
var req ollamaapi.ChatRequest
if req, err = o.createChatRequest(ctx, msgs, opts); err != nil {
return
}
respFunc := func(resp ollamaapi.ChatResponse) (streamErr error) {
channel <- resp.Message.Content
return
}
ctx := context.Background()
if err = o.client.Chat(ctx, &req, respFunc); err != nil {
return
}
@@ -124,7 +130,10 @@ func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
func (o *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions) (ret string, err error) {
bf := false
req := o.createChatRequest(msgs, opts)
var req ollamaapi.ChatRequest
if req, err = o.createChatRequest(ctx, msgs, opts); err != nil {
return
}
req.Stream = &bf
respFunc := func(resp ollamaapi.ChatResponse) (streamErr error) {
@@ -133,17 +142,20 @@ func (o *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
}
if err = o.client.Chat(ctx, &req, respFunc); err != nil {
fmt.Printf("FRED --> %s\n", err)
debuglog.Debug(debuglog.Basic, "Ollama chat request failed: %v\n", err)
}
return
}
func (o *Client) createChatRequest(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions) (ret ollamaapi.ChatRequest) {
messages := lo.Map(msgs, func(message *chat.ChatCompletionMessage, _ int) (ret ollamaapi.Message) {
return ollamaapi.Message{Role: message.Role, Content: message.Content}
})
func (o *Client) createChatRequest(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions) (ret ollamaapi.ChatRequest, err error) {
messages := make([]ollamaapi.Message, len(msgs))
for i, message := range msgs {
if messages[i], err = o.convertMessage(ctx, message); err != nil {
return
}
}
options := map[string]interface{}{
options := map[string]any{
"temperature": opts.Temperature,
"presence_penalty": opts.PresencePenalty,
"frequency_penalty": opts.FrequencyPenalty,
@@ -162,14 +174,85 @@ func (o *Client) createChatRequest(msgs []*chat.ChatCompletionMessage, opts *dom
return
}
func (o *Client) convertMessage(ctx context.Context, message *chat.ChatCompletionMessage) (ret ollamaapi.Message, err error) {
ret = ollamaapi.Message{Role: message.Role, Content: message.Content}
if len(message.MultiContent) == 0 {
return
}
// Pre-allocate with capacity hint
textParts := make([]string, 0, len(message.MultiContent))
if strings.TrimSpace(ret.Content) != "" {
textParts = append(textParts, strings.TrimSpace(ret.Content))
}
for _, part := range message.MultiContent {
switch part.Type {
case chat.ChatMessagePartTypeText:
if trimmed := strings.TrimSpace(part.Text); trimmed != "" {
textParts = append(textParts, trimmed)
}
case chat.ChatMessagePartTypeImageURL:
// Nil guard
if part.ImageURL == nil || part.ImageURL.URL == "" {
continue
}
var img []byte
if img, err = o.loadImageBytes(ctx, part.ImageURL.URL); err != nil {
return
}
ret.Images = append(ret.Images, ollamaapi.ImageData(img))
}
}
ret.Content = strings.Join(textParts, "\n")
return
}
func (o *Client) loadImageBytes(ctx context.Context, imageURL string) (ret []byte, err error) {
// Handle data URLs (base64 encoded)
if strings.HasPrefix(imageURL, "data:") {
parts := strings.SplitN(imageURL, ",", 2)
if len(parts) != 2 {
err = fmt.Errorf("invalid data URL format")
return
}
if ret, err = base64.StdEncoding.DecodeString(parts[1]); err != nil {
err = fmt.Errorf("failed to decode data URL: %w", err)
}
return
}
// Handle HTTP URLs with context
var req *http.Request
if req, err = http.NewRequestWithContext(ctx, http.MethodGet, imageURL, nil); err != nil {
return
}
var resp *http.Response
if resp, err = o.httpClient.Do(req); err != nil {
return
}
defer resp.Body.Close()
if resp.StatusCode >= http.StatusBadRequest {
err = fmt.Errorf("failed to fetch image %s: %s", imageURL, resp.Status)
return
}
ret, err = io.ReadAll(resp.Body)
return
}
func (o *Client) NeedsRawMode(modelName string) bool {
ollamaPrefixes := []string{
ollamaSearchStrings := []string{
"llama3",
"llama2",
"mistral",
}
for _, prefix := range ollamaPrefixes {
if strings.HasPrefix(modelName, prefix) {
for _, searchString := range ollamaSearchStrings {
if strings.Contains(modelName, searchString) {
return true
}
}

View File

@@ -0,0 +1,120 @@
package openai
import (
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"net/url"
"time"
"github.com/danielmiessler/fabric/internal/i18n"
debuglog "github.com/danielmiessler/fabric/internal/log"
)
// modelResponse represents a minimal model returned by the API.
// This mirrors the shape used by OpenAI-compatible providers that return
// either an array of models or an object with a `data` field.
type modelResponse struct {
ID string `json:"id"`
}
// errorResponseLimit defines the maximum length of error response bodies for truncation.
const errorResponseLimit = 1024
// maxResponseSize defines the maximum size of response bodies to prevent memory exhaustion.
const maxResponseSize = 10 * 1024 * 1024 // 10MB
// FetchModelsDirectly is used to fetch models directly from the API when the
// standard OpenAI SDK method fails due to a nonstandard format. This is useful
// for providers that return a direct array of models (e.g., GitHub Models) or
// other OpenAI-compatible implementations.
func FetchModelsDirectly(ctx context.Context, baseURL, apiKey, providerName string) ([]string, error) {
if ctx == nil {
ctx = context.Background()
}
if baseURL == "" {
return nil, fmt.Errorf(i18n.T("openai_api_base_url_not_configured"), providerName)
}
// Build the /models endpoint URL
fullURL, err := url.JoinPath(baseURL, "models")
if err != nil {
return nil, fmt.Errorf(i18n.T("openai_failed_to_create_models_url"), err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodGet, fullURL, nil)
if err != nil {
return nil, err
}
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", apiKey))
req.Header.Set("Accept", "application/json")
// TODO: Consider reusing a single http.Client instance (e.g., as a field on Client) instead of allocating a new one for
// each request.
client := &http.Client{
Timeout: 10 * time.Second,
}
resp, err := client.Do(req)
if err != nil {
return nil, err
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
// Read the response body for debugging, but limit the number of bytes read
bodyBytes, readErr := io.ReadAll(io.LimitReader(resp.Body, errorResponseLimit))
if readErr != nil {
return nil, fmt.Errorf(i18n.T("openai_unexpected_status_code_read_error"),
resp.StatusCode, providerName, readErr)
}
bodyString := string(bodyBytes)
return nil, fmt.Errorf(i18n.T("openai_unexpected_status_code_with_body"),
resp.StatusCode, providerName, bodyString)
}
// Read the response body once, with a size limit to prevent memory exhaustion
// Read up to maxResponseSize + 1 bytes to detect truncation
bodyBytes, err := io.ReadAll(io.LimitReader(resp.Body, maxResponseSize+1))
if err != nil {
return nil, err
}
if len(bodyBytes) > maxResponseSize {
return nil, fmt.Errorf(i18n.T("openai_models_response_too_large"), providerName, maxResponseSize)
}
// Try to parse as an object with data field (OpenAI format)
var openAIFormat struct {
Data []modelResponse `json:"data"`
}
// Try to parse as a direct array
var directArray []modelResponse
if err := json.Unmarshal(bodyBytes, &openAIFormat); err == nil {
debuglog.Debug(debuglog.Detailed, "Successfully parsed models response from %s using OpenAI format (found %d models)\n", providerName, len(openAIFormat.Data))
return extractModelIDs(openAIFormat.Data), nil
}
if err := json.Unmarshal(bodyBytes, &directArray); err == nil {
debuglog.Debug(debuglog.Detailed, "Successfully parsed models response from %s using direct array format (found %d models)\n", providerName, len(directArray))
return extractModelIDs(directArray), nil
}
var truncatedBody string
if len(bodyBytes) > errorResponseLimit {
truncatedBody = string(bodyBytes[:errorResponseLimit]) + "..."
} else {
truncatedBody = string(bodyBytes)
}
return nil, fmt.Errorf(i18n.T("openai_unable_to_parse_models_response"), truncatedBody)
}
func extractModelIDs(models []modelResponse) []string {
modelIDs := make([]string, 0, len(models))
for _, model := range models {
modelIDs = append(modelIDs, model.ID)
}
return modelIDs
}

View File

@@ -8,6 +8,7 @@ import (
"github.com/danielmiessler/fabric/internal/chat"
"github.com/danielmiessler/fabric/internal/domain"
debuglog "github.com/danielmiessler/fabric/internal/log"
"github.com/danielmiessler/fabric/internal/plugins"
openai "github.com/openai/openai-go"
"github.com/openai/openai-go/option"
@@ -83,13 +84,19 @@ func (o *Client) configure() (ret error) {
func (o *Client) ListModels() (ret []string, err error) {
var page *pagination.Page[openai.Model]
if page, err = o.ApiClient.Models.List(context.Background()); err != nil {
return
if page, err = o.ApiClient.Models.List(context.Background()); err == nil {
for _, mod := range page.Data {
ret = append(ret, mod.ID)
}
// SDK succeeded - return the result even if empty
return ret, nil
}
for _, mod := range page.Data {
ret = append(ret, mod.ID)
}
return
// SDK returned an error - fall back to direct API fetch.
// Some providers (e.g., GitHub Models) return non-standard response formats
// that the SDK fails to parse.
debuglog.Debug(debuglog.Basic, "SDK Models.List failed for %s: %v, falling back to direct API fetch\n", o.GetName(), err)
return FetchModelsDirectly(context.Background(), o.ApiBaseURL.Value, o.ApiKey.Value, o.GetName())
}
func (o *Client) SendStream(
@@ -165,10 +172,11 @@ func (o *Client) supportsResponsesAPI() bool {
func (o *Client) NeedsRawMode(modelName string) bool {
openaiModelsPrefixes := []string{
"glm",
"gpt-5",
"o1",
"o3",
"o4",
"gpt-5",
}
openAIModelsNeedingRaw := []string{
"gpt-4o-mini-search-preview",

View File

@@ -8,6 +8,7 @@ import (
"fmt"
"os"
"path/filepath"
"slices"
"strings"
"github.com/danielmiessler/fabric/internal/domain"
@@ -31,12 +32,7 @@ var ImageGenerationSupportedModels = []string{
// supportsImageGeneration checks if the given model supports the image_generation tool
func supportsImageGeneration(model string) bool {
for _, supportedModel := range ImageGenerationSupportedModels {
if model == supportedModel {
return true
}
}
return false
return slices.Contains(ImageGenerationSupportedModels, model)
}
// getOutputFormatFromExtension determines the API output format based on file extension

View File

@@ -345,7 +345,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
tests := []struct {
name string
opts *domain.ChatOptions
expected map[string]interface{}
expected map[string]any
}{
{
name: "All parameters specified",
@@ -356,7 +356,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
ImageBackground: "transparent",
ImageCompression: 0, // Not applicable for PNG
},
expected: map[string]interface{}{
expected: map[string]any{
"size": "1536x1024",
"quality": "high",
"background": "transparent",
@@ -372,7 +372,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
ImageBackground: "opaque",
ImageCompression: 75,
},
expected: map[string]interface{}{
expected: map[string]any{
"size": "1024x1024",
"quality": "medium",
"background": "opaque",
@@ -386,7 +386,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
ImageFile: "/tmp/test.webp",
ImageQuality: "low",
},
expected: map[string]interface{}{
expected: map[string]any{
"quality": "low",
"output_format": "webp",
},
@@ -396,7 +396,7 @@ func TestAddImageGenerationToolWithUserParameters(t *testing.T) {
opts: &domain.ChatOptions{
ImageFile: "/tmp/test.png",
},
expected: map[string]interface{}{
expected: map[string]any{
"output_format": "png",
},
},

View File

@@ -0,0 +1,58 @@
package openai
import (
"context"
"net/http"
"net/http/httptest"
"testing"
"github.com/stretchr/testify/assert"
)
// Ensures we can fetch models directly when a provider returns a direct array of models
// instead of the standard OpenAI list response structure.
func TestFetchModelsDirectly_DirectArray(t *testing.T) {
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
assert.Equal(t, "/models", r.URL.Path)
w.Header().Set("Content-Type", "application/json")
_, err := w.Write([]byte(`[{"id":"github-model"}]`))
assert.NoError(t, err)
}))
defer srv.Close()
models, err := FetchModelsDirectly(context.Background(), srv.URL, "test-key", "TestProvider")
assert.NoError(t, err)
assert.Equal(t, 1, len(models))
assert.Equal(t, "github-model", models[0])
}
// Ensures we can fetch models when a provider returns the standard OpenAI format
func TestFetchModelsDirectly_OpenAIFormat(t *testing.T) {
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
assert.Equal(t, "/models", r.URL.Path)
w.Header().Set("Content-Type", "application/json")
_, err := w.Write([]byte(`{"data":[{"id":"openai-model"}]}`))
assert.NoError(t, err)
}))
defer srv.Close()
models, err := FetchModelsDirectly(context.Background(), srv.URL, "test-key", "TestProvider")
assert.NoError(t, err)
assert.Equal(t, 1, len(models))
assert.Equal(t, "openai-model", models[0])
}
// Ensures we handle empty model lists correctly
func TestFetchModelsDirectly_EmptyArray(t *testing.T) {
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
assert.Equal(t, "/models", r.URL.Path)
w.Header().Set("Content-Type", "application/json")
_, err := w.Write([]byte(`[]`))
assert.NoError(t, err)
}))
defer srv.Close()
models, err := FetchModelsDirectly(context.Background(), srv.URL, "test-key", "TestProvider")
assert.NoError(t, err)
assert.Equal(t, 0, len(models))
}

View File

@@ -16,7 +16,7 @@ func TestBuildResponseRequestWithMaxTokens(t *testing.T) {
var msgs []*chat.ChatCompletionMessage
for i := 0; i < 2; i++ {
for range 2 {
msgs = append(msgs, &chat.ChatCompletionMessage{
Role: "User",
Content: "My msg",
@@ -42,7 +42,7 @@ func TestBuildResponseRequestNoMaxTokens(t *testing.T) {
var msgs []*chat.ChatCompletionMessage
for i := 0; i < 2; i++ {
for range 2 {
msgs = append(msgs, &chat.ChatCompletionMessage{
Role: "User",
Content: "My msg",

