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.
This commit is contained in:
Stan Girard 2024-05-11 20:50:13 +02:00 committed by GitHub
parent a1b74d00f5
commit 3086891cb7
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
4 changed files with 9 additions and 9 deletions

View File

@ -1,7 +1,7 @@
from typing import Optional from typing import Optional
from uuid import UUID from uuid import UUID
from langchain.embeddings.ollama import OllamaEmbeddings from langchain_community.embeddings import OllamaEmbeddings
from langchain_openai import OpenAIEmbeddings from langchain_openai import OpenAIEmbeddings
from logger import get_logger from logger import get_logger
from models.databases.supabase.supabase import SupabaseDB from models.databases.supabase.supabase import SupabaseDB

View File

@ -51,7 +51,7 @@ class GPT4Brain(KnowledgeBrainQA):
tools: Optional[List[BaseTool]] = None tools: Optional[List[BaseTool]] = None
tool_executor: Optional[ToolExecutor] = None tool_executor: Optional[ToolExecutor] = None
model_function: ChatOpenAI = None function_model: ChatOpenAI = None
def __init__( def __init__(
self, self,
@ -90,7 +90,7 @@ class GPT4Brain(KnowledgeBrainQA):
# Define the function that calls the model # Define the function that calls the model
def call_model(self, state): def call_model(self, state):
messages = state["messages"] messages = state["messages"]
response = self.model_function.invoke(messages) response = self.function_model.invoke(messages)
# We return a list, because this will get added to the existing list # We return a list, because this will get added to the existing list
return {"messages": [response]} return {"messages": [response]}
@ -166,11 +166,11 @@ class GPT4Brain(KnowledgeBrainQA):
return app return app
def get_chain(self): def get_chain(self):
self.model_function = ChatOpenAI( self.function_model = ChatOpenAI(
model="gpt-4-turbo", temperature=0, streaming=True model="gpt-4-turbo", temperature=0, streaming=True
) )
self.model_function = self.model_function.bind_tools(self.tools) self.function_model = self.function_model.bind_tools(self.tools)
graph = self.create_graph() graph = self.create_graph()

View File

@ -4,7 +4,7 @@ from typing import List, Optional
from uuid import UUID from uuid import UUID
from langchain.chains import ConversationalRetrievalChain from langchain.chains import ConversationalRetrievalChain
from langchain.embeddings.ollama import OllamaEmbeddings from langchain_community.embeddings import OllamaEmbeddings
from langchain.llms.base import BaseLLM from langchain.llms.base import BaseLLM
from langchain.prompts import HumanMessagePromptTemplate, SystemMessagePromptTemplate from langchain.prompts import HumanMessagePromptTemplate, SystemMessagePromptTemplate
from langchain.retrievers import ContextualCompressionRetriever from langchain.retrievers import ContextualCompressionRetriever

View File

@ -3,7 +3,7 @@ from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, Query, Request from fastapi import APIRouter, Depends, HTTPException, Query, Request
from fastapi.responses import StreamingResponse from fastapi.responses import StreamingResponse
from langchain.embeddings.ollama import OllamaEmbeddings from langchain_community.embeddings import OllamaEmbeddings
from langchain_openai import OpenAIEmbeddings from langchain_openai import OpenAIEmbeddings
from logger import get_logger from logger import get_logger
from middlewares.auth import AuthBearer, get_current_user from middlewares.auth import AuthBearer, get_current_user