feat: new summary using phi-4 and llama-index (#519)

* feat: add litellm backend implementation

* refactor: improve generate/completion methods for base LLM

* refactor: remove tokenizer logic

* style: apply code formatting

* fix: remove hallucinations from LLM responses

* refactor: comprehensive LLM and summarization rework

* chore: remove debug code

* feat: add structured output support to LiteLLM

* refactor: apply self-review improvements

* docs: add model structured output comments

* docs: update model structured output comments

* style: apply linting and formatting fixes

* fix: resolve type logic bug

* refactor: apply PR review feedback

* refactor: apply additional PR review feedback

* refactor: apply final PR review feedback

* fix: improve schema passing for LLMs without structured output

* feat: add PR comments and logger improvements

* docs: update README and add HTTP logging

* feat: improve HTTP logging

* feat: add summary chunking functionality

* fix: resolve title generation runtime issues

* refactor: apply self-review improvements

* style: apply linting and formatting

* feat: implement LiteLLM class structure

* style: apply linting and formatting fixes

* docs: env template model name fix

* chore: remove older litellm class

* chore: format

* refactor: simplify OpenAILLM

* refactor: OpenAILLM tokenizer

* refactor: self-review

* refactor: self-review

* refactor: self-review

* chore: format

* chore: remove LLM_USE_STRUCTURED_OUTPUT from envs

* chore: roll back migration lint changes

* chore: roll back migration lint changes

* fix: make summary llm configuration optional for the tests

* fix: missing f-string

* fix: tweak the prompt for summary title

* feat: try llamaindex for summarization

* fix: complete refactor of summary builder using llamaindex and structured output when possible

* fix: separate prompt as constant

* fix: typings

* fix: enhance prompt to prevent mentioning others subject while summarize one

* fix: various changes after self-review

* fix: from igor review

---------

Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>

CLAUDE.md

@@ -172,3 +172,7 @@ Modal.com integration for scalable ML processing:
 - **Audio Routing**: Use BlackHole (Mac) for merging multiple audio sources
 - **WebRTC**: Ensure proper CORS configuration for cross-origin streaming
 - **Database**: Run `uv run alembic upgrade head` after pulling schema changes
+
+## Pipeline/worker related info
+
+If you need to do any worker/pipeline related work, search for "Pipeline" classes and their "create" or "build" methods to find the main processor sequence. Look for task orchestration patterns (like "chord", "group", or "chain") to identify the post-processing flow with parallel execution chains. This will give you abstract vision on how processing pipeling is organized.