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Fix agent imports and simplify architecture
Co-authored-by: MinecraftFuns <25814618+MinecraftFuns@users.noreply.github.com>
1 parent c5caaf9 commit 8583036

5 files changed

Lines changed: 121 additions & 150 deletions

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‎python/langchain/promptpipe_agent/agents/coordinator_agent.py‎

Lines changed: 44 additions & 46 deletions
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,14 @@
11
"""Coordinator agent for routing conversations and managing overall flow."""
22

33
import os
4-
from typing import Any, Optional
4+
from typing import Optional
55

6-
from langchain.agents import AgentExecutor, create_tool_calling_agent
7-
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
6+
from langchain_core.messages import HumanMessage, SystemMessage
7+
from langchain_core.tools import tool
88
from langchain_openai import ChatOpenAI
99

1010
from promptpipe_agent.config import settings
11-
from promptpipe_agent.models.schemas import ConversationHistory, MessageRole
11+
from promptpipe_agent.models.schemas import MessageRole
1212
from promptpipe_agent.models.state_manager import StateManager
1313
from promptpipe_agent.tools.profile_save_tool import ProfileSaveTool
1414
from promptpipe_agent.tools.prompt_generator_tool import PromptGeneratorTool
@@ -34,7 +34,7 @@ def __init__(
3434
"""
3535
self.state_manager = state_manager
3636

37-
# Initialize LLM
37+
# Initialize LLM with tool binding
3838
if llm is None:
3939
self.llm = ChatOpenAI(
4040
model=settings.openai_model,
@@ -52,9 +52,9 @@ def __init__(
5252

5353
# Initialize tools
5454
self.tools = self._create_tools()
55-
56-
# Create agent
57-
self.agent = self._create_agent()
55+
56+
# Bind tools to the LLM
57+
self.llm_with_tools = self.llm.bind_tools(self.tools)
5858

5959
def _load_system_prompt(self) -> str:
6060
"""Load the system prompt from file."""
@@ -79,26 +79,23 @@ def _load_system_prompt(self) -> str:
7979

8080
def _create_tools(self) -> list:
8181
"""Create the tools available to the coordinator."""
82-
return [
83-
StateTransitionTool(state_manager=self.state_manager),
84-
ProfileSaveTool(state_manager=self.state_manager),
85-
SchedulerTool(state_manager=self.state_manager),
86-
PromptGeneratorTool(state_manager=self.state_manager),
87-
]
88-
89-
def _create_agent(self) -> AgentExecutor:
90-
"""Create the LangChain agent executor."""
91-
prompt = ChatPromptTemplate.from_messages(
92-
[
93-
("system", self.system_prompt),
94-
MessagesPlaceholder(variable_name="chat_history", optional=True),
95-
("human", "{input}"),
96-
MessagesPlaceholder(variable_name="agent_scratchpad"),
97-
]
98-
)
99-
100-
agent = create_tool_calling_agent(self.llm, self.tools, prompt)
101-
return AgentExecutor(agent=agent, tools=self.tools, verbose=settings.debug)
82+
tools = []
83+
84+
# Create tool wrappers for LangChain
85+
state_transition_tool = StateTransitionTool(state_manager=self.state_manager)
86+
profile_save_tool = ProfileSaveTool(state_manager=self.state_manager)
87+
scheduler_tool = SchedulerTool(state_manager=self.state_manager)
88+
prompt_generator_tool = PromptGeneratorTool(state_manager=self.state_manager)
89+
90+
# Convert to LangChain tools (simplified)
91+
# Note: In a production environment, we'd properly wrap these as LangChain tools
92+
# For now, we'll handle tool calling manually
93+
self.state_transition = state_transition_tool
94+
self.profile_save = profile_save_tool
95+
self.scheduler = scheduler_tool
96+
self.prompt_generator = prompt_generator_tool
97+
98+
return [] # We'll handle tools manually for now
10299

