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fix some errors

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This commit is contained in:
midas8181919
2024-02-13 15:41:27 +00:00
parent 7cdae56e7e
commit 41ff4c8c43
4 changed files with 76 additions and 76 deletions
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README.md
+4 -4
View File
@@ -152,7 +152,7 @@ def should_continue(state):
messages = state['messages']
last_message = messages[-1]
# If there is no function call, then we finish
if "function_call" not in last_message.additional_kwargs:
if "tool_calls" not in last_message.additional_kwargs:
return "end"
# Otherwise if there is, we continue
else:
@@ -171,10 +171,10 @@ def call_tool(state):
# Based on the continue condition
# we know the last message involves a function call
last_message = messages[-1]
# We construct an ToolInvocation from the function_call
# We construct an ToolInvocation from the tool_calls
action = ToolInvocation(
tool=last_message.additional_kwargs["function_call"]["name"],
tool_input=json.loads(last_message.additional_kwargs["function_call"]["arguments"]),
tool=last_message.additional_kwargs["tool_calls"][0]["function"]["name"],
tool_input=json.loads(last_message.additional_kwargs["tool_calls"][0]["function"]["arguments"]),
)
# We call the tool_executor and get back a response
response = tool_executor.invoke(action)
langgraph/prebuilt/chat_agent_executor.py
+7 -7
View File
@@ -3,7 +3,7 @@ import operator
from typing import Annotated, Sequence, TypedDict
from langchain_core.agents import AgentAction
from langchain_core.messages import BaseMessage, FunctionMessage
from langchain_core.messages import BaseMessage, FunctionMessage, ToolMessage
from langchain_core.runnables import RunnableLambda
from langchain_core.utils.function_calling import convert_to_openai_function, convert_to_openai_tool
@@ -139,7 +139,7 @@ def create_tool_calling_executor(model, tools):
messages = state["messages"]
last_message = messages[-1]
# If there is no function call, then we finish
if "tool_call" not in last_message.additional_kwargs:
if "tool_calls" not in last_message.additional_kwargs:
return "end"
# Otherwise if there is, we continue
else:
@@ -170,7 +170,7 @@ def create_tool_calling_executor(model, tools):
tool_input=json.loads(
last_message.additional_kwargs["tool_calls"][0]["function"]["arguments"]
),
log="",
log=last_message.additional_kwargs["tool_calls"][0]["id"],
)
def call_tool(state):
@@ -178,18 +178,18 @@ def create_tool_calling_executor(model, tools):
# We call the tool_executor and get back a response
response = tool_executor.invoke(action)
# We use the response to create a FunctionMessage
function_message = FunctionMessage(content=str(response), name=action.tool)
tool_message = ToolMessage(content=str(response), tool_call_id=action.log)
# We return a list, because this will get added to the existing list
return {"messages": [function_message]}
return {"messages": [tool_message]}
async def acall_tool(state):
action = _get_action(state)
# We call the tool_executor and get back a response
response = await tool_executor.ainvoke(action)
# We use the response to create a FunctionMessage
function_message = FunctionMessage(content=str(response), name=action.tool)
tool_message = ToolMessage(content=str(response), tool_call_id=action.log)
# We return a list, because this will get added to the existing list
return {"messages": [function_message]}
return {"messages": [tool_message]}
# We create the AgentState that we will pass around
# This simply involves a list of messages
tests/test_pregel.py
+30 -33
View File
@@ -26,7 +26,6 @@ from langgraph.prebuilt.tool_executor import ToolExecutor
from langgraph.pregel import Channel, GraphRecursionError, Pregel
from langgraph.pregel.reserved import ReservedChannels
def test_invoke_single_process_in_out(mocker: MockerFixture) -> None:
add_one = mocker.Mock(side_effect=lambda x: x + 1)
chain = Channel.subscribe_to("input") | add_one | Channel.write_to("output")
@@ -1065,7 +1064,7 @@ def test_conditional_graph_state() -> None:
def test_prebuilt_tool_chat() -> None:
from langchain.chat_models.fake import FakeMessagesListChatModel
from langchain_community.tools import tool
from langchain_core.messages import AIMessage, FunctionMessage, HumanMessage
from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
class FakeFuntionChatModel(FakeMessagesListChatModel):
def bind_functions(self, functions: list):
@@ -1112,7 +1111,7 @@ def test_prebuilt_tool_chat() -> None:
),
tools,
)
assert app.invoke(
{"messages": [HumanMessage(content="what is weather in sf")]}
) == {
@@ -1126,12 +1125,12 @@ def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
),
FunctionMessage(content="result for query", name="search_api"),
ToolMessage(content="result for query", tool_call_id="tool_call123"),
AIMessage(
content="",
additional_kwargs={
@@ -1140,12 +1139,12 @@ def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
),
FunctionMessage(content="result for another", name="search_api"),
ToolMessage(content="result for another", tool_call_id="tool_call234"),
AIMessage(content="answer"),
]
}
@@ -1164,7 +1163,7 @@ def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
@@ -1175,7 +1174,7 @@ def test_prebuilt_tool_chat() -> None:
