Update app.py

app.py

@@ -11,16 +11,15 @@ import os
 import gradio as gr
 import inspect
 import pandas as pd
-from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel
 
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-
+import openai
 
 # ‑‑‑ smol‑agents base imports (provided by the framework) ‑‑‑
-from smol_agents import (
+from smolagents import (
     Tool,
     PipelineTool,
     CodeAgent,
@@ -58,10 +57,8 @@ class SpeechToTextTool(PipelineTool):
         if not path.is_file():
             raise FileNotFoundError(f"No such audio file: {path}")
 
-        from openai import audio as _audio  # late import
-
         with path.open("rb") as fp:
-            resp = _audio.transcriptions.create(
+            resp = openai.audio.transcriptions.create(
                 file=fp,
                 model="whisper-1",
                 response_format="text",
@@ -122,16 +119,10 @@ class ExcelToTextTool(Tool):
 
 
 # ---------------------------------------------------------------------------
-# NEW: YouTube Question‑Answer Tool
+# YouTube Question‑Answer Tool
 # ---------------------------------------------------------------------------
 class YouTubeQATool(PipelineTool):
-    """Answer questions about the spoken content of a YouTube video.
-
-    • Downloads the auto‑generated or creator‑provided transcript using
-      **youtube‑transcript‑api** (no API key needed for most public videos).
-    • Feeds a compressed transcript + user question to GPT‑4o for an answer.
-    • Caches transcripts locally to avoid repeated network calls.
-    """
+    """Answer questions about the spoken content of a YouTube video."""
 
     name = "youtube_qa"
     description = (
@@ -151,12 +142,10 @@ class YouTubeQATool(PipelineTool):
     }
     output_type = "string"
 
-    # ––––– internal helpers ––––– ------------------------------------------------
-    _TRANSCRIPT_CACHE: dict[str, str] = {}  # simple in‑proc cache
+    _TRANSCRIPT_CACHE: dict[str, str] = {}
 
     @staticmethod
     def _extract_video_id(url: str) -> str:
-        """Return the 11‑char YouTube ID from a watch/shorts URL or raw ID."""
         if len(url) == 11 and "/" not in url:
             return url
         parsed = _urlparse.urlparse(url)
@@ -166,7 +155,6 @@ class YouTubeQATool(PipelineTool):
             qs = _urlparse.parse_qs(parsed.query)
             if "v" in qs:
                 return qs["v"][0]
-            # shorts/embedded
             return parsed.path.split("/")[-1]
         raise ValueError("Could not parse YouTube video ID from URL")
 
@@ -180,13 +168,12 @@ class YouTubeQATool(PipelineTool):
             return "Error: youtube‑transcript‑api library not installed."
         try:
             segments: List[dict] = YouTubeTranscriptApi.get_transcript(video_id)
-        except Exception as exc:  # private video, disabled captions, …
+        except Exception as exc:
             return f"Error fetching transcript: {exc}"
         text = " ".join(seg["text"] for seg in segments)
         cls._TRANSCRIPT_CACHE[video_id] = text
         return text
 
-    # ––––– main entry point ––––– -------------------------------------------
     def forward(self, url: str, question: str) -> str:  # type: ignore[override]
         try:
             vid = self._extract_video_id(url)
@@ -197,12 +184,11 @@ class YouTubeQATool(PipelineTool):
         if transcript.startswith("Error"):
             return transcript
 
-        # Keep prompt under ~15k chars – truncate transcript if necessary
         max_chars = 15000
         if len(transcript) > max_chars:
             transcript = transcript[:max_chars] + " …(truncated)…"
 
-        from openai import chat  # lazy import OpenAI client only here
+        import openai
 
         system = (
             "You are a meticulous assistant. Answer the user's question about "
@@ -215,14 +201,14 @@ class YouTubeQATool(PipelineTool):
             {"role": "user", "content": f"Question: {question}"},
         ]
         try:
-            resp = chat.completions.create(
-                model="gpt-4o",  # uses the same hosted model as the agent
+            resp = openai.chat.completions.create(
+                model="gpt-4o",
                 messages=messages,
                 temperature=0.2,
                 max_tokens=256,
             )
             return resp.choices[0].message.content.strip()
-        except Exception as exc:  # pragma: no cover
+        except Exception as exc:
             return f"Error generating answer: {exc}"
 
 
@@ -262,7 +248,7 @@ class BasicAgent:
         WikipediaSearchTool(),
         SpeechToTextTool(),
         ExcelToTextTool(),
-        YouTubeQATool(),  # <-- NEW
+        YouTubeQATool(),
     ]
 
     def __init__(self) -> None:
@@ -270,12 +256,7 @@ class BasicAgent:
             model=self._model,
             tools=self._tools,
             add_base_tools=True,
-            additional_authorized_imports=[
-                "numpy",
-                "pandas",
-                "csv",
-                "subprocess",
-            ],
+            additional_authorized_imports=["numpy", "pandas", "csv", "subprocess"],
         )
         print("BasicAgent initialized with YouTubeQATool.")