WIP: Multiple fixes and improvements
Backend: - Fixed auth issue where get_optional_user wasn't properly extracting tokens - Added user_id to conversational agent for proper auth context - Fixed DCA buy logic to support multiple buys on dips - Fixed sell logic to use amount_percent - Added comprehensive backtest engine tests - Fixed kline data validation for bad price data - Fixed chained tool calls handling Frontend: - BotCard now links to chat page instead of bot page - Chat page handles direct bot loading from dashboard - Various UI improvements and fixes Tests: - Added test_agent.py with mock client tests - Added test_backtest_engine.py with 7 comprehensive tests
This commit is contained in:
shokollm
164
src/backend/app/services/ai_agent/mock_client.py
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164
src/backend/app/services/ai_agent/mock_client.py
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"""Mock client for testing the ConversationalAgent without hitting real APIs."""
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from typing import List, Dict, Any, Optional
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class MockMiniMaxClient:
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"""Mock client that returns predefined responses for testing.
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Usage:
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mock = MockMiniMaxClient()
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mock.add_response({\"choices\": [...]}) # Add responses in order
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mock.add_response({\"choices\": [...]}) # Second call gets this
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agent = ConversationalAgent(client=mock)
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result = agent.chat(\"hello\")
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"""
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def __init__(self, responses: List[Dict[str, Any]] = None):
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self.responses = responses or []
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self.call_count = 0
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self.calls: List[Dict[str, Any]] = [] # Record all calls for assertions
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def add_response(self, response: Dict[str, Any]):
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"""Add a response to be returned on the next call."""
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self.responses.append(response)
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def chat(
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self,
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messages: List[Dict[str, str]],
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system_prompt: str,
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tools: Optional[List[Dict[str, Any]]] = None,
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temperature: float = 0.7,
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max_tokens: int = 2000,
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thinking_budget: int = 1500,
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) -> Dict[str, Any]:
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"""Return the next predefined response."""
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# Record the call for debugging/tests
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self.calls.append({
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"messages": messages,
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"system_prompt": system_prompt[:100] if system_prompt else None,
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"tool_calls_count": len(tools) if tools else 0,
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})
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if self.call_count < len(self.responses):
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response = self.responses[self.call_count]
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self.call_count += 1
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return response
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# Default response if no more predefined responses
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return {
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"choices": [{
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"message": {
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"content": "Mock response - no more responses configured",
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"role": "assistant",
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}
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}]
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}
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def reset(self):
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"""Reset call count and calls list."""
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self.call_count = 0
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self.calls = []
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def verify_call(self, call_index: int, expected_messages: int = None, expected_tool_count: int = None):
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"""Verify a specific call was made correctly."""
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if call_index >= len(self.calls):
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raise AssertionError(f"Call {call_index} was not made. Total calls: {len(self.calls)}")
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call = self.calls[call_index]
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if expected_messages is not None:
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actual = len(call["messages"])
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if actual != expected_messages:
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raise AssertionError(
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f"Call {call_index}: expected {expected_messages} messages, got {actual}"
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)
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if expected_tool_count is not None:
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actual = call["tool_calls_count"]
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if actual != expected_tool_count:
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raise AssertionError(
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f"Call {call_index}: expected {expected_tool_count} tools, got {actual}"
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)
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class MockMiniMaxClientWithToolCall(MockMiniMaxClient):
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"""Mock client that generates tool call responses based on message content."""
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def __init__(self, tool_handlers: Dict[str, Dict[str, Any]] = None):
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"""tool_handlers: dict mapping tool names to their responses."""
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super().__init__()
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self.tool_handlers = tool_handlers or {}
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def chat(
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self,
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messages: List[Dict[str, str]],
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system_prompt: str,
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tools: Optional[List[Dict[str, Any]]] = None,
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temperature: float = 0.7,
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max_tokens: int = 2000,
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thinking_budget: int = 1500,
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) -> Dict[str, Any]:
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"""Check if last message contains a tool call request and return appropriate response."""
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self.calls.append({
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"messages": messages,
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"system_prompt": system_prompt[:100] if system_prompt else None,
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"tool_calls_count": len(tools) if tools else 0,
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})
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# Get the last message
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if not messages:
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return {"choices": [{"message": {"content": "No messages", "role": "assistant"}}]}
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last_msg = messages[-1]
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# If it's a tool result, look for the tool that was called
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if last_msg.get("role") == "user" and "[TOOL RESULT]" in last_msg.get("content", ""):
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# Extract tool name from the content
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content = last_msg["content"]
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# Format: [TOOL RESULT] tool_name: result
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for tool_name in self.tool_handlers:
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if f"[TOOL RESULT] {tool_name}:" in content:
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return self.tool_handlers[tool_name]
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# Check if we should generate a tool call
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last_user_msg = ""
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for msg in reversed(messages):
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if msg.get("role") == "user" and "[TOOL RESULT]" not in msg.get("content", ""):
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last_user_msg = msg.get("content", "")
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break
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# Check each tool's trigger
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for tool_name, handler in self.tool_handlers.items():
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trigger = handler.get("trigger", "")
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if trigger and trigger.lower() in last_user_msg.lower():
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return {
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"choices": [{
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"message": {
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"content": handler.get("content", ""),
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"role": "assistant",
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"tool_calls": [{
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"id": f"call_{tool_name}",
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"type": "function",
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"function": {
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"name": tool_name,
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"arguments": handler.get("arguments", "{}")
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}
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}]
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}
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}]
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}
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# Default: return first available response or empty
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if self.responses:
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response = self.responses[0]
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self.call_count += 1
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return response
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return {
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"choices": [{
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"message": {
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"content": "How can I help you with your trading bot?",
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"role": "assistant",
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}
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}]
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}
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