{
"action": {
"messages": [
FunctionMessage(content="result for query", name="search_api")
ToolMessage(content="result for query", tool_call_id="tool_call123")
]
}
},
@@ -1190,7 +1189,7 @@ def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
@@ -1201,7 +1200,7 @@ def test_prebuilt_tool_chat() -> None:
{
"action": {
"messages": [
FunctionMessage(content="result for another", name="search_api")
ToolMessage(content="result for another", tool_call_id="tool_call234")
]
}
},
@@ -1218,12 +1217,12 @@ def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
),
FunctionMessage(content="result for query", name="search_api"),
ToolMessage(content="result for query", tool_call_id="tool_call123"),
AIMessage(
content="",
additional_kwargs={
@@ -1232,12 +1231,12 @@ def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
),
FunctionMessage(content="result for another", name="search_api"),
ToolMessage(content="result for another", tool_call_id="tool_call234"),
AIMessage(content="answer"),
]
}
@@ -1248,7 +1247,7 @@ def test_tool_message_graph() -> None:
from langchain.chat_models.fake import FakeMessagesListChatModel
from langchain_community.tools import tool
from langchain_core.agents import AgentAction
from langchain_core.messages import AIMessage, FunctionMessage, HumanMessage
from langchain_core.messages import AIMessage, ToolMessage, HumanMessage
class FakeFuntionChatModel(FakeMessagesListChatModel):
def bind_functions(self, functions: list):
@@ -1315,12 +1314,12 @@ def test_tool_message_graph() -> None:
tool_input=json.loads(
last_message.additional_kwargs["tool_calls"][0]["function"]["arguments"]
),
log="",
log=last_message.additional_kwargs["tool_calls"][0]["id"],
)
# We call the tool_executor and get back a response
response = tool_executor.invoke(action)
# We use the response to create a FunctionMessage
return FunctionMessage(content=str(response), name=action.tool)
# We use the response to create a ToolMessage
return ToolMessage(content=str(response), tool_call_id=action.log)
# Define a new graph
workflow = MessageGraph()
@@ -1373,12 +1372,12 @@ def test_tool_message_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
),
FunctionMessage(content="result for query", name="search_api"),
ToolMessage(content="result for query", tool_call_id="tool_call123"),
AIMessage(
content="",
additional_kwargs={
@@ -1387,12 +1386,12 @@ def test_tool_message_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
),
FunctionMessage(content="result for another", name="search_api"),
ToolMessage(content="result for another", tool_call_id="tool_call234"),
AIMessage(content="answer"),
]
@@ -1406,13 +1405,13 @@ def test_tool_message_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
)
},
{"action": FunctionMessage(content="result for query", name="search_api")},
{"action": ToolMessage(content="result for query", tool_call_id="tool_call123")},
{
"agent": AIMessage(
content="",
@@ -1422,13 +1421,13 @@ def test_tool_message_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
)
},
{"action": FunctionMessage(content="result for another", name="search_api")},
{"action": ToolMessage(content="result for another", tool_call_id="tool_call234")},
{"agent": AIMessage(content="answer")},
{
"__end__": [
@@ -1441,12 +1440,12 @@ def test_tool_message_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
),
FunctionMessage(content="result for query", name="search_api"),
ToolMessage(content="result for query", tool_call_id="tool_call123"),
AIMessage(
content="",
additional_kwargs={
@@ -1455,18 +1454,17 @@ def test_tool_message_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
),
FunctionMessage(content="result for another", name="search_api"),
ToolMessage(content="result for another", tool_call_id="tool_call234"),
AIMessage(content="answer"),
]
},
]
@deprecated("*")
def test_prebuilt_chat() -> None:
from langchain.chat_models.fake import FakeMessagesListChatModel
from langchain_community.tools import tool
@@ -1611,7 +1609,6 @@ def test_prebuilt_chat() -> None:
},
]
@deprecated("*")
def test_message_graph() -> None:
from langchain.chat_models.fake import FakeMessagesListChatModel
from langchain_community.tools import tool
tests/test_pregel_async.py
+35 -32
View File
@@ -1115,7 +1115,7 @@ async def test_conditional_graph_state() -> None:
async def test_prebuilt_tool_chat() -> None:
from langchain.chat_models.fake import FakeMessagesListChatModel
from langchain_community.tools import tool
from langchain_core.messages import AIMessage, FunctionMessage, HumanMessage
from langchain_core.messages import AIMessage, ToolMessage, HumanMessage
class FakeFuntionChatModel(FakeMessagesListChatModel):
def bind_functions(self, functions: list):
@@ -1128,7 +1128,7 @@ async def test_prebuilt_tool_chat() -> None:
tools = [search_api]
app = create_function_calling_executor(
app = create_tool_calling_executor(
FakeFuntionChatModel(
responses=[
AIMessage(
@@ -1163,6 +1163,9 @@ async def test_prebuilt_tool_chat() -> None:
tools,
)
res = await app.ainvoke(
{"messages": [HumanMessage(content="what is weather in sf")]}
)
assert await app.ainvoke(
{"messages": [HumanMessage(content="what is weather in sf")]}
) == {
@@ -1176,12 +1179,12 @@ async def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
