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fix(agent, forge): Fix Pydantic v2 protected namespace model_ warnings (#7340)

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Rename `model_*` fields to `llm_*`
This commit is contained in:
Krzysztof Czerwinski
2024-07-12 11:05:03 +01:00
committed by GitHub
parent 2ecce27653
commit bffb92bfbc
11 changed files with 23 additions and 23 deletions
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10
autogpt/autogpt/agent_factory/profile_generator.py
View File

@@ -19,7 +19,7 @@ logger = logging.getLogger(__name__)
class AgentProfileGeneratorConfiguration(SystemConfiguration):
model_classification: LanguageModelClassification = UserConfigurable(
llm_classification: LanguageModelClassification = UserConfigurable(
default=LanguageModelClassification.SMART_MODEL
)
_example_call: object = {
@@ -148,12 +148,12 @@ class AgentProfileGenerator(PromptStrategy):
def __init__(
self,
model_classification: LanguageModelClassification,
llm_classification: LanguageModelClassification,
system_prompt: str,
user_prompt_template: str,
create_agent_function: dict,
):
self._model_classification = model_classification
self._llm_classification = llm_classification
self._system_prompt_message = system_prompt
self._user_prompt_template = user_prompt_template
self._create_agent_function = CompletionModelFunction.model_validate(
@@ -161,8 +161,8 @@ class AgentProfileGenerator(PromptStrategy):
)
@property
def model_classification(self) -> LanguageModelClassification:
return self._model_classification
def llm_classification(self) -> LanguageModelClassification:
return self._llm_classification
def build_prompt(self, user_objective: str = "", **kwargs) -> ChatPrompt:
system_message = ChatMessage.system(self._system_prompt_message)

2
autogpt/autogpt/agents/agent.py
View File

@@ -119,7 +119,7 @@ class Agent(BaseAgent[OneShotAgentActionProposal], Configurable[AgentSettings]):
lambda x: self.llm_provider.count_tokens(x, self.llm.name),
llm_provider,
ActionHistoryConfiguration(
model_name=app_config.fast_llm, max_tokens=self.send_token_limit
llm_name=app_config.fast_llm, max_tokens=self.send_token_limit
),
)
.run_after(WatchdogComponent)

2
autogpt/autogpt/agents/prompt_strategies/one_shot.py
View File

@@ -100,7 +100,7 @@ class OneShotAgentPromptStrategy(PromptStrategy):
self.logger = logger
@property
def model_classification(self) -> LanguageModelClassification:
def llm_classification(self) -> LanguageModelClassification:
return LanguageModelClassification.FAST_MODEL # FIXME: dynamic switching
def build_prompt(

6
docs/content/forge/components/built-in-components.md
View File

@@ -40,7 +40,7 @@ Necessary for saving and loading agent's state (preserving session).
| Config variable | Details | Type | Default |
| ---------------- | -------------------------------------- | ----- | ---------------------------------- |
| `storage_path` | Path to agent files, e.g. state | `str` | `agents/{agent_id}/`[^1] |
| `storage_path` | Path to agent files, e.g. state | `str` | `agents/{agent_id}/`[^1] |
| `workspace_path` | Path to files that agent has access to | `str` | `agents/{agent_id}/workspace/`[^1] |
[^1] This option is set dynamically during component construction as opposed to by default inside the configuration model, `{agent_id}` is replaced with the agent's unique identifier.
@@ -84,7 +84,7 @@ Keeps track of agent's actions and their outcomes. Provides their summary to the
| Config variable | Details | Type | Default |
| ---------------------- | ------------------------------------------------------- | ----------- | ------------------ |
| `model_name` | Name of the llm model used to compress the history | `ModelName` | `"gpt-3.5-turbo"` |
| `llm_name` | Name of the llm model used to compress the history | `ModelName` | `"gpt-3.5-turbo"` |
| `max_tokens` | Maximum number of tokens to use for the history summary | `int` | `1024` |
| `spacy_language_model` | Language model used for summary chunking using spacy | `str` | `"en_core_web_sm"` |
| `full_message_count` | Number of cycles to include unsummarized in the prompt | `int` | `4` |
@@ -178,7 +178,7 @@ Allows agent to read websites using Selenium.
| Config variable | Details | Type | Default |
| ----------------------------- | ------------------------------------------- | --------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `model_name` | Name of the llm model used to read websites | `ModelName` | `"gpt-3.5-turbo"` |
| `llm_name` | Name of the llm model used to read websites | `ModelName` | `"gpt-3.5-turbo"` |
| `web_browser` | Web browser used by Selenium | `"chrome" \| "firefox" \| "safari" \| "edge"` | `"chrome"` |
| `headless` | Run browser in headless mode | `bool` | `True` |
| `user_agent` | User agent used by the browser | `str` | `"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36"` |

