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https://github.com/QuivrHQ/quivr.git
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3001fa1475
# Description - Created registry processor logic for automagically adding processors to quivr_core based Entrypoints - Added a langchain_community free `SimpleTxtParser` for the quivr_core base package - Added tests - Added brain_info - Enriched parsed documents metadata based on quivr_file metadata used Rich for `Brain.print_info()` to get a better output: 
43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
from langchain_core.embeddings import DeterministicFakeEmbedding
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from langchain_core.language_models import FakeListChatModel
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from rich.console import Console
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from rich.panel import Panel
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from rich.prompt import Prompt
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from quivr_core import Brain
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from quivr_core.config import LLMEndpointConfig
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from quivr_core.llm.llm_endpoint import LLMEndpoint
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if __name__ == "__main__":
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brain = Brain.from_files(
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name="test_brain",
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file_paths=["tests/processor/data/dummy.pdf"],
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llm=LLMEndpoint(
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llm=FakeListChatModel(responses=["good"]),
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llm_config=LLMEndpointConfig(model="fake_model", llm_base_url="local"),
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),
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embedder=DeterministicFakeEmbedding(size=20),
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)
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# Check brain info
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brain.print_info()
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console = Console()
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console.print(Panel.fit("Ask your brain !", style="bold magenta"))
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while True:
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# Get user input
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question = Prompt.ask("[bold cyan]Question[/bold cyan]")
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# Check if user wants to exit
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if question.lower() == "exit":
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console.print(Panel("Goodbye!", style="bold yellow"))
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break
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answer = brain.ask(question)
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# Print the answer with typing effect
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console.print(f"[bold green]Quivr Assistant[/bold green]: {answer.answer}")
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console.print("-" * console.width)
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brain.print_info()
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