dspy-goodmem 0.1.0

GoodMem integration for DSPy — a self-hosted memory backend for agents

dspy-goodmem

GoodMem integration for DSPy — a self-hosted memory backend for RAG pipelines and agents.

Ships a DSPy retriever (GoodMemRM), a raw HTTP client (GoodMemClient), and a tool factory (make_goodmem_tools) that exposes GoodMem's full space/memory lifecycle to dspy.ReAct agents — not just retrieval.

Installation

pip install dspy-goodmem

You also need a running GoodMem server. See docs.goodmem.ai for setup.

Quick start

import dspy
from dspy_goodmem import GoodMemRM

# Configure your LM (any LiteLLM-supported provider works)
dspy.configure(lm=dspy.LM("openai/gpt-5-mini"))

# Create a retriever backed by GoodMem
rm = GoodMemRM(
    space_ids=["<your-space-uuid>"],
    api_key="gm_...",
    base_url="https://localhost:8080",
    k=3,
)

# Build a simple RAG module
class RAG(dspy.Module):
    def __init__(self, retriever):
        super().__init__()
        self.retriever = retriever
        self.respond = dspy.ChainOfThought("context, question -> response")

    def forward(self, question):
        passages = self.retriever(question)
        context = "\n\n".join(p["long_text"] for p in passages)
        return self.respond(context=context, question=question)

rag = RAG(retriever=rm)
print(rag(question="What are the Series B terms?").response)

What's included

Export	Role
GoodMemRM	dspy.Retrieve subclass — returns dotdict({"long_text": ...}) passages for any DSPy pipeline
GoodMemClient	Low-level HTTP wrapper around all 11 GoodMem REST operations
make_goodmem_tools	Factory that produces 11 typed callables for dspy.Tool / dspy.ReAct

Agent memory lifecycle

Unlike retriever-only integrations, make_goodmem_tools lets a dspy.ReAct agent manage its own memory — create spaces, store new memories, retrieve, update, and delete — without a human in the loop:

import dspy
from dspy_goodmem import GoodMemClient, make_goodmem_tools

client = GoodMemClient(api_key="gm_...", base_url="https://localhost:8080")
tools = [dspy.Tool(fn) for fn in make_goodmem_tools(client)]

agent = dspy.ReAct("task -> result", tools=tools)
agent(task="Remember that the user prefers Python over Java, then recall my language preferences.")

GoodMem features you gain

• Bring your own embedding model — OpenAI, Voyage AI, Cohere, vLLM, TEI, Llama.cpp, including fully local/offline models
• Hybrid search — combine dense and sparse embedders (e.g. MiniLM + SPLADE) in a single space with configurable weights
• Configurable chunking — chunk size, overlap, separators, and mode set per space and handled on the server
• File ingestion — upload PDFs, DOCX, images, and other formats without manual text extraction
• Metadata filtering — SQL-style filters with JSONPath extraction, date ranges, regex, and array membership
• Reranking — pluggable reranker models re-score results after retrieval
• Auto-summary — an LLM generates a consolidated answer from retrieved chunks at query time
• Deep Research mode — multiple iterative search rounds with query refinement for open-ended topics
• Self-hosted — runs entirely on your infrastructure, no external API calls or quotas

Full examples

Two end-to-end examples cover the main usage patterns:

• examples/rag_pipeline_example.py — Classic RAG pipeline using GoodMemRM as a retriever with ChainOfThought and SemanticF1 evaluation.
• examples/react_agent_example.py — Agent-driven memory with dspy.ReAct and make_goodmem_tools, covering multi-turn conversation, cross-agent persistence, metadata filtering, and trajectory inspection.

Both load a .env file from the repo root if python-dotenv is installed (pip install dspy-goodmem[examples]), otherwise they read environment variables directly.

export OPENAI_API_KEY="sk-..."
export GOODMEM_API_KEY="gm_..."
export GOODMEM_BASE_URL="https://localhost:8080"

python examples/rag_pipeline_example.py
# or
python examples/react_agent_example.py

Development

pip install -e .[dev]
pytest tests/ -v

63 mocked unit tests cover the client, retriever, and tool factory — no live server required.

Related

• DSPy documentation
• GoodMem documentation

License

MIT — see LICENSE.