Update app.py
Browse files
app.py
CHANGED
@@ -2,7 +2,10 @@ import os
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import gradio as gr
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import cohere
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from crewai import Agent, Task, Crew, Process
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from langchain_groq import ChatGroq
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from langchain_community.tools import DuckDuckGoSearchRun, DuckDuckGoSearchResults
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from crewai_tools import tool, SeleniumScrapingTool, ScrapeWebsiteTool
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@@ -77,13 +80,18 @@ def kickoff_crew(topic: str) -> dict:
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# Initialize the Groq large language model
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groq_llm_70b = ChatGroq(temperature=0, groq_api_key=groq_api_key, model_name="llama3-70b-8192")
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# Define Agents with Groq LLM
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researcher = Agent(
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role='Researcher',
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goal='Collect detailed information on {topic}',
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tools=[search_results, web_scrapper],
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-
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backstory=(
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"As a diligent researcher, you explore the depths of the internet to "
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"unearth crucial information and insights on the assigned topics. "
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@@ -102,7 +110,7 @@ def kickoff_crew(topic: str) -> dict:
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editor = Agent(
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role='Editor',
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goal='Compile and refine the information into a comprehensive report on {topic}',
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-
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backstory=(
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"With a keen eye for detail and a strong command of language, you transform "
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"raw data into polished, insightful reports that are both informative and engaging. "
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import gradio as gr
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import cohere
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from crewai import Agent, Task, Crew, Process
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+
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from langchain_groq import ChatGroq
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from langchain_cohere import ChatCohere
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from langchain_community.tools import DuckDuckGoSearchRun, DuckDuckGoSearchResults
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from crewai_tools import tool, SeleniumScrapingTool, ScrapeWebsiteTool
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# Initialize the Groq large language model
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groq_llm_70b = ChatGroq(temperature=0, groq_api_key=groq_api_key, model_name="llama3-70b-8192")
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cohere_llm = ChatCohere(
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temperature=0.2,
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cohere_api_key=cohere_api_key,
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model="command-r-plus"
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)
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# Define Agents with Groq LLM
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researcher = Agent(
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role='Researcher',
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goal='Collect detailed information on {topic}',
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tools=[search_results, web_scrapper],
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llm=cohere_llm, # Assigning the Groq LLM here
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backstory=(
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"As a diligent researcher, you explore the depths of the internet to "
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"unearth crucial information and insights on the assigned topics. "
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editor = Agent(
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role='Editor',
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goal='Compile and refine the information into a comprehensive report on {topic}',
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llm=cohere_llm, # Assigning the Groq LLM here
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backstory=(
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"With a keen eye for detail and a strong command of language, you transform "
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"raw data into polished, insightful reports that are both informative and engaging. "
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