View File

@@ -2,104 +2,12 @@ package openai_compatible
import (
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"net/url"
"time"
"github.com/danielmiessler/fabric/internal/plugins/ai/openai"
)
// Model represents a model returned by the API
type Model struct {
ID string `json:"id"`
}
// ErrorResponseLimit defines the maximum length of error response bodies for truncation.
const errorResponseLimit = 1024 // Limit for error response body size
// DirectlyGetModels is used to fetch models directly from the API
// when the standard OpenAI SDK method fails due to a nonstandard format.
// This is useful for providers like Together that return a direct array of models.
// DirectlyGetModels is used to fetch models directly from the API when the
// standard OpenAI SDK method fails due to a nonstandard format.
func (c *Client) DirectlyGetModels(ctx context.Context) ([]string, error) {
if ctx == nil {
ctx = context.Background()
}
baseURL := c.ApiBaseURL.Value
if baseURL == "" {
return nil, fmt.Errorf("API base URL not configured for provider %s", c.GetName())
}
// Build the /models endpoint URL
fullURL, err := url.JoinPath(baseURL, "models")
if err != nil {
return nil, fmt.Errorf("failed to create models URL: %w", err)
}
req, err := http.NewRequestWithContext(ctx, "GET", fullURL, nil)
if err != nil {
return nil, err
}
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", c.ApiKey.Value))
req.Header.Set("Accept", "application/json")
// TODO: Consider reusing a single http.Client instance (e.g., as a field on Client) instead of allocating a new one for each request.
client := &http.Client{
Timeout: 10 * time.Second,
}
resp, err := client.Do(req)
if err != nil {
return nil, err
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
// Read the response body for debugging
bodyBytes, _ := io.ReadAll(resp.Body)
bodyString := string(bodyBytes)
if len(bodyString) > errorResponseLimit { // Truncate if too large
bodyString = bodyString[:errorResponseLimit] + "..."
}
return nil, fmt.Errorf("unexpected status code: %d from provider %s, response body: %s",
resp.StatusCode, c.GetName(), bodyString)
}
// Read the response body once
bodyBytes, err := io.ReadAll(resp.Body)
if err != nil {
return nil, err
}
// Try to parse as an object with data field (OpenAI format)
var openAIFormat struct {
Data []Model `json:"data"`
}
// Try to parse as a direct array (Together format)
var directArray []Model
if err := json.Unmarshal(bodyBytes, &openAIFormat); err == nil && len(openAIFormat.Data) > 0 {
return extractModelIDs(openAIFormat.Data), nil
}
if err := json.Unmarshal(bodyBytes, &directArray); err == nil && len(directArray) > 0 {
return extractModelIDs(directArray), nil
}
var truncatedBody string
if len(bodyBytes) > errorResponseLimit {
truncatedBody = string(bodyBytes[:errorResponseLimit]) + "..."
} else {
truncatedBody = string(bodyBytes)
}
return nil, fmt.Errorf("unable to parse models response; raw response: %s", truncatedBody)
}
func extractModelIDs(models []Model) []string {
modelIDs := make([]string, 0, len(models))
for _, model := range models {
modelIDs = append(modelIDs, model.ID)
}
return modelIDs
return openai.FetchModelsDirectly(ctx, c.ApiBaseURL.Value, c.ApiKey.Value, c.GetName())
}

View File

@@ -2,6 +2,7 @@ package openai_compatible
import (
"context"
"fmt"
"os"
"strings"
@@ -12,17 +13,21 @@ import (
type ProviderConfig struct {
Name string
BaseURL string
ImplementsResponses bool // Whether the provider supports OpenAI's new Responses API
ModelsURL string // Optional: Custom endpoint for listing models (if different from BaseURL/models)
ImplementsResponses bool // Whether the provider supports OpenAI's new Responses API
}
// Client is the common structure for all OpenAI-compatible providers
type Client struct {
*openai.Client
modelsURL string // Custom URL for listing models (if different from BaseURL/models)
}
// NewClient creates a new OpenAI-compatible client for the specified provider
func NewClient(providerConfig ProviderConfig) *Client {
client := &Client{}
client := &Client{
modelsURL: providerConfig.ModelsURL,
}
client.Client = openai.NewClientCompatibleWithResponses(
providerConfig.Name,
providerConfig.BaseURL,
@@ -34,17 +39,89 @@ func NewClient(providerConfig ProviderConfig) *Client {
// ListModels overrides the default ListModels to handle different response formats
func (c *Client) ListModels() ([]string, error) {
// If a custom models URL is provided, handle it
if c.modelsURL != "" {
// Check for static model list
if strings.HasPrefix(c.modelsURL, "static:") {
return c.getStaticModels(c.modelsURL)
}
// TODO: Handle context properly in Fabric by accepting and propagating a context.Context
// instead of creating a new one here.
return openai.FetchModelsDirectly(context.Background(), c.modelsURL, c.Client.ApiKey.Value, c.GetName())
}
// First try the standard OpenAI SDK approach
models, err := c.Client.ListModels()
if err == nil && len(models) > 0 { // only return if OpenAI SDK returns models
return models, nil
}
// TODO: Handle context properly in Fabric by accepting and propagating a context.Context
// instead of creating a new one here.
// Fall back to direct API fetch
return c.DirectlyGetModels(context.Background())
}
// getStaticModels returns a predefined list of models for providers that don't support model discovery
func (c *Client) getStaticModels(modelsKey string) ([]string, error) {
switch modelsKey {
case "static:abacus":
return []string{
"route-llm",
"gpt-4o-2024-11-20",
"gpt-4o-mini",
"o4-mini",
"o3-pro",
"o3",
"o3-mini",
"gpt-4.1",
"gpt-4.1-mini",
"gpt-4.1-nano",
"gpt-5",
"gpt-5-mini",
"gpt-5-nano",
"gpt-5.1",
"gpt-5.1-chat-latest",
"openai/gpt-oss-120b",
"claude-3-7-sonnet-20250219",
"claude-sonnet-4-20250514",
"claude-opus-4-20250514",
"claude-opus-4-1-20250805",
"claude-sonnet-4-5-20250929",
"claude-haiku-4-5-20251001",
"claude-opus-4-5-20251101",
"meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
"meta-llama/Meta-Llama-3.1-70B-Instruct",
"meta-llama/Meta-Llama-3.1-8B-Instruct",
"llama-3.3-70b-versatile",
"gemini-2.0-flash-001",
"gemini-2.0-pro-exp-02-05",
"gemini-2.5-pro",
"gemini-2.5-flash",
"gemini-3-pro-preview",
"qwen-2.5-coder-32b",
"Qwen/Qwen2.5-72B-Instruct",
"Qwen/QwQ-32B",
"Qwen/Qwen3-235B-A22B-Instruct-2507",
"Qwen/Qwen3-32B",
"qwen/qwen3-coder-480b-a35b-instruct",
"qwen/qwen3-Max",
"grok-4-0709",
"grok-4-fast-non-reasoning",
"grok-4-1-fast-non-reasoning",
"grok-code-fast-1",
"kimi-k2-turbo-preview",
"deepseek/deepseek-v3.1",
"deepseek-ai/DeepSeek-V3.1-Terminus",
"deepseek-ai/DeepSeek-R1",
"deepseek-ai/DeepSeek-V3.2",
"zai-org/glm-4.5",
"zai-org/glm-4.6",
}, nil
default:
return nil, fmt.Errorf("unknown static model list: %s", modelsKey)
}
}
// ProviderMap is a map of provider name to ProviderConfig for O(1) lookup
var ProviderMap = map[string]ProviderConfig{
"AIML": {
@@ -62,6 +139,12 @@ var ProviderMap = map[string]ProviderConfig{
BaseURL: "https://api.deepseek.com",
ImplementsResponses: false,
},
"GitHub": {
Name: "GitHub",
BaseURL: "https://models.github.ai/inference",
ModelsURL: "https://models.github.ai/catalog", // FetchModelsDirectly will append /models
ImplementsResponses: false,
},
"GrokAI": {
Name: "GrokAI",
BaseURL: "https://api.x.ai/v1",
@@ -107,6 +190,17 @@ var ProviderMap = map[string]ProviderConfig{
BaseURL: "https://api.venice.ai/api/v1",
ImplementsResponses: false,
},
"Z AI": {
Name: "Z AI",
BaseURL: "https://api.z.ai/api/paas/v4",
ImplementsResponses: false,
},
"Abacus": {
Name: "Abacus",
BaseURL: "https://routellm.abacus.ai/v1/",
ModelsURL: "static:abacus", // Special marker for static model list
ImplementsResponses: false,
},
}
// GetProviderByName returns the provider configuration for a given name with O(1) lookup

View File

@@ -20,6 +20,16 @@ func TestCreateClient(t *testing.T) {
provider: "Groq",
exists: true,
},
{
name: "Existing provider - Z AI",
provider: "Z AI",
exists: true,
},
{
name: "Existing provider - Abacus",
provider: "Abacus",
exists: true,
},
{
name: "Non-existent provider",
provider: "NonExistent",

View File

@@ -4,6 +4,7 @@ import (
"context"
"fmt"
"os"
"strings"
"sync"
"github.com/danielmiessler/fabric/internal/domain"
@@ -107,18 +108,19 @@ func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, o
return "", fmt.Errorf("perplexity API request failed: %w", err) // Corrected capitalization
}
content := resp.GetLastContent()
var content strings.Builder
content.WriteString(resp.GetLastContent())
// Append citations if available
citations := resp.GetCitations()
if len(citations) > 0 {
content += "\n\n# CITATIONS\n\n"
content.WriteString("\n\n# CITATIONS\n\n")
for i, citation := range citations {
content += fmt.Sprintf("- [%d] %s\n", i+1, citation)
content.WriteString(fmt.Sprintf("- [%d] %s\n", i+1, citation))
}
}
return content, nil
return content.String(), nil
}
func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions, channel chan string) error {

View File

@@ -25,9 +25,12 @@ type VendorsManager struct {
Models *VendorsModels
}
// AddVendors registers one or more vendors with the manager.
// Vendors are stored with lowercase keys to enable case-insensitive lookup.
func (o *VendorsManager) AddVendors(vendors ...Vendor) {
for _, vendor := range vendors {
o.VendorsByName[vendor.GetName()] = vendor
name := strings.ToLower(vendor.GetName())
o.VendorsByName[name] = vendor
o.Vendors = append(o.Vendors, vendor)
}
}
@@ -63,8 +66,10 @@ func (o *VendorsManager) HasVendors() bool {
return len(o.Vendors) > 0
}
// FindByName returns a vendor by name. Lookup is case-insensitive.
// For example, "OpenAI", "openai", and "OPENAI" all match the same vendor.
func (o *VendorsManager) FindByName(name string) Vendor {
return o.VendorsByName[name]
return o.VendorsByName[strings.ToLower(name)]
}
func (o *VendorsManager) readModels() (err error) {
@@ -143,9 +148,9 @@ func (o *VendorsManager) SetupVendor(vendorName string, configuredVendors map[st
func (o *VendorsManager) setupVendorTo(vendor Vendor, configuredVendors map[string]Vendor) {
if vendorErr := vendor.Setup(); vendorErr == nil {
fmt.Printf("[%v] configured\n", vendor.GetName())
configuredVendors[vendor.GetName()] = vendor
configuredVendors[strings.ToLower(vendor.GetName())] = vendor
} else {
delete(configuredVendors, vendor.GetName())
delete(configuredVendors, strings.ToLower(vendor.GetName()))
fmt.Printf("[%v] skipped\n", vendor.GetName())
}
}

View File

@@ -0,0 +1,66 @@
package ai
import (
"bytes"
"context"
"testing"
"github.com/danielmiessler/fabric/internal/chat"
"github.com/danielmiessler/fabric/internal/domain"
)
type stubVendor struct {
name string
}
func (v *stubVendor) GetName() string { return v.name }
func (v *stubVendor) GetSetupDescription() string { return "" }
func (v *stubVendor) IsConfigured() bool { return true }
func (v *stubVendor) Configure() error { return nil }
func (v *stubVendor) Setup() error { return nil }
func (v *stubVendor) SetupFillEnvFileContent(*bytes.Buffer) {}
func (v *stubVendor) ListModels() ([]string, error) { return nil, nil }
func (v *stubVendor) SendStream([]*chat.ChatCompletionMessage, *domain.ChatOptions, chan string) error {
return nil
}
func (v *stubVendor) Send(context.Context, []*chat.ChatCompletionMessage, *domain.ChatOptions) (string, error) {
return "", nil
}
func (v *stubVendor) NeedsRawMode(string) bool { return false }
func TestVendorsManagerFindByNameCaseInsensitive(t *testing.T) {
manager := NewVendorsManager()
vendor := &stubVendor{name: "OpenAI"}
manager.AddVendors(vendor)
if got := manager.FindByName("openai"); got != vendor {
t.Fatalf("FindByName lowercase = %v, want %v", got, vendor)
}
if got := manager.FindByName("OPENAI"); got != vendor {
t.Fatalf("FindByName uppercase = %v, want %v", got, vendor)
}
if got := manager.FindByName("OpenAI"); got != vendor {
t.Fatalf("FindByName mixed case = %v, want %v", got, vendor)
}
}
func TestVendorsManagerSetupVendorToCaseInsensitive(t *testing.T) {
manager := NewVendorsManager()
vendor := &stubVendor{name: "OpenAI"}
configured := map[string]Vendor{}
manager.setupVendorTo(vendor, configured)
// Verify vendor is stored with lowercase key
if _, ok := configured["openai"]; !ok {
t.Fatalf("setupVendorTo should store vendor using lowercase key")
}
// Verify original case key is not used
if _, ok := configured["OpenAI"]; ok {
t.Fatalf("setupVendorTo should not store vendor using original case key")
}
}

View File

@@ -134,7 +134,7 @@ func (o *StorageEntity) buildFileName(name string) string {
return fmt.Sprintf("%s%v", name, o.FileExtension)
}
func (o *StorageEntity) SaveAsJson(name string, item interface{}) (err error) {
func (o *StorageEntity) SaveAsJson(name string, item any) (err error) {
var jsonString []byte
if jsonString, err = json.Marshal(item); err == nil {
err = o.Save(name, jsonString)
@@ -145,7 +145,7 @@ func (o *StorageEntity) SaveAsJson(name string, item interface{}) (err error) {
return err
}
func (o *StorageEntity) LoadAsJson(name string, item interface{}) (err error) {
func (o *StorageEntity) LoadAsJson(name string, item any) (err error) {
var content []byte
if content, err = o.Load(name); err != nil {
return

View File

@@ -92,7 +92,11 @@ func (o *PluginBase) Setup() (err error) {
return
}
err = o.Configure()
// After Setup, run ConfigureCustom if present, but skip re-validation
// since Ask() already validated user input (or allowed explicit reset)
if o.ConfigureCustom != nil {
err = o.ConfigureCustom()
}
return
}
@@ -198,16 +202,21 @@ func (o *SetupQuestion) Ask(label string) (err error) {
var answer string
fmt.Scanln(&answer)
answer = strings.TrimRight(answer, "\n")
isReset := strings.ToLower(answer) == AnswerReset
if answer == "" {
answer = o.Value
} else if strings.ToLower(answer) == AnswerReset {
} else if isReset {
answer = ""
}
err = o.OnAnswer(answer)
err = o.OnAnswerWithReset(answer, isReset)
return
}
func (o *SetupQuestion) OnAnswer(answer string) (err error) {
return o.OnAnswerWithReset(answer, false)
}
func (o *SetupQuestion) OnAnswerWithReset(answer string, isReset bool) (err error) {
if o.Type == SettingTypeBool {
if answer == "" {
o.Value = ""
@@ -226,6 +235,11 @@ func (o *SetupQuestion) OnAnswer(answer string) (err error) {
return
}
}
// Skip validation when explicitly resetting a value - the user intentionally
// wants to clear the value even if it's required
if isReset {
return nil
}
err = o.IsValidErr()
return
}

