ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/browser-use-rpa/browser-use/browser_use/llm/groq/chat.py

@@ -0,0 +1,229 @@
+import logging
+from dataclasses import dataclass
+from typing import Literal, TypeVar, overload
+
+from groq import (
+	APIError,
+	APIResponseValidationError,
+	APIStatusError,
+	AsyncGroq,
+	NotGiven,
+	RateLimitError,
+	Timeout,
+)
+from groq.types.chat import ChatCompletion, ChatCompletionToolChoiceOptionParam, ChatCompletionToolParam
+from groq.types.chat.completion_create_params import (
+	ResponseFormatResponseFormatJsonSchema,
+	ResponseFormatResponseFormatJsonSchemaJsonSchema,
+)
+from httpx import URL
+from pydantic import BaseModel
+
+from browser_use.llm.base import BaseChatModel, ChatInvokeCompletion
+from browser_use.llm.exceptions import ModelProviderError, ModelRateLimitError
+from browser_use.llm.groq.parser import try_parse_groq_failed_generation
+from browser_use.llm.groq.serializer import GroqMessageSerializer
+from browser_use.llm.messages import BaseMessage
+from browser_use.llm.schema import SchemaOptimizer
+from browser_use.llm.views import ChatInvokeUsage
+
+GroqVerifiedModels = Literal[
+	'meta-llama/llama-4-maverick-17b-128e-instruct',
+	'meta-llama/llama-4-scout-17b-16e-instruct',
+	'qwen/qwen3-32b',
+	'moonshotai/kimi-k2-instruct',
+	'openai/gpt-oss-20b',
+	'openai/gpt-oss-120b',
+]
+
+JsonSchemaModels = [
+	'meta-llama/llama-4-maverick-17b-128e-instruct',
+	'meta-llama/llama-4-scout-17b-16e-instruct',
+	'openai/gpt-oss-20b',
+	'openai/gpt-oss-120b',
+]
+
+ToolCallingModels = [
+	'moonshotai/kimi-k2-instruct',
+]
+
+T = TypeVar('T', bound=BaseModel)
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class ChatGroq(BaseChatModel):
+	"""
+	A wrapper around AsyncGroq that implements the BaseLLM protocol.
+	"""
+
+	# Model configuration
+	model: GroqVerifiedModels | str
+
+	# Model params
+	temperature: float | None = None
+	service_tier: Literal['auto', 'on_demand', 'flex'] | None = None
+	top_p: float | None = None
+	seed: int | None = None
+
+	# Client initialization parameters
+	api_key: str | None = None
+	base_url: str | URL | None = None
+	timeout: float | Timeout | NotGiven | None = None
+	max_retries: int = 10  # Increase default retries for automation reliability
+
+	def get_client(self) -> AsyncGroq:
+		return AsyncGroq(api_key=self.api_key, base_url=self.base_url, timeout=self.timeout, max_retries=self.max_retries)
+
+	@property
+	def provider(self) -> str:
+		return 'groq'
+
+	@property
+	def name(self) -> str:
+		return str(self.model)
+
+	def _get_usage(self, response: ChatCompletion) -> ChatInvokeUsage | None:
+		usage = (
+			ChatInvokeUsage(
+				prompt_tokens=response.usage.prompt_tokens,
+				completion_tokens=response.usage.completion_tokens,
+				total_tokens=response.usage.total_tokens,
+				prompt_cached_tokens=None,  # Groq doesn't support cached tokens
+				prompt_cache_creation_tokens=None,
+				prompt_image_tokens=None,
+			)
+			if response.usage is not None
+			else None
+		)
+		return usage
+
+	@overload
+	async def ainvoke(self, messages: list[BaseMessage], output_format: None = None) -> ChatInvokeCompletion[str]: ...
+
+	@overload
+	async def ainvoke(self, messages: list[BaseMessage], output_format: type[T]) -> ChatInvokeCompletion[T]: ...
