dspy-haystack-integration

# DSPy + Haystack Integration ## Goal Use DSPy's optimization capabilities to automatically improve prompts in Haystack pipelines. ## When to Use - You have existing Haystack pipelines - Manual prompt tuning is tedious - Need data-driven prompt optimization - Want to combine Haystack components with DSPy optimization ## Inputs | Input | Type | Description | |-------|------|-------------| | `haystack_pipeline` | `Pipeline` | Existing Haystack pipeline | | `trainset` | `list[dspy.Example]` | Training examples | | `metric` | `callable` | Evaluation function | ## Outputs | Output | Type | Description | |--------|------|-------------| | `optimized_prompt` | `str` | DSPy-optimized prompt | | `optimized_pipeline` | `Pipeline` | Updated Haystack pipeline | ## Workflow ### Phase 1: Build Initial Haystack Pipeline ```python from haystack import Pipeline from haystack.components.generators import OpenAIGenerator from haystack.components.builders import PromptBuilder from haystack.components.retrievers.in_memory import InMemoryBM25Retriever from haystack.document_stores.in_memory import InMemoryDocumentStore # Setup document store doc_store = InMemoryDocumentStore() doc_store.write_documents(documents) # Initial generic prompt initial_prompt = """ Context: {{context}} Question: {{question}} Answer: """ # Build pipeline pipeline = Pipeline() pipeline.add_component("retriever", InMemoryBM25Retriever(document_store=doc_store)) pipeline.add_component("prompt_builder", PromptBui...