feat: first try

app.py

@@ -2,6 +2,11 @@ import os
 import gradio as gr
 import requests
 import inspect
+from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+from llama_index.readers.youtube_transcript import YoutubeTranscriptReader
+from llama_index.core.tools import FunctionTool
+from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec
+from llama_index.core.agent.workflow import AgentWorkflow
 import pandas as pd
 
 # (Keep Constants as is)
@@ -12,10 +17,35 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
+        self.llm = HuggingFaceInferenceAPI(model_name="Qwen/Qwen2.5-Coder-32B-Instruct")
         print("BasicAgent initialized.")
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
+        def get_answers_from_youtube_transcript(youtube_link: str, query: str) -> str:
+            """Fetches transcript of the given youtube_link and returns matching answers based on query.
+                Args:
+                youtube_link (str): youtube video link for which we need to answer questions on.
+                query (str): question to answer from video transcript.
+            """
+            loader = YoutubeTranscriptReader()
+            documents = loader.load_data(
+                ytlinks=[youtube_link]
+            )
+
+            text = documents[0].text_resource.text
+
+            return "Here's the transcript from the video, examine and formulate answer based on what is said in the transcript: \n" + text
+
+        youtube_transcript_answer_tool = FunctionTool.from_defaults(
+            get_answers_from_youtube_transcript,
+            name="get_answers_from_youtube_transcript",
+            description="Fetches transcript of the given youtube_link and returns matching answers based on query.",
+        )
+
+        duckduckgoSearchTools = DuckDuckGoSearchToolSpec().to_tool_list()
+
+        agent = AgentWorkflow.from_tools_or_functions([*duckduckgoSearchTools, youtube_transcript_answer_tool], llm=self.llm)
+        fixed_answer = agent.run(question)
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer
 

requirements.txt

@@ -1,2 +1,8 @@
 gradio
-requests
+requests
+llama_index
+llama_index-llms-ollama
+llama_index-tools-duckduckgo
+llama_index-readers-youtube_transcript
+llama_index-retrievers-bm25
+llama_index-llms-huggingface_api