Spaces:
Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
@@ -1,4 +1,5 @@
|
|
1 |
import os
|
|
|
2 |
import requests
|
3 |
import pandas as pd
|
4 |
import gradio as gr
|
@@ -8,37 +9,33 @@ from langchain.docstore.document import Document
|
|
8 |
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
9 |
from langchain_community.retrievers import BM25Retriever
|
10 |
|
11 |
-
from smolagents import Tool, CodeAgent
|
12 |
from huggingface_hub.inference_api import InferenceApi
|
|
|
13 |
|
14 |
-
|
15 |
-
# Wrapper class to adapt HuggingFace Inference API to have .generate()
|
16 |
class HuggingFaceInferenceWrapper:
|
17 |
def __init__(self, inference_api):
|
18 |
self.inference_api = inference_api
|
19 |
|
20 |
def generate(self, prompt: str, **kwargs) -> str:
|
21 |
-
|
22 |
-
|
23 |
-
if isinstance(
|
24 |
-
return
|
25 |
-
elif isinstance(
|
26 |
-
return
|
27 |
else:
|
28 |
-
|
29 |
|
30 |
|
|
|
31 |
hf_token = os.getenv("HUGGINGFACE_API_KEY")
|
32 |
-
|
|
|
33 |
|
34 |
-
|
35 |
-
|
36 |
-
print("Set HUGGINGFACE_API_KEY in env.")
|
37 |
-
else:
|
38 |
-
print("No HUGGINGFACE_API_KEY found in env.")
|
39 |
|
40 |
-
print("HUGGINGFACE_API_KEY in env:", "HUGGINGFACE_API_KEY" in os.environ)
|
41 |
-
print("HUGGINGFACE_API_KEY value (masked):", os.environ.get("HUGGINGFACE_API_KEY", "")[:5] + "...")
|
42 |
|
43 |
def run_and_submit_all(profile: gr.OAuthProfile | None):
|
44 |
space_id = os.getenv("SPACE_ID")
|
@@ -102,17 +99,13 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
|
|
102 |
|
103 |
retriever_tool = RetrieverTool(docs_processed)
|
104 |
|
105 |
-
#
|
106 |
-
inference_api = InferenceApi(repo_id="Qwen/Qwen2.5-VL-7B-Instruct", token=hf_token)
|
107 |
-
# Wrap it so it supports .generate()
|
108 |
-
model_wrapper = HuggingFaceInferenceWrapper(inference_api)
|
109 |
-
|
110 |
agent = CodeAgent(
|
111 |
tools=[retriever_tool],
|
112 |
-
model=
|
113 |
max_steps=4,
|
114 |
verbosity_level=2,
|
115 |
-
stream_outputs=False, #
|
116 |
)
|
117 |
|
118 |
except Exception as e:
|
@@ -121,6 +114,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
|
|
121 |
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else "Code repo URL not available"
|
122 |
print(agent_code)
|
123 |
|
|
|
124 |
try:
|
125 |
response = requests.get(questions_url, timeout=15)
|
126 |
response.raise_for_status()
|
@@ -132,6 +126,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
|
|
132 |
|
133 |
results_log = []
|
134 |
answers_payload = []
|
|
|
135 |
for item in questions_data:
|
136 |
task_id = item.get("task_id")
|
137 |
question_text = item.get("question")
|
@@ -148,7 +143,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
|
|
148 |
return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
|
149 |
|
150 |
submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
|
151 |
-
|
152 |
try:
|
153 |
response = requests.post(submit_url, json=submission_data, timeout=60)
|
154 |
response.raise_for_status()
|
@@ -163,23 +157,21 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
|
|
163 |
results_df = pd.DataFrame(results_log)
|
164 |
return final_status, results_df
|
165 |
except Exception as e:
|
166 |
-
status_message = f"Submission Failed: {e}"
|
167 |
results_df = pd.DataFrame(results_log)
|
168 |
-
return
|
|
|
169 |
|
|
|
170 |
|
171 |
with gr.Blocks() as demo:
|
172 |
gr.Markdown("# Basic Agent Evaluation Runner")
|
173 |
gr.Markdown(
|
174 |
"""
|
175 |
**Instructions:**
|
176 |
-
1.
|
177 |
-
2.
|
178 |
-
3.
|
179 |
---
|
180 |
-
**Disclaimers:**
|
181 |
-
Once clicking on the "submit" button, it can take quite some time (this is the time for the agent to go through all the questions).
|
182 |
-
This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a separate action or even to answer the questions asynchronously.
