Added csv_agent files

.env

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+COHERE_API_KEY=p9Qnpw98wKgjWBBgiCW3JWBmskTkd6AL3kkutDYA

Sample_Data.csv

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+usecase,run,score,temperature,tokens,latency
+extract_names,A,0.5,0.3,103,1.12
+draft_email,A,0.6,0.3,252,2.5
+summarize_article,A,0.8,0.3,350,4.2
+extract_names,B,0.2,0.3,101,2.85
+draft_email,B,0.4,0.3,230,3.2
+summarize_article,B,0.6,0.3,370,4.2
+extract_names,C,0.7,0.3,101,2.22
+draft_email,C,0.5,0.3,221,2.5
+summarize_article,C,0.1,0.3,361,3.9
+extract_names,D,0.7,0.5,120,3.2
+draft_email,D,0.8,0.5,280,3.4
+summarize_article,D,0.9,0.5,342,4.8

csv_agent_with_chart.py

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+import os
+import re
+import tempfile
+import pandas as pd
+import gradio as gr
+from dotenv import load_dotenv
+from PIL import Image
+from langchain_cohere import ChatCohere, create_csv_agent
+
+# Load environment variables
+load_dotenv()
+COHERE_API_KEY = os.getenv("COHERE_API_KEY")
+os.environ['COHERE_API_KEY'] = COHERE_API_KEY
+
+# Initialize the Cohere LLM
+llm = ChatCohere(cohere_api_key=COHERE_API_KEY,
+                 model="command-r-plus-08-2024",
+                 temperature=0)
+
+# Placeholders
+agent_executor = None
+uploaded_df = None
+
+# Upload CSV
+def upload_csv(file):
+    global agent_executor, uploaded_df
+    try:
+        uploaded_df = pd.read_csv(file.name)
+        temp_csv_path = os.path.join(tempfile.gettempdir(), "temp.csv")
+        uploaded_df.to_csv(temp_csv_path, index=False)
+        agent_executor = create_csv_agent(llm, temp_csv_path)
+        return "✅ CSV uploaded successfully!", uploaded_df.head(), gr.update(visible=False)
+    except Exception as e:
+        return f"❌ Error uploading CSV: {e}", None, gr.update(visible=False)
+
+# Handle User Questions
+def ask_question(question):
+    global agent_executor
+
+    if not agent_executor:
+        return "❗ Please upload a CSV file first.", gr.update(visible=False)
+
+    try:
+        # Agent Response
+        response = agent_executor.invoke({"input": question})
+        response_message = response.get("output")
+
+        # Detect Markdown-style image reference
+        image_match = re.search(r'!\[.*?\]\("(?P<filename>[^"]+\.png)"\)', response_message)
+        if image_match:
+            image_path = image_match.group("filename")
+
+            # Remove the Markdown image reference from the response
+            response_message = re.sub(r'!\[.*?\]\("[^"]+\.png"\)', '', response_message).strip()
+
+            # Check if the image exists and load it
+            if os.path.exists(image_path):
+                return response_message, gr.update(value=image_path, visible=True)
+
+        return response_message, gr.update(visible=False)
+
+    except Exception as e:
+        return f"⚠️ Failed to process the question: {e}", gr.update(visible=False)
+
+# Reset Agent
+def reset_agent():
+    global agent_executor, uploaded_df
+    agent_executor = None
+    uploaded_df = None
+    return gr.update(value="🔄 Agent reset. You can upload a new CSV."), None, gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)
+
+# Gradio Interface
+with gr.Blocks(css="""
+    .gr-input, .gr-output, textarea, .gr-dataframe, .gr-image {
+        background-color: #e6f7ff !important;
+        border: 2px solid #007acc !important;
+        padding: 10px !important;
+        border-radius: 8px !important;
+    }
+    label, .gr-box label {
+        color: #003366 !important;
+        font-weight: bold !important;
+        font-size: 14px !important;
+    }
+""") as demo:
+    gr.Markdown("# 📊 CSV Agent with Cohere LLM \n ### Nader Afshar")
+
+    # File Upload Section
+    with gr.Row():
+        file_input = gr.File(label="Upload CSV", file_types=['.csv'])
+        upload_button = gr.Button("Upload")
+
+    upload_status = gr.Textbox(label="Upload Status", interactive=False)
+    df_head_output = gr.Dataframe(label="CSV Preview (Head)", interactive=False)
+
+    # Question Section
+    question_input = gr.Textbox(label="Ask a Question", placeholder="Type your question here...")
+    submit_button = gr.Button("Submit Question")
+
+    # Output Section
+    response_output = gr.Textbox(label="Response", interactive=False)
+    image_output = gr.Image(label="Generated Chart", visible=False)
+
+    # Reset Button
+    reset_button = gr.Button("Reset Agent")
+
+    # Event Handlers
+    upload_button.click(upload_csv, inputs=file_input, outputs=[upload_status, df_head_output, image_output])
+    submit_button.click(ask_question, inputs=question_input, outputs=[response_output, image_output])
+    reset_button.click(reset_agent, outputs=[upload_status, df_head_output, image_output, file_input, upload_button])
+
+# Launch the Gradio App
+demo.launch()

requirements.txt

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+torch
+pandas==2.2.2                  # For CSV file handling
+python-dotenv==1.0.1           # For loading environment variables
+langchain==0.3.11              # Core LangChain library
+langchain-experimental==0.3.3  # For experimental LangChain features
+cohere==5.13.3                 # Cohere LLM
+langchain-cohere==0.3.3        # Cohere extensions for langchain
+python-multipart==0.0.6        # For file upload handling in FastAPI