+
+	async def ainvoke(
+		self, messages: list[BaseMessage], output_format: type[T] | None = None
+	) -> ChatInvokeCompletion[T] | ChatInvokeCompletion[str]:
+		groq_messages = GroqMessageSerializer.serialize_messages(messages)
+
+		try:
+			if output_format is None:
+				return await self._invoke_regular_completion(groq_messages)
+			else:
+				return await self._invoke_structured_output(groq_messages, output_format)
+
+		except RateLimitError as e:
+			raise ModelRateLimitError(message=e.response.text, status_code=e.response.status_code, model=self.name) from e
+
+		except APIResponseValidationError as e:
+			raise ModelProviderError(message=e.response.text, status_code=e.response.status_code, model=self.name) from e
+
+		except APIStatusError as e:
+			if output_format is None:
+				raise ModelProviderError(message=e.response.text, status_code=e.response.status_code, model=self.name) from e
+			else:
+				try:
+					logger.debug(f'Groq failed generation: {e.response.text}; fallback to manual parsing')
+
+					parsed_response = try_parse_groq_failed_generation(e, output_format)
+
+					logger.debug('Manual error parsing successful ✅')
+
+					return ChatInvokeCompletion(
+						completion=parsed_response,
+						usage=None,  # because this is a hacky way to get the outputs
+						# TODO: @groq needs to fix their parsers and validators
+					)
+				except Exception as _:
+					raise ModelProviderError(message=str(e), status_code=e.response.status_code, model=self.name) from e
+
+		except APIError as e:
+			raise ModelProviderError(message=e.message, model=self.name) from e
+		except Exception as e:
+			raise ModelProviderError(message=str(e), model=self.name) from e
+
+	async def _invoke_regular_completion(self, groq_messages) -> ChatInvokeCompletion[str]:
+		"""Handle regular completion without structured output."""
+		chat_completion = await self.get_client().chat.completions.create(
+			messages=groq_messages,
+			model=self.model,
+			service_tier=self.service_tier,
+			temperature=self.temperature,
+			top_p=self.top_p,
+			seed=self.seed,
+		)
+		usage = self._get_usage(chat_completion)
+		return ChatInvokeCompletion(
+			completion=chat_completion.choices[0].message.content or '',
+			usage=usage,
+		)
+
+	async def _invoke_structured_output(self, groq_messages, output_format: type[T]) -> ChatInvokeCompletion[T]:
+		"""Handle structured output using either tool calling or JSON schema."""
+		schema = SchemaOptimizer.create_optimized_json_schema(output_format)
+
+		if self.model in ToolCallingModels:
+			response = await self._invoke_with_tool_calling(groq_messages, output_format, schema)
+		else:
+			response = await self._invoke_with_json_schema(groq_messages, output_format, schema)
+
+		if not response.choices[0].message.content:
+			raise ModelProviderError(
+				message='No content in response',
+				status_code=500,
+				model=self.name,
+			)
+
+		parsed_response = output_format.model_validate_json(response.choices[0].message.content)
+		usage = self._get_usage(response)
+
+		return ChatInvokeCompletion(
+			completion=parsed_response,
+			usage=usage,
+		)
+
+	async def _invoke_with_tool_calling(self, groq_messages, output_format: type[T], schema) -> ChatCompletion:
+		"""Handle structured output using tool calling."""
+		tool = ChatCompletionToolParam(
+			function={
+				'name': output_format.__name__,
+				'description': f'Extract information in the format of {output_format.__name__}',
+				'parameters': schema,
+			},
+			type='function',
+		)
+		tool_choice: ChatCompletionToolChoiceOptionParam = 'required'
+
+		return await self.get_client().chat.completions.create(
+			model=self.model,
+			messages=groq_messages,
+			temperature=self.temperature,
+			top_p=self.top_p,
+			seed=self.seed,
+			tools=[tool],
+			tool_choice=tool_choice,
+			service_tier=self.service_tier,
+		)
+
+	async def _invoke_with_json_schema(self, groq_messages, output_format: type[T], schema) -> ChatCompletion:
+		"""Handle structured output using JSON schema."""
