Spaces:
Runtime error
Runtime error
Jean-Baptiste Pin
commited on
Commit
·
7ce8f44
1
Parent(s):
32d41ae
Got it
Browse files- README.md +107 -1
- app.py +65 -13
- prompts.yaml +9 -25
- requirements.txt +20 -1
README.md
CHANGED
@@ -12,4 +12,110 @@ hf_oauth: true
|
|
12 |
hf_oauth_expiration_minutes: 480
|
13 |
---
|
14 |
|
15 |
-
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
12 |
hf_oauth_expiration_minutes: 480
|
13 |
---
|
14 |
|
15 |
+
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
16 |
+
|
17 |
+
---
|
18 |
+
QWEN 3 jinja
|
19 |
+
|
20 |
+
{%- if tools %}
|
21 |
+
{{- '<|im_start|>system\n' }}
|
22 |
+
{%- if messages[0].role == 'system' %}
|
23 |
+
{{- messages[0].content + '\n\n' }}
|
24 |
+
{%- endif %}
|
25 |
+
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
26 |
+
{%- for tool in tools %}
|
27 |
+
{{- "\n" }}
|
28 |
+
{{- tool | tojson }}
|
29 |
+
{%- endfor %}
|
30 |
+
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
31 |
+
{%- else %}
|
32 |
+
{%- if messages[0].role == 'system' %}
|
33 |
+
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
34 |
+
{%- endif %}
|
35 |
+
{%- endif %}
|
36 |
+
|
37 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
38 |
+
|
39 |
+
{#— scan backward without using reverse filter —#}
|
40 |
+
{%- for i in range(messages|length - 1, -1, -1) %}
|
41 |
+
{%- set message = messages[i] %}
|
42 |
+
{%- set index = i %}
|
43 |
+
{%- set tool_start = "<tool_response>" %}
|
44 |
+
{%- set tool_start_length = tool_start|length %}
|
45 |
+
{%- set start_of_message = message.content[:tool_start_length] %}
|
46 |
+
{%- set tool_end = "</tool_response>" %}
|
47 |
+
{%- set tool_end_length = tool_end|length %}
|
48 |
+
{%- set start_pos = (message.content|length) - tool_end_length %}
|
49 |
+
{%- if start_pos < 0 %}
|
50 |
+
{%- set start_pos = 0 %}
|
51 |
+
{%- endif %}
|
52 |
+
{%- set end_of_message = message.content[start_pos:] %}
|
53 |
+
{%- if ns.multi_step_tool and message.role == "user" and not (start_of_message == tool_start and end_of_message == tool_end) %}
|
54 |
+
{%- set ns.multi_step_tool = false %}
|
55 |
+
{%- set ns.last_query_index = index %}
|
56 |
+
{%- endif %}
|
57 |
+
{%- endfor %}
|
58 |
+
|
59 |
+
{%- for message in messages %}
|
60 |
+
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
61 |
+
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
62 |
+
{%- elif message.role == "assistant" %}
|
63 |
+
{%- set content = message.content %}
|
64 |
+
{%- set reasoning_content = '' %}
|
65 |
+
{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
|
66 |
+
{%- set reasoning_content = message.reasoning_content %}
|
67 |
+
{%- else %}
|
68 |
+
{%- if '</think>' in message.content %}
|
69 |
+
{%- set content = (message.content.split('</think>')|last).lstrip('\n') %}
|
70 |
+
{%- set reasoning_content = (message.content.split('</think>')|first).rstrip('\n') %}
|
71 |
+
{%- set reasoning_content = (reasoning_content.split('<think>')|last).lstrip('\n') %}
|
72 |
+
{%- endif %}
|
73 |
+
{%- endif %}
|
74 |
+
{%- if loop.index0 > ns.last_query_index %}
|
75 |
+
{%- if loop.last or (not loop.last and reasoning_content) %}
|
76 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
77 |
+
{%- else %}
|
78 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
79 |
+
{%- endif %}
|
80 |
+
{%- else %}
|
81 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
82 |
+
{%- endif %}
|
83 |
+
{%- if message.tool_calls %}
|
84 |
+
{%- for tool_call in message.tool_calls %}
|
85 |
+
{%- if (loop.first and content) or (not loop.first) %}
|
86 |
+
{{- '\n' }}
|
87 |
+
{%- endif %}
|
88 |
+
{%- if tool_call.function %}
|
89 |
+
{%- set tool_call = tool_call.function %}
|
90 |
+
{%- endif %}
|
91 |
+
{{- '<tool_call>\n{"name": "' }}
|
92 |
+
{{- tool_call.name }}
|
93 |
+
{{- '", "arguments": ' }}
|
94 |
+
{%- if tool_call.arguments is string %}
|
95 |
+
{{- tool_call.arguments }}
|
96 |
+
{%- else %}
|
97 |
+
{{- tool_call.arguments | tojson }}
|
98 |
+
{%- endif %}
|
99 |
+
{{- '}\n</tool_call>' }}
|
100 |
+
{%- endfor %}
|
101 |
+
{%- endif %}
|
102 |
+
{{- '<|im_end|>\n' }}
|
103 |
+
{%- elif message.role == "tool" %}
|
104 |
+
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
105 |
+
{{- '<|im_start|>user' }}
|
106 |
+
{%- endif %}
|
107 |
+
{{- '\n<tool_response>\n' }}
|
108 |
+
{{- message.content }}
|
109 |
+
{{- '\n</tool_response>' }}
|
110 |
+
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
111 |
+
{{- '<|im_end|>\n' }}
|
112 |
+
{%- endif %}
|
113 |
+
{%- endif %}
|
114 |
+
{%- endfor %}
|
115 |
+
|
116 |
+
{%- if add_generation_prompt %}
|
117 |
+
{{- '<|im_start|>assistant\n' }}
|
118 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
119 |
+
{{- '<think>\n\n</think>\n\n' }}
|
120 |
+
{%- endif %}
|
121 |
+
{%- endif %}
|
app.py
CHANGED
@@ -11,16 +11,61 @@ from smolagents import (
|
|
11 |
FinalAnswerTool,
|
12 |
VisitWebpageTool,
|
13 |
LiteLLMModel,
|
|
|
14 |
tool
|
15 |
)
|
16 |
from markdownify import markdownify
|
17 |
from litellm import completion
|
18 |
from qwen_vl_utils import process_vision_info
|
|
|
|
|
|
|
|
|
|
|
19 |
|
20 |
# (Keep Constants as is)
|
21 |
# --- Constants ---
|
22 |
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
|
23 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
24 |
@tool
|
25 |
def analyze_video(url: str, question: str) -> str:
|
26 |
"""Analyze a video and answer the question.
|
@@ -56,7 +101,7 @@ def analyze_video(url: str, question: str) -> str:
|
|
56 |
# }
|
57 |
|
58 |
response = completion(
|
59 |
-
api_base="http://192.168.1.
|
60 |
model="lm_studio/qwen2.5-vl-7b-instruct",
|
61 |
messages=messages,
|
62 |
)
|
@@ -68,13 +113,13 @@ class BasicAgent:
|
|
68 |
def __init__(self):
|
69 |
with open("prompts.yaml", 'r') as stream:
|
70 |
prompt_templates = yaml.safe_load(stream)
|
71 |
-
model = LiteLLMModel(model_id="lm_studio/qwen2.5-coder-14b-instruct", api_base="http://192.168.1.
|
72 |
self.agent = CodeAgent(
|
73 |
model=model,
|
74 |
-
additional_authorized_imports=["time", "pandas", "numpy"],
|
75 |
-
tools=[DuckDuckGoSearchTool(),VisitWebpageTool(),FinalAnswerTool()], ## add your tools here (don't remove final answer)
|
76 |
-
max_steps=
|
77 |
-
verbosity_level=
|
78 |
grammar=None,
|
79 |
planning_interval=None,
|
80 |
name=None,
|
@@ -82,8 +127,15 @@ class BasicAgent:
|
|
82 |
prompt_templates=prompt_templates
|
83 |
)
|
84 |
print("BasicAgent initialized.")
|
85 |
-
def __call__(self, question: str):
|
86 |
print(f"Agent received question (first 100 chars): {question[:100]}...")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
87 |
fixed_answer = self.agent.run(question, False, True);
|
88 |
print(f"Agent returning fixed answer: {fixed_answer}")
|
89 |
return fixed_answer
|
@@ -93,7 +145,6 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
|
|
93 |
Fetches all questions, runs the BasicAgent on them, submits all answers,
|
94 |
and displays the results.
