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https://github.com/StanGirard/quivr.git
synced 2024-09-11 13:15:41 +03:00
fix(openai): user key now used for llm model
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@ -152,7 +152,8 @@ class BaseBrainPicking(BaseModel):
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This function should also call: _create_qa, get_chat_history and format_chat_history.
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It should also update the chat_history in the DB.
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"""
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async def generate_stream(self, question: str) -> AsyncIterable:
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"""
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Generate a streaming answer to a given question using QA Chain.
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@ -46,7 +46,7 @@ class OpenAIBrainPicking(QABaseBrainPicking):
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openai_api_key=self.openai_api_key
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) # pyright: ignore reportPrivateUsage=none
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def _create_llm(self, model, streaming=False, callbacks=None) -> BaseLLM:
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def _create_llm(self, model, temperature=0, streaming=False, callbacks=None) -> BaseLLM:
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"""
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Determine the language model to be used.
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:param model: Language model name to be used.
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@ -55,9 +55,10 @@ class OpenAIBrainPicking(QABaseBrainPicking):
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:return: Language model instance
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"""
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return ChatOpenAI(
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temperature=self.temperature,
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temperature=temperature,
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model=model,
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streaming=streaming,
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verbose=True,
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callbacks=callbacks,
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openai_api_key=self.openai_api_key,
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) # pyright: ignore reportPrivateUsage=none
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@ -13,7 +13,6 @@ from repository.chat.get_chat_history import get_chat_history
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from repository.chat.update_chat_history import update_chat_history
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from supabase.client import Client, create_client
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from vectorstore.supabase import CustomSupabaseVectorStore
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from langchain.chat_models import ChatOpenAI
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from repository.chat.update_message_by_id import update_message_by_id
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import json
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@ -175,12 +174,8 @@ class QABaseBrainPicking(BaseBrainPicking):
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callback = self.callbacks[0]
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callback = AsyncIteratorCallbackHandler()
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self.callbacks = [callback]
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model = ChatOpenAI(
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streaming=True,
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verbose=True,
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callbacks=[callback],
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)
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llm = ChatOpenAI(temperature=0)
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model = self._create_llm(model=self.model, streaming=True, callbacks=self.callbacks)
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llm = self._create_llm(model=self.model,temperature=self.temperature)
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question_generator = LLMChain(llm=llm, prompt=CONDENSE_QUESTION_PROMPT)
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doc_chain = load_qa_chain(model, chain_type="stuff")
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qa = ConversationalRetrievalChain(
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@ -1,4 +1,4 @@
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export const GITHUB_URL = "https://github.com/stangirard/quivr";
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export const TWITTER_URL = "https://twitter.com/quivr_brain";
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export const DISCORD_URL = "https://discord.gg/HUpRgp2HG8";
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export const DEFAULT_BACKEND_URL = "http://localhost:5000";
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export const DEFAULT_BACKEND_URL = "http://localhost:5050";
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