Spaces:
Sleeping
Sleeping
update app.py to have more models
Browse files
app.py
CHANGED
@@ -1,6 +1,6 @@
|
|
1 |
import logging
|
2 |
import json
|
3 |
-
from transformers import pipeline
|
4 |
import gradio as gr
|
5 |
|
6 |
# Configure logging
|
@@ -8,19 +8,46 @@ logging.basicConfig(level=logging.DEBUG,
|
|
8 |
format='%(asctime)s - %(levelname)s - %(message)s')
|
9 |
logger = logging.getLogger(__name__)
|
10 |
|
11 |
-
#
|
12 |
-
|
13 |
-
|
14 |
-
|
15 |
-
|
16 |
-
|
17 |
-
|
18 |
-
|
19 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
20 |
|
21 |
def generate_test_cases(method, url, headers, payload=""):
|
22 |
try:
|
23 |
-
#
|
24 |
logger.info(f"Generating test cases for:")
|
25 |
logger.info(f"Method: {method}")
|
26 |
logger.info(f"URL: {url}")
|
@@ -29,48 +56,72 @@ def generate_test_cases(method, url, headers, payload=""):
|
|
29 |
|
30 |
# Validate inputs
|
31 |
if not method or not url:
|
32 |
-
logger.warning("Method or URL is missing")
|
33 |
return "Error: Method and URL are required"
|
34 |
|
35 |
-
#
|
36 |
try:
|
37 |
headers_dict = json.loads(headers) if headers else {}
|
38 |
payload_dict = json.loads(payload) if payload else {}
|
39 |
except json.JSONDecodeError as json_error:
|
40 |
-
logger.error(f"JSON parsing error: {json_error}")
|
41 |
return f"JSON Parsing Error: {json_error}"
|
42 |
|
43 |
-
#
|
44 |
prompt = f"""
|
45 |
-
Generate
|
46 |
-
|
47 |
-
|
48 |
-
|
49 |
-
|
50 |
-
|
51 |
-
|
52 |
-
|
53 |
-
|
54 |
-
|
55 |
-
|
56 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
57 |
"""
|
58 |
|
59 |
# Check if generator is available
|
60 |
if generator is None:
|
61 |
-
|
62 |
-
return "Error: Model generator not initialized"
|
63 |
|
64 |
# Generate test cases
|
65 |
-
logger.info("Attempting to generate test cases")
|
66 |
try:
|
67 |
-
response = generator(prompt
|
68 |
generated_text = response[0]['generated_text']
|
69 |
|
70 |
logger.info("Test cases generated successfully")
|
71 |
logger.debug(f"Generated Text: {generated_text}")
|
72 |
|
73 |
return generated_text
|
|
|
74 |
except Exception as generation_error:
|
75 |
logger.error(f"Test case generation error: {generation_error}")
|
76 |
return f"Error generating test cases: {generation_error}"
|
@@ -79,7 +130,7 @@ def generate_test_cases(method, url, headers, payload=""):
|
|
79 |
logger.error(f"Unexpected error: {overall_error}")
|
80 |
return f"Unexpected error: {overall_error}"
|
81 |
|
82 |
-
#
|
83 |
iface = gr.Interface(
|
84 |
fn=generate_test_cases,
|
85 |
inputs=[
|
@@ -89,8 +140,8 @@ iface = gr.Interface(
|
|
89 |
gr.Textbox(label="Payload (JSON format)", placeholder='e.g., {"key": "value"}'),
|
90 |
],
|
91 |
outputs="text",
|
92 |
-
title="API Test Case Generator",
|
93 |
-
description="
|
94 |
)
|
95 |
|
96 |
# Main execution
|
|
|
1 |
import logging
|
2 |
import json
|
3 |
+
from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
|
4 |
import gradio as gr
|
5 |
|
6 |
# Configure logging
|
|
|
8 |
format='%(asctime)s - %(levelname)s - %(message)s')
|
9 |
logger = logging.getLogger(__name__)
|
10 |
|
11 |
+
# Try multiple models in succession
|
12 |
+
MODELS_TO_TRY = [
|
13 |
+
"google/flan-t5-large", # More capable than base
|
14 |
+
"google/flan-t5-xl", # Even more capable
|
15 |
+
"facebook/bart-large-cnn", # Alternative model
|
16 |
+
"t5-large" # Fallback T5 model
|
17 |
+
]
|
18 |
+
|
19 |
+
def load_model():
|
20 |
+
for model_name in MODELS_TO_TRY:
|
21 |
+
try:
|
22 |
+
logger.info(f"Attempting to load model: {model_name}")
|
23 |
+
|
24 |
+
# Load model and tokenizer
|
25 |
+
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
|
26 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
27 |
+
|
28 |
+
# Create pipeline with specific model and tokenizer
|
29 |
+
generator = pipeline(
|
30 |
+
