Think Ai main code

.gitignore

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+# Environment files
+.env
+
+# Virtual environments
+venv/
+env/
+
+# Compiled files
+__pycache__/
+*.pyc
+*.pyo
+
+# Logs
+*.log
+
+# OS-specific
+.DS_Store
+Thumbs.db
+desktop.ini
+
+# IDE/Editor-specific
+.vscode/
+.idea/
+*.iml
+
+# Build and distribution
+/build/
+/dist/
+/*.egg-info
+
+# Temporary files
+*.bak
+*.swp
+*~
+
+# Dependency files
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Test coverage
+.coverage
+coverage/
+*.cover
+*.coverage.*
+
+# Custom project files
+secrets.json
+config.local.json

app.py

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+import os
+from dotenv import load_dotenv
+import time
+import streamlit as st
+from langchain_groq import ChatGroq
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+
+load_dotenv()
+groq_api_key= os.getenv("GROQ_API_KEY")
+
+p1 = os.getenv("pmpt1")
+p2 = os.getenv("pmpt2")
+p3 = os.getenv("pmpt3")
+p4 = os.getenv("pmpt4")
+p5 = os.getenv("pmpt5")
+p6 = os.getenv("pmpt6")
+p7 = os.getenv("pmpt7")
+p8 = os.getenv("pmpt8")
+p9 = os.getenv("pmpt9")
+p10 = os.getenv("pmpt10")
+p11 = os.getenv("pmpt11")
+p12 = os.getenv("pmpt12")
+p13 = os.getenv("pmpt13")
+p14 = os.getenv("pmpt14")
+p15 = os.getenv("pmpt15")
+p16 = os.getenv("pmpt16")
+p17 = os.getenv("pmpt17")
+p18 = os.getenv("pmpt18")
+p19 = os.getenv("pmpt19")
+p20 = os.getenv("pmpt20")
+p21 = os.getenv("pmpt21")
+p22 = os.getenv("pmpt22")
+p23 = os.getenv("pmpt23")
+p24 = os.getenv("pmpt24")
+p25 = os.getenv("pmpt25")
+
+prompt1 = ChatPromptTemplate.from_messages([("system",p1),("user", "Question:{query1}")])
+prompt2 = ChatPromptTemplate.from_messages([("system",p2),("user", "Question:{query1}")])
+prompt3 = ChatPromptTemplate.from_messages([("system",p3),("user", "Question:{query1}")])
+prompt4 = ChatPromptTemplate.from_messages([("system",p4),("user", "Question:{query1}")])
+prompt5 = ChatPromptTemplate.from_messages([("system",p5),("user", "Question:{query1}")])
+prompt6 = ChatPromptTemplate.from_messages([("system",p6), ("user", "Question:{query1}")])
+prompt7 = ChatPromptTemplate.from_messages([("system",p7), ("user", "Question:{query1}")])
+prompt8 = ChatPromptTemplate.from_messages([("system",p8), ("user", "Question:{query1}")])
+prompt9 = ChatPromptTemplate.from_messages([("system",p9), ("user", "Question:{query1}")])
+prompt10 = ChatPromptTemplate.from_messages([("system", p10), ("user", "Question:{query1}")])
+prompt11 = ChatPromptTemplate.from_messages([("system", p11), ("user", "Question:{query1}")])
+prompt12 = ChatPromptTemplate.from_messages([("system", p12), ("user", "Question:{query1}")])
+prompt13 = ChatPromptTemplate.from_messages([("system", p13), ("user", "Question:{query1}")])
+prompt14 = ChatPromptTemplate.from_messages([("system", p14), ("user", "Question:{query1}")])
+prompt15 = ChatPromptTemplate.from_messages([("system", p15), ("user", "Question:{query1}")])
+prompt16 = ChatPromptTemplate.from_messages([("system", p16), ("user", "Question:{query1}")])
+prompt17 = ChatPromptTemplate.from_messages([("system", p17), ("user", "Question:{query1}")])
+prompt18 = ChatPromptTemplate.from_messages([("system", p18), ("user", "Question:{query1}")])
+prompt19 = ChatPromptTemplate.from_messages([("system", p19), ("user", "Question:{query1}")])
+prompt20 = ChatPromptTemplate.from_messages([("system", p20), ("user", "Question:{query1}")])
+prompt21 = ChatPromptTemplate.from_messages([("system", p21), ("user", "Question:{query1}")])
+prompt22 = ChatPromptTemplate.from_messages([("system", p22), ("user", "Question:{query1}")])
+prompt23 = ChatPromptTemplate.from_messages([("system", p23), ("user", "Question:{query1}")])
+prompt24 = ChatPromptTemplate.from_messages([("system", p24), ("user", "Question:{query1}")])
+prompt25 = ChatPromptTemplate.from_messages([("system", p25), ("user", "Question:{query1}")])
+
+
+
+llm1 = ChatGroq(model_name="llama3-70b-8192", groq_api_key=groq_api_key)
+output_parser =  StrOutputParser()
+
+chain1 = prompt1| llm1| output_parser
+chain2 = prompt2| llm1| output_parser
+chain3 = prompt3| llm1| output_parser
+chain4 = prompt4| llm1| output_parser
+chain5 = prompt5| llm1| output_parser
+chain6 = prompt6| llm1| output_parser
+chain7 = prompt7| llm1| output_parser
+chain8 = prompt8| llm1| output_parser
+chain9 = prompt9| llm1| output_parser
+chain10 = prompt10| llm1| output_parser
+chain11 = prompt11| llm1| output_parser
+chain12 = prompt12| llm1| output_parser
+chain13 = prompt13| llm1| output_parser