View File

@@ -116,6 +116,91 @@ func TestSetupQuestion_Ask(t *testing.T) {
assert.Equal(t, "user_value", setting.Value)
}
func TestSetupQuestion_Ask_Reset(t *testing.T) {
// Test that resetting a required field doesn't produce an error
setting := &Setting{
EnvVariable: "TEST_RESET_SETTING",
Value: "existing_value",
Required: true,
}
question := &SetupQuestion{
Setting: setting,
Question: "Enter test setting:",
}
input := "reset\n"
fmtInput := captureInput(input)
defer fmtInput()
err := question.Ask("TestConfigurable")
// Should NOT return an error even though the field is required
assert.NoError(t, err)
// Value should be cleared
assert.Equal(t, "", setting.Value)
}
func TestSetupQuestion_OnAnswerWithReset(t *testing.T) {
tests := []struct {
name string
setting *Setting
answer string
isReset bool
expectError bool
expectValue string
}{
{
name: "reset required field should not error",
setting: &Setting{
EnvVariable: "TEST_SETTING",
Value: "old_value",
Required: true,
},
answer: "",
isReset: true,
expectError: false,
expectValue: "",
},
{
name: "empty answer on required field should error",
setting: &Setting{
EnvVariable: "TEST_SETTING",
Value: "",
Required: true,
},
answer: "",
isReset: false,
expectError: true,
expectValue: "",
},
{
name: "valid answer on required field should not error",
setting: &Setting{
EnvVariable: "TEST_SETTING",
Value: "",
Required: true,
},
answer: "new_value",
isReset: false,
expectError: false,
expectValue: "new_value",
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
question := &SetupQuestion{
Setting: tt.setting,
Question: "Test question",
}
err := question.OnAnswerWithReset(tt.answer, tt.isReset)
if tt.expectError {
assert.Error(t, err)
} else {
assert.NoError(t, err)
}
assert.Equal(t, tt.expectValue, tt.setting.Value)
})
}
}
func TestSettings_IsConfigured(t *testing.T) {
settings := Settings{
{EnvVariable: "TEST_SETTING1", Value: "value1", Required: true},

View File

@@ -187,9 +187,10 @@ esac`
executor := NewExtensionExecutor(registry)
// Helper function to create and register extension
createExtension := func(name, opName, cmdTemplate string, config map[string]interface{}) error {
createExtension := func(name, opName, cmdTemplate string, config map[string]any) error {
configPath := filepath.Join(tmpDir, name+".yaml")
configContent := `name: ` + name + `
var configContent strings.Builder
configContent.WriteString(`name: ` + name + `
executable: ` + testScript + `
type: executable
timeout: 30s
@@ -199,14 +200,14 @@ operations:
config:
output:
method: file
file_config:`
file_config:`)
// Add config options
for k, v := range config {
configContent += "\n " + k + ": " + strings.TrimSpace(v.(string))
configContent.WriteString("\n " + k + ": " + strings.TrimSpace(v.(string)))
}
if err := os.WriteFile(configPath, []byte(configContent), 0644); err != nil {
if err := os.WriteFile(configPath, []byte(configContent.String()), 0644); err != nil {
return err
}
@@ -216,7 +217,7 @@ config:
// Test basic fixed file output
t.Run("BasicFixedFile", func(t *testing.T) {
outputFile := filepath.Join(tmpDir, "output.txt")
config := map[string]interface{}{
config := map[string]any{
"output_file": `"output.txt"`,
"work_dir": `"` + tmpDir + `"`,
"cleanup": "true",
@@ -241,7 +242,7 @@ config:
// Test no work_dir specified
t.Run("NoWorkDir", func(t *testing.T) {
config := map[string]interface{}{
config := map[string]any{
"output_file": `"direct-output.txt"`,
"cleanup": "true",
}
@@ -263,7 +264,7 @@ config:
outputFile := filepath.Join(tmpDir, "cleanup-test.txt")
// Test with cleanup enabled
config := map[string]interface{}{
config := map[string]any{
"output_file": `"cleanup-test.txt"`,
"work_dir": `"` + tmpDir + `"`,
"cleanup": "true",
@@ -307,7 +308,7 @@ config:
// Test error cases
t.Run("ErrorCases", func(t *testing.T) {
outputFile := filepath.Join(tmpDir, "error-test.txt")
config := map[string]interface{}{
config := map[string]any{
"output_file": `"error-test.txt"`,
"work_dir": `"` + tmpDir + `"`,
"cleanup": "true",
@@ -341,7 +342,7 @@ config:
// Test with missing output_file
t.Run("MissingOutputFile", func(t *testing.T) {
config := map[string]interface{}{
config := map[string]any{
"work_dir": `"` + tmpDir + `"`,
"cleanup": "true",
}

View File

@@ -30,7 +30,7 @@ type ExtensionDefinition struct {
Operations map[string]OperationConfig `yaml:"operations"`
// Additional config
Config map[string]interface{} `yaml:"config"`
Config map[string]any `yaml:"config"`
}
type OperationConfig struct {
@@ -53,7 +53,7 @@ type ExtensionRegistry struct {
// Helper methods for Config access
func (e *ExtensionDefinition) GetOutputMethod() string {
if output, ok := e.Config["output"].(map[string]interface{}); ok {
if output, ok := e.Config["output"].(map[string]any); ok {
if method, ok := output["method"].(string); ok {
return method
}
@@ -61,9 +61,9 @@ func (e *ExtensionDefinition) GetOutputMethod() string {
return "stdout" // default to stdout if not specified
}
func (e *ExtensionDefinition) GetFileConfig() map[string]interface{} {
if output, ok := e.Config["output"].(map[string]interface{}); ok {
if fileConfig, ok := output["file_config"].(map[string]interface{}); ok {
func (e *ExtensionDefinition) GetFileConfig() map[string]any {
if output, ok := e.Config["output"].(map[string]any); ok {
if fileConfig, ok := output["file_config"].(map[string]any); ok {
return fileConfig
}
}

View File

@@ -33,7 +33,7 @@ func init() {
var pluginPattern = regexp.MustCompile(`\{\{plugin:([^:]+):([^:]+)(?::([^}]+))?\}\}`)
var extensionPattern = regexp.MustCompile(`\{\{ext:([^:]+):([^:]+)(?::([^}]+))?\}\}`)
func debugf(format string, a ...interface{}) {
func debugf(format string, a ...any) {
debuglog.Debug(debuglog.Trace, format, a...)
}

View File

@@ -16,7 +16,7 @@ func toTitle(s string) string {
lower := strings.ToLower(s)
runes := []rune(lower)
for i := 0; i < len(runes); i++ {
for i := range runes {
// Capitalize if previous char is non-letter AND
// (we're at the end OR next char is not space)
if i == 0 || !unicode.IsLetter(runes[i-1]) {

View File

@@ -2,14 +2,25 @@ package restapi
import (
"net/http"
"strings"
"github.com/gin-gonic/gin"
)
const APIKeyHeader = "X-API-Key"
// APIKeyMiddleware validates API key for protected endpoints.
// Swagger documentation endpoints (/swagger/*) are exempt from authentication
// to allow users to browse and test the API documentation freely.
func APIKeyMiddleware(apiKey string) gin.HandlerFunc {
return func(c *gin.Context) {
// Skip authentication for Swagger documentation endpoints
// This allows public access to API docs even when authentication is enabled
if strings.HasPrefix(c.Request.URL.Path, "/swagger/") {
c.Next()
return
}
headerApiKey := c.GetHeader(APIKeyHeader)
if headerApiKey == "" {

View File

@@ -55,6 +55,17 @@ func NewChatHandler(r *gin.Engine, registry *core.PluginRegistry, db *fsdb.Db) *
return handler
}
// HandleChat godoc
// @Summary Stream chat completions
// @Description Stream AI responses using Server-Sent Events (SSE)
// @Tags chat
// @Accept json
// @Produce text/event-stream
// @Param request body ChatRequest true "Chat request with prompts and options"
// @Success 200 {object} StreamResponse "Streaming response"
// @Failure 400 {object} map[string]string
// @Security ApiKeyAuth
// @Router /chat [post]
func (h *ChatHandler) HandleChat(c *gin.Context) {
var request ChatRequest

View File

@@ -17,6 +17,15 @@ func NewModelsHandler(r *gin.Engine, vendorManager *ai.VendorsManager) {
r.GET("/models/names", handler.GetModelNames)
}
// GetModelNames godoc
// @Summary List all available models
// @Description Get a list of all available AI models grouped by vendor
// @Tags models
// @Produce json
// @Success 200 {object} map[string]interface{} "Returns models (array) and vendors (map)"
// @Failure 500 {object} map[string]string
// @Security ApiKeyAuth
// @Router /models/names [get]
func (h *ModelsHandler) GetModelNames(c *gin.Context) {
vendorsModels, err := h.vendorManager.GetModels()
if err != nil {
@@ -24,7 +33,7 @@ func (h *ModelsHandler) GetModelNames(c *gin.Context) {
return
}
response := make(map[string]interface{})
response := make(map[string]any)
vendors := make(map[string][]string)
for _, groupItems := range vendorsModels.GroupsItems {

View File

@@ -102,7 +102,7 @@ func ServeOllama(registry *core.PluginRegistry, address string, version string)
// Ollama Endpoints
r.GET("/api/tags", typeConversion.ollamaTags)
r.GET("/api/version", func(c *gin.Context) {
c.Data(200, "application/json", []byte(fmt.Sprintf("{\"%s\"}", version)))
c.Data(200, "application/json", fmt.Appendf(nil, "{\"%s\"}", version))
})
r.POST("/api/chat", typeConversion.ollamaChat)
@@ -224,7 +224,7 @@ func (f APIConvert) ollamaChat(c *gin.Context) {
c.JSON(http.StatusInternalServerError, gin.H{"error": "testing endpoint"})
return
}
for _, word := range strings.Split(fabricResponse.Content, " ") {
for word := range strings.SplitSeq(fabricResponse.Content, " ") {
forwardedResponse = OllamaResponse{
Model: "",
CreatedAt: "",

View File

@@ -1,6 +1,7 @@
package restapi
import (
"maps"
"net/http"
"github.com/danielmiessler/fabric/internal/plugins/db/fsdb"
@@ -32,6 +33,16 @@ func NewPatternsHandler(r *gin.Engine, patterns *fsdb.PatternsEntity) (ret *Patt
}
// Get handles the GET /patterns/:name route - returns raw pattern without variable processing
// @Summary Get a pattern
// @Description Retrieve a pattern by name
// @Tags patterns
// @Accept json
// @Produce json
// @Param name path string true "Pattern name"
// @Success 200 {object} fsdb.Pattern
// @Failure 500 {object} map[string]string
// @Security ApiKeyAuth
// @Router /patterns/{name} [get]
func (h *PatternsHandler) Get(c *gin.Context) {
name := c.Param("name")
@@ -58,6 +69,18 @@ type PatternApplyRequest struct {
}
// ApplyPattern handles the POST /patterns/:name/apply route
// @Summary Apply pattern with variables
// @Description Apply a pattern with variable substitution
// @Tags patterns
// @Accept json
// @Produce json
// @Param name path string true "Pattern name"
// @Param request body PatternApplyRequest true "Pattern application request"
// @Success 200 {object} fsdb.Pattern
// @Failure 400 {object} map[string]string
// @Failure 500 {object} map[string]string
// @Security ApiKeyAuth
// @Router /patterns/{name}/apply [post]
func (h *PatternsHandler) ApplyPattern(c *gin.Context) {
name := c.Param("name")
@@ -74,9 +97,7 @@ func (h *PatternsHandler) ApplyPattern(c *gin.Context) {
variables[key] = values[0]
}
}
for key, value := range request.Variables {
variables[key] = value
}
maps.Copy(variables, request.Variables)
pattern, err := h.patterns.GetApplyVariables(name, variables, request.Input)
if err != nil {

View File

@@ -2,11 +2,30 @@ package restapi
import (
"log/slog"
"net/http"
"os"
"path/filepath"
"github.com/danielmiessler/fabric/internal/core"
"github.com/gin-gonic/gin"
swaggerFiles "github.com/swaggo/files"
ginSwagger "github.com/swaggo/gin-swagger"
_ "github.com/danielmiessler/fabric/docs" // swagger docs
)
// @title Fabric REST API
// @version 1.0
// @description REST API for Fabric AI augmentation framework. Provides endpoints for chat completions, pattern management, contexts, sessions, and more.
// @contact.name Fabric Support
// @contact.url https://github.com/danielmiessler/fabric
// @license.name MIT
// @license.url https://opensource.org/licenses/MIT
// @host localhost:8080
// @BasePath /
// @securityDefinitions.apikey ApiKeyAuth
// @in header
// @name X-API-Key
func Serve(registry *core.PluginRegistry, address string, apiKey string) (err error) {
r := gin.New()
@@ -20,6 +39,32 @@ func Serve(registry *core.PluginRegistry, address string, apiKey string) (err er
slog.Warn("Starting REST API server without API key authentication. This may pose security risks.")
}
// Swagger UI and documentation endpoint with custom YAML handler
r.GET("/swagger/*any", func(c *gin.Context) {
// Check if request is for swagger.yaml
if c.Param("any") == "/swagger.yaml" {
// Try to find swagger.yaml relative to current directory or executable
yamlPath := "docs/swagger.yaml"
if _, err := os.Stat(yamlPath); os.IsNotExist(err) {
// Try relative to executable
if exePath, err := os.Executable(); err == nil {
yamlPath = filepath.Join(filepath.Dir(exePath), "docs", "swagger.yaml")
}
}
if _, err := os.Stat(yamlPath); err != nil {
c.JSON(http.StatusNotFound, gin.H{"error": "swagger.yaml not found - generate it with: swag init -g internal/server/serve.go -o docs"})
return
}
c.File(yamlPath)
return
}
// For all other swagger paths, use the default handler
ginSwagger.WrapHandler(swaggerFiles.Handler)(c)
})
// Register routes
fabricDb := registry.Db
NewPatternsHandler(r, fabricDb.Patterns)

