Comments (2)
I tried the given examples of the notebook on the ChatGPT API. It seems ChatGPT perform surprisingly well by simply giving the original question without any Prompting engineering....
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Btw we have an open PR for this, @vfilinkov
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Related Issues (20)
- Failed to install with optional extra such as dspy-ai[pinecone] HOT 3
- Is this an "Example Retriever" optimisation or it can also produce prompt from scratch like "LLM as Optimizers" ? HOT 3
- ModuleNotFoundError: No module named 'openai.error' HOT 4
- Update to the latest OpenAI library HOT 6
- Are the save/load functions in BaseModule class meant to save/load the compiled model? HOT 7
- VLLM support not yet merged HOT 2
- How to set prompt templates for local models? HOT 2
- Drop prompt from output is determined in an unclear manner in HFModel HOT 3
- inspect-app development discontinued? HOT 3
- How to actually input lm and rm to this dspy?? HOT 3
- Implementing a Product Description Shortening and Categorization Pipeline with DSPy HOT 5
- tree-of-thoughts-implementation HOT 4
- Support for Chat-Completion model APIs
- BootstrapFewShot teleprompter explanation HOT 4
- Deployment of a compiled program HOT 3
- Standardize Vector Search Retrievers HOT 8
- Integrate Google Gemini and AWS Bedrock HOT 2
- CUDA memoory error when using BootstrapFinetune HOT 5
- Implement FunSearch in DSPy HOT 4
- Upgrade OpenAI Python library HOT 7
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