|
95 |
"""
|
96 |
-
|
97 |
# --- Determine HF Space Runtime URL and Repo URL ---
|
98 |
space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
|
99 |
|
@@ -105,8 +156,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
|
|
105 |
return "Please Login to Hugging Face with the button.", None
|
106 |
|
107 |
api_url = DEFAULT_API_URL
|
108 |
-
|
109 |
-
questions_url = f"{api_url}/random-question"
|
110 |
submit_url = f"{api_url}/submit"
|
111 |
|
112 |
# 1. Instantiate Agent ( modify this part to create your agent)
|
@@ -143,15 +194,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
|
|
143 |
# 3. Run your Agent
|
144 |
results_log = []
|
145 |
answers_payload = []
|
146 |
-
print(f"Running agent on {len(
|
147 |
-
for item in
|
148 |
task_id = item.get("task_id")
|
149 |
question_text = item.get("question")
|
|
|
150 |
if not task_id or question_text is None:
|
151 |
print(f"Skipping item with missing task_id or question: {item}")
|
152 |
continue
|
153 |
try:
|
154 |
-
submitted_answer = agent(question_text)
|
155 |
answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
|
156 |
print(f"Question: {item}, Task ID: {task_id}, Submitted Answer: {submitted_answer}")
|
157 |
results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
|
|
|
11 |
FinalAnswerTool,
|
12 |
VisitWebpageTool,
|
13 |
LiteLLMModel,
|
14 |
+
WikipediaSearchTool,
|
15 |
tool
|
16 |
)
|
17 |
from markdownify import markdownify
|
18 |
from litellm import completion
|
19 |
from qwen_vl_utils import process_vision_info
|
20 |
+
from urllib.parse import urlparse
|
21 |
+
from typing import List, Optional, Dict, Any
|
22 |
+
import tempfile
|
23 |
+
from io import BytesIO
|
24 |
+
from PIL import Image
|
25 |
|
26 |
# (Keep Constants as is)
|
27 |
# --- Constants ---
|
28 |
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
|
29 |
|
30 |
+
@tool
|
31 |
+
def download_file_from_url(url: str, filename: Optional[str] = None) -> str:
|
32 |
+
"""
|
33 |
+
Download a file from a URL and save it to a temporary location.
|
34 |
+
|
35 |
+
Args:
|
36 |
+
url: The URL to download from
|
37 |
+
filename: Optional filename, will generate one based on URL if not provided
|
38 |
+
|
39 |
+
Returns:
|
40 |
+
Path to the downloaded file
|
41 |
+
"""
|
42 |
+
try:
|
43 |
+
# Parse URL to get filename if not provided
|
44 |
+
if not filename:
|
45 |
+
path = urlparse(url).path
|
46 |
+
filename = os.path.basename(path)
|
47 |
+
if not filename:
|
48 |
+
# Generate a random name if we couldn't extract one
|
49 |
+
import uuid
|
50 |
+
filename = f"downloaded_{uuid.uuid4().hex[:8]}"
|
51 |
+
|
52 |
+
# Create temporary file
|
53 |
+
temp_dir = tempfile.gettempdir()
|
54 |
+
filepath = os.path.join(temp_dir, filename)
|
55 |
+
|
56 |
+
# Download the file
|
57 |
+
response = requests.get(url, stream=True)
|
58 |
+
response.raise_for_status()
|
59 |
+
|
60 |
+
# Save the file
|
61 |
+
with open(filepath, 'wb') as f:
|
62 |
+
for chunk in response.iter_content(chunk_size=8192):
|
63 |
+
f.write(chunk)
|
64 |
+
|
65 |
+
return f"File downloaded to {filepath}. You can now process this file."
|
66 |
+
except Exception as e:
|
67 |
+
return f"Error downloading file: {str(e)}"
|
68 |
+
|
69 |
@tool
|
70 |
def analyze_video(url: str, question: str) -> str:
|
71 |
"""Analyze a video and answer the question.