|
183 |
"""
|
184 |
)
|
185 |
|
@@ -190,11 +182,7 @@ with gr.Blocks() as demo:
|
|
190 |
status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
|
191 |
results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
|
192 |
|
193 |
-
run_button.click(
|
194 |
-
fn=run_and_submit_all,
|
195 |
-
outputs=[status_output, results_table]
|
196 |
-
)
|
197 |
-
|
198 |
|
199 |
if __name__ == "__main__":
|
200 |
print("\n" + "-" * 30 + " App Starting " + "-" * 30)
|
|
|
1 |
import os
|
2 |
+
import json
|
3 |
import requests
|
4 |
import pandas as pd
|
5 |
import gradio as gr
|
|
|
9 |
from langchain.text_splitter import RecursiveCharacterTextSplitter
|
10 |
from langchain_community.retrievers import BM25Retriever
|
11 |
|
|
|
12 |
from huggingface_hub.inference_api import InferenceApi
|
13 |
+
from smolagents import Tool, CodeAgent
|
14 |
|
15 |
+
# ----- HF Inference Wrapper -----
|
|
|
16 |
class HuggingFaceInferenceWrapper:
|
17 |
def __init__(self, inference_api):
|
18 |
self.inference_api = inference_api
|
19 |
|
20 |
def generate(self, prompt: str, **kwargs) -> str:
|
21 |
+
raw_response = self.inference_api(inputs=prompt, raw_response=True)
|
22 |
+
json_data = json.loads(raw_response.content)
|
23 |
+
if isinstance(json_data, dict) and "generated_text" in json_data:
|
24 |
+
return json_data["generated_text"].strip()
|
25 |
+
elif isinstance(json_data, list) and len(json_data) > 0 and "generated_text" in json_data[0]:
|
26 |
+
return json_data[0]["generated_text"].strip()
|
27 |
else:
|
28 |
+
return str(json_data)
|
29 |
|
30 |
|
31 |
+
# ----- Setup HF API -----
|
32 |
hf_token = os.getenv("HUGGINGFACE_API_KEY")
|
33 |
+
if not hf_token:
|
34 |
+
raise ValueError("HUGGINGFACE_API_KEY environment variable is not set")
|
35 |
|
36 |
+
inference_api = InferenceApi(repo_id="Qwen/Qwen2.5-VL-7B-Instruct", token=hf_token)
|
37 |
+
model = HuggingFaceInferenceWrapper(inference_api)
|
|
|
|
|
|
|
38 |
|
|
|
|
|
39 |
|
40 |
def run_and_submit_all(profile: gr.OAuthProfile | None):
|
41 |
space_id = os.getenv("SPACE_ID")
|
|
|
99 |
|
100 |
retriever_tool = RetrieverTool(docs_processed)
|
101 |
|
102 |
+
# Instantiate CodeAgent with our wrapped model
|
|
|
|
|
|
|
|
|
103 |
agent = CodeAgent(
|
104 |
tools=[retriever_tool],
|
105 |
+
model=model,
|
106 |
max_steps=4,
|
107 |
verbosity_level=2,
|
108 |
+
stream_outputs=False, # Must be False for this wrapper
|
109 |
)
|
110 |
|
111 |
except Exception as e:
|
|
|
114 |
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else "Code repo URL not available"
|
115 |
print(agent_code)
|
116 |
|
117 |
+
# Fetch Questions
|
118 |
try:
|
119 |
response = requests.get(questions_url, timeout=15)
|
120 |
response.raise_for_status()
|
|
|
126 |
|
127 |
results_log = []
|
128 |
answers_payload = []
|
129 |
+
|
130 |
for item in questions_data:
|
131 |
task_id = item.get("task_id")
|
132 |
question_text = item.get("question")
|
|
|
143 |
return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
|
144 |
|
145 |
submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
|
|
|
146 |
try:
|
147 |
response = requests.post(submit_url, json=submission_data, timeout=60)
|
148 |
response.raise_for_status()
|
|
|
157 |
results_df = pd.DataFrame(results_log)
|
158 |
return final_status, results_df
|
159 |
except Exception as e:
|
|
|
160 |
results_df = pd.DataFrame(results_log)
|
161 |
+
return f"Submission Failed: {e}", results_df
|
162 |
+
|
163 |
|
164 |
+
# --- Gradio UI ---
|
165 |
|
166 |
with gr.Blocks() as demo:
|
167 |
gr.Markdown("# Basic Agent Evaluation Runner")
|
168 |
gr.Markdown(
|
169 |
"""
|
170 |
**Instructions:**
|
171 |
+
1. Clone this space and modify the code to define your agent's logic, tools, packages, etc.
|
172 |
+
2. Log in with the Hugging Face button.
|
173 |
+
3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
|
174 |
---
|
|
|
|
|
|
|
175 |
"""
|
176 |
)
|
177 |
|
|
|
182 |
status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
|
183 |
results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
|
184 |
|
185 |
+
run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
|
|
|
|
|
|
|
|
|
186 |
|
187 |
if __name__ == "__main__":
|
188 |
print("\n" + "-" * 30 + " App Starting " + "-" * 30)
|