Quickly building a tool-using DSPy module that leverages Chroma Cloud search.

chroma_dspy_demo.py

import chromadb
import dspy

# Chose your LM. I'm using Qwen3-4B, hosted by LM Studio
lm = dspy.LM(
    'openai/qwen_qwen3-4b-thinking-2507', 
    api_base="http://127.0.0.1:1234/v1", 
    api_key="blah", 
    max_tokens=262144
)
dspy.configure(lm=lm)

# Connect to Chroma
client = chromadb.CloudClient(
  api_key='YOUR_KEY',
  tenant='YOUR_TENANT',
  database='YOUR_DB'
)

# A function for DSPy to use that preps the result for LM usage
def find_relevant_content(query):
    """
    Find relevant snippets from blog posts that are similar to the provided query.
    """
    collection = client.get_or_create_collection(name='posts')
    results = collection.query(query_texts=[query], include=['documents'])
    return results['documents'][0]

# The DSPy signature
class ParagraphWriter(dspy.Signature):
    """
    Given an intro sentence, generate a complete paragraph.
    Only use information you obtain from any tools, though you can rewrite what you find.
    """
    intro_sentence: str = dspy.InputField()
    completed_paragraph: str = dspy.OutputField()
    
# The DSPy module
writer = dspy.ReAct(ParagraphWriter, tools=[find_informing_content])

# Try it out!
result = writer(intro_sentence="AI is reshaping how we labor, learn, and communicate, yet most of us don’t understand how these systems work.")
print(result.completed_paragraph)