|
|
|
101 |
# }
|
102 |
|
103 |
response = completion(
|
104 |
+
api_base="http://192.168.1.183:1234/v1",
|
105 |
model="lm_studio/qwen2.5-vl-7b-instruct",
|
106 |
messages=messages,
|
107 |
)
|
|
|
113 |
def __init__(self):
|
114 |
with open("prompts.yaml", 'r') as stream:
|
115 |
prompt_templates = yaml.safe_load(stream)
|
116 |
+
model = LiteLLMModel(model_id="lm_studio/qwen2.5-coder-14b-instruct", api_base="http://192.168.1.183:1234/v1")
|
117 |
self.agent = CodeAgent(
|
118 |
model=model,
|
119 |
+
additional_authorized_imports=["time", "pandas", "numpy", "re", "openpyxl"],
|
120 |
+
tools=[DuckDuckGoSearchTool(),VisitWebpageTool(),WikipediaSearchTool(), download_file_from_url, FinalAnswerTool()], ## add your tools here (don't remove final answer)
|
121 |
+
max_steps=16,
|
122 |
+
verbosity_level=1,
|
123 |
grammar=None,
|
124 |
planning_interval=None,
|
125 |
name=None,
|
|
|
127 |
prompt_templates=prompt_templates
|
128 |
)
|
129 |
print("BasicAgent initialized.")
|
130 |
+
def __call__(self, question: str, file: str, taskId: str):
|
131 |
print(f"Agent received question (first 100 chars): {question[:100]}...")
|
132 |
+
if file :
|
133 |
+
if file.endswith('png') :
|
134 |
+
images = [Image.open(BytesIO(requests.get(f"{DEFAULT_API_URL}/files/{taskId}", timeout=10).content)).convert("RGB")]
|
135 |
+
fixed_answer_pict = self.agent.run(question, False, True, images);
|
136 |
+
return fixed_answer_pict;
|
137 |
+
else:
|
138 |
+
question = question + f" You can donwload the file associated at {DEFAULT_API_URL}/files/{taskId}"
|
139 |
fixed_answer = self.agent.run(question, False, True);
|
140 |
print(f"Agent returning fixed answer: {fixed_answer}")
|
141 |
return fixed_answer
|
|
|
145 |
Fetches all questions, runs the BasicAgent on them, submits all answers,
|
146 |
and displays the results.
|
147 |
"""
|
|
|
148 |
# --- Determine HF Space Runtime URL and Repo URL ---
|
149 |
space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
|
150 |
|
|
|
156 |
return "Please Login to Hugging Face with the button.", None
|
157 |
|
158 |
api_url = DEFAULT_API_URL
|
159 |
+
questions_url = f"{api_url}/questions"
|
160 |
+
# questions_url = f"{api_url}/random-question"
|
161 |
submit_url = f"{api_url}/submit"
|
162 |
|
163 |
# 1. Instantiate Agent ( modify this part to create your agent)
|
|
|
194 |
# 3. Run your Agent
|
195 |
results_log = []
|
196 |
answers_payload = []
|
197 |
+
print(f"Running agent on {len(questions_data)} questions...")
|
198 |
+
for item in questions_data:
|
199 |
task_id = item.get("task_id")
|
200 |
question_text = item.get("question")
|
201 |
+
question_file = item.get("file_name")
|
202 |
if not task_id or question_text is None:
|
203 |
print(f"Skipping item with missing task_id or question: {item}")
|
204 |
continue
|
205 |
try:
|
206 |
+
submitted_answer = agent(question_text, question_file, task_id)
|
207 |
answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
|
208 |
print(f"Question: {item}, Task ID: {task_id}, Submitted Answer: {submitted_answer}")
|
209 |
results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
|
prompts.yaml
CHANGED
@@ -9,28 +9,7 @@ system_prompt: |-
|
|
9 |
These print outputs will then appear in the 'Observation:' field, which will be available as input for the next step.
|
10 |
In the end you have to return a final answer using the `final_answer` tool.
|
11 |
|
12 |
-
You may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags.
|
13 |
-
|
14 |
-
|
15 |
Here are a few examples using notional tools:
|
16 |
-
---
|
17 |
-
Task: "Generate an image of the oldest person in this document."
|
18 |
-
|
19 |
-
Thought: I will proceed step by step and use the following tools: `document_qa` to find the oldest person in the document, then `image_generator` to generate an image according to the answer.
|
20 |
-
Code:
|
21 |
-
```py
|
22 |
-
answer = document_qa(document=document, question="Who is the oldest person mentioned?")
