init

functionality/rag/react_agent_integration.py

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+# -*- coding: utf-8 -*-
+"""The example of integrating ReAct agent with RAG."""
+import asyncio
+import os
+
+from agentscope.agent import ReActAgent, UserAgent
+from agentscope.embedding import DashScopeTextEmbedding
+from agentscope.formatter import DashScopeChatFormatter
+from agentscope.message import Msg
+from agentscope.model import DashScopeChatModel
+from agentscope.rag import QdrantStore, SimpleKnowledge, TextReader
+
+
+async def main() -> None:
+    """The main entry point for the ReAct agent with RAG example."""
+
+    # Create an in-memory knowledge base instance
+    print("Creating the knowledge base...")
+    knowledge = SimpleKnowledge(
+        embedding_store=QdrantStore(
+            location=":memory:",
+            collection_name="test_collection",
+            dimensions=1024,  # The dimension of the embedding vectors
+        ),
+        embedding_model=DashScopeTextEmbedding(
+            api_key=os.environ["DASHSCOPE_API_KEY"],
+            model_name="text-embedding-v4",
+        ),
+    )
+
+    # Insert some documents into the knowledge base
+    # This could be done offline and only once
+    print("Inserting documents into the knowledge base...")
+    reader = TextReader(chunk_size=100, split_by="char")
+    documents = await reader(
+        # Fake personal profile for demonstration
+        "I'm John Doe, 28 years old. My best friend is James "
+        "Smith. I live in San Francisco. I work at OpenAI as a "
+        "software engineer. I love hiking and photography. "
+        "My father is Michael Doe, a doctor. I'm very proud of him. "
+        "My mother is Sarah Doe, a teacher. She is very kind and "
+        "always helps me with my studies.\n"
+        "I'm now a PhD student at Stanford University, majoring in "
+        "Computer Science. My advisor is Prof. Jane Williams, who is "
+        "a leading expert in artificial intelligence. I have published "
+        "several papers in top conferences, such as NeurIPS and ICML. ",
+    )
+
+    print("Inserting documents into the knowledge base...")
+    await knowledge.add_documents(documents)
+
+    # Integrate into the ReActAgent by the `knowledge` argument
+    print("Creating the agent...")
+    agent = ReActAgent(
+        name="Friday",
+        sys_prompt="You are a helpful assistant named Friday.",
+        model=DashScopeChatModel(
+            api_key=os.environ["DASHSCOPE_API_KEY"],
+            model_name="qwen-max",
+        ),
+        formatter=DashScopeChatFormatter(),
+        # Equip the agent with the knowledge base
+        knowledge=knowledge,
+        print_hint_msg=True,
+    )
+    user = UserAgent(name="user")
+
+    # Start the conversation
+    print("Start the conversation...")
+    msg = Msg("user", "Do you know who is my best friend?", "user")
+    while True:
+        msg = await agent(msg)
+        msg = await user(msg)
+        if msg.get_text_content() == "exit":
+            break
+
+
+asyncio.run(main())