Update quick start examples (#120)

examples/quick_start/gemini_example_chat.py

@@ -0,0 +1,67 @@
+"""
+Usage:
+export GCP_PROJECT_ID=******
+python3 gemini_example_chat.py
+"""
+import sglang as sgl
+
+
+@sgl.function
+def multi_turn_question(s, question_1, question_2):
+    s += sgl.user(question_1)
+    s += sgl.assistant(sgl.gen("answer_1", max_tokens=256))
+    s += sgl.user(question_2)
+    s += sgl.assistant(sgl.gen("answer_2", max_tokens=256))
+
+
+def single():
+    state = multi_turn_question.run(
+        question_1="What is the capital of the United States?",
+        question_2="List two local attractions.",
+    )
+
+    for m in state.messages():
+        print(m["role"], ":", m["content"])
+
+    print("answer_1", state["answer_1"])
+
+
+def stream():
+    state = multi_turn_question.run(
+        question_1="What is the capital of the United States?",
+        question_2="List two local attractions.",
+        stream=True
+    )
+
+    for out in state.text_iter():
+        print(out, end="", flush=True)
+    print()
+
+
+def batch():
+    states = multi_turn_question.run_batch([
+        {"question_1": "What is the capital of the United States?",
+         "question_2": "List two local attractions."},
+
+        {"question_1": "What is the capital of France?",
+         "question_2": "What is the population of this city?"},
+    ])
+
+    for s in states:
+        print(s.messages())
+
+
+if __name__ == "__main__":
+    sgl.set_default_backend(sgl.VertexAI("gemini-pro"))
+
+    # Run a single request
+    print("\n========== single ==========\n")
+    single()
+
+    # Stream output
+    print("\n========== stream ==========\n")
+    stream()
+
+    # Run a batch of requests
+    print("\n========== batch ==========\n")
+    batch()