new update

agent.py

@@ -1,11 +1,24 @@
 # use a multimodal llm 
+from typing import Any
 from llama_index.core.agent.workflow import AgentWorkflow
+from llama_index.core.workflow import Context
 
+class Basic_Agent():
+    """base class for our basic agent"""
+    def __init__(self, tool, llm_model) -> None:
+        self.tool =  tool
+        self.llm_model = llm_model
+
+    async def __call__(self, input_prompt:str) -> str:
+        """a basic agent with the ability to take decisions, act by calling the right tools and provide answer to the input prompt query string"""
+        agent = AgentWorkflow.from_tools_or_functions(
+            tools_or_functions=self.tool,
+            llm=self.llm_model
+        )
+
+        ctx = Context(agent)
+        result  = await agent.run(input_prompt,
+                                  ctx=ctx
+                                  )
+        return str(result)
 
-def basic_agent(tool, llm_model):
-    """a basic agent with the ability to take decisions, act by calling the right tools and provide answer to the input prompt query string"""
-    agent = AgentWorkflow.from_tools_or_functions(
-        tools_or_functions=tool,
-        llm=llm_model
-    )
-    return agent

app.py

@@ -1,40 +1,61 @@
-from json import tool
+
 import os
 import gradio as gr
 import requests
-import inspect
 import pandas as pd
-from agent import basic_agent
+from agent import Basic_Agent
 from tools import search_tool, image_tool, video_tool
 from llama_index.llms.ollama import Ollama
-from llama_index.core.workflow import Context
+import asyncio
+from together import Together
+from dotenv import load_dotenv
+from llama_index.llms.together import TogetherLLM
+
+
+load_dotenv()
 
+TOGETHER_API_KEY = os.getenv("TOGETHER_API_KEY")
 
 
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# # --- Basic Agent Definition ---
-# # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-# class BasicAgent:
-#     def __init__(self):
-#         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."
-#         print(f"Agent returning fixed answer: {fixed_answer}")
-#         return fixed_answer
 tools = [search_tool, image_tool, video_tool]
 
-llm = Ollama(
-    model="llama3.1",
-    base_url="http://localhost:7860", 
-    request_timeout=120.0)
+# llm = Ollama(
+#     model="llama3.1",
+#     request_timeout=120.0)
+
+together_client =  Together(timeout=120)
+
+# creating an LLM wrapper around our client
+
+# class TogetherLLMWrapper():
+#     def __init__(self, model = 'meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo'):
+#         self.model =  model
+
+#     def __call__(self, prompt:str) -> str:
+#         response = together_client.completions.create(
+#             prompt=prompt,
+#             model=self.model,
+#             max_tokens=1000,
+#             temperature=0.7,
+#             top_p=0.9,
+#         )
+#         return response.choices[0].text # type: ignore
+
+# llm = TogetherLLMWrapper()
+
 
-agent = basic_agent(tool=tools, llm_model=llm)
+llm = TogetherLLM(
+    model='meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo',
+    api_key=TOGETHER_API_KEY,
+    temperature=0.7,
+    max_tokens=1000
+)
 
-ctx = Context(agent)
+agent = Basic_Agent(tool=tools, llm_model=llm)
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
@@ -98,7 +119,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = agent.run(question_text, ctx=ctx)
+            submitted_answer = asyncio.run(agent(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:

requirements.txt

@@ -7,4 +7,6 @@ python-dotenv
 llama-index
 llama-index-llms-ollama
 llama-index-multi-modal-llms-ollama
-opencv-python
+opencv-python
+together
+llama-index-llms-together

tools.py

@@ -15,7 +15,6 @@ brave_api_key = os.getenv('BRAVE_API_KEY', 'No key')
 mm_model = OllamaMultiModal(
         model='llava',
         temperature=0.7,
-        base_url="http://localhost:7860",
     )
 
 search_tool_spec = BraveSearchToolSpec(api_key=brave_api_key)