LLM-Analysis-TDS-Project-2 / tools /encode_image_to_base64.py
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from shared_store import BASE64_STORE
import os
import base64, uuid
from langchain_core.tools import tool
@tool
def encode_image_to_base64(image_path: str) -> str:
"""
Encode an image file into a full Base64 string without exposing the binary
output to the LLM.
This tool reads an image from the given file path, converts it into a
Base64-encoded string, and stores the *full* Base64 value in a shared
in-memory dictionary (BASE64_STORE). Instead of returning the large Base64
blob—which can overwhelm conversation memory, break routing, or cause LLM
tool-call loops—the tool returns a lightweight placeholder of the form:
BASE64_KEY:<uuid>
The LLM uses this placeholder as the 'answer' during reasoning. Later,
the post_request tool detects the placeholder and replaces it with the
original Base64 string from BASE64_STORE before submitting it to the server.
This design prevents:
- Extremely large Base64 strings from entering the conversation history
- Agent freezing or malformed function calls
- Token overflow crashes
- Misrouting caused by Base64 being misinterpreted as HTML or a tool call
Parameters
----------
image_path : str
The file system path of the image to encode. Can be PNG, JPG, GIF,
WEBP, or any binary image format.
Returns
-------
str
A small placeholder token referencing the full Base64 string stored
in memory, e.g. "BASE64_KEY:4f9d93ea-7e94-4edc-962c-e6f7d358c2a3".
"""
try:
image_path = os.path.join("LLMFiles", image_path)
with open(image_path, "rb") as f:
raw = f.read()
encoded = base64.b64encode(raw).decode("utf-8")
key = str(uuid.uuid4())
BASE64_STORE[key] = encoded
return f"BASE64_KEY:{key}"
except Exception as e:
return f"Error occurred: {e}"