Create Analyser.py

Analyser.py

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+pip install streamlit crewai crewai-tools embedchain gemini-ai serper
+
+import os
+import streamlit as st
+from crewai import Agent, Task, Crew
+from crewai_tools import SerperDevTool
+from embedchain.embedder import GeminiEmbedder
+from embedchain import App
+
+# Set API Keys
+gemini_api_key = "AIzaSyAC_i-I9uCP2UP14H89uigWP7MDM2xQno8"
+serper_api_key = "b86545fdabc35dcb13fd8cc0a9b88c3a17b6dc89"
+os.environ["GEMINIAI_API_KEY"] = gemini_api_key
+os.environ["SERPER_API_KEY"] = serper_api_key
+
+# Initialize Gemini Embedding Model
+gemini_embedder = GeminiEmbedder(api_key=gemini_api_key)
+
+# Initialize Serper Tool
+search_tool = SerperDevTool(api_key=serper_api_key)
+
+# Initialize EmbedChain App (Optional for Future Use)
+embedchain_app = App(embedding_model=gemini_embedder)
+
+# Create Agents
+researcher = Agent(
+    role="Market Researcher",
+    goal="Gather detailed information about G10X and its competitors.",
+    tools=[search_tool],
+    verbose=True,
+    backstory="You specialize in market research and can extract detailed company insights."
+)
+
+analyzer = Agent(
+    role="Data Analyzer",
+    goal="Analyze the strengths, weaknesses, and market positioning of G10X.",
+    tools=[search_tool],
+    verbose=True,
+    backstory="Your expertise lies in identifying business trends and company insights."
+)
+
+comparator = Agent(
+    role="Comparator",
+    goal="Compare G10X with its competitors and provide actionable suggestions.",
+    tools=[search_tool],
+    verbose=True,
+    backstory="You excel at comparing companies and offering improvement suggestions."
+)
+
+# Define Tasks
+research_task = Task(
+    description="Conduct research on G10X and its competitors.",
+    expected_output="Detailed research document with company insights.",
+    agent=researcher,
+    async_execution=True
+)
+
+analysis_task = Task(
+    description="Analyze G10X's business performance, strengths, and weaknesses.",
+    expected_output="Comprehensive analysis of G10X.",
+    agent=analyzer,
+    async_execution=True
+)
+
+comparison_task = Task(
+    description="Compare G10X with its competitors and provide improvement suggestions.",
+    expected_output="Comparison document with actionable recommendations for G10X.",
+    agent=comparator,
+    async_execution=True
+)
+
+# Final Analysis Article Task
+final_article_task = Task(
+    description="Combine insights from all agents to generate a final analysis article for G10X.",
+    expected_output="A well-structured analysis article about G10X.",
+    context=[research_task, analysis_task, comparison_task],
+    agent=None  # This will use all agents' outputs
+)
+
+# Crew Setup
+company_analysis_crew = Crew(
+    agents=[researcher, analyzer, comparator],
+    tasks=[research_task, analysis_task, comparison_task, final_article_task],
+    verbose=True
+)
+
+# Streamlit Interface
+st.title("G10X Company Analyzer")
+
+# Input Section
+st.header("Enter Details")
+company_name = st.text_input("Company Name", "G10X")
+competitor_list = st.text_area(
+    "List of Competitors (comma-separated)",
+    "Competitor A, Competitor B, Competitor C"
+)
+
+if st.button("Start Analysis"):
+    st.write("Running Analysis... Please wait.")
+    
+    # Kick off the Crew Process
+    inputs = {"company_name": company_name, "competitors": competitor_list.split(",")}
+    results = company_analysis_crew.kickoff(inputs=inputs)
+
+    # Display Results
+    st.success("Analysis Completed!")
+    
+    if "final_article.md" in results:
+        st.header("Final Analysis Article")
+        st.markdown(results["final_article.md"], unsafe_allow_html=True)