fixed_openaiAPI

analyzer.py

@@ -26,7 +26,7 @@ def analyze_code(code: str) -> str:
         "{\n  'strength': '...', \n  'weaknesses': '...', \n  'speciality': '...', \n  'relevance rating': 'high'\n}"
     )
     response = client.chat.completions.create(
-        model="openai/gpt-4.1-nano",  # Updated to GPT-4.1 Nano model
+        model="gpt-4.1-nano",  # Updated model ID
         messages=[
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": code}
@@ -254,7 +254,7 @@ def analyze_code_chunk(code: str, user_requirements: str = "") -> str:
     )
     
     response = client.chat.completions.create(
-        model="openai/gpt-4.1-nano",
+        model="gpt-4.1-nano",
         messages=[
             {"role": "system", "content": chunk_prompt},
             {"role": "user", "content": code}
@@ -288,7 +288,7 @@ def aggregate_chunk_analyses(chunk_jsons: list, user_requirements: str = "") ->
     )
     user_content = "Here are the chunk analyses:\n" + "\n".join(chunk_jsons)
     response = client.chat.completions.create(
-        model="openai/gpt-4.1-nano",
+        model="gpt-4.1-nano",
         messages=[
             {"role": "system", "content": aggregation_prompt},
             {"role": "user", "content": user_content}
@@ -344,7 +344,7 @@ Repository chunk:
 Provide a clear, conversational summary in 2-3 paragraphs:"""
         
         response = client.chat.completions.create(
-            model="openai/gpt-4.1-nano",
+            model="gpt-4.1-nano",
             messages=[
                 {"role": "system", "content": "You are an expert code analyst creating conversational summaries for a repository assistant chatbot."},
                 {"role": "user", "content": context_prompt}
@@ -397,7 +397,7 @@ Create a well-structured overview covering:
 Make this comprehensive but conversational - it will be used by a chatbot to answer user questions about the repository."""
             
             response = client.chat.completions.create(
-                model="openai/gpt-4.1-nano",
+                model="gpt-4.1-nano",
                 messages=[
                     {"role": "system", "content": "You are creating a comprehensive repository summary for a chatbot assistant."},
                     {"role": "user", "content": final_prompt}

app.py

@@ -128,7 +128,7 @@ Selected repositories:"""
             # client.base_url = os.getenv("base_url")
             
             response = client.chat.completions.create(
-                model="openai/gpt-4.1-nano",
+                model="gpt-4.1-nano",
                 messages=[
                     {"role": "system", "content": "You are an expert at analyzing and ranking repositories based on user requirements. Always return valid JSON."},
                     {"role": "user", "content": prompt}

chatbot_page.py

@@ -28,7 +28,7 @@ def chat_with_user(user_message, history):
             messages.append({"role": "assistant", "content": msg[1]})
     messages.append({"role": "user", "content": user_message})
     response = client.chat.completions.create(
-        model="openai/gpt-4.1-nano",
+        model="gpt-4.1-nano",
         messages=messages,
         max_tokens=256,
         temperature=0.7
@@ -54,7 +54,7 @@ def extract_keywords_from_conversation(history):
         "Conversation:\n" + conversation + "\n\nExtract about 5 keywords for Hugging Face repo search."
     )
     response = client.chat.completions.create(
-        model="openai/gpt-4.1-nano",
+        model="gpt-4.1-nano",
         messages=[
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": user_prompt}

repo_explorer.py

@@ -278,7 +278,7 @@ Answer the user's question based on your comprehensive knowledge of this reposit
         client = OpenAI(api_key=os.getenv("OpenAI_API"))
         
         response = client.chat.completions.create(
-            model="openai/gpt-4.1-nano",
+            model="gpt-4.1-nano",
             messages=[
                 {"role": "system", "content": repo_system_prompt},
                 {"role": "user", "content": user_message}