+		return await self.get_client().chat.completions.create(
+			model=self.model,
+			messages=groq_messages,
+			temperature=self.temperature,
+			top_p=self.top_p,
+			seed=self.seed,
+			response_format=ResponseFormatResponseFormatJsonSchema(
+				json_schema=ResponseFormatResponseFormatJsonSchemaJsonSchema(
+					name=output_format.__name__,
+					description='Model output schema',
+					schema=schema,
+				),
+				type='json_schema',
+			),
+			service_tier=self.service_tier,
+		)

chapter9/browser-use-rpa/browser-use/browser_use/llm/groq/parser.py

@@ -0,0 +1,158 @@
+import json
+import logging
+import re
+from typing import TypeVar
+
+from groq import APIStatusError
+from pydantic import BaseModel
+
+logger = logging.getLogger(__name__)
+
+T = TypeVar('T', bound=BaseModel)
+
+
+class ParseFailedGenerationError(Exception):
+	pass
+
+
+def try_parse_groq_failed_generation(
+	error: APIStatusError,
+	output_format: type[T],
+) -> T:
+	"""Extract JSON from model output, handling both plain JSON and code-block-wrapped JSON."""
+	try:
+		content = error.body['error']['failed_generation']  # type: ignore
+
+		# If content is wrapped in code blocks, extract just the JSON part
+		if '```' in content:
+			# Find the JSON content between code blocks
+			content = content.split('```')[1]
+			# Remove language identifier if present (e.g., 'json\n')
+			if '\n' in content:
+				content = content.split('\n', 1)[1]
+
+		# remove html-like tags before the first { and after the last }
+		# This handles cases like <|header_start|>assistant<|header_end|> and <function=AgentOutput>
+		# Only remove content before { if content doesn't already start with {
+		if not content.strip().startswith('{'):
+			content = re.sub(r'^.*?(?=\{)', '', content, flags=re.DOTALL)
+
+		# Remove common HTML-like tags and patterns at the end, but be more conservative
+		# Look for patterns like </function>, <|header_start|>, etc. after the JSON
+		content = re.sub(r'\}(\s*<[^>]*>.*?$)', '}', content, flags=re.DOTALL)
+		content = re.sub(r'\}(\s*<\|[^|]*\|>.*?$)', '}', content, flags=re.DOTALL)
+
+		# Handle extra characters after the JSON, including stray braces
+		# Find the position of the last } that would close the main JSON object
+		content = content.strip()
+
+		if content.endswith('}'):
+			# Try to parse and see if we get valid JSON
+			try:
+				json.loads(content)
+			except json.JSONDecodeError:
+				# If parsing fails, try to find the correct end of the JSON
+				# by counting braces and removing anything after the balanced JSON
+				brace_count = 0
+				last_valid_pos = -1
+				for i, char in enumerate(content):
+					if char == '{':
+						brace_count += 1
+					elif char == '}':
+						brace_count -= 1
+						if brace_count == 0:
+							last_valid_pos = i + 1
+							break
+
+				if last_valid_pos > 0:
+					content = content[:last_valid_pos]
+
+		# Fix control characters in JSON strings before parsing
+		# This handles cases where literal control characters appear in JSON values
+		content = _fix_control_characters_in_json(content)
+
+		# Parse the cleaned content
+		result_dict = json.loads(content)
+
+		# some models occasionally respond with a list containing one dict: https://github.com/browser-use/browser-use/issues/1458
+		if isinstance(result_dict, list) and len(result_dict) == 1 and isinstance(result_dict[0], dict):
+			result_dict = result_dict[0]
+
+		logger.debug(f'Successfully parsed model output: {result_dict}')
+		return output_format.model_validate(result_dict)
+
+	except KeyError as e:
+		raise ParseFailedGenerationError(e) from e
+
+	except json.JSONDecodeError as e:
+		logger.warning(f'Failed to parse model output: {content} {str(e)}')
+		raise ValueError(f'Could not parse response. {str(e)}')
+
+	except Exception as e:
+		raise ParseFailedGenerationError(error.response.text) from e
+
+
+def _fix_control_characters_in_json(content: str) -> str:
+	"""Fix control characters in JSON string values to make them valid JSON."""
