in cloud-run-gemini-chat/Application/CloudRun/Python-Django/geminiapp/gcp_gemini.py [0:0]
def ask_gemini(api_key, model, question):
''' Interact with Google Gemini '''
#---------------------------------------------------------------------
# Google Gemini REST API Documentation
# https://ai.google.dev/api/rest
#---------------------------------------------------------------------
#---------------------------------------------------------------------
# Validate api_key
#---------------------------------------------------------------------
if api_key is None or len(api_key) == 0:
return "Internal Error: Missing API Key"
#---------------------------------------------------------------------
# Verify question parameter
#
# TODO: Validate question
# Only the string length for zero is checked at this time.
# What is the maximum length supported. Gemini specifies token
# which is about 4 characters.
# https://ai.google.dev/models/gemini
# Gemini 1.0 Pro input token limit is 30,720.
# Gemini 1.5 Pro input token limit is 1,048,576.
#---------------------------------------------------------------------
if question is None or len(question) == 0:
return "Please enter a question"
#---------------------------------------------------------------------
# Get the Gemini Model to use
#---------------------------------------------------------------------
url = get_gemini_model_endpoint(model)
headers = {
"x-goog-api-key": api_key,
"Content-type": "application/json"
}
#---------------------------------------------------------------------
# Format the JSON request
#---------------------------------------------------------------------
data = {
"contents": [
{
"parts":[
{
"text": question
}
]
}
]
}
#---------------------------------------------------------------------
# Issue the HTTP POST request
#---------------------------------------------------------------------
try:
# print(json.dumps(data, indent=4)) # debug
response = requests.post(url, headers=headers, json=data, timeout=120)
# print(response.status_code) # debug
# print(response.content) # debug
if response.status_code == 404:
print(response.content) # print error message
msg = "**Error: The Gemini model is not available for your project or does not exist**"
return markdown.markdown(msg)
if response.status_code >= 400:
print(response.content) # print error message
msg = "**Error: Request to Gemini failed**"
return markdown.markdown(msg)
#---------------------------------------------------------------------
# Process the output
# TODO: This needs better handling.
# Gemini returns various formats that are not yet documented.
# An important item is to process the key "finishReason".
# Normal requests return "STOP", but I have seen "SAFETY"
# which means the request was rejected. See the link:
# https://ai.google.dev/api/rest/v1/GenerateContentResponse#FinishReason
#
# https://ai.google.dev/api/rest/v1/Content
#---------------------------------------------------------------------
resp = response.json()
# print(json.dumps(resp, indent=4)) # debug
reason = resp["candidates"][0]["finishReason"]
# print("Reason:", reason) # debug
if reason == "STOP":
# Good status
text = get_gemini_response_text(resp)
elif reason == "MAX_TOKENS":
# Error
text = "**Gemini Error: The maximum number of tokens as specified in the request was reached.**"
elif reason == "RECITATION":
# Error
text = "**Gemini Error: The candidate content was flagged for recitation reasons.**"
elif reason == "SAFETY":
# Error
text = "**Gemini Error: The candidate content was flagged for safety reasons.**"
else:
# Error
text = f"**Gemini Error: Gemini refused the question for {reason}**"
#---------------------------------------------------------------------
# Gemini returns Markdown, convert to HTML
#---------------------------------------------------------------------
html = markdown.markdown(text, extensions=['tables'])
return html.replace('<table>', '<table class="table table-striped">')
except Exception as e:
print(e) # print error message
return None