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Hotfix for Detailed report azureopenai support and azureopenai LLM documentation improvement

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This commit is contained in:
Paul Norris
2024-04-04 14:58:07 +01:00
parent dc2e3a1f2e
commit 5642cce1b7
2 changed files with 19 additions and 8 deletions
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17
gpt_researcher/llm_provider/azureopenai/azureopenai.py
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@@ -4,13 +4,18 @@ from colorama import Fore, Style
from langchain_openai import AzureChatOpenAI
'''
Please note: Needs additional env vars such as:
AZURE_OPENAI_ENDPOINT e.g. https://xxxx.openai.azure.com/",
OPENAI_API_VERSION,
OPENAI_API_TYPE
Please note:
Needs additional env vars such as:
AZURE_OPENAI_ENDPOINT e.g. https://xxxx.openai.azure.com/",
AZURE_OPENAI_API_KEY e.g "xxxxxxxxxxxxxxxxxxxxx",
OPENAI_API_VERSION, e.g. "2024-03-01-preview" but needs to updated over time as API verison updates,
AZURE_EMBEDDING_MODEL e.g. "ada2" The Azure OpenAI embedding model deployment name.
Note new entry in config.py to specify the Azure OpenAI embedding model name:
self.azure_embedding_model = os.getenv('AZURE_EMBEDDING_MODEL', "INSERT_EMBEDDIGN_MODEL_DEPLOYMENT_NAME")
config.py settings for Azure OpenAI should look like:
self.embedding_provider = os.getenv('EMBEDDING_PROVIDER', 'azureopenai')
self.llm_provider = os.getenv('LLM_PROVIDER', "azureopenai")
self.fast_llm_model = os.getenv('FAST_LLM_MODEL', "gpt-3.5-turbo-16k") #Deployment name of your GPT3.5T model as per azure OpenAI studio deployment section
self.smart_llm_model = os.getenv('SMART_LLM_MODEL', "gpt4") #Deployment name of your GPT4 1106-Preview+ (GPT4T) model as per azure OpenAI studio deployment section
'''
class AzureOpenAIProvider:

10
gpt_researcher/utils/llm.py
View File

@@ -123,7 +123,13 @@ async def construct_subtopics(task: str, data: str, config, subtopics: list = []
print(f"\n🤖 Calling {config.smart_llm_model}...\n")
model = ChatOpenAI(model=config.smart_llm_model)
if config.llm_provider == "openai":
model = ChatOpenAI(model=config.smart_llm_model)
elif config.llm_provider == "azureopenai":
from langchain_openai import AzureChatOpenAI
model = AzureChatOpenAI(model=config.smart_llm_model)
else:
return []
chain = prompt | model | parser
@@ -138,4 +144,4 @@ async def construct_subtopics(task: str, data: str, config, subtopics: list = []
except Exception as e:
print("Exception in parsing subtopics : ", e)
return subtopics
return subtopics