+	try:
+		# First try to parse as-is to see if it's already valid
+		json.loads(content)
+		return content
+	except json.JSONDecodeError:
+		pass
+
+	# More sophisticated approach: only escape control characters inside string values
+	# while preserving JSON structure formatting
+
+	result = []
+	i = 0
+	in_string = False
+	escaped = False
+
+	while i < len(content):
+		char = content[i]
+
+		if not in_string:
+			# Outside of string - check if we're entering a string
+			if char == '"':
+				in_string = True
+			result.append(char)
+		else:
+			# Inside string - handle escaping and control characters
+			if escaped:
+				# Previous character was backslash, so this character is escaped
+				result.append(char)
+				escaped = False
+			elif char == '\\':
+				# This is an escape character
+				result.append(char)
+				escaped = True
+			elif char == '"':
+				# End of string
+				result.append(char)
+				in_string = False
+			elif char == '\n':
+				# Literal newline inside string - escape it
+				result.append('\\n')
+			elif char == '\r':
+				# Literal carriage return inside string - escape it
+				result.append('\\r')
+			elif char == '\t':
+				# Literal tab inside string - escape it
+				result.append('\\t')
+			elif char == '\b':
+				# Literal backspace inside string - escape it
+				result.append('\\b')
+			elif char == '\f':
+				# Literal form feed inside string - escape it
+				result.append('\\f')
+			elif ord(char) < 32:
+				# Other control characters inside string - convert to unicode escape
+				result.append(f'\\u{ord(char):04x}')
+			else:
+				# Normal character inside string
+				result.append(char)
+
+		i += 1
+
+	return ''.join(result)

chapter9/browser-use-rpa/browser-use/browser_use/llm/groq/serializer.py

@@ -0,0 +1,159 @@
+from typing import overload
+
+from groq.types.chat import (
+	ChatCompletionAssistantMessageParam,
+	ChatCompletionContentPartImageParam,
+	ChatCompletionContentPartTextParam,
+	ChatCompletionMessageParam,
+	ChatCompletionMessageToolCallParam,
+	ChatCompletionSystemMessageParam,
+	ChatCompletionUserMessageParam,
+)
+from groq.types.chat.chat_completion_content_part_image_param import ImageURL
+from groq.types.chat.chat_completion_message_tool_call_param import Function
+
+from browser_use.llm.messages import (
+	AssistantMessage,
+	BaseMessage,
+	ContentPartImageParam,
+	ContentPartRefusalParam,
+	ContentPartTextParam,
+	SystemMessage,
+	ToolCall,
+	UserMessage,
+)
+
+
+class GroqMessageSerializer:
+	"""Serializer for converting between custom message types and OpenAI message param types."""
+
+	@staticmethod
+	def _serialize_content_part_text(part: ContentPartTextParam) -> ChatCompletionContentPartTextParam:
+		return ChatCompletionContentPartTextParam(text=part.text, type='text')
+
+	@staticmethod
+	def _serialize_content_part_image(part: ContentPartImageParam) -> ChatCompletionContentPartImageParam:
+		return ChatCompletionContentPartImageParam(
+			image_url=ImageURL(url=part.image_url.url, detail=part.image_url.detail),
+			type='image_url',
+		)
+
+	@staticmethod
+	def _serialize_user_content(
+		content: str | list[ContentPartTextParam | ContentPartImageParam],
+	) -> str | list[ChatCompletionContentPartTextParam | ChatCompletionContentPartImageParam]:
+		"""Serialize content for user messages (text and images allowed)."""
