fall back to langchain

app.py

@@ -17,11 +17,11 @@ from langchain.tools import tool
 # from langgraph.prebuilt import tools_condition
 # from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
 from langchain.agents import initialize_agent, AgentType
-# from langchain_community.llms import HuggingFaceHub
-# from langchain_community.chat_models import ChatHuggingFace
+from langchain_community.llms import HuggingFaceHub
+from langchain_community.chat_models import ChatHuggingFace
 # import openai
 # from openai import OpenAI
-from langchain_openai import ChatOpenAI
+# from langchain_openai import ChatOpenAI
 
 ## # Load environment variables from .env file
 # --- Constants ---
@@ -31,9 +31,9 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # load_dotenv()
 HF_ACCESS_KEY = os.getenv('HF_ACCESS_KEY')
 WEATHER_API_KEY = os.getenv('WEATHER_API_KEY')
-OPENAI_MODEL =  os.getenv('OPENAI_MODEL') #'gpt-3.5-turbo-0613'
-OPENAI_KEY = os.getenv('OPENAI_KEY')
-client = OpenAI(api_key = OPENAI_KEY)
+# OPENAI_MODEL =  os.getenv('OPENAI_MODEL') #'gpt-3.5-turbo-0613'
+# OPENAI_KEY = os.getenv('OPENAI_KEY')
+# client = OpenAI(api_key = OPENAI_KEY)
 
 ########## ----- DEFINING TOOLS -----##########
 
@@ -271,11 +271,11 @@ Instructions:
 
 ## --- Initialize Hugging Face Model ---
 # Generate the chat interface, including the tools
-'''
-llm = HuggingFaceEndpoint(
+
+llm = HuggingFaceHub(
     repo_id="Qwen/Qwen2.5-Coder-32B-Instruct",
     huggingfacehub_api_token=HF_ACCESS_KEY,
-    model_kwargs={'prompt': system_prompt}
+    # model_kwargs={'prompt': system_prompt}
     # system_prompt=system_prompt,
 )
 chat_llm = ChatHuggingFace(llm=llm)
@@ -285,7 +285,7 @@ llm = ChatOpenAI(
     model_name=OPENAI_MODEL,
     temperature=0.1
 )
-
+'''
 # chat = ChatHuggingFace(llm=llm, verbose=True)
 # tools = [search_tool, fetch_weather]
 # chat_with_tools = chat.bind_tools(tools)
@@ -295,7 +295,7 @@ agent = initialize_agent(
     llm=llm,
     # llm=chat_llm,
     agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
-    agent_kwargs={"system_message": system_prompt},
+    # agent_kwargs={"system_message": system_prompt},
     verbose=True,
     handle_parsing_errors=True
 )
@@ -365,9 +365,9 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            # full_prompt = f"{system_prompt}\n Input Question: {question_text}"
-            # submitted_answer = agent.run(full_prompt)
-            submitted_answer = agent.run(question_text)
+            full_prompt = f"{system_prompt}\n Input Question: {question_text}"
+            submitted_answer = agent.run(full_prompt)
+            # submitted_answer = agent.run(question_text)
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e: