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This commit is contained in:
Madhu 2025-01-04 23:58:25 +05:30
parent d3cfeaab2e
commit 340aa821fb
1 changed files with 19 additions and 12 deletions
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31
ai_agent_tutorials/ai_data_visualisation_agent/test.py
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@ -7,6 +7,9 @@ from together import Together
from e2b_code_interpreter import Sandbox from e2b_code_interpreter import Sandbox
from typing import Optional, List, Any from typing import Optional, List, Any
import tempfile import tempfile
import base64
from io import BytesIO
from PIL import Image
# Load environment variables # Load environment variables
load_dotenv() load_dotenv()
@ -86,7 +89,7 @@ def chat_with_llm(e2b_code_interpreter, user_message):
user_message: User's query string user_message: User's query string
Returns: Returns:
List of results from code execution Base64-encoded image data or None if no image is generated
""" """
print(f"\n{'='*50}\nUser message: {user_message}\n{'='*50}") print(f"\n{'='*50}\nUser message: {user_message}\n{'='*50}")
@ -119,10 +122,15 @@ Important: Always use '/data.csv' as the path when reading the dataset.
if python_code: if python_code:
# Execute the code in the sandbox # Execute the code in the sandbox
code_interpreter_results = code_interpret(e2b_code_interpreter, python_code) code_interpreter_results = code_interpret(e2b_code_interpreter, python_code)
return code_interpreter_results
# Return the base64-encoded image data
if code_interpreter_results and hasattr(code_interpreter_results[0], "png"):
return code_interpreter_results[0].png
else:
return None
else: else:
print(f"Failed to match any Python code in model's response: {response_message}") print(f"Failed to match any Python code in model's response: {response_message}")
return [] return None
# Function to upload a dataset to the E2B Sandbox # Function to upload a dataset to the E2B Sandbox
def upload_dataset(code_interpreter: Sandbox, uploaded_file: Any) -> str: def upload_dataset(code_interpreter: Sandbox, uploaded_file: Any) -> str:
@ -177,19 +185,18 @@ def main():
# Get and execute the visualization code # Get and execute the visualization code
with st.spinner("Generating visualization..."): with st.spinner("Generating visualization..."):
code_results = chat_with_llm(code_interpreter, user_query) image_data = chat_with_llm(code_interpreter, user_query)
# Display results # Display results
if code_results: if image_data:
first_result = code_results[0] # Decode the base64-encoded image data
image_bytes = base64.b64decode(image_data)
image = Image.open(BytesIO(image_bytes))
# If there's an image output # Display the image in Streamlit
if hasattr(first_result, "png"): st.image(image, caption="Generated Visualization")
st.image(first_result.png, caption="Generated Visualization")
else: else:
st.write("Results:", first_result) st.error("No visualization generated")
else:
st.error("No results generated")
except Exception as e: except Exception as e:
st.error(f"An error occurred: {e}") st.error(f"An error occurred: {e}")