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fix: Update import statements for OllamaEmbeddings (#2584)
This pull request fixes the import statements for OllamaEmbeddings in multiple files. The import statements are updated to use the correct package name "langchain_community.embeddings" instead of "langchain.embeddings.ollama". This ensures that the code can be compiled and executed without any import errors.
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@ -1,7 +1,7 @@
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from typing import Optional
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from uuid import UUID
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from langchain.embeddings.ollama import OllamaEmbeddings
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from langchain_community.embeddings import OllamaEmbeddings
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from langchain_openai import OpenAIEmbeddings
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from logger import get_logger
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from models.databases.supabase.supabase import SupabaseDB
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@ -35,13 +35,13 @@ chat_service = ChatService()
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class GPT4Brain(KnowledgeBrainQA):
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"""
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GPT4Brain integrates with GPT-4 to provide real-time answers and supports various tools to enhance its capabilities.
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Available Tools:
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- WebSearchTool: Performs web searches to find relevant information.
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- ImageGeneratorTool: Generates images based on textual descriptions.
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- URLReaderTool: Reads and summarizes content from URLs.
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- EmailSenderTool: Sends emails with specified content.
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Use Cases:
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- WebSearchTool can be used to find the latest news articles on a specific topic or to gather information from various websites.
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- ImageGeneratorTool is useful for creating visual content based on textual prompts, such as generating a company logo based on a description.
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@ -51,7 +51,7 @@ class GPT4Brain(KnowledgeBrainQA):
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tools: Optional[List[BaseTool]] = None
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tool_executor: Optional[ToolExecutor] = None
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model_function: ChatOpenAI = None
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function_model: ChatOpenAI = None
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def __init__(
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self,
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@ -90,7 +90,7 @@ class GPT4Brain(KnowledgeBrainQA):
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# Define the function that calls the model
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def call_model(self, state):
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messages = state["messages"]
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response = self.model_function.invoke(messages)
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response = self.function_model.invoke(messages)
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# We return a list, because this will get added to the existing list
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return {"messages": [response]}
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@ -166,11 +166,11 @@ class GPT4Brain(KnowledgeBrainQA):
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return app
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def get_chain(self):
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self.model_function = ChatOpenAI(
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self.function_model = ChatOpenAI(
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model="gpt-4-turbo", temperature=0, streaming=True
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)
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self.model_function = self.model_function.bind_tools(self.tools)
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self.function_model = self.function_model.bind_tools(self.tools)
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graph = self.create_graph()
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@ -4,7 +4,7 @@ from typing import List, Optional
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from uuid import UUID
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from langchain.chains import ConversationalRetrievalChain
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from langchain.embeddings.ollama import OllamaEmbeddings
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from langchain_community.embeddings import OllamaEmbeddings
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from langchain.llms.base import BaseLLM
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from langchain.prompts import HumanMessagePromptTemplate, SystemMessagePromptTemplate
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from langchain.retrievers import ContextualCompressionRetriever
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@ -3,7 +3,7 @@ from uuid import UUID
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from fastapi import APIRouter, Depends, HTTPException, Query, Request
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from fastapi.responses import StreamingResponse
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from langchain.embeddings.ollama import OllamaEmbeddings
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from langchain_community.embeddings import OllamaEmbeddings
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from langchain_openai import OpenAIEmbeddings
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from logger import get_logger
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from middlewares.auth import AuthBearer, get_current_user
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