* initial knowledge

* WIP

* Adding core knowledge sources

* Improve types and better support for file paths

* added additional sources

* fix linting

* update yaml to include optional deps

* adding in lorenze feedback

* ensure embeddings are persisted

* improvements all around Knowledge class

* return this

* properly reset memory

* properly reset memory+knowledge

* consolodation and improvements

* linted

* cleanup rm unused embedder

* fix test

* fix duplicate

* generating cassettes for knowledge test

* updated default embedder

* None embedder to use default on pipeline cloning

* improvements

* fixed text_file_knowledge

* mypysrc fixes

* type check fixes

* added extra cassette

* just mocks

* linted

* mock knowledge query to not spin up db

* linted

* verbose run

* put a flag

* fix

* adding docs

* better docs

* improvements from review

* more docs

* linted

* rm print

* more fixes

* clearer docs

* added docstrings and type hints for cli

---------

Co-authored-by: João Moura <joaomdmoura@gmail.com>
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
This commit is contained in:
Brandon Hancock (bhancock_ai)
2024-11-20 18:40:08 -05:00
committed by GitHub
parent fde1ee45f9
commit 14a36d3f5e
37 changed files with 2302 additions and 266 deletions

View File

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import json
from typing import Any, Dict, List
from pathlib import Path
from crewai.knowledge.source.base_file_knowledge_source import BaseFileKnowledgeSource
class JSONKnowledgeSource(BaseFileKnowledgeSource):
"""A knowledge source that stores and queries JSON file content using embeddings."""
def load_content(self) -> Dict[Path, str]:
"""Load and preprocess JSON file content."""
super().load_content() # Validate the file path
paths = [self.file_path] if isinstance(self.file_path, Path) else self.file_path
content: Dict[Path, str] = {}
for path in paths:
with open(path, "r", encoding="utf-8") as json_file:
data = json.load(json_file)
content[path] = self._json_to_text(data)
return content
def _json_to_text(self, data: Any, level: int = 0) -> str:
"""Recursively convert JSON data to a text representation."""
text = ""
indent = " " * level
if isinstance(data, dict):
for key, value in data.items():
text += f"{indent}{key}: {self._json_to_text(value, level + 1)}\n"
elif isinstance(data, list):
for item in data:
text += f"{indent}- {self._json_to_text(item, level + 1)}\n"
else:
text += f"{str(data)}"
return text
def add(self) -> None:
"""
Add JSON file content to the knowledge source, chunk it, compute embeddings,
and save the embeddings.
"""
content_str = (
str(self.content) if isinstance(self.content, dict) else self.content
)
new_chunks = self._chunk_text(content_str)
self.chunks.extend(new_chunks)
self.save_documents(metadata=self.metadata)
def _chunk_text(self, text: str) -> List[str]:
"""Utility method to split text into chunks."""
return [
text[i : i + self.chunk_size]
for i in range(0, len(text), self.chunk_size - self.chunk_overlap)
]