Update app.py

app.py

@@ -36,6 +36,7 @@ search_tool = DuckDuckGoSearchTool()
 print("Search tool created.")
 
 ### CREATE LLM ENGINE ############
+# Below is an example of how to build an OpenAI engine:
 from openai import OpenAI
 from transformers.agents.llm_engine import MessageRole, get_clean_message_list
 
@@ -62,21 +63,20 @@ class OpenAIEngine:
         )
         return response.choices[0].message.content
 
-from transformers import ReactCodeAgent, ReactJsonAgent, HfEngine
-
-llm_engine = OpenAIEngine()
+# But instead we use HF one, since it's free:
+from transformers import ReactCodeAgent, HfApiEngine
 
 agent = ReactCodeAgent(
-    llm_engine=llm_engine,
+    llm_engine=HfApiEngine("meta-llama/Meta-Llama-3.1-70B-Instruct"),
     tools=[search_tool],
-    max_iterations=20
+    max_iterations=10
 )
 
 print("Agent initiated")
 
 topics = "Large Language Models, Tech, GPUs, AI"
 
-intermediate_report = agent.run(
+report = agent.run(
     f"""Give me a complete newsletter in markdown format of the latest developments in these topics: {topics}, with a consistent style and layout with URL.
 Each topic should have its markdown-formatted analysis, including a rundown, detailed bullet points,
 and a "Why it matters" section. For each topic there should be at least 3 articles with URL
@@ -99,55 +99,13 @@ Also, gather all news at once using a for loop on all topics with google_search,
 Make sure that you didn't forget any topic! If no news are found for any specific topic, specify 'No news on this topic were found in the last 24 hours'."""
 )
 
-print("Intermediate report created:")
-print(intermediate_report)
-
-openai_client = OpenAI(
-    api_key=os.getenv('OPENAI_API_KEY')
-)
-
-messages = [
-    {
-        "role": "user",
-        "content": f"""Below you will find a report about important news in each topic of this list : {topics}.
-Reformulate it into proper markdown, taking care to follow this example format for each topic:
-'# Top stories in AI today:\\n\\n
-- AI takes spotlight in Super Bowl commercials\\n
-- Altman seeks TRILLIONS for global AI chip initiative\\n\\n
-## AI takes spotlight in Super Bowl commercials\\n\\n
-**url:** https://example.com/story1 \\n\\
-**The Rundown:** AI made a splash in this year\'s Super Bowl commercials...\\n\\n
-**The details:** (fill this)\\\n\\n
-**Why it matters::** (fill this)\\n\\n
-## Altman seeks TRILLIONS for global AI chip initiative\\n\\n
-**The Rundown:** OpenAI CEO Sam Altman is reportedly angling to raise TRILLIONS of dollars...\\n\\n'
-**The details:** (fill this)\\n\\n
-**Why it matters::** (fill this)\\n\\n'
-Now go on! MAKE SURE TO INCLUDE ALL TOPICS, DO NOT DELETE ANY INFORMATION: you need to have 10 different headlines 'Top stories in X' in total, one for each topic.
-(if no information is to be found on a specific topic, you can put in the content 'No stories found in the last 24 hours for this topic')
-Write it as markdown, but no need to put specific tags at the beginning and end like '```markdown'.
-Here is the report :
-{intermediate_report}
-"""
-    }
-]
-response = openai_client.chat.completions.create(
-    model="gpt-4o-mini",
-    messages=messages,
-    temperature=0.5,
-)
-clean_report = response.choices[0].message.content
 
 
 date = datetime.today().strftime('%Y-%m-%d')
 
-def create_newsletter(date, clean_report):
-    newsletter = clean_report
-    upload_newsletter(date, newsletter)
-
-create_newsletter(date, clean_report)
+upload_newsletter(date, report)
 
-print("Clean report pushed to dataset!")
+print("Report pushed to dataset!")
 
 with gr.Blocks() as demo:
     gr.Markdown(f"{date}, topics: {topics}\n### ✅ Newsletter generated! Content below 👇")