View File

@@ -26,10 +26,11 @@ import (
"strings"
"time"
"github.com/danielmiessler/fabric/internal/i18n"
debuglog "github.com/danielmiessler/fabric/internal/log"
"github.com/danielmiessler/fabric/internal/plugins"
"github.com/kballard/go-shellquote"
debuglog "github.com/danielmiessler/fabric/internal/log"
"google.golang.org/api/option"
"google.golang.org/api/youtube/v3"
)
@@ -85,7 +86,7 @@ type YouTube struct {
func (o *YouTube) initService() (err error) {
if o.service == nil {
if o.ApiKey.Value == "" {
err = fmt.Errorf("YouTube API key required for comments and metadata. Run 'fabric --setup' to configure")
err = fmt.Errorf("%s", i18n.T("youtube_api_key_required"))
return
}
o.normalizeRegex = regexp.MustCompile(`[^a-zA-Z0-9]+`)
@@ -109,41 +110,66 @@ func (o *YouTube) GetVideoOrPlaylistId(url string) (videoId string, playlistId s
}
if videoId == "" && playlistId == "" {
err = fmt.Errorf("invalid YouTube URL, can't get video or playlist ID: '%s'", url)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_invalid_url"), url))
}
return
}
func (o *YouTube) GrabTranscriptForUrl(url string, language string) (ret string, err error) {
var videoId string
// extractAndValidateVideoId extracts a video ID from the given URL and validates
// that the URL points to a video rather than a playlist-only resource.
// It returns an error if the URL is invalid or contains only playlist information.
func (o *YouTube) extractAndValidateVideoId(url string) (videoId string, err error) {
var playlistId string
if videoId, playlistId, err = o.GetVideoOrPlaylistId(url); err != nil {
return
} else if videoId == "" && playlistId != "" {
err = fmt.Errorf("URL is a playlist, not a video")
return "", err
}
if videoId == "" && playlistId != "" {
return "", fmt.Errorf("%s", i18n.T("youtube_url_is_playlist_not_video"))
}
if videoId == "" {
return "", fmt.Errorf("%s", i18n.T("youtube_no_video_id_found"))
}
return videoId, nil
}
func (o *YouTube) GrabTranscriptForUrl(url string, language string) (ret string, err error) {
var videoId string
if videoId, err = o.extractAndValidateVideoId(url); err != nil {
return
}
return o.GrabTranscript(videoId, language)
}
// GrabTranscript retrieves the transcript for the specified video ID using yt-dlp.
// The language parameter specifies the preferred subtitle language code (e.g., "en", "es").
// It returns the transcript text or an error if the transcript cannot be retrieved.
func (o *YouTube) GrabTranscript(videoId string, language string) (ret string, err error) {
// Use yt-dlp for reliable transcript extraction
return o.GrabTranscriptWithArgs(videoId, language, "")
}
// GrabTranscriptWithArgs retrieves the transcript for the specified video ID using yt-dlp
// with custom command-line arguments. The language parameter specifies the preferred subtitle
// language code. The additionalArgs parameter allows passing extra yt-dlp options like
// "--cookies-from-browser brave" for authentication.
// It returns the transcript text or an error if the transcript cannot be retrieved.
func (o *YouTube) GrabTranscriptWithArgs(videoId string, language string, additionalArgs string) (ret string, err error) {
// Use yt-dlp for reliable transcript extraction
return o.tryMethodYtDlp(videoId, language, additionalArgs)
}
// GrabTranscriptWithTimestamps retrieves the transcript with timestamps for the specified
// video ID using yt-dlp. The language parameter specifies the preferred subtitle language code.
// Each line in the returned transcript is prefixed with a timestamp in [HH:MM:SS] format.
// It returns the timestamped transcript text or an error if the transcript cannot be retrieved.
func (o *YouTube) GrabTranscriptWithTimestamps(videoId string, language string) (ret string, err error) {
// Use yt-dlp for reliable transcript extraction with timestamps
return o.GrabTranscriptWithTimestampsWithArgs(videoId, language, "")
}
// GrabTranscriptWithTimestampsWithArgs retrieves the transcript with timestamps for the specified
// video ID using yt-dlp with custom command-line arguments. The language parameter specifies the
// preferred subtitle language code. The additionalArgs parameter allows passing extra yt-dlp options.
// Each line in the returned transcript is prefixed with a timestamp in [HH:MM:SS] format.
// It returns the timestamped transcript text or an error if the transcript cannot be retrieved.
func (o *YouTube) GrabTranscriptWithTimestampsWithArgs(videoId string, language string, additionalArgs string) (ret string, err error) {
// Use yt-dlp for reliable transcript extraction with timestamps
return o.tryMethodYtDlpWithTimestamps(videoId, language, additionalArgs)
}
@@ -153,10 +179,10 @@ func detectError(ytOutput io.Reader) error {
curLine := scanner.Text()
debuglog.Debug(debuglog.Trace, "%s\n", curLine)
errorMessages := map[string]string{
"429": "YouTube rate limit exceeded. Try again later or use different yt-dlp arguments like '--sleep-requests 1' to slow down requests.",
"Too Many Requests": "YouTube rate limit exceeded. Try again later or use different yt-dlp arguments like '--sleep-requests 1' to slow down requests.",
"Sign in to confirm you're not a bot": "YouTube requires authentication (bot detection). Use --yt-dlp-args='--cookies-from-browser BROWSER' where BROWSER is chrome, firefox, brave, etc.",
"Use --cookies-from-browser": "YouTube requires authentication (bot detection). Use --yt-dlp-args='--cookies-from-browser BROWSER' where BROWSER is chrome, firefox, brave, etc.",
"429": i18n.T("youtube_rate_limit_exceeded"),
"Too Many Requests": i18n.T("youtube_rate_limit_exceeded"),
"Sign in to confirm you're not a bot": i18n.T("youtube_auth_required_bot_detection"),
"Use --cookies-from-browser": i18n.T("youtube_auth_required_bot_detection"),
}
for key, message := range errorMessages {
@@ -166,7 +192,7 @@ func detectError(ytOutput io.Reader) error {
}
}
if err := scanner.Err(); err != nil {
return fmt.Errorf("Error reading yt-dlp stderr")
return fmt.Errorf("%s", i18n.T("youtube_ytdlp_stderr_error"))
}
return nil
}
@@ -192,14 +218,14 @@ func noLangs(args []string) []string {
func (o *YouTube) tryMethodYtDlpInternal(videoId string, language string, additionalArgs string, processVTTFileFunc func(filename string) (string, error)) (ret string, err error) {
// Check if yt-dlp is available
if _, err = exec.LookPath("yt-dlp"); err != nil {
err = fmt.Errorf("yt-dlp not found in PATH. Please install yt-dlp to use YouTube transcript functionality")
err = fmt.Errorf("%s", i18n.T("youtube_ytdlp_not_found"))
return
}
// Create a temporary directory for yt-dlp output (cross-platform)
tempDir := filepath.Join(os.TempDir(), "fabric-youtube-"+videoId)
if err = os.MkdirAll(tempDir, 0755); err != nil {
err = fmt.Errorf("failed to create temp directory: %v", err)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_failed_create_temp_dir"), err))
return
}
defer os.RemoveAll(tempDir)
@@ -231,7 +257,7 @@ func (o *YouTube) tryMethodYtDlpInternal(videoId string, language string, additi
if additionalArgs != "" {
additionalArgsList, err := shellquote.Split(additionalArgs)
if err != nil {
return "", fmt.Errorf("invalid yt-dlp arguments: %v", err)
return "", fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_invalid_ytdlp_arguments"), err))
}
args = append(args, additionalArgsList...)
}
@@ -302,7 +328,7 @@ func (o *YouTube) readAndCleanVTTFile(filename string) (ret string, err error) {
ret = strings.TrimSpace(textBuilder.String())
if ret == "" {
err = fmt.Errorf("no transcript content found in VTT file")
err = fmt.Errorf("%s", i18n.T("youtube_no_transcript_content"))
}
return
}
@@ -372,7 +398,7 @@ func (o *YouTube) readAndFormatVTTWithTimestamps(filename string) (ret string, e
ret = strings.TrimSpace(textBuilder.String())
if ret == "" {
err = fmt.Errorf("no transcript content found in VTT file")
err = fmt.Errorf("%s", i18n.T("youtube_no_transcript_content"))
}
return
}
@@ -418,7 +444,7 @@ func shouldIncludeRepeat(lastTimestamp, currentTimestamp string) bool {
func parseTimestampToSeconds(timestamp string) (int, error) {
parts := strings.Split(timestamp, ":")
if len(parts) < 2 || len(parts) > 3 {
return 0, fmt.Errorf("invalid timestamp format: %s", timestamp)
return 0, fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_invalid_timestamp_format"), timestamp))
}
var hours, minutes, seconds int
@@ -448,20 +474,27 @@ func parseTimestampToSeconds(timestamp string) (int, error) {
return hours*3600 + minutes*60 + seconds, nil
}
func parseSeconds(seconds_str string) (int, error) {
var seconds int
var err error
if strings.Contains(seconds_str, ".") {
// Handle fractional seconds
second_parts := strings.Split(seconds_str, ".")
if seconds, err = strconv.Atoi(second_parts[0]); err != nil {
return 0, err
}
} else {
if seconds, err = strconv.Atoi(seconds_str); err != nil {
return 0, err
func parseSeconds(secondsStr string) (int, error) {
if secondsStr == "" {
return 0, fmt.Errorf("%s", i18n.T("youtube_empty_seconds_string"))
}
// Extract integer part (before decimal point if present)
intPart := secondsStr
if idx := strings.Index(secondsStr, "."); idx != -1 {
if idx == 0 {
// Handle cases like ".5" -> treat as "0"
intPart = "0"
} else {
intPart = secondsStr[:idx]
}
}
seconds, err := strconv.Atoi(intPart)
if err != nil {
return 0, fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_invalid_seconds_format"), secondsStr, err))
}
return seconds, nil
}
@@ -497,11 +530,7 @@ func (o *YouTube) GrabDurationForUrl(url string) (ret int, err error) {
}
var videoId string
var playlistId string
if videoId, playlistId, err = o.GetVideoOrPlaylistId(url); err != nil {
return
} else if videoId == "" && playlistId != "" {
err = fmt.Errorf("URL is a playlist, not a video")
if videoId, err = o.extractAndValidateVideoId(url); err != nil {
return
}
return o.GrabDuration(videoId)
@@ -510,7 +539,7 @@ func (o *YouTube) GrabDurationForUrl(url string) (ret int, err error) {
func (o *YouTube) GrabDuration(videoId string) (ret int, err error) {
var videoResponse *youtube.VideoListResponse
if videoResponse, err = o.service.Videos.List([]string{"contentDetails"}).Id(videoId).Do(); err != nil {
err = fmt.Errorf("error getting video details: %v", err)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_error_getting_video_details"), err))
return
}
@@ -518,7 +547,7 @@ func (o *YouTube) GrabDuration(videoId string) (ret int, err error) {
matches := durationRegex.FindStringSubmatch(durationStr)
if len(matches) == 0 {
return 0, fmt.Errorf("invalid duration string: %s", durationStr)
return 0, fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_invalid_duration_string"), durationStr))
}
hours, _ := strconv.Atoi(matches[1])
@@ -532,11 +561,7 @@ func (o *YouTube) GrabDuration(videoId string) (ret int, err error) {
func (o *YouTube) Grab(url string, options *Options) (ret *VideoInfo, err error) {
var videoId string
var playlistId string
if videoId, playlistId, err = o.GetVideoOrPlaylistId(url); err != nil {
return
} else if videoId == "" && playlistId != "" {
err = fmt.Errorf("URL is a playlist, not a video")
if videoId, err = o.extractAndValidateVideoId(url); err != nil {
return
}
@@ -544,14 +569,14 @@ func (o *YouTube) Grab(url string, options *Options) (ret *VideoInfo, err error)
if options.Metadata {
if ret.Metadata, err = o.GrabMetadata(videoId); err != nil {
err = fmt.Errorf("error getting video metadata: %v", err)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_error_getting_metadata"), err))
return
}
}
if options.Duration {
if ret.Duration, err = o.GrabDuration(videoId); err != nil {
err = fmt.Errorf("error parsing video duration: %v", err)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_error_parsing_duration"), err))
return
}
@@ -559,7 +584,7 @@ func (o *YouTube) Grab(url string, options *Options) (ret *VideoInfo, err error)
if options.Comments {
if ret.Comments, err = o.GrabComments(videoId); err != nil {
err = fmt.Errorf("error getting comments: %v", err)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_error_getting_comments"), err))
return
}
}
@@ -643,12 +668,12 @@ func (o *YouTube) SaveVideosToCSV(filename string, videos []*VideoMeta) (err err
func (o *YouTube) FetchAndSavePlaylist(playlistID, filename string) (err error) {
var videos []*VideoMeta
if videos, err = o.FetchPlaylistVideos(playlistID); err != nil {
err = fmt.Errorf("error fetching playlist videos: %v", err)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("error_fetching_playlist_videos"), err))
return
}
if err = o.SaveVideosToCSV(filename, videos); err != nil {
err = fmt.Errorf("error saving videos to CSV: %v", err)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_error_saving_csv"), err))
return
}
@@ -659,7 +684,7 @@ func (o *YouTube) FetchAndSavePlaylist(playlistID, filename string) (err error)
func (o *YouTube) FetchAndPrintPlaylist(playlistID string) (err error) {
var videos []*VideoMeta
if videos, err = o.FetchPlaylistVideos(playlistID); err != nil {
err = fmt.Errorf("error fetching playlist videos: %v", err)
err = fmt.Errorf("%s", fmt.Sprintf(i18n.T("error_fetching_playlist_videos"), err))
return
}
@@ -694,11 +719,11 @@ func (o *YouTube) findVTTFilesWithFallback(dir, requestedLanguage string) ([]str
})
if err != nil {
return nil, fmt.Errorf("failed to walk directory: %v", err)
return nil, fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_failed_walk_directory"), err))
}
if len(vttFiles) == 0 {
return nil, fmt.Errorf("no VTT files found in directory")
return nil, fmt.Errorf("%s", i18n.T("youtube_no_vtt_files_found"))
}
// If no specific language requested, return the first file
@@ -769,11 +794,11 @@ func (o *YouTube) GrabMetadata(videoId string) (metadata *VideoMetadata, err err
call := o.service.Videos.List([]string{"snippet", "statistics"}).Id(videoId)
var response *youtube.VideoListResponse
if response, err = call.Do(); err != nil {
return nil, fmt.Errorf("error getting video metadata: %v", err)
return nil, fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_error_getting_metadata"), err))
}
if len(response.Items) == 0 {
return nil, fmt.Errorf("no video found with ID: %s", videoId)
return nil, fmt.Errorf("%s", fmt.Sprintf(i18n.T("youtube_no_video_found_with_id"), videoId))
}
video := response.Items[0]

View File

@@ -0,0 +1,168 @@
package youtube
import (
"strings"
"testing"
)
func TestParseSeconds(t *testing.T) {
tests := []struct {
name string
input string
want int
wantErr bool
}{
{
name: "integer seconds",
input: "42",
want: 42,
wantErr: false,
},
{
name: "fractional seconds",
input: "42.567",
want: 42,
wantErr: false,
},
{
name: "zero",
input: "0",
want: 0,
wantErr: false,
},
{
name: "zero with fraction",
input: "0.999",
want: 0,
wantErr: false,
},
{
name: "decimal point at start",
input: ".5",
want: 0,
wantErr: false,
},
{
name: "invalid input",
input: "abc",
want: 0,
wantErr: true,
},
{
name: "empty string",
input: "",
want: 0,
wantErr: true,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got, err := parseSeconds(tt.input)
// Check error condition
if tt.wantErr {
if err == nil {
t.Errorf("parseSeconds(%q) expected error but got none", tt.input)
}
return
}
// Check success condition
if err != nil {
t.Fatalf("parseSeconds(%q) unexpected error: %v", tt.input, err)
}
if got != tt.want {
t.Errorf("parseSeconds(%q) = %d, want %d", tt.input, got, tt.want)
}
})
}
}
func TestExtractAndValidateVideoId(t *testing.T) {
yt := NewYouTube()
tests := []struct {
name string
url string
wantId string
wantError bool
errorMsg string
}{
{
name: "valid video URL",
url: "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
wantId: "dQw4w9WgXcQ",
wantError: false,
},
{
name: "valid short URL",
url: "https://youtu.be/dQw4w9WgXcQ",
wantId: "dQw4w9WgXcQ",
wantError: false,
},
{
name: "video with playlist URL - should extract video",
url: "https://www.youtube.com/watch?v=dQw4w9WgXcQ&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf",
wantId: "dQw4w9WgXcQ",
wantError: false,
},
{
name: "playlist-only URL",
url: "https://www.youtube.com/playlist?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf",
wantId: "",
wantError: true,
errorMsg: "URL is a playlist, not a video",
},
{
name: "invalid URL",
url: "https://example.com",
wantId: "",
wantError: true,
errorMsg: "invalid YouTube URL",
},
{
name: "empty URL",
url: "",
wantId: "",
wantError: true,
},
{
name: "malformed URL",
url: "not-a-url",
wantId: "",
wantError: true,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got, err := yt.extractAndValidateVideoId(tt.url)
if tt.wantError {
if err == nil {
t.Errorf("extractAndValidateVideoId(%q) expected error but got none", tt.url)
return
}
if tt.errorMsg != "" && !strings.Contains(err.Error(), tt.errorMsg) {
t.Errorf("extractAndValidateVideoId(%q) error = %v, want error containing %q", tt.url, err, tt.errorMsg)
}
// Verify empty videoId is returned on error
if got != "" {
t.Errorf("extractAndValidateVideoId(%q) returned videoId %q on error, want empty string", tt.url, got)
}
return
}
if err != nil {
t.Errorf("extractAndValidateVideoId(%q) unexpected error = %v", tt.url, err)
return
}
if got != tt.wantId {
t.Errorf("extractAndValidateVideoId(%q) = %q, want %q", tt.url, got, tt.wantId)
}
})
}
}