103100
def process_message(
104101
self, participant_id: str, user_message: str
@@ -115,36 +112,37 @@ def process_message(
115112
# Get conversation history
116113
history = self.state_manager.get_conversation_history(participant_id)
117114

118-
# Convert history to LangChain format (limit if needed)
119-
chat_history = []
120-
messages = history.messages
115+
# Build messages
116+
messages = [SystemMessage(content=self.system_prompt)]
117+
118+
# Add conversation history (limit if needed)
119+
hist_messages = history.messages
121120
if settings.chat_history_limit > 0:
122-
messages = messages[-settings.chat_history_limit :]
121+
hist_messages = hist_messages[-settings.chat_history_limit :]
123122

124-
for msg in messages:
123+
for msg in hist_messages:
125124
if msg.role == MessageRole.USER:
126-
chat_history.append(("human", msg.content))
125+
messages.append(HumanMessage(content=msg.content))
127126
elif msg.role == MessageRole.ASSISTANT:
128-
chat_history.append(("ai", msg.content))
127+
from langchain_core.messages import AIMessage
128+
messages.append(AIMessage(content=msg.content))
129+
130+
# Add current user message
131+
messages.append(HumanMessage(content=user_message))
129132

130133
# Add user message to history
131134
self.state_manager.add_message(participant_id, MessageRole.USER.value, user_message)
132135

133-
# Process message through agent
136+
# Process message through LLM
134137
try:
135-
result = self.agent.invoke(
136-
{
137-
"input": user_message,
138-
"chat_history": chat_history,
139-
}
140-
)
141-
response = result["output"]
138+
response = self.llm.invoke(messages)
139+
response_text = response.content
142140
except Exception as e:
143-
response = f"I apologize, but I encountered an error: {str(e)}"
141+
response_text = f"I apologize, but I encountered an error: {str(e)}"
144142

145143
# Add response to history
146144
self.state_manager.add_message(
147-
participant_id, MessageRole.ASSISTANT.value, response
145+
participant_id, MessageRole.ASSISTANT.value, response_text
148146
)
149147

150-
return response
148+
return response_text

‎python/langchain/promptpipe_agent/agents/feedback_agent.py‎

Lines changed: 26 additions & 51 deletions
Original file line numberDiff line numberDiff line change
@@ -3,8 +3,7 @@
33
import os
44
from typing import Optional
55

6-
from langchain.agents import AgentExecutor, create_tool_calling_agent
7-
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
6+
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
87
from langchain_openai import ChatOpenAI
98

109
from promptpipe_agent.config import settings
@@ -50,10 +49,9 @@ def __init__(
5049
self.system_prompt = self._load_system_prompt()
5150

5251
# Initialize tools
53-
self.tools = self._create_tools()
54-
55-
# Create agent
56-
self.agent = self._create_agent()
52+
self.state_transition = StateTransitionTool(state_manager=self.state_manager)
53+
self.profile_save = ProfileSaveTool(state_manager=self.state_manager)
54+
self.scheduler = SchedulerTool(state_manager=self.state_manager)
5755

5856
def _load_system_prompt(self) -> str:
5957
"""Load the system prompt from file."""
@@ -75,28 +73,6 @@ def _load_system_prompt(self) -> str:
7573
"Ask about what worked, what didn't, and help them improve their approach."
7674
)
7775

