mirror of
https://github.com/aljazceru/Auto-GPT.git
synced 2025-12-18 22:44:21 +01:00
Fix regression: restore api_base and organization configurability (#4933)
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@@ -86,7 +86,18 @@ class Config(SystemSettings):
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plugins: list[str]
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authorise_key: str
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def get_azure_kwargs(self, model: str) -> dict[str, str]:
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def get_openai_credentials(self, model: str) -> dict[str, str]:
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credentials = {
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"api_key": self.openai_api_key,
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"api_base": self.openai_api_base,
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"organization": self.openai_organization,
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}
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if self.use_azure:
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azure_credentials = self.get_azure_credentials(model)
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credentials.update(azure_credentials)
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return credentials
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def get_azure_credentials(self, model: str) -> dict[str, str]:
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"""Get the kwargs for the Azure API."""
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# Fix --gpt3only and --gpt4only in combination with Azure
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@@ -71,17 +71,14 @@ def create_text_completion(
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if temperature is None:
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temperature = config.temperature
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if config.use_azure:
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kwargs = config.get_azure_kwargs(model)
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else:
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kwargs = {"model": model}
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kwargs.update(config.get_openai_credentials(model))
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response = iopenai.create_text_completion(
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prompt=prompt,
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**kwargs,
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temperature=temperature,
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max_tokens=max_output_tokens,
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api_key=config.openai_api_key,
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)
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logger.debug(f"Response: {response}")
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@@ -137,9 +134,7 @@ def create_chat_completion(
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if message is not None:
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return message
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chat_completion_kwargs["api_key"] = config.openai_api_key
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if config.use_azure:
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chat_completion_kwargs.update(config.get_azure_kwargs(model))
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chat_completion_kwargs.update(config.get_openai_credentials(model))
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if functions:
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chat_completion_kwargs["functions"] = [
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@@ -179,12 +174,7 @@ def check_model(
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config: Config,
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) -> str:
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"""Check if model is available for use. If not, return gpt-3.5-turbo."""
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openai_credentials = {
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"api_key": config.openai_api_key,
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}
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if config.use_azure:
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openai_credentials.update(config.get_azure_kwargs(model_name))
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openai_credentials = config.get_openai_credentials(model_name)
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api_manager = ApiManager()
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models = api_manager.get_models(**openai_credentials)
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@@ -41,10 +41,8 @@ def get_embedding(
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input = [text.replace("\n", " ") for text in input]
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model = config.embedding_model
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if config.use_azure:
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kwargs = config.get_azure_kwargs(model)
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else:
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kwargs = {"model": model}
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kwargs.update(config.get_openai_credentials(model))
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logger.debug(
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f"Getting embedding{f's for {len(input)} inputs' if multiple else ''}"
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@@ -57,7 +55,6 @@ def get_embedding(
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embeddings = iopenai.create_embedding(
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input,
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**kwargs,
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api_key=config.openai_api_key,
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).data
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if not multiple:
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@@ -174,18 +174,32 @@ azure_model_map:
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fast_llm = config.fast_llm
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smart_llm = config.smart_llm
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assert config.get_azure_kwargs(config.fast_llm)["deployment_id"] == "FAST-LLM_ID"
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assert config.get_azure_kwargs(config.smart_llm)["deployment_id"] == "SMART-LLM_ID"
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assert (
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config.get_azure_credentials(config.fast_llm)["deployment_id"] == "FAST-LLM_ID"
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)
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assert (
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config.get_azure_credentials(config.smart_llm)["deployment_id"]
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== "SMART-LLM_ID"
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)
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# Emulate --gpt4only
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config.fast_llm = smart_llm
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assert config.get_azure_kwargs(config.fast_llm)["deployment_id"] == "SMART-LLM_ID"
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assert config.get_azure_kwargs(config.smart_llm)["deployment_id"] == "SMART-LLM_ID"
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assert (
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config.get_azure_credentials(config.fast_llm)["deployment_id"] == "SMART-LLM_ID"
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)
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assert (
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config.get_azure_credentials(config.smart_llm)["deployment_id"]
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== "SMART-LLM_ID"
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)
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# Emulate --gpt3only
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config.fast_llm = config.smart_llm = fast_llm
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assert config.get_azure_kwargs(config.fast_llm)["deployment_id"] == "FAST-LLM_ID"
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assert config.get_azure_kwargs(config.smart_llm)["deployment_id"] == "FAST-LLM_ID"
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assert (
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config.get_azure_credentials(config.fast_llm)["deployment_id"] == "FAST-LLM_ID"
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)
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assert (
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config.get_azure_credentials(config.smart_llm)["deployment_id"] == "FAST-LLM_ID"
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)
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del os.environ["USE_AZURE"]
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del os.environ["AZURE_CONFIG_FILE"]
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