From cbb986b5a2b65fed8ee257722eb86a088c3b7ff1 Mon Sep 17 00:00:00 2001
From: Ivaylo Gochkov <ivaylo@gochkov.com>
Date: Mon, 28 Oct 2024 22:19:10 +0100
Subject: [PATCH] fixed warnings

---
 Dockerfile                                  | 7 -------
 gpt_researcher/llm_provider/generic/base.py | 2 +-
 gpt_researcher/memory/embeddings.py         | 2 +-
 gpt_researcher/scraper/arxiv/arxiv.py       | 2 +-
 4 files changed, 3 insertions(+), 10 deletions(-)

diff --git a/Dockerfile b/Dockerfile
index ba4e29a32..9cb4fba85 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -29,13 +29,6 @@ RUN pip install --no-cache-dir -r requirements.txt && \
 # Stage 3: Final stage with non-root user and app
 FROM gpt-researcher-install AS gpt-researcher
 
-# Use environment variables for API keys (defaults can be overridden at runtime)
-ARG OPENAI_API_KEY
-ARG TAVILY_API_KEY
-
-ENV OPENAI_API_KEY=${OPENAI_API_KEY}
-ENV TAVILY_API_KEY=${TAVILY_API_KEY}
-
 # Create a non-root user for security
 RUN useradd -ms /bin/bash gpt-researcher && \
     chown -R gpt-researcher:gpt-researcher /usr/src/app
diff --git a/gpt_researcher/llm_provider/generic/base.py b/gpt_researcher/llm_provider/generic/base.py
index 7e64a8254..e7c8e2814 100644
--- a/gpt_researcher/llm_provider/generic/base.py
+++ b/gpt_researcher/llm_provider/generic/base.py
@@ -68,7 +68,7 @@ def from_provider(cls, provider: str, **kwargs: Any):
             llm = ChatFireworks(**kwargs)
         elif provider == "ollama":
             _check_pkg("langchain_community")
-            from langchain_community.chat_models import ChatOllama
+            from langchain_ollama import ChatOllama
             
             llm = ChatOllama(base_url=os.environ["OLLAMA_BASE_URL"], **kwargs)
         elif provider == "together":
diff --git a/gpt_researcher/memory/embeddings.py b/gpt_researcher/memory/embeddings.py
index 0e917ed4e..5bfcc8cb5 100644
--- a/gpt_researcher/memory/embeddings.py
+++ b/gpt_researcher/memory/embeddings.py
@@ -17,7 +17,7 @@ def __init__(self, embedding_provider: str, model: str, **embdding_kwargs: Any):
         _embeddings = None
         match embedding_provider:
             case "ollama":
-                from langchain_community.embeddings import OllamaEmbeddings
+                from langchain_ollama import OllamaEmbeddings
 
                 _embeddings = OllamaEmbeddings(
                     model=model,
diff --git a/gpt_researcher/scraper/arxiv/arxiv.py b/gpt_researcher/scraper/arxiv/arxiv.py
index e3c902830..2af550417 100644
--- a/gpt_researcher/scraper/arxiv/arxiv.py
+++ b/gpt_researcher/scraper/arxiv/arxiv.py
@@ -18,5 +18,5 @@ def scrape(self):
         """
         query = self.link.split("/")[-1]
         retriever = ArxivRetriever(load_max_docs=2, doc_content_chars_max=None)
-        docs = retriever.get_relevant_documents(query=query)
+        docs = retriever.invoke(query=query)
         return docs[0].page_content