Llama 3 RAG Demo with DSPy Optimization, Ollama, and Weaviate!

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Hey everyone! Thank you so much for watching this overview of Llama 3 looking at the release notes and seeing a demo of how to integrate it with DSPy through Ollama and how to use DSPy's MIPRO to find the optimal prompt when using this new large language model for RAG!

Chapters
0:00 Llama3!!
1:28 Release Notes
5:35 Performance Reporting
9:50 Training Details
17:32 DSPy Demo!
  1. Connor Shorten
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Комментарии
Автор

This is so different from RAG using GPT. Lots to learn

dianaliu
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Dear Connor, that was the fastest release ever!

LaHoraMaker
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Is it me, or at least the last part is a digital avatar?

cipritom
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Would love to see an interface to groq please!

VincentFulco
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Two questions:
- Why use gpt-4 instead of gpt-4-turbo for the teleprompter?
- What are you using to make your pointer act like that?

tobkin
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Great video, Connor. Have you tested out if SAMMO is better than DSPy for production?

catchychazz
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Is llama really OSS if we don’t know how or what it is trained on?

Tarun_Mamidi
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I tried the implementation but i keep getting the error "model not found"

charismaowojoameh
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I ran your notebook and got the following error.

print(RAG()("What is binary quantization?").answer)

AttributeError Traceback (most recent call last)
Cell In[7], line 1
----> 1 print(RAG()("What is binary quantization?").answer)

File ~/code/vector_search/weaviate/recipes/.wenv/lib/python3.11/site-packages/dspy/primitives/program.py:26, in Module.__call__(self, *args, **kwargs)
25 def __call__(self, *args, **kwargs):
---> 26 return self.forward(*args, **kwargs)

Cell In[6], line 16
15 def forward(self, question):
---> 16 context =
17 pred = self.generate_answer(context=context, question=question).answer
18 return dspy.Prediction(context=context, answer=pred, question=question)

File ~/code/vector_search/weaviate/recipes/.wenv/lib/python3.11/site-packages/dspy/retrieve/retrieve.py:30, in Retrieve.__call__(self, *args, **kwargs)
29 def __call__(self, *args, **kwargs):
---> 30 return self.forward(*args, **kwargs)

File ~/code/vector_search/weaviate/recipes/.wenv/lib/python3.11/site-packages/dspy/retrieve/retrieve.py:39, in Retrieve.forward(self, query_or_queries, k)
36 # print(queries)
37 # TODO: Consider removing any quote-like markers that surround the query too.
38 k = k if k is not None else self.k
---> 39 passages = dsp.retrieveEnsemble(queries, k=k)
40 return Prediction(passages=passages)
...
79 .do()
81 results =
82 parsed_results = for result in results]

AttributeError: 'WeaviateClient' object has no attribute 'query'

PeterWilliams
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Hey, what version of Weaviate-client you are using????

koljanos
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maybe just me but the blur/smooth filter to the face cam makes me suspect that face cam is AI generated 🤣🤣🤣🤣🤣🤣

leeme