+chain14 = prompt14| llm1| output_parser
+chain15 = prompt15| llm1| output_parser
+chain16 = prompt16| llm1| output_parser
+chain17 = prompt17| llm1| output_parser
+chain18 = prompt18| llm1| output_parser
+chain19 = prompt19| llm1| output_parser
+chain20 = prompt20| llm1| output_parser
+chain21 = prompt21| llm1| output_parser
+chain22 = prompt22| llm1| output_parser
+chain23 = prompt23| llm1| output_parser
+chain24 = prompt24| llm1| output_parser
+chain25 = prompt25| llm1| output_parser
+
+
+
+def  generate_ai_content(thinking_type, usr_ip):
+    if thinking_type == "Analytical Thinking": return chain1.invoke({"query1": usr_ip})
+    elif headline == "Creative Thinking":return chain2.invoke({"query1": usr_ip})
+    elif headline == "Critical Thinking": return chain3.invoke({"query1": usr_ip})
+    elif headline == "Logical Thinking": return chain4.invoke({"query1": usr_ip})
+    elif headline == "Lateral Thinking": return chain5.invoke({"query1": usr_ip})
+    elif headline == "Divergent Thinking": return chain6.invoke({"query1": usr_ip})
+    elif headline == "Convergent Thinking": return chain7.invoke({"query1": usr_ip})
+    elif headline == "Empathetic Thinking": return chain8.invoke({"query1": usr_ip})
+    elif headline == "Systems Thinking": return chain9.invoke({"query1": usr_ip})
+    elif headline == "Intuitive Thinking": return chain10.invoke({"query1": usr_ip})
+    elif headline == "Strategic Thinking": return chain11.invoke({"query1": usr_ip})
+    elif headline == "Collaborative Thinking": return chain12.invoke({"query1": usr_ip})
+    elif headline == "Reverse Thinking": return chain13.invoke({"query1": usr_ip})
+    elif headline == "Practical Thinking": return chain14.invoke({"query1": usr_ip})
+    elif headline == "Mind Mapping": return chain15.invoke({"query1": usr_ip})
+    elif headline == "Trial-and-Error Thinking": return chain16.invoke({"query1": usr_ip})
+    elif headline == "Root Cause Analysis": return chain17.invoke({"query1": usr_ip})
+    elif headline == "Optimistic Thinking": return chain18.invoke({"query1": usr_ip})
+    elif headline == "Pessimistic Thinking": return chain19.invoke({"query1": usr_ip})
+    elif headline == "Abstract Thinking": return chain20.invoke({"query1": usr_ip})
+    elif headline == "Habitual Thinking": return chain21.invoke({"query1": usr_ip})
+    elif headline == "Scenario Thinking": return chain22.invoke({"query1": usr_ip})
+    elif headline == "Mathematical Thinking": return chain23.invoke({"query1": usr_ip})
+    elif headline == "Ethical Thinking": return chain24.invoke({"query1": usr_ip})
+    elif headline == "Design Thinking": return chain25.invoke({"query1": usr_ip})
+        
+
+st.title("Think AI")
+st.text("Think AI is designed to explore all the posible ways to approch a problem to find the perfect solution.")
+st.write("### Ask anything")
+col1, col2 = st.columns([4, 1])
+with col1:
+    user_input = st.text_area("Enter your text:", key="input_text", height=68)
+with col2:
+    submit = st.button("Submit")
+
+
+if submit and user_input.strip():
+    counter = 0
+    st.write("---")
+    st.write("### Generated Content")
+    headlines = ["Analytical Thinking", "Creative Thinking", "Critical Thinking","Logical Thinking", 
+                   "Lateral Thinking","Divergent Thinking", "Convergent Thinking", "Empathetic Thinking", 
+                   "Systems Thinking", "Intuitive Thinking","Strategic Thinking", "Collaborative Thinking", 
+                   "Reverse Thinking", "Practical Thinking", "Mind Mapping","Trial-and-Error Thinking", 
+                   "Root Cause Analysis", "Optimistic Thinking", "Pessimistic Thinking", "Abstract Thinking",
+                   "Habitual Thinking", "Scenario Thinking", "Mathematical Thinking", "Ethical Thinking", 
+                   "Design Thinking", 
+                   ]
+    for headline in headlines:
+
+        if counter >=5:
+            time.sleep(3)
+            counter =0 
+        
+        st.write(f"#### {headline}")
+
+        ai_content = generate_ai_content(headline, user_input)
+        st.markdown(ai_content,unsafe_allow_html=True)
+        # st.text_area(f" ", value=ai,key=headline)
+        counter+=1
+
+        st.markdown(
+            """
+            <hr style="border: none; border-top: 3px double #000; margin-top: 20px; margin-bottom: 20px;">
+            """,
+            unsafe_allow_html=True
+        )
+
+# End the box container
+st.markdown('</div>', unsafe_allow_html=True)