View File

@@ -133,7 +133,7 @@ func (o *GroupsItemsSelector[I]) Print(shellCompleteList bool) {
func (o *GroupsItemsSelector[I]) HasGroup(group string) (ret bool) {
for _, groupItems := range o.GroupsItems {
if ret = groupItems.Group == group; ret {
if ret = strings.EqualFold(groupItems.Group, group); ret {
break
}
}
@@ -146,7 +146,7 @@ func (o *GroupsItemsSelector[I]) FindGroupsByItemFirst(item I) (ret string) {
for _, groupItems := range o.GroupsItems {
if groupItems.ContainsItemBy(func(groupItem I) bool {
groupItemKey := o.GetItemKey(groupItem)
return groupItemKey == itemKey
return strings.EqualFold(groupItemKey, itemKey)
}) {
ret = groupItems.Group
break
@@ -161,7 +161,7 @@ func (o *GroupsItemsSelector[I]) FindGroupsByItem(item I) (groups []string) {
for _, groupItems := range o.GroupsItems {
if groupItems.ContainsItemBy(func(groupItem I) bool {
groupItemKey := o.GetItemKey(groupItem)
return groupItemKey == itemKey
return strings.EqualFold(groupItemKey, itemKey)
}) {
groups = append(groups, groupItems.Group)
}

View File

@@ -22,6 +22,9 @@ schema = 3
[mod."github.com/Azure/azure-sdk-for-go/sdk/internal"]
version = "v1.11.2"
hash = "sha256-O4Vo6D/fus3Qhs/Te644+jh2LfiG5PpiMkW0YWIbLCs="
[mod."github.com/KyleBanks/depth"]
version = "v1.2.1"
hash = "sha256-czR52MfeKA2FdStXCebTMQRKT8jaWQcbV214O3j49qU="
[mod."github.com/Microsoft/go-winio"]
version = "v0.6.2"
hash = "sha256-tVNWDUMILZbJvarcl/E7tpSnkn7urqgSHa2Eaka5vSU="
@@ -32,8 +35,8 @@ schema = 3
version = "v1.3.3"
hash = "sha256-jv7ZshpSd7FZzKKN6hqlUgiR8C3y85zNIS/hq7g76Ho="
[mod."github.com/anthropics/anthropic-sdk-go"]
version = "v1.16.0"
hash = "sha256-hD6Ix+V5IBFfoaCuAZemrDQx/+G111fCYHn2FAxFuEE="
version = "v1.19.0"
hash = "sha256-ubYeau5XL0tx4c/79L58rzJGOdOWs9z6WQOtN6mpgxw="
[mod."github.com/araddon/dateparse"]
version = "v0.0.0-20210429162001-6b43995a97de"
hash = "sha256-UuX84naeRGMsFOgIgRoBHG5sNy1CzBkWPKmd6VbLwFw="
@@ -88,18 +91,21 @@ schema = 3
[mod."github.com/aws/smithy-go"]
version = "v1.23.0"
hash = "sha256-75k+gn1lbQB1TzjV3HeEJeuyPPfX2huKhONXo98SUKg="
[mod."github.com/bytedance/gopkg"]
version = "v0.1.3"
hash = "sha256-GyUbPfn41y/mgj0cQOa4tm+aj70C2K50VBZxZc/tcZE="
[mod."github.com/bytedance/sonic"]
version = "v1.13.3"
hash = "sha256-Nnt5b2NkIvSXhGERQmyI0ka28hbWi7A7Zn3dsAjPcEA="
version = "v1.14.2"
hash = "sha256-S6EGwzt3TaTUjU1SdtorTdAq3xwROzSGZT6ynfLNq8o="
[mod."github.com/bytedance/sonic/loader"]
version = "v0.2.4"
hash = "sha256-rv9LnePpm4OspSVbfSoVbohXzhu+dxE1BH1gm3mTmTc="
version = "v0.4.0"
hash = "sha256-Hc2bB9nLEFhyipIVHKnJmi6WMoWPCe0REK3bmQThO4A="
[mod."github.com/cloudflare/circl"]
version = "v1.6.1"
hash = "sha256-Dc69V12eIFnJoUNmwg6VKXHfAMijbAeEVSDe8AiOaLo="
[mod."github.com/cloudwego/base64x"]
version = "v0.1.5"
hash = "sha256-MyUYTveN48DhnL8mwAgCRuMExLct98uzSPsmYlfaa4I="
version = "v0.1.6"
hash = "sha256-VzYJsGubsDk3FAMH6e0Xk0Cl4HtUFHHmWkVASUYidsI="
[mod."github.com/coder/websocket"]
version = "v1.8.13"
hash = "sha256-NbF0aPhy8YR3jRM6LMMQTtkeGTFba0eIBPAUsqI9KOk="
@@ -116,14 +122,14 @@ schema = 3
version = "v1.0.4"
hash = "sha256-c1JKoRSndwwOyOxq9ddCe+8qn7mG9uRq2o/822x5O/c="
[mod."github.com/gabriel-vasile/mimetype"]
version = "v1.4.9"
hash = "sha256-75uELLqb01djHTe7KdXvUidBK7SuejarYouEUuxaj8Q="
version = "v1.4.12"
hash = "sha256-vY2g58yUrkT//8fttRKhS9rbg89YSae/BzOARS5uH30="
[mod."github.com/gin-contrib/sse"]
version = "v1.1.0"
hash = "sha256-2VP6zHEsPi0u2ZYpOTcLulwj1Gsmb6oA19qcP2/AzVM="
[mod."github.com/gin-gonic/gin"]
version = "v1.10.1"
hash = "sha256-D98+chAdjb6JcLPkscOr8TgTW87UqA4h3cnY0XIr16c="
version = "v1.11.0"
hash = "sha256-tFP0u7TZyB1V8b1mdnTWMrfdcwzf9yO86RZr026K8Ao="
[mod."github.com/go-git/gcfg"]
version = "v1.5.1-0.20230307220236-3a3c6141e376"
hash = "sha256-f4k0gSYuo0/q3WOoTxl2eFaj7WZpdz29ih6CKc8Ude8="
@@ -139,6 +145,36 @@ schema = 3
[mod."github.com/go-logr/stdr"]
version = "v1.2.2"
hash = "sha256-rRweAP7XIb4egtT1f2gkz4sYOu7LDHmcJ5iNsJUd0sE="
[mod."github.com/go-openapi/jsonpointer"]
version = "v0.22.4"
hash = "sha256-V76k+oQUyqkWcpa64bOirteoCfdn1Xm9TLH0/7W4Uxc="
[mod."github.com/go-openapi/jsonreference"]
version = "v0.21.4"
hash = "sha256-R+Q/MOSRTMiOaZutRmjv/qwbU9/cUWN59Hwr2LgDz2U="
[mod."github.com/go-openapi/spec"]
version = "v0.22.2"
hash = "sha256-o9A6ZVaVPUVP2ssO0I4CDTuGyRuhL/VCM28jU0l32ps="
[mod."github.com/go-openapi/swag/conv"]
version = "v0.25.4"
hash = "sha256-uHgTdZC76LMSsq+x+RyeclnOgBsS0ID2cLgfjzFk0KQ="
[mod."github.com/go-openapi/swag/jsonname"]
version = "v0.25.4"
hash = "sha256-Z6uETeudh8W+/SGxFBnOB/VlJeRPRkFgCyJmntpz7bc="
[mod."github.com/go-openapi/swag/jsonutils"]
version = "v0.25.4"
hash = "sha256-TQGeMImUuL5BWDoBHKAjZ1BvvxPXkFrV3TMgb82IrLk="
[mod."github.com/go-openapi/swag/loading"]
version = "v0.25.4"
hash = "sha256-xr8OnFqB/kwBj3yf9HiLJwDcpL7I3/qJYlKb6VWbVFA="
[mod."github.com/go-openapi/swag/stringutils"]
version = "v0.25.4"
hash = "sha256-rVo5NBH+oLLX9kaemUYWILd+TKw/TDTB8UdSz+mn3m8="
[mod."github.com/go-openapi/swag/typeutils"]
version = "v0.25.4"
hash = "sha256-59RHnK6ugsAUc+A8DZCj7gZ3bJnt01Al7T/1kzM9PpA="
[mod."github.com/go-openapi/swag/yamlutils"]
version = "v0.25.4"
hash = "sha256-zba7QX7Ds05oZq1opP/vwRSBEDaJ1pKm+9DgrsOuR9w="
[mod."github.com/go-playground/locales"]
version = "v0.14.1"
hash = "sha256-BMJGAexq96waZn60DJXZfByRHb8zA/JP/i6f/YrW9oQ="
@@ -146,8 +182,8 @@ schema = 3
version = "v0.18.1"
hash = "sha256-2/B2qP51zfiY+k8G0w0D03KXUc7XpWj6wKY7NjNP/9E="
[mod."github.com/go-playground/validator/v10"]
version = "v10.26.0"
hash = "sha256-/jMKICp8LTcJVt+b4YRTnJM84r7HK6aT0oqO7Q8SRs8="
version = "v10.29.0"
hash = "sha256-HFiWBwxNlzoyMlRwA92rAiEGjBy9Dz/ZUKSRp8pXB2Y="
[mod."github.com/go-shiori/dom"]
version = "v0.0.0-20230515143342-73569d674e1c"
hash = "sha256-4lm9KZfR2XnfZU9KTG+4jqLYZqbfL74AMO4y3dKpIbg="
@@ -157,6 +193,9 @@ schema = 3
[mod."github.com/goccy/go-json"]
version = "v0.10.5"
hash = "sha256-/EtlGihP0/7oInzMC5E0InZ4b5Ad3s4xOpqotloi3xw="
[mod."github.com/goccy/go-yaml"]
version = "v1.19.1"
hash = "sha256-zlT9y4wkvyv7RBv48jdJqOM2lrDMLrC6Z6hCl90c5hQ="
[mod."github.com/gogs/chardet"]
version = "v0.0.0-20211120154057-b7413eaefb8f"
hash = "sha256-4MeqBJsh4U+ZEbfdDwdciTYMlQWkCil2KJbUxHjBSIo="
@@ -212,8 +251,8 @@ schema = 3
version = "v1.2.0"
hash = "sha256-Ta7ZOmyX8gG5tzWbY2oES70EJPfI90U7CIJS9EAce0s="
[mod."github.com/klauspost/cpuid/v2"]
version = "v2.2.10"
hash = "sha256-o21Tk5sD7WhhLUoqSkymnjLbzxl0mDJCTC1ApfZJrC0="
version = "v2.3.0"
hash = "sha256-50JhbQyT67BK38HIdJihPtjV7orYp96HknI2VP7A9Yc="
[mod."github.com/leodido/go-urn"]
version = "v1.4.0"
hash = "sha256-Q6kplWkY37Tzy6GOme3Wut40jFK4Izun+ij/BJvcEu0="
@@ -236,8 +275,8 @@ schema = 3
version = "v0.11.7"
hash = "sha256-3Wn1JWmil0aQQ2I/r398HbnUsi8ADoroqNyPziuxn/c="
[mod."github.com/openai/openai-go"]
version = "v1.8.2"
hash = "sha256-O8aV3zEj6o8kIlzlkYaTW4RzvwR3qNUBYiN8SuTM1R0="
version = "v1.12.0"
hash = "sha256-JHLlKvDwERPf728GUXBsKU58ODgCxcxEe9TKJTGAG1w="
[mod."github.com/otiai10/copy"]
version = "v1.14.1"
hash = "sha256-8RR7u17SbYg9AeBXVHIv5ZMU+kHmOcx0rLUKyz6YtU0="
@@ -256,6 +295,12 @@ schema = 3
[mod."github.com/pmezard/go-difflib"]
version = "v1.0.1-0.20181226105442-5d4384ee4fb2"
hash = "sha256-XA4Oj1gdmdV/F/+8kMI+DBxKPthZ768hbKsO3d9Gx90="
[mod."github.com/quic-go/qpack"]
version = "v0.6.0"
hash = "sha256-xaxHnTKIZt1cHK5ZqTuSTOt5RNSjQB37GlrIgEGBskM="
[mod."github.com/quic-go/quic-go"]
version = "v0.57.1"
hash = "sha256-MdXc0GRVp3YuN9XFoGFOjgIcIMp7yoLqwfEikZp1i4w="
[mod."github.com/samber/lo"]
version = "v1.50.0"
hash = "sha256-KDFks82BKu39sGt0f972IyOkohV2U0r1YvsnlNLdugY="
@@ -277,6 +322,15 @@ schema = 3
[mod."github.com/stretchr/testify"]
version = "v1.11.1"
hash = "sha256-sWfjkuKJyDllDEtnM8sb/pdLzPQmUYWYtmeWz/5suUc="
[mod."github.com/swaggo/files"]
version = "v1.0.1"
hash = "sha256-bNBmpJaM7g1BNwd7VxNIRSdY35NKSXhYHGfnZsSEUZ8="
[mod."github.com/swaggo/gin-swagger"]
version = "v1.6.1"
hash = "sha256-9TQuEmPpDO2QL0c9VwjK9uwB1jka08Ox6fje2RwVpUc="
[mod."github.com/swaggo/swag"]
version = "v1.16.6"
hash = "sha256-na5+ZylxPFKoMJcgx8nmSJXMMkKFCyuh1qSkb7Qth/I="
[mod."github.com/tidwall/gjson"]
version = "v1.18.0"
hash = "sha256-CO6hqDu8Y58Po6A01e5iTpwiUBQ5khUZsw7czaJHw0I="
@@ -293,8 +347,8 @@ schema = 3
version = "v0.15.1"
hash = "sha256-HLk6oUe7EoITrNvP0y8D6BtIgIcmDZYtb/xl/dufIoY="
[mod."github.com/ugorji/go/codec"]
version = "v1.2.14"
hash = "sha256-PoVXlCBE8SvMWpXx9FRsQOSAmE/+5SnPGr4m5BGoyIo="
version = "v1.3.1"
hash = "sha256-VQtXVaKxXjm5Q60hCgVKZxNywl6SJFPqju6JNjADp4w="
[mod."github.com/xanzy/ssh-agent"]
version = "v0.3.3"
hash = "sha256-l3pGB6IdzcPA/HLk93sSN6NM2pKPy+bVOoacR5RC2+c="
@@ -313,30 +367,42 @@ schema = 3
[mod."go.opentelemetry.io/otel/trace"]
version = "v1.36.0"
hash = "sha256-owWD9x1lp8aIJqYt058BXPUsIMHdk3RI0escso0BxwA="
[mod."go.uber.org/mock"]
version = "v0.6.0"
hash = "sha256-m11cxIbrvOowa6xj11AztzfFk86DwR6SNO1lStcKzvo="
[mod."go.yaml.in/yaml/v3"]
version = "v3.0.4"
hash = "sha256-NkGFiDPoCxbr3LFsI6OCygjjkY0rdmg5ggvVVwpyDQ4="
[mod."golang.org/x/arch"]
version = "v0.18.0"
hash = "sha256-tUpUPERjmRi7zldj0oPlnbnBhEkcI9iQGvP1HqlsK10="
version = "v0.23.0"
hash = "sha256-ynvhsw8ZYgKTzFn1wnIj3/p+1O/Ty5PX1Lnj+NMTAQQ="
[mod."golang.org/x/crypto"]
version = "v0.41.0"
hash = "sha256-o5Di0lsFmYnXl7a5MBTqmN9vXMCRpE9ay71C1Ar8jEY="
version = "v0.46.0"
hash = "sha256-I8N/spcw3/h0DFA+V1WK38HctckWIB9ep93DEVCALxU="
[mod."golang.org/x/exp"]
version = "v0.0.0-20250531010427-b6e5de432a8b"
hash = "sha256-QaFfjyB+pogCkUkJskR9xnXwkCOU828XJRrzwwLm6Ms="
[mod."golang.org/x/mod"]
version = "v0.31.0"
hash = "sha256-ZVNmaZADgM3+30q9rW8q4gP6ySkT7r1eb4vrHIlpCjM="
[mod."golang.org/x/net"]
version = "v0.43.0"
hash = "sha256-bf3iQFrsC8BoarVaS0uSspEFAcr1zHp1uziTtBpwV34="
version = "v0.48.0"
hash = "sha256-oZpddsiJwWCH3Aipa+XXpy7G/xHY5fEagUSok7T0bXE="
[mod."golang.org/x/oauth2"]
version = "v0.30.0"
hash = "sha256-btD7BUtQpOswusZY5qIU90uDo38buVrQ0tmmQ8qNHDg="
[mod."golang.org/x/sync"]
version = "v0.16.0"
hash = "sha256-sqKDRESeMzLe0jWGWltLZL/JIgrn0XaIeBWCzVN3Bks="
version = "v0.19.0"
hash = "sha256-RbRZ+sKZUurOczGhhzOoY/sojTlta3H9XjL4PXX/cno="
[mod."golang.org/x/sys"]
version = "v0.35.0"
hash = "sha256-ZKM8pesQE6NAFZeKQ84oPn5JMhGr8g4TSwLYAsHMGSI="
version = "v0.39.0"
hash = "sha256-dxTBu/JAWUkPbjFIXXRFdhQWyn+YyEpIC+tWqGo0Y6U="
[mod."golang.org/x/text"]
version = "v0.28.0"
hash = "sha256-8UlJniGK+km4Hmrw6XMxELnExgrih7+z8tU26Cntmto="
version = "v0.32.0"
hash = "sha256-9PXtWBKKY9rG4AgjSP4N+I1DhepXhy8SF/vWSIDIoWs="
[mod."golang.org/x/tools"]
version = "v0.40.0"
hash = "sha256-ksmhTnH9btXKiRbbE0KGh02nbeNqNBQKcfwvx9dE7t0="
[mod."google.golang.org/api"]
version = "v0.247.0"
hash = "sha256-UzTtydHmNqh1OXbxcN5qNKQxb5dV6h2Mo6DH4P219Ec="
@@ -353,8 +419,8 @@ schema = 3
version = "v1.74.2"
hash = "sha256-tvYMdfu/ZQZRPZNmnQI4CZpg46CM8+mD49hw0gFheGs="
[mod."google.golang.org/protobuf"]
version = "v1.36.7"
hash = "sha256-6xCU+t2AVPcscMKenVs4etGqutYGPDXCQ3DCD3PpTq4="
version = "v1.36.11"
hash = "sha256-7W+6jntfI/awWL3JP6yQedxqP5S9o3XvPgJ2XxxsIeE="
[mod."gopkg.in/warnings.v0"]
version = "v0.1.2"
hash = "sha256-ATVL9yEmgYbkJ1DkltDGRn/auGAjqGOfjQyBYyUo8s8="