+		if isinstance(content, str):
+			return content
+
+		serialized_parts: list[ChatCompletionContentPartTextParam | ChatCompletionContentPartImageParam] = []
+		for part in content:
+			if part.type == 'text':
+				serialized_parts.append(GroqMessageSerializer._serialize_content_part_text(part))
+			elif part.type == 'image_url':
+				serialized_parts.append(GroqMessageSerializer._serialize_content_part_image(part))
+		return serialized_parts
+
+	@staticmethod
+	def _serialize_system_content(
+		content: str | list[ContentPartTextParam],
+	) -> str:
+		"""Serialize content for system messages (text only)."""
+		if isinstance(content, str):
+			return content
+
+		serialized_parts: list[str] = []
+		for part in content:
+			if part.type == 'text':
+				serialized_parts.append(GroqMessageSerializer._serialize_content_part_text(part)['text'])
+
+		return '\n'.join(serialized_parts)
+
+	@staticmethod
+	def _serialize_assistant_content(
+		content: str | list[ContentPartTextParam | ContentPartRefusalParam] | None,
+	) -> str | None:
+		"""Serialize content for assistant messages (text and refusal allowed)."""
+		if content is None:
+			return None
+		if isinstance(content, str):
+			return content
+
+		serialized_parts: list[str] = []
+		for part in content:
+			if part.type == 'text':
+				serialized_parts.append(GroqMessageSerializer._serialize_content_part_text(part)['text'])
+
+		return '\n'.join(serialized_parts)
+
+	@staticmethod
+	def _serialize_tool_call(tool_call: ToolCall) -> ChatCompletionMessageToolCallParam:
+		return ChatCompletionMessageToolCallParam(
+			id=tool_call.id,
+			function=Function(name=tool_call.function.name, arguments=tool_call.function.arguments),
+			type='function',
+		)
+
+	# endregion
+
+	# region - Serialize overloads
+	@overload
+	@staticmethod
+	def serialize(message: UserMessage) -> ChatCompletionUserMessageParam: ...
+
+	@overload
+	@staticmethod
+	def serialize(message: SystemMessage) -> ChatCompletionSystemMessageParam: ...
+
+	@overload
+	@staticmethod
+	def serialize(message: AssistantMessage) -> ChatCompletionAssistantMessageParam: ...
+
+	@staticmethod
+	def serialize(message: BaseMessage) -> ChatCompletionMessageParam:
+		"""Serialize a custom message to an OpenAI message param."""
+
+		if isinstance(message, UserMessage):
+			user_result: ChatCompletionUserMessageParam = {
+				'role': 'user',
+				'content': GroqMessageSerializer._serialize_user_content(message.content),
+			}
+			if message.name is not None:
+				user_result['name'] = message.name
+			return user_result
+
+		elif isinstance(message, SystemMessage):
+			system_result: ChatCompletionSystemMessageParam = {
+				'role': 'system',
+				'content': GroqMessageSerializer._serialize_system_content(message.content),
+			}
+			if message.name is not None:
+				system_result['name'] = message.name
+			return system_result
+
+		elif isinstance(message, AssistantMessage):
+			# Handle content serialization
+			content = None
+			if message.content is not None:
+				content = GroqMessageSerializer._serialize_assistant_content(message.content)
+
+			assistant_result: ChatCompletionAssistantMessageParam = {'role': 'assistant'}
+
+			# Only add content if it's not None
+			if content is not None:
+				assistant_result['content'] = content
+
+			if message.name is not None:
+				assistant_result['name'] = message.name
+
+			if message.tool_calls:
+				assistant_result['tool_calls'] = [GroqMessageSerializer._serialize_tool_call(tc) for tc in message.tool_calls]
+
+			return assistant_result
+
+		else:
+			raise ValueError(f'Unknown message type: {type(message)}')
+
+	@staticmethod
+	def serialize_messages(messages: list[BaseMessage]) -> list[ChatCompletionMessageParam]:
+		return [GroqMessageSerializer.serialize(m) for m in messages]