"text2text-generation",
|
31 |
+
model=model,
|
32 |
+
tokenizer=tokenizer,
|
33 |
+
max_length=500,
|
34 |
+
num_return_sequences=1
|
35 |
+
)
|
36 |
+
|
37 |
+
logger.info(f"Successfully loaded model: {model_name}")
|
38 |
+
return generator
|
39 |
+
except Exception as model_load_error:
|
40 |
+
logger.error(f"Failed to load model {model_name}: {model_load_error}")
|
41 |
+
|
42 |
+
logger.error("Failed to load any model")
|
43 |
+
return None
|
44 |
+
|
45 |
+
# Load model at startup
|
46 |
+
generator = load_model()
|
47 |
|
48 |
def generate_test_cases(method, url, headers, payload=""):
|
49 |
try:
|
50 |
+
# Detailed logging
|
51 |
logger.info(f"Generating test cases for:")
|
52 |
logger.info(f"Method: {method}")
|
53 |
logger.info(f"URL: {url}")
|
|
|
56 |
|
57 |
# Validate inputs
|
58 |
if not method or not url:
|
|
|
59 |
return "Error: Method and URL are required"
|
60 |
|
61 |
+
# Safely parse JSON inputs
|
62 |
try:
|
63 |
headers_dict = json.loads(headers) if headers else {}
|
64 |
payload_dict = json.loads(payload) if payload else {}
|
65 |
except json.JSONDecodeError as json_error:
|
|
|
66 |
return f"JSON Parsing Error: {json_error}"
|
67 |
|
68 |
+
# Comprehensive prompt for test case generation
|
69 |
prompt = f"""
|
70 |
+
Generate detailed API test cases with the following specifications:
|
71 |
+
|
72 |
+
Test Case Scenario: API Endpoint Testing
|
73 |
+
|
74 |
+
HTTP Method: {method}
|
75 |
+
API Endpoint: {url}
|
76 |
+
Request Headers: {json.dumps(headers_dict)}
|
77 |
+
Request Payload: {json.dumps(payload_dict)}
|
78 |
+
|
79 |
+
Test Case Requirements:
|
80 |
+
1. Happy Path Scenarios:
|
81 |
+
- Successful request with valid inputs
|
82 |
+
- Verify correct response status code
|
83 |
+
- Validate response structure and content
|
84 |
+
|
85 |
+
2. Negative Test Scenarios:
|
86 |
+
- Invalid authentication
|
87 |
+
- Malformed request payload
|
88 |
+
- Missing required headers
|
89 |
+
- Out-of-range parameter values
|
90 |
+
|
91 |
+
3. Edge Case Considerations:
|
92 |
+
- Maximum/minimum input limits
|
93 |
+
- Special character handling
|
94 |
+
- Unicode and internationalization testing
|
95 |
+
|
96 |
+
4. Performance and Security Checks:
|
97 |
+
- Response time validation
|
98 |
+
- Payload size limits
|
99 |
+
- Basic security vulnerability checks
|
100 |
+
|
101 |
+
Output Format:
|
102 |
+
For each test case, provide:
|
103 |
+
- Test Case ID
|
104 |
+
- Description
|
105 |
+
- Preconditions
|
106 |
+
- Input Data
|
107 |
+
- Expected Result
|
108 |
+
- Actual Result Verification Steps
|
109 |
"""
|
110 |
|
111 |
# Check if generator is available
|
112 |
if generator is None:
|
113 |
+
return "Error: No suitable model available for test case generation"
|
|
|
114 |
|
115 |
# Generate test cases
|
|
|
116 |
try:
|
117 |
+
response = generator(prompt)
|
118 |
generated_text = response[0]['generated_text']
|
119 |
|
120 |
logger.info("Test cases generated successfully")
|
121 |
logger.debug(f"Generated Text: {generated_text}")
|
122 |
|
123 |
return generated_text
|
124 |
+
|
125 |
except Exception as generation_error:
|
126 |
logger.error(f"Test case generation error: {generation_error}")
|
127 |
return f"Error generating test cases: {generation_error}"
|
|
|
130 |
logger.error(f"Unexpected error: {overall_error}")
|
131 |
return f"Unexpected error: {overall_error}"
|
132 |
|
133 |
+
# Gradio Interface
|
134 |
iface = gr.Interface(
|
135 |
fn=generate_test_cases,
|
136 |
inputs=[
|
|
|
140 |
gr.Textbox(label="Payload (JSON format)", placeholder='e.g., {"key": "value"}'),
|
141 |
],
|
142 |
outputs="text",
|
143 |
+
title="Comprehensive API Test Case Generator",
|
144 |
+
description="Advanced test case generation using AI-powered language models"
|
145 |
)
|
146 |
|
147 |
# Main execution
|