View File

@@ -1 +1 @@
"1.4.324"
"1.4.351"

View File

@@ -18,7 +18,7 @@ FROM alpine:latest
LABEL org.opencontainers.image.description="A Docker image for running the Fabric CLI. See https://github.com/danielmiessler/Fabric/tree/main/scripts/docker for details."
RUN apk add --no-cache ca-certificates \
RUN apk add --no-cache ca-certificates yt-dlp \
&& mkdir -p /root/.config/fabric
COPY --from=builder /fabric /usr/local/bin/fabric

View File

@@ -3,6 +3,7 @@
"""Extracts pattern information from the ~/.config/fabric/patterns directory,
creates JSON files for pattern extracts and descriptions, and updates web static files.
"""
import os
import json
import shutil
@@ -33,7 +34,13 @@ def get_pattern_extract(pattern_path):
def extract_pattern_info():
"""Extract pattern information from the patterns directory"""
script_dir = os.path.dirname(os.path.abspath(__file__))
patterns_dir = os.path.expanduser("~/.config/fabric/patterns")
local_patterns_dir = os.path.join(script_dir, "..", "..", "data", "patterns")
if os.path.exists(local_patterns_dir):
patterns_dir = local_patterns_dir
else:
patterns_dir = os.path.expanduser("~/.config/fabric/patterns")
print(f"\nScanning patterns directory: {patterns_dir}")
extracts_path = os.path.join(script_dir, "pattern_extracts.json")

View File

@@ -1101,14 +1101,6 @@
"REVIEW"
]
},
{
"patternName": "get_youtube_rss",
"description": "Generate RSS feed URLs for YouTube channels.",
"tags": [
"CONVERSION",
"DEVELOPMENT"
]
},
{
"patternName": "humanize",
"description": "Transform technical content into approachable language.",
@@ -1932,6 +1924,14 @@
"tags": [
"VISUALIZE"
]
},
{
"patternName": "concall_summary",
"description": "Extract strategic insights from earnings transcripts for investors.",
"tags": [
"SUMMARIZE",
"BUSINESS"
]
}
]
}

View File

@@ -540,10 +540,6 @@
"patternName": "get_wow_per_minute",
"pattern_extract": "# IDENTITY\n\nYou are an expert at determining the wow-factor of content as measured per minute of content, as determined by the steps below.\n\n# GOALS\n\n- The goal is to determine how densely packed the content is with wow-factor. Note that wow-factor can come from multiple types of wow, such as surprise, novelty, insight, value, and wisdom, and also from multiple types of content such as business, science, art, or philosophy.\n\n- The goal is to determine how rewarding this content will be for a viewer in terms of how often they'll be surprised, learn something new, gain insight, find practical value, or gain wisdom.\n\n# STEPS\n\n- Fully and deeply consume the content at least 319 times, using different interpretive perspectives each time.\n\n- Construct a giant virtual whiteboard in your mind.\n\n- Extract the ideas being presented in the content and place them on your giant virtual whiteboard.\n\n- Extract the novelty of those ideas and place them on your giant virtual whiteboard.\n\n- Extract the insights from those ideas and place them on your giant virtual whiteboard.\n\n- Extract the value of those ideas and place them on your giant virtual whiteboard.\n\n- Extract the wisdom of those ideas and place them on your giant virtual whiteboard."
},
{
"patternName": "get_youtube_rss",
"pattern_extract": "# IDENTITY AND GOALS\n\nYou are a YouTube infrastructure expert that returns YouTube channel RSS URLs.\n\nYou take any input in, especially YouTube channel IDs, or full URLs, and return the RSS URL for that channel.\n\n# STEPS\n\nHere is the structure for YouTube RSS URLs and their relation to the channel ID and or channel URL:\n\nIf the channel URL is https://www.youtube.com/channel/UCnCikd0s4i9KoDtaHPlK-JA, the RSS URL is https://www.youtube.com/feeds/videos.xml?channel_id=UCnCikd0s4i9KoDtaHPlK-JA\n\n- Extract the channel ID from the channel URL.\n\n- Construct the RSS URL using the channel ID.\n\n- Output the RSS URL.\n\n# OUTPUT\n\n- Output only the RSS URL and nothing else.\n\n- Don't complain, just do it.\n\n# INPUT"
},
{
"patternName": "humanize",
"pattern_extract": "# IDENTITY and PURPOSE\n\nYou are a real person whose job is to make text sound natural, conversational, and relatable, just like how an average person talks or writes. Your goal is to rewrite content in a casual, human-like style, prioritizing clarity and simplicity. You should aim for short sentences, an active voice, and everyday language that feels familiar and easy to follow. Avoid long, complex sentences or technical jargon. Instead, focus on breaking ideas into smaller, easy-to-understand parts. Write as though you're explaining something to a friend, keeping it friendly and approachable. Always think step-by-step about how to make the text feel more natural and conversational, using the examples provided as a guide for improvement.\n\nWhile rewriting, ensure the original meaning and tone are preserved. Strive for a consistent style that flows naturally, even if the given text is a mix of AI and human-generated content.\n\n# YOUR TASK\n\nYour task is to rewrite the given AI-generated text to make it sound like it was written by a real person. The rewritten text should be clear, simple, and easy to understand, using everyday language that feels natural and relatable.\n\n- Focus on clarity: Make sure the text is straightforward and avoids unnecessary complexity.\n- Keep it simple: Use common words and phrases that anyone can understand.\n- Prioritize short sentences: Break down long, complicated sentences into smaller, more digestible ones.\n- Maintain context: Ensure that the rewritten text accurately reflects the original meaning and tone.\n- Harmonize mixed content: If the text contains a mix of human and AI styles, edit to ensure a consistent, human-like flow.\n- Iterate if necessary: Revisit and refine the text to enhance its naturalness and readability.\n\nYour goal is to make the text approachable and authentic, capturing the way a real person would write or speak.\n\n# STEPS\n\n1. Carefully read the given text and understand its meaning and tone.\n2. Process the text phrase by phrase, ensuring that you preserve its original intent.\n3. Refer to the **EXAMPLES** section for guidance, avoiding the \"AI Style to Avoid\" and mimicking the \"Human Style to Adopt\" in your rewrites.\n4. If no relevant example exists in the **EXAMPLES** section:"
@@ -935,6 +931,10 @@
{
"patternName": "create_conceptmap",
"pattern_extract": "--- ### IDENTITY AND PURPOSE You are an intelligent assistant specialized in **knowledge visualization and educational data structuring**. You are capable of reading unstructured textual content (.txt or .md files), extracting **main concepts, subthemes, and logical relationships**, and transforming them into a **fully interactive conceptual map** built in **HTML using Vis.js (vis-network)**. You understand hierarchical, causal, and correlative relations between ideas and express them through **nodes and directed edges**. You ensure that the resulting HTML file is **autonomous, interactive, and visually consistent** with the Vis.js framework. You are precise, systematic, and maintain semantic coherence between concepts and their relationships. You automatically name the output file according to the **detected topic**, ensuring compatibility and clarity (e.g., `map_hist_china.html`). --- ### TASK You are given a `.txt` or `.md` file containing explanatory, conceptual, or thematic content. Your task is to: 1. **Extract** the main concepts and secondary ideas. 2. **Identify logical or hierarchical relationships** among these concepts using concise action verbs. 3. **Structure the output** as a self-contained, interactive HTML document that visually represents these relationships using the **Vis.js (vis-network)** library. The goal is to generate a **fully functional conceptual map** that can be opened directly in a browser without external dependencies. --- ### ACTIONS 1. **Analyze and Extract Concepts** - Read and process the uploaded `.txt` or `.md` file. - Identify main themes, subthemes, and key terms. - Convert each key concept into a node. 2. **Map Relationships** - Detect logical and hierarchical relations between concepts. - Use short, descriptive verbs such as: \"causes\", \"contributes to\", \"depends on\", \"evolves into\", \"results in\", \"influences\", \"generates\" / \"creates\", \"culminates in. 3. **Generate Node Structure** ```json {\"id\": \"conceito_id\", \"label\": \"Conceito\", \"title\": \"<b>Concept:</b> Conceito<br><i>Drag to position, double-click to release.</i>\"} ``` 4. **Generate Edge Structure** ```json {\"from\": \"conceito_origem\", \"to\": \"conceito_destino\", \"label\": \"verbo\", \"title\": \"<b>Relationship:</b> verbo\"} ``` 5. **Apply Visual and Physical Configuration** ```js shape: \"dot\", color: { border: \"#4285F4\", background: \"#ffffff\", highlight: { border: \"#34A853\", background: \"#e6f4ea\" } }, font: { size: 14, color: \"#3c4043\" }, borderWidth: 2, size: 20 // Edges color: { color: \"#dee2e6\", highlight: \"#34A853\" }, arrows: { to: { enabled: true, scaleFactor: 0.7 } }, font: { align: \"middle\", size: 12, color: \"#5f6368\" }, width: 2 // Physics physics: { solver: \"forceAtlas2Based\", forceAtlas2Based: { gravitationalConstant: -50, centralGravity: 0.005, springLength: 100, springConstant: 0.18 }, maxVelocity: 146, minVelocity: 0.1, stabilization: { iterations: 150 } } ``` 6. **Implement Interactivity** ```js // Fix node on drag end network.on(\"dragEnd\", (params) => { if (params.nodes.length > 0) { nodes.update({ id: params.nodes[0], fixed: true }); } }); // Release node on double click network.on(\"doubleClick\", (params) => { if (params.nodes.length > 0) { nodes.update({ id: params.nodes[0], fixed: false }); } }); ``` 7. **Assemble the Complete HTML Structure** ```html <head> <title>Mapa Conceitual — [TEMA DETECTADO DO ARQUIVO]</title> <script src=\"https://unpkg.com/vis-network/standalone/umd/vis-network.min.js\"></script> <link href=\"https://unpkg.com/vis-network/styles/vis-network.min.css\" rel=\"stylesheet\" /> </head> <body> <div id=\"map\"></div> <script type=\"text/javascript\"> // nodes, edges, options, and interactive network initialization </script> </body> ``` 8. **Auto-name Output File** Automatically save the generated HTML file based on the detected topic: ``` mapa_[tema_detectado].html ``` --- ###"
},
{
"patternName": "concall_summary",
"pattern_extract": "# IDENTITY and PURPOSE You are an equity research analyst specializing in earnings and conference call analysis. Your role involves carefully examining transcripts to extract actionable insights that can inform investment decisions. You need to focus on several key areas, including management commentary, analyst questions, financial and operational insights, risks and red flags, hidden signals, and an executive summary. Your task is to distill complex information into clear, concise bullet points, capturing strategic themes, growth drivers, and potential concerns. It is crucial to interpret the tone, identify contradictions, and highlight any subtle cues that may indicate future strategic shifts or risks. Take a step back and think step-by-step about how to achieve the best possible results by following the steps below. # STEPS * Analyze the transcript to extract management commentary, focusing on strategic themes, growth drivers, margin commentary, guidance, tone analysis, and any contradictions or vague areas. * Extract a summary of the content in exactly **25 words**, including who is presenting and the content being discussed; place this under a **SUMMARY** section. * For each analyst's question, determine the underlying concern, summarize managements exact answer, evaluate if the answers address the question fully, and identify anything the management avoided or deflected. * Gather financial and operational insights, including commentary on demand, pricing, capacity, market share, cost inflation, raw material trends, and supply-chain issues. * Identify risks and red flags by noting any negative commentary, early warning signs, unusual wording, delayed responses, repeated disclaimers, and areas where management seemed less confident. * Detect hidden signals such as forward-looking hints, unasked but important questions, and subtle cues about strategy shifts or stress. * Create an executive summary in bullet points, listing the 10 most important takeaways, 3 surprises, and 3 things to track in the next quarter. # OUTPUT STRUCTURE * MANAGEMENT COMMENTARY * Key strategic themes * Growth drivers discussed * Margin commentary * Guidance (explicit + implicit) * Tone analysis (positive/neutral/negative) * Any contradictions or vague areas * ANALYST QUESTIONS (Q&A) * For each analyst (use bullets, one analyst per bullet-group): * Underlying concern (what the question REALLY asked) * Managements exact answer (concise) * Answer completeness (Yes/No — short explanation) * Items management avoided or deflected * FINANCIAL & OPERATIONAL INSIGHTS * Demand, pricing, capacity, market share commentary * Cost inflation, raw material trends, supply-chain issues * Segment-wise performance and commentary (if applicable) * RISKS & RED FLAGS * Negative commentary or early-warning signs * Unusual wording, delayed responses, repeated disclaimers * Areas where management was less confident * HIDDEN SIGNALS * Forward-looking hints and tone shifts * Important topics not asked by analysts but relevant * Subtle cues of strategy change, stress, or opportunity * EXECUTIVE SUMMARY * 10 most important takeaways (bullet points) * 3 surprises (bullet points) * 3 things to track next quarter (bullet points) * SUMMARY (exactly 25 words) * A single 25-word sentence summarizing who presented and what was discussed # OUTPUT INSTRUCTIONS * Only output Markdown. * Provide everything in"
}
]
}

