chore: Add PyPI package support for uvx/pip installation (#1764)

* Initial plan

* Add package structure and resource path utilities

- Created langbot/ package with __init__.py and __main__.py entry point
- Added paths utility to find frontend and resource files from package installation
- Updated config loading to use resource paths
- Updated frontend serving to use resource paths
- Added MANIFEST.in for package data inclusion
- Updated pyproject.toml with build system and entry points

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* Add PyPI publishing workflow and update license

- Created GitHub Actions workflow to build frontend and publish to PyPI
- Added license field to pyproject.toml to fix deprecation warning
- Updated .gitignore to exclude build artifacts
- Tested package building successfully

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* Add PyPI installation documentation

- Created PYPI_INSTALLATION.md with detailed installation and usage instructions
- Updated README.md to feature uvx/pip installation as recommended method
- Updated README_EN.md with same changes for English documentation

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* Address code review feedback

- Made package-data configuration more specific to langbot package only
- Improved path detection with caching to avoid repeated file I/O
- Removed sys.path searching which was incorrect for package data
- Removed interactive input() call for non-interactive environment compatibility
- Simplified error messages for version check

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* Fix code review issues

- Use specific exception types instead of bare except
- Fix misleading comments about directory levels
- Remove redundant existence check before makedirs with exist_ok=True
- Use context manager for file opening to ensure proper cleanup

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* Simplify package configuration and document behavioral differences

- Removed redundant package-data configuration, relying on MANIFEST.in
- Added documentation about behavioral differences between package and source installation
- Clarified that include-package-data=true uses MANIFEST.in for data files

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

* chore: update pyproject.toml

* chore: try pack templates in langbot/

* chore: update

* chore: update

* chore: update

* chore: update

* chore: update

* chore: adjust dir structure

* chore: fix imports

* fix: read default-pipeline-config.json

* fix: read default-pipeline-config.json

* fix: tests

* ci: publish pypi

* chore: bump version 4.6.0-beta.1 for testing

* chore: add templates/**

* fix: send adapters and requesters icons

* chore: bump version 4.6.0b2 for testing

* chore: add platform field for docker-compose.yaml

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>

src/langbot/pkg/rag/knowledge/services/embedder.py

@@ -0,0 +1,47 @@
+from __future__ import annotations
+import uuid
+from typing import List
+from langbot.pkg.rag.knowledge.services.base_service import BaseService
+from langbot.pkg.entity.persistence import rag as persistence_rag
+from langbot.pkg.core import app
+from langbot.pkg.provider.modelmgr.requester import RuntimeEmbeddingModel
+import sqlalchemy
+
+
+class Embedder(BaseService):
+    def __init__(self, ap: app.Application) -> None:
+        super().__init__()
+        self.ap = ap
+
+    async def embed_and_store(
+        self, kb_id: str, file_id: str, chunks: List[str], embedding_model: RuntimeEmbeddingModel
+    ) -> list[persistence_rag.Chunk]:
+        # save chunk to db
+        chunk_entities: list[persistence_rag.Chunk] = []
+        chunk_ids: list[str] = []
+
+        for chunk_text in chunks:
+            chunk_uuid = str(uuid.uuid4())
+            chunk_ids.append(chunk_uuid)
+            chunk_entity = persistence_rag.Chunk(uuid=chunk_uuid, file_id=file_id, text=chunk_text)
+            chunk_entities.append(chunk_entity)
+
+        chunk_dicts = [
+            self.ap.persistence_mgr.serialize_model(persistence_rag.Chunk, chunk) for chunk in chunk_entities
+        ]
+
+        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.Chunk).values(chunk_dicts))
+
+        # get embeddings
+        embeddings_list: list[list[float]] = await embedding_model.requester.invoke_embedding(
+            model=embedding_model,
+            input_text=chunks,
+            extra_args={},  # TODO: add extra args
+        )
+
+        # save embeddings to vdb
+        await self.ap.vector_db_mgr.vector_db.add_embeddings(kb_id, chunk_ids, embeddings_list, chunk_dicts)
+
+        self.ap.logger.info(f'Successfully saved {len(chunk_entities)} embeddings to Knowledge Base.')
+
+        return chunk_entities