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my-project-public — gitlawb

#1	"""LLM Client for Solana Trading Agent - Supports OpenRouter and multiple providers"""
#2
#3	import json
#4	import logging
#5	from typing import Optional, Any
#6	from dataclasses import dataclass, field
#7
#8	import httpx
#9
#10	logger = logging.getLogger(__name__)
#11
#12
#13	@dataclass
#14	class ToolCall:
#15	"""Tool call from LLM response"""
#16	id: str
#17	name: str
#18	arguments: dict[str, Any]
#19
#20
#21	@dataclass
#22	class LLMResponse:
#23	"""Response from LLM"""
#24	content: str = ""
#25	thinking: str = ""
#26	tool_calls: list[ToolCall] = field(default_factory=list)
#27	finish_reason: str = ""
#28	usage: Optional[dict] = None
#29
#30
#31	@dataclass
#32	class Message:
#33	"""Conversation message"""
#34	role: str
#35	content: str = ""
#36	thinking: str = ""
#37	tool_calls: list[ToolCall] = None
#38	tool_call_id: str = ""
#39	name: str = ""
#40
#41	def to_dict(self) -> dict:
#42	d = {"role": self.role, "content": self.content}
#43	if self.tool_calls:
#44	d["tool_calls"] = [
#45	{
#46	"id": tc.id,
#47	"type": "function",
#48	"function": {
#49	"name": tc.name,
#50	"arguments": json.dumps(tc.arguments)
#51	}
#52	}
#53	for tc in self.tool_calls
#54	]
#55	if self.tool_call_id:
#56	d["tool_call_id"] = self.tool_call_id
#57	if self.name:
#58	d["name"] = self.name
#59	return d
#60
#61
#62	class LLMClient:
#63	"""LLM Client supporting OpenRouter and OpenAI-compatible APIs"""
#64
#65	def __init__(
#66	self,
#67	api_key: str,
#68	api_base: str = "https://openrouter.ai/api/v1",
#69	model: str = "anthropic/claude-sonnet-4",
#70	timeout: float = 120.0,
#71	max_tokens: int = 4096,
#72	):
#73	"""
#74	Initialize LLM client.
#75
#76	Args:
#77	api_key: API key for authentication
#78	api_base: Base URL for the API
#79	model: Model name to use
#80	timeout: Request timeout in seconds
#81	max_tokens: Maximum tokens in response
#82	"""
#83	self.api_key = api_key
#84	self.api_base = api_base.rstrip("/")
#85	self.model = model
#86	self.timeout = timeout
#87	self.max_tokens = max_tokens
#88
#89	self._client = httpx.AsyncClient(
#90	base_url=self.api_base,
#91	headers={
#92	"Authorization": f"Bearer {api_key}",
#93	"Content-Type": "application/json",
#94	"HTTP-Referer": "https://github.com/mawd-bot",
#95	"X-Title": "MAWD Solana Trading Agent",
#96	},
#97	timeout=timeout
#98	)
#99
#100	logger.info(f"Initialized LLM client: {model} @ {api_base}")
#101
#102	async def generate(
#103	self,
#104	messages: list[Message],
#105	tools: list = None,
#106	) -> LLMResponse:
#107	"""
#108	Generate response from LLM.
#109
#110	Args:
#111	messages: List of conversation messages
#112	tools: Optional list of Tool objects
#113
#114	Returns:
#115	LLMResponse with content and optional tool calls
#116	"""
#117	# Format messages
#118	formatted_messages = []
#119	for msg in messages:
#120	if isinstance(msg, Message):
#121	formatted_messages.append(msg.to_dict())
#122	elif isinstance(msg, dict):
#123	formatted_messages.append(msg)
#124	else:
#125	formatted_messages.append({"role": "user", "content": str(msg)})
#126
#127	# Build payload
#128	payload = {
#129	"model": self.model,
#130	"messages": formatted_messages,
#131	"max_tokens": self.max_tokens,
#132	}
#133
#134	# Add tools if provided
#135	if tools:
#136	formatted_tools = []
#137	for tool in tools:
#138	if hasattr(tool, 'to_openai_schema'):
#139	formatted_tools.append(tool.to_openai_schema())
#140	elif hasattr(tool, 'to_schema'):
#141	schema = tool.to_schema()
#142	formatted_tools.append({
#143	"type": "function",
#144	"function": {
#145	"name": schema["name"],
#146	"description": schema["description"],
#147	"parameters": schema["input_schema"],
#148	}
#149	})
#150	elif isinstance(tool, dict):
#151	formatted_tools.append(tool)
#152
#153	if formatted_tools:
#154	payload["tools"] = formatted_tools
#155	payload["tool_choice"] = "auto"
#156
#157	# Make request
#158	try:
#159	response = await self._client.post("/chat/completions", json=payload)
#160	response.raise_for_status()
#161	data = response.json()
#162	except httpx.HTTPStatusError as e:
#163	logger.error(f"LLM request failed: {e.response.status_code} - {e.response.text}")
#164	raise
#165	except Exception as e:
#166	logger.error(f"LLM request failed: {e}")
#167	raise
#168
#169	# Parse response
#170	choice = data.get("choices", [{}])[0]
#171	message = choice.get("message", {})
#172
#173	# Extract tool calls
#174	tool_calls = []
#175	raw_tool_calls = message.get("tool_calls", [])
#176	for tc in raw_tool_calls:
#177	func = tc.get("function", {})
#178	try:
#179	args = json.loads(func.get("arguments", "{}"))
#180	except json.JSONDecodeError:
#181	args = {}
#182
#183	tool_calls.append(ToolCall(
#184	id=tc.get("id", ""),
#185	name=func.get("name", ""),
#186	arguments=args,
#187	))
#188
#189	# Build response
#190	return LLMResponse(
#191	content=message.get("content", "") or "",
#192	thinking=message.get("thinking", "") or "",
#193	tool_calls=tool_calls,
#194	finish_reason=choice.get("finish_reason", ""),
#195	usage=data.get("usage"),
#196	)
#197
#198	async def close(self):
#199	"""Close the HTTP client"""
#200	await self._client.aclose()
#201
#202	async def __aenter__(self):
#203	return self
#204
#205	async def __aexit__(self, exc_type, exc_val, exc_tb):
#206	await self.close()
#207

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