Openai

app.py

@@ -5,13 +5,13 @@ import inspect
 import pandas as pd
 import ast
 import operator
+import time
 from typing import List, Dict, Any, Optional, Annotated
 from langgraph.graph import Graph, StateGraph
 from langgraph.prebuilt import ToolNode
 from tools import simple_search
-from huggingface_hub import InferenceClient
+from openai import OpenAI
 from typing_extensions import TypedDict
-import time
 
 def override(_, new): return new
 
@@ -19,7 +19,7 @@ print("trial")
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-HF_TOKEN = os.getenv("HF_TOKEN")  # Make sure to set this environment variable
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")  # Make sure to set this environment variable
 
 
 class AgentState(TypedDict):
@@ -33,16 +33,12 @@ class AgentState(TypedDict):
 
 class BasicAgent:
     def __init__(self):
-        print("Initializing BasicAgent with Qwen2.5-Coder-7B-Instruct...")
-        if not HF_TOKEN:
-            raise ValueError("HF_TOKEN environment variable not set. Please set your Hugging Face API token.")
+        print("Initializing BasicAgent with OpenAI...")
+        if not OPENAI_API_KEY:
+            raise ValueError("OPENAI_API_KEY environment variable not set. Please set your OpenAI API key.")
         
-        # Initialize LLM client
-        self.llm = InferenceClient(
-            # model="Qwen/Qwen2.5-Coder-7B-Instruct",
-            model = "mistralai/Mistral-7B-Instruct-v0.2",
-            token=HF_TOKEN
-        )
+        # Initialize OpenAI client
+        self.llm = OpenAI(api_key=OPENAI_API_KEY)
         
         # Create the agent workflow
         print("Creating workflow variable")
@@ -54,16 +50,21 @@ class BasicAgent:
         try:
             print("=== Sending prompt ===")
             print(prompt[:500])
-            response = self.llm.text_generation(
-                prompt,
-                max_new_tokens=200,
+            response = self.llm.chat.completions.create(
+                model="gpt-3.5-turbo",
+                messages=[
+                    {"role": "system", "content": "You are a helpful AI assistant that provides clear and concise answers."},
+                    {"role": "user", "content": prompt}
+                ],
+                max_tokens=200,
                 temperature=0.7,
                 top_p=0.95,
-                repetition_penalty=1.1
+                frequency_penalty=0.1
             )
             print("=== Received response ===")
-            print(response)
-            return response
+            response_text = response.choices[0].message.content
+            print(response_text)
+            return response_text
         except Exception as e:
             print(f"Error calling LLM API: {e}")
             return f"Error getting response from LLM: {str(e)}"

requirements.txt

@@ -5,4 +5,5 @@ pydantic
 duckduckgo-search
 langchain
 langchain-community
-huggingface-hub
+huggingface-hub
+openai