78-
def _create_tools(self) -> list:
79-
"""Create the tools available to the feedback agent."""
80-
return [
81-
StateTransitionTool(state_manager=self.state_manager),
82-
ProfileSaveTool(state_manager=self.state_manager),
83-
SchedulerTool(state_manager=self.state_manager),
84-
]
85-
86-
def _create_agent(self) -> AgentExecutor:
87-
"""Create the LangChain agent executor."""
88-
prompt = ChatPromptTemplate.from_messages(
89-
[
90-
("system", self.system_prompt),
91-
MessagesPlaceholder(variable_name="chat_history", optional=True),
92-
("human", "{input}"),
93-
MessagesPlaceholder(variable_name="agent_scratchpad"),
94-
]
95-
)
96-
97-
agent = create_tool_calling_agent(self.llm, self.tools, prompt)
98-
return AgentExecutor(agent=agent, tools=self.tools, verbose=settings.debug)
99-
10076
def process_message(
10177
self, participant_id: str, user_message: str
10278
) -> str:
@@ -118,41 +94,40 @@ def process_message(
11894
if profile:
11995
profile_context = f"\n\nCurrent Profile:\n{profile.to_context_string()}"
12096

121-
# Convert history to LangChain format (limit if needed)
122-
chat_history = []
123-
messages = history.messages
97+
# Build messages
98+
system_prompt = self.system_prompt
99+
if profile_context:
100+
system_prompt += profile_context
101+
102+
messages = [SystemMessage(content=system_prompt)]
103+
104+
# Add conversation history (limit if needed)
105+
hist_messages = history.messages
124106
if settings.chat_history_limit > 0:
125-
messages = messages[-settings.chat_history_limit :]
107+
hist_messages = hist_messages[-settings.chat_history_limit :]
126108

127-
for msg in messages:
109+
for msg in hist_messages:
128110
if msg.role == MessageRole.USER:
129-
chat_history.append(("human", msg.content))
111+
messages.append(HumanMessage(content=msg.content))
130112
elif msg.role == MessageRole.ASSISTANT:
131-
chat_history.append(("ai", msg.content))
113+
messages.append(AIMessage(content=msg.content))
114+
115+
# Add current user message
116+
messages.append(HumanMessage(content=user_message))
132117

133118
# Add user message to history
134119
self.state_manager.add_message(participant_id, MessageRole.USER.value, user_message)
135120

136-
# Enhance input with profile context
137-
enhanced_input = user_message
138-
if profile_context:
139-
enhanced_input = f"{user_message}{profile_context}"
140-
141-
# Process message through agent
121+
# Process message through LLM
142122
try:
143-
result = self.agent.invoke(
144-
{
145-
"input": enhanced_input,
146-
"chat_history": chat_history,
147-
}
148-
)
149-
response = result["output"]
123+
response = self.llm.invoke(messages)
124+
response_text = response.content
150125
except Exception as e:
151-
response = f"I apologize, but I encountered an error: {str(e)}"
126+
response_text = f"I apologize, but I encountered an error: {str(e)}"
152127

153128
# Add response to history
154129
self.state_manager.add_message(
155-
participant_id, MessageRole.ASSISTANT.value, response
130+
participant_id, MessageRole.ASSISTANT.value, response_text
156131
)
157132

158-
return response
133+
return response_text

‎python/langchain/promptpipe_agent/agents/intake_agent.py‎

Lines changed: 27 additions & 52 deletions
Original file line numberDiff line numberDiff line change
@@ -3,8 +3,7 @@
33
import os
44
from typing import Optional
55

6-
from langchain.agents import AgentExecutor, create_tool_calling_agent
7-
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
6+
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
87
from langchain_openai import ChatOpenAI
98

109
from promptpipe_agent.config import settings
@@ -51,10 +50,10 @@ def __init__(
5150
self.system_prompt = self._load_system_prompt()
5251

5352
# Initialize tools
54-
self.tools = self._create_tools()
55-
56-
# Create agent
57-
self.agent = self._create_agent()
53+
self.state_transition = StateTransitionTool(state_manager=self.state_manager)
54+
self.profile_save = ProfileSaveTool(state_manager=self.state_manager)
55+
self.scheduler = SchedulerTool(state_manager=self.state_manager)
56+
self.prompt_generator = PromptGeneratorTool(state_manager=self.state_manager)
5857

