名称修改

langchain_zhipuai/agents/all_tools_agent.py

@@ -56,7 +56,7 @@ def _perform_agent_action(
             # We then call the tool on the tool input to get an observation
             # TODO: platform adapter tool for all  tools,
             #       view tools binding langchain_zhipuai/agents/zhipuai_all_tools/base.py:188
-            if "code_interpreter" in agent_action.tool:
+            if agent_action.tool in AdapterAllToolStructType.__members__.values():
                 observation = tool.run(
                     {
                         "agent_action": agent_action,

langchain_zhipuai/agents/format_scratchpad/all_tools.py

@@ -73,13 +73,19 @@ def format_to_zhipuai_all_tool_messages(
 
         elif isinstance(agent_action, DrawingToolAgentAction):
             if isinstance(observation, DrawingToolOutput):
-                messages.append(AIMessage(content=str(observation)))
+                new_messages = list(agent_action.message_log) + [
+                    _create_tool_message(agent_action, observation)
+                ]
+                messages.extend([new for new in new_messages if new not in messages])
             else:
                 raise ValueError(f"Unknown observation type: {type(observation)}")
 
         elif isinstance(agent_action, WebBrowserAgentAction):
             if isinstance(observation, WebBrowserToolOutput):
-                messages.append(AIMessage(content=str(observation)))
+                new_messages = list(agent_action.message_log) + [
+                    _create_tool_message(agent_action, observation)
+                ]
+                messages.extend([new for new in new_messages if new not in messages])
             else:
                 raise ValueError(f"Unknown observation type: {type(observation)}")
 

langchain_zhipuai/embeddings/base.py

@@ -38,7 +38,7 @@
 logger = logging.getLogger(__name__)
 
 
-class ZhipuAIAIEmbeddings(BaseModel, Embeddings):
+class ZhipuAIEmbeddings(BaseModel, Embeddings):
     """ZhipuAI embedding models.
 
     To use, you should have the

tests/integration_tests/all_tools/test_alltools.py

@@ -35,7 +35,7 @@ async def test_all_tools_code_interpreter(logging_conf):
 
     agent_executor = ZhipuAIAllToolsRunnable.create_agent_executor(
         model_name="glm-4-alltools",
-        tools=[{"type": "code_interpreter"}, shell],
+        tools=[shell],
     )
     chat_iterator = agent_executor.invoke(
         chat_input="看下本地文件有哪些，告诉我你用的是什么文件,查看当前目录"
@@ -56,24 +56,6 @@ async def test_all_tools_code_interpreter(logging_conf):
             if item.status == AgentStatus.llm_end:
                 print("llm_end:" + item.text)
 
-    chat_iterator = agent_executor.invoke(chat_input="打印下test_alltools.py")
-    async for item in chat_iterator:
-        if isinstance(item, AllToolsAction):
-            print("AllToolsAction:" + str(item.to_json()))
-
-        elif isinstance(item, AllToolsFinish):
-            print("AllToolsFinish:" + str(item.to_json()))
-
-        elif isinstance(item, AllToolsActionToolStart):
-            print("AllToolsActionToolStart:" + str(item.to_json()))
-
-        elif isinstance(item, AllToolsActionToolEnd):
-            print("AllToolsActionToolEnd:" + str(item.to_json()))
-        elif isinstance(item, AllToolsLLMStatus):
-            if item.status == AgentStatus.llm_end:
-                print("llm_end:" + item.text)
-
-
 @pytest.mark.asyncio
 async def test_all_tools_code_interpreter_sandbox_none(logging_conf):
     logging.config.dictConfig(logging_conf)  # type: ignore

tests/integration_tests/embeddings/test_embeddings.py

@@ -1,25 +1,25 @@
-"""Test openai embeddings."""
+"""Test zhipuai embeddings."""
 import numpy as np
 import pytest
 
-from langchain_zhipuai.embeddings.base import ZhipuAIAIEmbeddings
+from langchain_zhipuai.embeddings.base import ZhipuAIEmbeddings
 
 
 @pytest.mark.scheduled
-def test_openai_embedding_documents() -> None:
-    """Test openai embeddings."""
+def test_zhipuai_embedding_documents() -> None:
+    """Test zhipuai embeddings."""
     documents = ["foo bar"]
-    embedding = ZhipuAIAIEmbeddings()
+    embedding = ZhipuAIEmbeddings()
     output = embedding.embed_documents(documents)
     assert len(output) == 1
     assert len(output[0]) == 1024
 
 
 @pytest.mark.scheduled
-def test_openai_embedding_documents_multiple() -> None:
-    """Test openai embeddings."""
+def test_zhipuai_embedding_documents_multiple() -> None:
+    """Test zhipuai embeddings."""
     documents = ["foo bar", "bar foo", "foo"]
-    embedding = ZhipuAIAIEmbeddings(chunk_size=2)
+    embedding = ZhipuAIEmbeddings(chunk_size=2)
     embedding.embedding_ctx_length = 8191
     output = embedding.embed_documents(documents)
     assert len(output) == 3
@@ -29,10 +29,10 @@ def test_openai_embedding_documents_multiple() -> None:
 
 
 @pytest.mark.scheduled
-async def test_openai_embedding_documents_async_multiple() -> None:
-    """Test openai embeddings."""
+async def test_zhipuai_embedding_documents_async_multiple() -> None:
+    """Test zhipuai embeddings."""
     documents = ["foo bar", "bar foo", "foo"]
-    embedding = ZhipuAIAIEmbeddings(chunk_size=2)
+    embedding = ZhipuAIEmbeddings(chunk_size=2)
     embedding.embedding_ctx_length = 8191
     output = await embedding.aembed_documents(documents)
     assert len(output) == 3
@@ -42,30 +42,30 @@ async def test_openai_embedding_documents_async_multiple() -> None:
 
 
 @pytest.mark.scheduled
-def test_openai_embedding_query() -> None:
-    """Test openai embeddings."""
+def test_zhipuai_embedding_query() -> None:
+    """Test zhipuai embeddings."""
     document = "foo bar"
-    embedding = ZhipuAIAIEmbeddings()
+    embedding = ZhipuAIEmbeddings()
     output = embedding.embed_query(document)
     assert len(output) == 1024
 
 
 @pytest.mark.scheduled
-async def test_openai_embedding_async_query() -> None:
-    """Test openai embeddings."""
+async def test_zhipuai_embedding_async_query() -> None:
+    """Test zhipuai embeddings."""
     document = "foo bar"
-    embedding = ZhipuAIAIEmbeddings()
+    embedding = ZhipuAIEmbeddings()
     output = await embedding.aembed_query(document)
     assert len(output) == 1024
 
 
 @pytest.mark.scheduled
 def test_embed_documents_normalized() -> None:
-    output = ZhipuAIAIEmbeddings().embed_documents(["foo walked to the market"])
+    output = ZhipuAIEmbeddings().embed_documents(["foo walked to the market"])
     assert np.isclose(np.linalg.norm(output[0]), 1.0)
 
 
 @pytest.mark.scheduled
 def test_embed_query_normalized() -> None:
-    output = ZhipuAIAIEmbeddings().embed_query("foo walked to the market")
+    output = ZhipuAIEmbeddings().embed_query("foo walked to the market")
     assert np.isclose(np.linalg.norm(output), 1.0)