View File

@@ -26,9 +26,9 @@
"eslint-plugin-svelte": "^2.46.1",
"lucide-svelte": "^0.309.0",
"mdsvex": "^0.11.2",
"patch-package": "^8.0.0",
"patch-package": "^8.0.1",
"pdf-to-markdown-core": "github:jzillmann/pdf-to-markdown#modularize",
"pdfjs-dist": "^4.2.67",
"pdfjs-dist": "^5.4.449",
"postcss": "^8.5.3",
"postcss-load-config": "^6.0.1",
"rehype-autolink-headings": "^7.1.0",

565
web/pnpm-lock.yaml generated

File diff suppressed because it is too large Load Diff

View File

@@ -1,239 +1,284 @@
import { get } from "svelte/store";
import type {
ChatRequest,
StreamResponse,
ChatError as IChatError,
ChatPrompt
} from '$lib/interfaces/chat-interface';
import { get } from 'svelte/store';
import { modelConfig } from '$lib/store/model-store';
import { systemPrompt, selectedPatternName, patternVariables } from '$lib/store/pattern-store';
import { chatConfig } from '$lib/store/chat-config';
import { messageStore } from '$lib/store/chat-store';
import { languageStore } from '$lib/store/language-store';
import { selectedStrategy } from '$lib/store/strategy-store';
ChatPrompt,
ChatRequest,
ChatError as IChatError,
StreamResponse,
} from "$lib/interfaces/chat-interface";
import { chatConfig } from "$lib/store/chat-config";
import { languageStore } from "$lib/store/language-store";
import { modelConfig } from "$lib/store/model-store";
import {
patternVariables,
selectedPatternName,
systemPrompt,
} from "$lib/store/pattern-store";
import { selectedStrategy } from "$lib/store/strategy-store";
class LanguageValidator {
constructor(private targetLanguage: string) {}
constructor(private targetLanguage: string) {}
enforceLanguage(content: string): string {
if (this.targetLanguage === 'en') return content;
return `[Language: ${this.targetLanguage}]\n${content}`;
}
enforceLanguage(content: string): string {
if (this.targetLanguage === "en") return content;
return `[Language: ${this.targetLanguage}]\n${content}`;
}
}
export class ChatError extends Error implements IChatError {
constructor(
message: string,
public readonly code: string = 'CHAT_ERROR',
public readonly details?: unknown
) {
super(message);
this.name = 'ChatError';
}
constructor(
message: string,
public readonly code: string = "CHAT_ERROR",
public readonly details?: unknown,
) {
super(message);
this.name = "ChatError";
}
}
export class ChatService {
private validator: LanguageValidator;
private validator: LanguageValidator;
constructor() {
this.validator = new LanguageValidator(get(languageStore));
}
constructor() {
this.validator = new LanguageValidator(get(languageStore));
}
private async fetchStream(request: ChatRequest): Promise<ReadableStream<StreamResponse>> {
try {
console.log('\n=== ChatService Request Start ===');
console.log('1. Request details:', {
language: get(languageStore),
pattern: get(selectedPatternName),
promptCount: request.prompts?.length,
messageCount: request.messages?.length
});
// NEW: Log the full payload before sending to backend
console.log('Final ChatRequest payload:', JSON.stringify(request, null, 2));
private async fetchStream(
request: ChatRequest,
): Promise<ReadableStream<StreamResponse>> {
try {
console.log("\n=== ChatService Request Start ===");
console.log("1. Request details:", {
language: get(languageStore),
pattern: get(selectedPatternName),
promptCount: request.prompts?.length,
messageCount: request.messages?.length,
});
// NEW: Log the full payload before sending to backend
console.log(
"Final ChatRequest payload:",
JSON.stringify(request, null, 2),
);
const response = await fetch('/api/chat', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(request),
});
const response = await fetch("/api/chat", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(request),
});
if (!response.ok) {
throw new ChatError(`HTTP error! status: ${response.status}`, 'HTTP_ERROR', { status: response.status });
}
if (!response.ok) {
throw new ChatError(
`HTTP error! status: ${response.status}`,
"HTTP_ERROR",
{ status: response.status },
);
}
const reader = response.body?.getReader();
if (!reader) {
throw new ChatError('Response body is null', 'NULL_RESPONSE');
}
const reader = response.body?.getReader();
if (!reader) {
throw new ChatError("Response body is null", "NULL_RESPONSE");
}
return this.createMessageStream(reader);
} catch (error) {
if (error instanceof ChatError) throw error;
throw new ChatError('Failed to fetch chat stream', 'FETCH_ERROR', error);
}
}
return this.createMessageStream(reader);
} catch (error) {
if (error instanceof ChatError) throw error;
throw new ChatError("Failed to fetch chat stream", "FETCH_ERROR", error);
}
}
private cleanPatternOutput(content: string): string {
// Remove markdown fence if present
let cleaned = content.replace(/^```markdown\n/, '');
cleaned = cleaned.replace(/\n```$/, '');
private cleanPatternOutput(content: string): string {
// Remove markdown fence if present
let cleaned = content.replace(/^```markdown\n/, "");
cleaned = cleaned.replace(/\n```$/, "");
// Existing cleaning
cleaned = cleaned.replace(/^# OUTPUT\s*\n/, '');
cleaned = cleaned.replace(/^\s*\n/, '');
cleaned = cleaned.replace(/\n\s*$/, '');
cleaned = cleaned.replace(/^#\s+([A-Z]+):/gm, '$1:');
cleaned = cleaned.replace(/^#\s+([A-Z]+)\s*$/gm, '$1');
cleaned = cleaned.trim();
cleaned = cleaned.replace(/\n{3,}/g, '\n\n');
return cleaned;
}
// Existing cleaning
cleaned = cleaned.replace(/^# OUTPUT\s*\n/, "");
cleaned = cleaned.replace(/^\s*\n/, "");
cleaned = cleaned.replace(/\n\s*$/, "");
cleaned = cleaned.replace(/^#\s+([A-Z]+):/gm, "$1:");
cleaned = cleaned.replace(/^#\s+([A-Z]+)\s*$/gm, "$1");
cleaned = cleaned.trim();
cleaned = cleaned.replace(/\n{3,}/g, "\n\n");
return cleaned;
}
private createMessageStream(reader: ReadableStreamDefaultReader<Uint8Array>): ReadableStream<StreamResponse> {
let buffer = '';
const cleanPatternOutput = this.cleanPatternOutput.bind(this);
const language = get(languageStore);
const validator = new LanguageValidator(language);
private createMessageStream(
reader: ReadableStreamDefaultReader<Uint8Array>,
): ReadableStream<StreamResponse> {
let buffer = "";
const cleanPatternOutput = this.cleanPatternOutput.bind(this);
const language = get(languageStore);
const validator = new LanguageValidator(language);
const processResponse = (response: StreamResponse) => {
const pattern = get(selectedPatternName);
const processResponse = (response: StreamResponse) => {
const pattern = get(selectedPatternName);
if (pattern) {
response.content = cleanPatternOutput(response.content);
// Simplified format determination - always markdown unless mermaid
const isMermaid = [
'graph TD', 'gantt', 'flowchart',
'sequenceDiagram', 'classDiagram', 'stateDiagram'
].some(starter => response.content.trim().startsWith(starter));
if (pattern) {
response.content = cleanPatternOutput(response.content);
// Simplified format determination - always markdown unless mermaid
const isMermaid = [
"graph TD",
"gantt",
"flowchart",
"sequenceDiagram",
"classDiagram",
"stateDiagram",
].some((starter) => response.content.trim().startsWith(starter));
response.format = isMermaid ? 'mermaid' : 'markdown';
}
response.format = isMermaid ? "mermaid" : "markdown";
}
if (response.type === 'content') {
response.content = validator.enforceLanguage(response.content);
}
if (response.type === "content") {
response.content = validator.enforceLanguage(response.content);
}
return response;
};
return new ReadableStream({
async start(controller) {
try {
while (true) {
const { done, value } = await reader.read();
if (done) break;
return response;
};
return new ReadableStream({
async start(controller) {
try {
while (true) {
const { done, value } = await reader.read();
if (done) break;
buffer += new TextDecoder().decode(value);
const messages = buffer.split('\n\n').filter(msg => msg.startsWith('data: '));
buffer += new TextDecoder().decode(value);
const messages = buffer
.split("\n\n")
.filter((msg) => msg.startsWith("data: "));
if (messages.length > 1) {
buffer = messages.pop() || '';
for (const msg of messages) {
try {
let response = JSON.parse(msg.slice(6)) as StreamResponse;
response = processResponse(response);
controller.enqueue(response);
} catch (parseError) {
console.error('Error parsing stream message:', parseError);
}
}
}
}
if (messages.length > 1) {
buffer = messages.pop() || "";
for (const msg of messages) {
try {
let response = JSON.parse(msg.slice(6)) as StreamResponse;
response = processResponse(response);
controller.enqueue(response);
} catch (parseError) {
console.error("Error parsing stream message:", parseError);
}
}
}
}
if (buffer.startsWith('data: ')) {
try {
let response = JSON.parse(buffer.slice(6)) as StreamResponse;
response = processResponse(response);
controller.enqueue(response);
} catch (parseError) {
console.error('Error parsing final message:', parseError);
}
}
} catch (error) {
controller.error(new ChatError('Stream processing error', 'STREAM_ERROR', error));
} finally {
reader.releaseLock();
controller.close();
}
},
cancel() {
reader.cancel();
}
});
}
if (buffer.startsWith("data: ")) {
try {
let response = JSON.parse(buffer.slice(6)) as StreamResponse;
response = processResponse(response);
controller.enqueue(response);
} catch (parseError) {
console.error("Error parsing final message:", parseError);
}
}
} catch (error) {
controller.error(
new ChatError("Stream processing error", "STREAM_ERROR", error),
);
} finally {
reader.releaseLock();
controller.close();
}
},
cancel() {
reader.cancel();
},
});
}
private createChatPrompt(userInput: string, systemPromptText?: string): ChatPrompt {
const config = get(modelConfig);
const language = get(languageStore);
private createChatPrompt(
userInput: string,
systemPromptText?: string,
): ChatPrompt {
const config = get(modelConfig);
const language = get(languageStore);
const languageInstruction = language !== 'en'
? `You MUST respond in ${language} language. All output must be in ${language}. `
// ? `You MUST respond in ${language} language. ALL output, including section headers, titles, and formatting, MUST be translated into ${language}. It is CRITICAL that you translate ALL headers, such as SUMMARY, IDEAS, QUOTES, TAKEAWAYS, MAIN POINTS, etc., into ${language}. Maintain markdown formatting in the response. Do not output any English headers.`
: '';
const languageInstruction =
language !== "en"
? `You MUST respond in ${language} language. All output must be in ${language}. `
: // ? `You MUST respond in ${language} language. ALL output, including section headers, titles, and formatting, MUST be translated into ${language}. It is CRITICAL that you translate ALL headers, such as SUMMARY, IDEAS, QUOTES, TAKEAWAYS, MAIN POINTS, etc., into ${language}. Maintain markdown formatting in the response. Do not output any English headers.`
"";
const finalSystemPrompt = languageInstruction + (systemPromptText ?? get(systemPrompt));
const finalSystemPrompt =
languageInstruction + (systemPromptText ?? get(systemPrompt));
const finalUserInput = language !== 'en'
? `${userInput}\n\nIMPORTANT: Respond in ${language} language only.`
: userInput;
const finalUserInput =
language !== "en"
? `${userInput}\n\nIMPORTANT: Respond in ${language} language only.`
: userInput;
return {
userInput: finalUserInput,
systemPrompt: finalSystemPrompt,
model: config.model,
patternName: get(selectedPatternName),
strategyName: get(selectedStrategy), // Add selected strategy to prompt
variables: get(patternVariables) // Add pattern variables
};
}
public async createChatRequest(userInput: string, systemPromptText?: string, isPattern: boolean = false): Promise<ChatRequest> {
const prompt = this.createChatPrompt(userInput, systemPromptText);
const config = get(chatConfig);
const language = get(languageStore);
return {
prompts: [prompt],
messages: [],
language: language, // Add language at the top level for backend compatibility
...config
};
}
public async streamPattern(userInput: string, systemPromptText?: string): Promise<ReadableStream<StreamResponse>> {
const request = await this.createChatRequest(userInput, systemPromptText, true);
return this.fetchStream(request);
}
public async streamChat(userInput: string, systemPromptText?: string): Promise<ReadableStream<StreamResponse>> {
const request = await this.createChatRequest(userInput, systemPromptText);
return this.fetchStream(request);
}
public async processStream(
stream: ReadableStream<StreamResponse>,
onContent: (content: string, response?: StreamResponse) => void,
onError: (error: Error) => void
): Promise<void> {
const reader = stream.getReader();
try {
while (true) {
const { done, value } = await reader.read();
if (done) break;
if (value.type === 'error') {
throw new ChatError(value.content, 'STREAM_CONTENT_ERROR');
}
if (value.type === 'content') {
onContent(value.content, value);
}
}
} catch (error) {
onError(error instanceof ChatError ? error : new ChatError('Stream processing error', 'STREAM_ERROR', error));
} finally {
reader.releaseLock();
}
}
return {
userInput: finalUserInput,
systemPrompt: finalSystemPrompt,
model: config.model,
patternName: get(selectedPatternName),
strategyName: get(selectedStrategy), // Add selected strategy to prompt
variables: get(patternVariables), // Add pattern variables
};
}
public async createChatRequest(
userInput: string,
systemPromptText?: string,
isPattern: boolean = false,
): Promise<ChatRequest> {
const prompt = this.createChatPrompt(userInput, systemPromptText);
const config = get(chatConfig);
const language = get(languageStore);
return {
prompts: [prompt],
messages: [],
language: language, // Add language at the top level for backend compatibility
...config,
};
}
public async streamPattern(
userInput: string,
systemPromptText?: string,
): Promise<ReadableStream<StreamResponse>> {
const request = await this.createChatRequest(
userInput,
systemPromptText,
true,
);
return this.fetchStream(request);
}
public async streamChat(
userInput: string,
systemPromptText?: string,
): Promise<ReadableStream<StreamResponse>> {
const request = await this.createChatRequest(userInput, systemPromptText);
return this.fetchStream(request);
}
public async processStream(
stream: ReadableStream<StreamResponse>,
onContent: (content: string, response?: StreamResponse) => void,
onError: (error: Error) => void,
): Promise<void> {
const reader = stream.getReader();
try {
while (true) {
const { done, value } = await reader.read();
if (done) break;
if (value.type === "error") {
throw new ChatError(value.content, "STREAM_CONTENT_ERROR");
}
if (value.type === "content") {
onContent(value.content, value);
}
}
} catch (error) {
onError(
error instanceof ChatError
? error
: new ChatError("Stream processing error", "STREAM_ERROR", error),
);
} finally {
reader.releaseLock();
}
}
}