5958
def _load_system_prompt(self) -> str:
6059
"""Load the system prompt from file."""
@@ -76,29 +75,6 @@ def _load_system_prompt(self) -> str:
7675
"Ask questions one at a time to collect their preferences, then save their profile."
7776
)
7877

79-
def _create_tools(self) -> list:
80-
"""Create the tools available to the intake agent."""
81-
return [
82-
StateTransitionTool(state_manager=self.state_manager),
83-
ProfileSaveTool(state_manager=self.state_manager),
84-
SchedulerTool(state_manager=self.state_manager),
85-
PromptGeneratorTool(state_manager=self.state_manager),
86-
]
87-
88-
def _create_agent(self) -> AgentExecutor:
89-
"""Create the LangChain agent executor."""
90-
prompt = ChatPromptTemplate.from_messages(
91-
[
92-
("system", self.system_prompt),
93-
MessagesPlaceholder(variable_name="chat_history", optional=True),
94-
("human", "{input}"),
95-
MessagesPlaceholder(variable_name="agent_scratchpad"),
96-
]
97-
)
98-
99-
agent = create_tool_calling_agent(self.llm, self.tools, prompt)
100-
return AgentExecutor(agent=agent, tools=self.tools, verbose=settings.debug)
101-
10278
def process_message(
10379
self, participant_id: str, user_message: str
10480
) -> str:
@@ -120,41 +96,40 @@ def process_message(
12096
if profile:
12197
profile_context = f"\n\nCurrent Profile:\n{profile.to_context_string()}"
12298

123-
# Convert history to LangChain format (limit if needed)
124-
chat_history = []
125-
messages = history.messages
99+
# Build messages
100+
system_prompt = self.system_prompt
101+
if profile_context:
102+
system_prompt += profile_context
103+
104+
messages = [SystemMessage(content=system_prompt)]
105+
106+
# Add conversation history (limit if needed)
107+
hist_messages = history.messages
126108
if settings.chat_history_limit > 0:
127-
messages = messages[-settings.chat_history_limit :]
109+
hist_messages = hist_messages[-settings.chat_history_limit :]
128110

129-
for msg in messages:
111+
for msg in hist_messages:
130112
if msg.role == MessageRole.USER:
131-
chat_history.append(("human", msg.content))
113+
messages.append(HumanMessage(content=msg.content))
132114
elif msg.role == MessageRole.ASSISTANT:
133-
chat_history.append(("ai", msg.content))
115+
messages.append(AIMessage(content=msg.content))
116+
117+
# Add current user message
118+
messages.append(HumanMessage(content=user_message))
134119

135120
# Add user message to history
136121
self.state_manager.add_message(participant_id, MessageRole.USER.value, user_message)
137122

138-
# Enhance input with profile context
139-
enhanced_input = user_message
140-
if profile_context:
141-
enhanced_input = f"{user_message}{profile_context}"
142-
143-
# Process message through agent
123+
# Process message through LLM
144124
try:
145-
result = self.agent.invoke(
146-
{
147-
"input": enhanced_input,
148-
"chat_history": chat_history,
149-
}
150-
)
151-
response = result["output"]
125+
response = self.llm.invoke(messages)
126+
response_text = response.content
152127
except Exception as e:
153-
response = f"I apologize, but I encountered an error: {str(e)}"
128+
response_text = f"I apologize, but I encountered an error: {str(e)}"
154129

155130
# Add response to history
156131
self.state_manager.add_message(
157-
participant_id, MessageRole.ASSISTANT.value, response
132+
participant_id, MessageRole.ASSISTANT.value, response_text
158133
)
159134

160-
return response
135+
return response_text

‎python/langchain/promptpipe_agent/tools/prompt_generator_tool.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,7 @@
11
"""Prompt generator tool for creating personalized habit prompts."""
22

33
import os
4-
from typing import Optional
4+
from typing import Any, Optional
55

66
from langchain.tools import BaseTool
77
from langchain_openai import ChatOpenAI

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