dspy-demo.py

Author: makelinux

llm/dspy-demo.py

@@ -0,0 +1,63 @@
+#!/usr/bin/env python3
+
+print("Loading...")
+
+import dspy
+
+print("Connecting...")
+
+#lm = dspy.LM('gemini/gemini-2.5-pro-preview-03-25', api_key='GEMINI_API_KEY')
+
+#dspy.settings.configure(track_usage=True)
+
+import os
+lm = dspy.LM(
+    model="openai/" + os.getenv("INFERENCE_MODEL", "gemini/models/gemini-flash-latest"),
+    api_base=os.getenv("OPENAI_EP", "http://localhost:8321/v1"),
+    api_key="none"
+)
+
+print(len(lm.history))
+dspy.configure(lm=lm, track_usage=True)
+
+result1 = lm("Say this is a test!", temperature=0.7)
+print("Result 1:", result1)
+
+result2 = lm(messages=[{"role": "user", "content": "Say this is a test!"}])
+print("Result 2:", result2)
+
+# Define a module (ChainOfThought) and assign it a signature (return an answer, given a question).
+qa = dspy.ChainOfThought('question -> answer')
+
+# Run with the default LM configured with `dspy.configure` above.
+r = qa(question="How many floors are in the castle David Gregory inherited?")
+print(r.reasoning)
+print(r.answer)
+
+c = dspy.Predict('sentence -> sentiment: bool')
+print(c(sentence="it's a charming and often affecting journey.").sentiment)
+
+
+if False:
+    class Hop(dspy.Module):
+        def __init__(self, num_docs=10, num_hops=4):
+            self.num_docs, self.num_hops = num_docs, num_hops
+            self.generate_query = dspy.ChainOfThought('claim, notes -> query')
+            self.append_notes = dspy.ChainOfThought('claim, notes, context -> new_notes: list[str], titles: list[str]')
+
+        def forward(self, claim: str) -> list[str]:
+            notes = []
+            titles = []
+
+            for _ in range(self.num_hops):
+                query = self.generate_query(claim=claim, notes=notes).query
+                context = search(query, k=self.num_docs)
+                prediction = self.append_notes(claim=claim, notes=notes, context=context)
+                notes.extend(prediction.new_notes)
+                titles.extend(prediction.titles)
+
+            return dspy.Prediction(notes=notes, titles=list(set(titles)))
+    hop = Hop()
+    print(hop(claim="Stephen Curry is the best 3 pointer shooter ever in the human history"))
+
+print(len(lm.history))