View File

@@ -1,78 +1,74 @@
import { createPipeline, transformers } from 'pdf-to-markdown-core/lib/src';
import { PARSE_SCHEMA } from 'pdf-to-markdown-core/lib/src/PdfParser';
import * as pdfjs from 'pdfjs-dist';
import pdfConfig from './pdf-config';
import { createPipeline, transformers } from "pdf-to-markdown-core/lib/src";
import { PARSE_SCHEMA } from "pdf-to-markdown-core/lib/src/PdfParser";
// pdfjs-dist v5+ requires browser APIs at import time, so we use dynamic imports
let pdfjs: typeof import("pdfjs-dist") | null = null;
export class PdfConversionService {
constructor() {
if (typeof window !== 'undefined') {
console.log('PDF.js version:', pdfjs.version);
// Initialize PDF.js configuration from the shared config
pdfConfig.initialize();
console.log('Worker configuration complete');
}
}
private async ensureInitialized(): Promise<typeof import("pdfjs-dist")> {
if (!pdfjs) {
// Dynamic import to avoid SSR issues with pdfjs-dist v5+
pdfjs = await import("pdfjs-dist");
const pdfConfig = (await import("./pdf-config")).default;
console.log("PDF.js version:", pdfjs.version);
await pdfConfig.initialize();
console.log("Worker configuration complete");
}
return pdfjs;
}
async convertToMarkdown(file: File): Promise<string> {
console.log('Starting PDF conversion:', {
fileName: file.name,
fileSize: file.size
});
async convertToMarkdown(file: File): Promise<string> {
console.log("Starting PDF conversion:", {
fileName: file.name,
fileSize: file.size,
});
const buffer = await file.arrayBuffer();
console.log('Buffer created:', buffer.byteLength);
const pdfjsLib = await this.ensureInitialized();
const pipeline = createPipeline(pdfjs, {
transformConfig: {
transformers
}
});
console.log('Pipeline created');
const buffer = await file.arrayBuffer();
console.log("Buffer created:", buffer.byteLength);
const result = await pipeline.parse(
buffer,
(progress) => console.log('Processing:', {
stage: progress.stages,
details: progress.stageDetails,
progress: progress.stageProgress
})
);
console.log('Parse complete, validating result');
const pipeline = createPipeline(pdfjsLib, {
transformConfig: {
transformers,
},
});
console.log("Pipeline created");
const transformed = result.transform();
console.log('Transform applied:', transformed);
const result = await pipeline.parse(buffer, (progress) =>
console.log("Processing:", {
stage: progress.stages,
details: progress.stageDetails,
progress: progress.stageProgress,
}),
);
console.log("Parse complete, validating result");
const markdown = transformed.convert({
convert: (items) => {
console.log('PDF Structure:', {
itemCount: items.length,
firstItem: items[0],
schema: PARSE_SCHEMA // ['transform', 'width', 'height', 'str', 'fontName', 'dir']
});
const text = items
.map(item => item.value('str')) // Using 'str' instead of 'text' based on PARSE_SCHEMA
.filter(Boolean)
.join('\n');
console.log('Converted text:', {
length: text.length,
preview: text.substring(0, 100)
});
return text;
}
});
const transformed = result.transform();
console.log("Transform applied:", transformed);
return markdown;
}
const markdown = transformed.convert({
convert: (items) => {
console.log("PDF Structure:", {
itemCount: items.length,
firstItem: items[0],
schema: PARSE_SCHEMA, // ['transform', 'width', 'height', 'str', 'fontName', 'dir']
});
const text = items
.map((item) => item.value("str")) // Using 'str' instead of 'text' based on PARSE_SCHEMA
.filter(Boolean)
.join("\n");
console.log("Converted text:", {
length: text.length,
preview: text.substring(0, 100),
});
return text;
},
});
return markdown;
}
}

View File

@@ -1,20 +1,19 @@
import { browser } from '$app/environment';
import { GlobalWorkerOptions } from 'pdfjs-dist';
import { browser } from "$app/environment";
// Set up the worker source location - point to static file in public directory
const workerSrc = '/pdf.worker.min.mjs';
// Configure the worker options only on the client side
if (browser) {
GlobalWorkerOptions.workerSrc = workerSrc;
}
// Export the configuration
// Export the configuration - accepts pdfjs module to avoid top-level import
// This is necessary because pdfjs-dist v5+ uses browser APIs at import time
export default {
initialize: () => {
if (browser) {
console.log('PDF.js worker initialized at', workerSrc);
}
}
};
initialize: async () => {
if (browser) {
// Dynamic import to avoid SSR issues
const pdfjs = await import("pdfjs-dist");
const { GlobalWorkerOptions, version } = pdfjs;
// Use CDN-hosted worker to avoid bundling third-party minified code in the repo
const workerSrc = `https://unpkg.com/pdfjs-dist@${version}/build/pdf.worker.min.mjs`;
GlobalWorkerOptions.workerSrc = workerSrc;
console.log(`PDF.js worker v${version} initialized from CDN`);
}
},
};

View File

@@ -1,19 +1,24 @@
import { writable, derived, get } from 'svelte/store';
import type { ChatState, Message, StreamResponse } from '$lib/interfaces/chat-interface';
import { ChatService, ChatError } from '$lib/services/ChatService';
import { languageStore } from '$lib/store/language-store';
import { selectedPatternName } from '$lib/store/pattern-store';
import { derived, get, writable } from "svelte/store";
import { browser } from "$app/environment";
import type {
ChatState,
Message,
StreamResponse,
} from "$lib/interfaces/chat-interface";
import { ChatError, ChatService } from "$lib/services/ChatService";
import { languageStore } from "$lib/store/language-store";
import { selectedPatternName } from "$lib/store/pattern-store";
// Initialize chat service
const chatService = new ChatService();
// Local storage key for persisting messages
const MESSAGES_STORAGE_KEY = 'chat_messages';
const MESSAGES_STORAGE_KEY = "chat_messages";
// Load initial messages from local storage
const initialMessages = typeof localStorage !== 'undefined'
? JSON.parse(localStorage.getItem(MESSAGES_STORAGE_KEY) || '[]')
: [];
// Load initial messages from local storage (only in browser)
const initialMessages = browser
? JSON.parse(localStorage.getItem(MESSAGES_STORAGE_KEY) || "[]")
: [];
// Separate stores for different concerns
export const messageStore = writable<Message[]>(initialMessages);
@@ -21,134 +26,144 @@ export const streamingStore = writable<boolean>(false);
export const errorStore = writable<string | null>(null);
export const currentSession = writable<string | null>(null);
// Subscribe to messageStore changes to persist messages
if (typeof localStorage !== 'undefined') {
messageStore.subscribe($messages => {
localStorage.setItem(MESSAGES_STORAGE_KEY, JSON.stringify($messages));
});
// Subscribe to messageStore changes to persist messages (only in browser)
if (browser) {
messageStore.subscribe(($messages) => {
localStorage.setItem(MESSAGES_STORAGE_KEY, JSON.stringify($messages));
});
}
// Derived store for chat state
export const chatState = derived(
[messageStore, streamingStore],
([$messages, $streaming]) => ({
messages: $messages,
isStreaming: $streaming
})
[messageStore, streamingStore],
([$messages, $streaming]) => ({
messages: $messages,
isStreaming: $streaming,
}),
);
// Error handling utility
function handleError(error: Error | string) {
const errorMessage = error instanceof ChatError
? `${error.code}: ${error.message}`
: error instanceof Error
? error.message
: error;
const errorMessage =
error instanceof ChatError
? `${error.code}: ${error.message}`
: error instanceof Error
? error.message
: error;
errorStore.set(errorMessage);
streamingStore.set(false);
return errorMessage;
errorStore.set(errorMessage);
streamingStore.set(false);
return errorMessage;
}
export const setSession = (sessionName: string | null) => {
currentSession.set(sessionName);
if (!sessionName) {
clearMessages();
}
currentSession.set(sessionName);
if (!sessionName) {
clearMessages();
}
};
export const clearMessages = () => {
messageStore.set([]);
errorStore.set(null);
if (typeof localStorage !== 'undefined') {
localStorage.removeItem(MESSAGES_STORAGE_KEY);
}
messageStore.set([]);
errorStore.set(null);
if (typeof localStorage !== "undefined") {
localStorage.removeItem(MESSAGES_STORAGE_KEY);
}
};
export const revertLastMessage = () => {
messageStore.update(messages => messages.slice(0, -1));
messageStore.update((messages) => messages.slice(0, -1));
};
export async function sendMessage(
content: string,
systemPromptText?: string,
isSystem: boolean = false,
) {
try {
console.log("\n=== Message Processing Start ===");
console.log("1. Initial state:", {
isSystem,
hasSystemPrompt: !!systemPromptText,
currentLanguage: get(languageStore),
pattern: get(selectedPatternName),
});
export async function sendMessage(content: string, systemPromptText?: string, isSystem: boolean = false) {
try {
console.log('\n=== Message Processing Start ===');
console.log('1. Initial state:', {
isSystem,
hasSystemPrompt: !!systemPromptText,
currentLanguage: get(languageStore),
pattern: get(selectedPatternName)
});
const $streaming = get(streamingStore);
if ($streaming) {
throw new ChatError(
"Message submission blocked - already streaming",
"STREAMING_BLOCKED",
);
}
const $streaming = get(streamingStore);
if ($streaming) {
throw new ChatError('Message submission blocked - already streaming', 'STREAMING_BLOCKED');
}
streamingStore.set(true);
errorStore.set(null);
streamingStore.set(true);
errorStore.set(null);
// Add message
messageStore.update((messages) => [
...messages,
{
role: isSystem ? "system" : "user",
content,
},
]);
// Add message
messageStore.update(messages => [...messages, {
role: isSystem ? 'system' : 'user',
content
}]);
console.log("2. Message added:", {
role: isSystem ? "system" : "user",
language: get(languageStore),
});
console.log('2. Message added:', {
role: isSystem ? 'system' : 'user',
language: get(languageStore)
});
if (!isSystem) {
console.log("3. Preparing chat stream:", {
language: get(languageStore),
pattern: get(selectedPatternName),
hasSystemPrompt: !!systemPromptText,
});
if (!isSystem) {
console.log('3. Preparing chat stream:', {
language: get(languageStore),
pattern: get(selectedPatternName),
hasSystemPrompt: !!systemPromptText
});
const stream = await chatService.streamChat(content, systemPromptText);
console.log("4. Stream created");
const stream = await chatService.streamChat(content, systemPromptText);
console.log('4. Stream created');
await chatService.processStream(
stream,
(content: string, response?: StreamResponse) => {
messageStore.update((messages) => {
const newMessages = [...messages];
const lastMessage = newMessages[newMessages.length - 1];
await chatService.processStream(
stream,
(content: string, response?: StreamResponse) => {
messageStore.update(messages => {
const newMessages = [...messages];
const lastMessage = newMessages[newMessages.length - 1];
if (lastMessage?.role === "assistant") {
lastMessage.content = content;
lastMessage.format = response?.format;
console.log("Message updated:", {
role: "assistant",
format: lastMessage.format,
});
} else {
newMessages.push({
role: "assistant",
content,
format: response?.format,
});
}
if (lastMessage?.role === 'assistant') {
lastMessage.content = content;
lastMessage.format = response?.format;
console.log('Message updated:', {
role: 'assistant',
format: lastMessage.format
});
} else {
newMessages.push({
role: 'assistant',
content,
format: response?.format
});
}
return newMessages;
});
},
(error) => {
handleError(error);
},
);
}
return newMessages;
});
},
(error) => {
handleError(error);
}
);
}
streamingStore.set(false);
} catch (error) {
if (error instanceof Error) {
handleError(error);
} else {
handleError(String(error));
}
throw error;
}
streamingStore.set(false);
} catch (error) {
if (error instanceof Error) {
handleError(error);
} else {
handleError(String(error));
}
throw error;
}
}
// Re-export types for convenience

View File

@@ -1,13 +1,14 @@
import { writable } from 'svelte/store';
import { browser } from '$app/environment';
// Load favorites from localStorage if available
const storedFavorites = typeof localStorage !== 'undefined'
const storedFavorites = browser
? JSON.parse(localStorage.getItem('favoritePatterns') || '[]')
: [];
const createFavoritesStore = () => {
const { subscribe, set, update } = writable<string[]>(storedFavorites);
return {
subscribe,
toggleFavorite: (patternName: string) => {
@@ -17,7 +18,7 @@ const createFavoritesStore = () => {
: [...favorites, patternName];
// Save to localStorage
if (typeof localStorage !== 'undefined') {
if (browser) {
localStorage.setItem('favoritePatterns', JSON.stringify(newFavorites));
}
@@ -26,11 +27,11 @@ const createFavoritesStore = () => {
},
reset: () => {
set([]);
if (typeof localStorage !== 'undefined') {
if (browser) {
localStorage.removeItem('favoritePatterns');
}
}
};
};
export const favorites = createFavoritesStore();
export const favorites = createFavoritesStore();

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