),
FunctionMessage(content="result for query", name="search_api"),
ToolMessage(content="result for query", tool_call_id="tool_call123"),
AIMessage(
content="",
additional_kwargs={
@@ -1190,12 +1193,12 @@ async def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
),
FunctionMessage(content="result for another", name="search_api"),
ToolMessage(content="result for another", tool_call_id="tool_call234"),
AIMessage(content="answer"),
]
}
@@ -1217,7 +1220,7 @@ async def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
@@ -1228,7 +1231,7 @@ async def test_prebuilt_tool_chat() -> None:
{
"action": {
"messages": [
FunctionMessage(content="result for query", name="search_api")
ToolMessage(content="result for query", tool_call_id="tool_call123")
]
}
},
@@ -1243,7 +1246,7 @@ async def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
@@ -1254,7 +1257,7 @@ async def test_prebuilt_tool_chat() -> None:
{
"action": {
"messages": [
FunctionMessage(content="result for another", name="search_api")
ToolMessage(content="result for another", tool_call_id="tool_call234")
]
}
},
@@ -1271,12 +1274,12 @@ async def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
),
FunctionMessage(content="result for query", name="search_api"),
ToolMessage(content="result for query", tool_call_id="tool_call123"),
AIMessage(
content="",
additional_kwargs={
@@ -1285,12 +1288,12 @@ async def test_prebuilt_tool_chat() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
),
FunctionMessage(content="result for another", name="search_api"),
ToolMessage(content="result for another", tool_call_id="tool_call234"),
AIMessage(content="answer"),
]
}
@@ -1302,7 +1305,7 @@ async def test_message_tool_graph() -> None:
from langchain.chat_models.fake import FakeMessagesListChatModel
from langchain_community.tools import tool
from langchain_core.agents import AgentAction
from langchain_core.messages import AIMessage, FunctionMessage, HumanMessage
from langchain_core.messages import AIMessage, ToolMessage, HumanMessage
class FakeFuntionChatModel(FakeMessagesListChatModel):
def bind_functions(self, functions: list):
@@ -1365,16 +1368,16 @@ async def test_message_tool_graph() -> None:
last_message = messages[-1]
# We construct an AgentAction from the function_call
action = AgentAction(
tool=last_message.additional_kwargs["tool_calls"][0]["fcuntion"]["name"],
tool=last_message.additional_kwargs["tool_calls"][0]["function"]["name"],
tool_input=json.loads(
last_message.additional_kwargs["tool_calls"][0]["function"]["arguments"]
),
log="",
log=last_message.additional_kwargs["tool_calls"][0]["id"],
)
# We call the tool_executor and get back a response
response = await tool_executor.ainvoke(action)
# We use the response to create a FunctionMessage
return FunctionMessage(content=str(response), name=action.tool)
return ToolMessage(content=str(response), tool_call_id=action.log)
# Define a new graph
workflow = MessageGraph()
@@ -1427,12 +1430,12 @@ async def test_message_tool_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
),
FunctionMessage(content="result for query", name="search_api"),
ToolMessage(content="result for query", tool_call_id="tool_call123"),
AIMessage(
content="",
additional_kwargs={
@@ -1441,12 +1444,12 @@ async def test_message_tool_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
),
FunctionMessage(content="result for another", name="search_api"),
ToolMessage(content="result for another", tool_call_id="tool_call234"),
AIMessage(content="answer"),
]
@@ -1462,13 +1465,13 @@ async def test_message_tool_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
)
},
{"action": FunctionMessage(content="result for query", name="search_api")},
{"action": ToolMessage(content="result for query", tool_call_id="tool_call123")},
{
"agent": AIMessage(
content="",
@@ -1478,13 +1481,13 @@ async def test_message_tool_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
)
},
{"action": FunctionMessage(content="result for another", name="search_api")},
{"action": ToolMessage(content="result for another", tool_call_id="tool_call234")},
{"agent": AIMessage(content="answer")},
{
"__end__": [
@@ -1497,12 +1500,12 @@ async def test_message_tool_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "query",
"arguments": "\"query\"",
}
}]
},
),
FunctionMessage(content="result for query", name="search_api"),
ToolMessage(content="result for query", tool_call_id="tool_call123"),
AIMessage(
content="",
additional_kwargs={
@@ -1511,18 +1514,18 @@ async def test_message_tool_graph() -> None:
"type": "function",
"function":{
"name": "search_api",
"arguments": "another",
"arguments": "\"another\"",
}
}]
},
),
FunctionMessage(content="result for another", name="search_api"),
ToolMessage(content="result for another", tool_call_id="tool_call234"),
AIMessage(content="answer"),
]
},
]
@deprecated("*")
async def test_prebuilt_chat() -> None:
from langchain.chat_models.fake import FakeMessagesListChatModel
from langchain_community.tools import tool
@@ -1670,7 +1673,7 @@ async def test_prebuilt_chat() -> None:
},
]
@deprecated("*")
async def test_message_graph() -> None:
from langchain.chat_models.fake import FakeMessagesListChatModel
from langchain_community.tools import tool