Update app.py

app.py

@@ -1,63 +1,61 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
+from composio_crewai import ComposioToolSet, App, Action
+from crewai import Agent, Task, Crew, Process
+from langchain_openai import ChatOpenAI
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+llm = ChatOpenAI(model="gpt-4")
+
+toolset = ComposioToolSet()
+tools = toolset.get_tools(apps=[App.SERPAPI, App.WEBTOOL])
+
+def find_hackernews_posts(message):
+    profile = message
+
+    hacnews_agent = Agent(
+        role="Technical Researcher",
+        goal="Find the best technical posts on Hackernews",
+        backstory="You are a technical person who loves reading Hackernews and looking for technical posts. You spend all your time looking for interesting posts of the day.",
+        llm=llm,
+        tools=tools
+    )
+
+    hacnews_task = Task(
+        description=f"""
+            Use the serp tool to search for the user's twitter profile of name {profile} to read his bio, 
+            and then scrape it. Based on his bio, find good technical hackernews posts suited to his bio.
+        """,
+        expected_output="A list of technical hackernews posts printed",
+        agent=hacnews_agent,
+        tools=tools
+    )
+
+    crew = Crew(
+        agents=[hacnews_agent],
+        tasks=[hacnews_task],
+        process=Process.sequential,
+        verbose=True
+    )
+
+    result = crew.kickoff()
+    return result
+
+chat_interface = gr.ChatInterface(
+    fn=find_hackernews_posts,
+    title="HackerNews Post Finder",
+    description="Enter a Twitter username to find relevant technical HackerNews posts.",
+    examples=[
+        ["elonmusk"],
+        ["naval"],
+        ["paulg"]
     ],
+    retry_btn=None,
+    undo_btn=None,
+    clear_btn="Clear"
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    chat_interface.launch()