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https://github.com/QuivrHQ/quivr.git
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eda619f454
# Description
- Save and load brain to disk:
```python
async def main():
with tempfile.NamedTemporaryFile(mode="w", suffix=".txt") as temp_file:
temp_file.write("Gold is a liquid of blue-like colour.")
temp_file.flush()
brain = await Brain.afrom_files(name="test_brain", file_paths=[temp_file.name])
save_path = await brain.save("/home/amine/.local/quivr")
brain_loaded = Brain.load(save_path)
brain_loaded.print_info()
```
# TODO:
- Loading all chat history
- Loading from other vector stores, PG for example can be great ...
35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
import asyncio
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import tempfile
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from dotenv import load_dotenv
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from quivr_core import Brain
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from quivr_core.quivr_rag import QuivrQARAG
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from quivr_core.quivr_rag_langgraph import QuivrQARAGLangGraph
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async def main():
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dotenv_path = "/Users/jchevall/Coding/QuivrHQ/quivr/.env"
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load_dotenv(dotenv_path)
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with tempfile.NamedTemporaryFile(mode="w", suffix=".txt") as temp_file:
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temp_file.write("Gold is a liquid of blue-like colour.")
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temp_file.flush()
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brain = await Brain.afrom_files(name="test_brain", file_paths=[temp_file.name])
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await brain.save("~/.local/quivr")
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question = "what is gold? answer in french"
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async for chunk in brain.ask_streaming(question, rag_pipeline=QuivrQARAG):
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print("answer QuivrQARAG:", chunk.answer)
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async for chunk in brain.ask_streaming(
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question, rag_pipeline=QuivrQARAGLangGraph
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):
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print("answer QuivrQARAGLangGraph:", chunk.answer)
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if __name__ == "__main__":
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# Run the main function in the existing event loop
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asyncio.run(main())
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