Fix OpenAI proxy issues for HuggingFace compatibility

streamlit_app.py

@@ -15,6 +15,12 @@ from langchain_core.messages import AIMessage, HumanMessage
 import requests
 import json
 from langchain_core.output_parsers import StrOutputParser
+from openai import OpenAI
+
+# Disable proxies to prevent validation errors on Hugging Face
+os.environ["OPENAI_PROXY"] = ""
+os.environ["HTTPS_PROXY"] = ""
+os.environ["HTTP_PROXY"] = ""
 
 # Global variable to store ArXiv sources
 ARXIV_SOURCES = []
@@ -95,39 +101,23 @@ def load_document_chunks():
 @st.cache_resource
 def get_chat_model():
     """Get the chat model for initial RAG."""
-    import os
-    # DEBUG START - HF Compatibility fix
-    api_key = os.environ.get("OPENAI_API_KEY", "")
-    print(f"DEBUG: Initializing chat model with API key: {api_key[:4]}...")
-    # DEBUG END
-    return ChatOpenAI(api_key=api_key, model="gpt-4.1-mini")
+    return ChatOpenAI(
+        model="gpt-4.1-mini",  # Use model not model_name
+        temperature=0,
+    )
 
 @st.cache_resource
 def get_agent_model():
     """Get the more powerful model for agent and evaluation."""
-    import os
-    # DEBUG START - HF Compatibility fix
-    api_key = os.environ.get("OPENAI_API_KEY", "")
-    print(f"DEBUG: Initializing agent model with API key: {api_key[:4]}...")
-    # DEBUG END
-    return ChatOpenAI(api_key=api_key, model="gpt-4.1")
+    return ChatOpenAI(
+        model="gpt-4.1",  # Use model not model_name
+        temperature=0,
+    )
 
 @st.cache_resource
 def get_embedding_model():
     """Get the embedding model."""
-    import os
-    from langchain_openai import OpenAIEmbeddings
-    
-    # DEBUG START - HF Compatibility fix
-    api_key = os.environ.get("OPENAI_API_KEY", "")
-    print(f"DEBUG: Initializing embeddings with API key: {api_key[:4]}...")
-    # DEBUG END
-    
-    # Most minimal parameters possible
-    return OpenAIEmbeddings(
-        model="text-embedding-3-small",
-        api_key=api_key
-    )
+    return OpenAIEmbeddings(model="text-embedding-3-small")
 
 @st.cache_resource
 def setup_qdrant_client():