4
forge/forge/components/README.md
View File

@@ -116,7 +116,7 @@ You can set sensitive variables in the `.json` file as well but it's recommended
"github_username": null
},
"ActionHistoryConfiguration": {
"model_name": "gpt-3.5-turbo",
"llm_name": "gpt-3.5-turbo",
"max_tokens": 1024,
"spacy_language_model": "en_core_web_sm"
},
@@ -129,7 +129,7 @@ You can set sensitive variables in the `.json` file as well but it's recommended
"duckduckgo_max_attempts": 3
},
"WebSeleniumConfiguration": {
"model_name": "gpt-3.5-turbo",
"llm_name": "gpt-3.5-turbo",
"web_browser": "chrome",
"headless": true,
"user_agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36",

4
forge/forge/components/action_history/action_history.py
View File

@@ -16,7 +16,7 @@ from .model import ActionResult, AnyProposal, Episode, EpisodicActionHistory
class ActionHistoryConfiguration(BaseModel):
model_name: ModelName = OpenAIModelName.GPT3
llm_name: ModelName = OpenAIModelName.GPT3
"""Name of the llm model used to compress the history"""
max_tokens: int = 1024
"""Maximum number of tokens to use up with generated history messages"""
@@ -97,7 +97,7 @@ class ActionHistoryComponent(
async def after_execute(self, result: ActionResult) -> None:
self.event_history.register_result(result)
await self.event_history.handle_compression(
self.llm_provider, self.config.model_name, self.config.spacy_language_model
self.llm_provider, self.config.llm_name, self.config.spacy_language_model
)
@staticmethod

8
forge/forge/components/web/selenium.py
View File

@@ -55,7 +55,7 @@ class BrowsingError(CommandExecutionError):
class WebSeleniumConfiguration(BaseModel):
model_name: ModelName = OpenAIModelName.GPT3
llm_name: ModelName = OpenAIModelName.GPT3
"""Name of the llm model used to read websites"""
web_browser: Literal["chrome", "firefox", "safari", "edge"] = "chrome"
"""Web browser used by Selenium"""
@@ -164,7 +164,7 @@ class WebSeleniumComponent(
elif get_raw_content:
if (
output_tokens := self.llm_provider.count_tokens(
text, self.config.model_name
text, self.config.llm_name
)
) > MAX_RAW_CONTENT_LENGTH:
oversize_factor = round(output_tokens / MAX_RAW_CONTENT_LENGTH, 1)
@@ -382,7 +382,7 @@ class WebSeleniumComponent(
text,
topics_of_interest=topics_of_interest,
llm_provider=self.llm_provider,
model_name=self.config.model_name,
model_name=self.config.llm_name,
spacy_model=self.config.browse_spacy_language_model,
)
return "\n".join(f"* {i}" for i in information)
@@ -391,7 +391,7 @@ class WebSeleniumComponent(
text,
question=question,
llm_provider=self.llm_provider,
model_name=self.config.model_name,
model_name=self.config.llm_name,
spacy_model=self.config.browse_spacy_language_model,
)
return result

2
forge/forge/llm/prompting/base.py
View File

@@ -10,7 +10,7 @@ from .schema import ChatPrompt, LanguageModelClassification
class PromptStrategy(abc.ABC):
@property
@abc.abstractmethod
def model_classification(self) -> LanguageModelClassification:
def llm_classification(self) -> LanguageModelClassification:
...
@abc.abstractmethod

4
forge/forge/llm/providers/_openai_base.py
View File

@@ -224,7 +224,7 @@ class BaseOpenAIChatProvider(
tool_calls=tool_calls or None,
),
parsed_result=parsed_result,
model_info=self.CHAT_MODELS[model_name],
llm_info=self.CHAT_MODELS[model_name],
prompt_tokens_used=t_input,
completion_tokens_used=t_output,
)
@@ -457,7 +457,7 @@ class BaseOpenAIEmbeddingProvider(
return EmbeddingModelResponse(
embedding=embedding_parser(response.data[0].embedding),
model_info=self.EMBEDDING_MODELS[model_name],
llm_info=self.EMBEDDING_MODELS[model_name],
prompt_tokens_used=response.usage.prompt_tokens,
)

2
forge/forge/llm/providers/anthropic.py
View File

@@ -309,7 +309,7 @@ class AnthropicProvider(BaseChatModelProvider[AnthropicModelName, AnthropicSetti
return ChatModelResponse(
response=assistant_msg,
parsed_result=parsed_result,
model_info=ANTHROPIC_CHAT_MODELS[model_name],
llm_info=ANTHROPIC_CHAT_MODELS[model_name],
prompt_tokens_used=t_input,
completion_tokens_used=t_output,
)

2
forge/forge/llm/providers/schema.py
View File

@@ -186,7 +186,7 @@ class ModelResponse(BaseModel):
prompt_tokens_used: int
completion_tokens_used: int
model_info: ModelInfo
llm_info: ModelInfo
class ModelProviderConfiguration(SystemConfiguration):