|
23 |
-
print(answer)
|
24 |
-
```<end_code>
|
25 |
-
Observation: "The oldest person in the document is John Doe, a 55 year old lumberjack living in Newfoundland."
|
26 |
-
|
27 |
-
Thought: I will now generate an image showcasing the oldest person.
|
28 |
-
Code:
|
29 |
-
```py
|
30 |
-
image = image_generator("A portrait of John Doe, a 55-year-old man living in Canada.")
|
31 |
-
final_answer(image)
|
32 |
-
```<end_code>
|
33 |
-
|
34 |
---
|
35 |
Task: "What is the result of the following operation: 5 + 3 + 1294.678?"
|
36 |
|
@@ -183,8 +162,7 @@ system_prompt: |-
|
|
183 |
9. The state persists between code executions: so if in one step you've created variables or imported modules, these will all persist.
|
184 |
10. Don't give up! You're in charge of solving the task, not providing directions to solve it.
|
185 |
|
186 |
-
|
187 |
-
|
188 |
Now Begin!
|
189 |
planning:
|
190 |
initial_plan: |-
|
@@ -225,6 +203,7 @@ planning:
|
|
225 |
"""
|
226 |
{% endfor %}
|
227 |
```
|
|
|
228 |
|
229 |
{%- if managed_agents and managed_agents.values() | list %}
|
230 |
You can also give tasks to team members.
|
@@ -287,6 +266,7 @@ planning:
|
|
287 |
{%- endfor %}"""
|
288 |
{% endfor %}
|
289 |
```
|
|
|
290 |
|
291 |
{%- if managed_agents and managed_agents.values() | list %}
|
292 |
You can also give tasks to team members.
|
@@ -317,6 +297,10 @@ managed_agent:
|
|
317 |
### 2. Task outcome (extremely detailed version):
|
318 |
### 3. Additional context (if relevant):
|
319 |
|
|
|
|
|
|
|
|
|
320 |
Put all these in your final_answer tool, everything that you do not pass as an argument to final_answer will be lost.
|
321 |
And even if your task resolution is not successful, please return as much context as possible, so that your manager can act upon this feedback.
|
322 |
report: |-
|
@@ -326,7 +310,7 @@ final_answer:
|
|
326 |
pre_messages: |-
|
327 |
An agent tried to answer a user query but it got stuck and failed to do so. You are tasked with providing an answer instead. Here is the agent's memory:
|
328 |
post_messages: |-
|
|
|
|
|
329 |
Based on the above, please provide an answer to the following user task:
|
330 |
{{task}}
|
331 |
-
We expect submissions to be json-line files with the following format. The first two fields are mandatory, reasoning_trace is optional:
|
332 |
-
```{"model_answer": "Answer 1 from your model", "reasoning_trace": ""}```
|
|
|
9 |
These print outputs will then appear in the 'Observation:' field, which will be available as input for the next step.
|
10 |
In the end you have to return a final answer using the `final_answer` tool.
|
11 |
|
|
|
|
|
|
|
12 |
Here are a few examples using notional tools:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
13 |
---
|
14 |
Task: "What is the result of the following operation: 5 + 3 + 1294.678?"
|
15 |
|
|
|
162 |
9. The state persists between code executions: so if in one step you've created variables or imported modules, these will all persist.
|
163 |
10. Don't give up! You're in charge of solving the task, not providing directions to solve it.
|
164 |
|
165 |
+
Be careful to follow the exact submission format and instruction.
|
|
|
166 |
Now Begin!
|
167 |
planning:
|
168 |
initial_plan: |-
|
|
|
203 |
"""
|
204 |
{% endfor %}
|
205 |
```
|
206 |
+
You must prefer generic tools over specific one: for example prefer search or visit web page instead of wikipedia. Use wikipedia only when stated.
|
207 |
|
208 |
{%- if managed_agents and managed_agents.values() | list %}
|
209 |
You can also give tasks to team members.
|
|
|
266 |
{%- endfor %}"""
|
267 |
{% endfor %}
|
268 |
```
|
269 |
+
You must prefer generic tools over specific one: for example prefer search or visit web page instead of wikipedia. Use wikipedia only when stated.
|
270 |
|
271 |
{%- if managed_agents and managed_agents.values() | list %}
|
272 |
You can also give tasks to team members.
|
|
|
297 |
### 2. Task outcome (extremely detailed version):
|
298 |
### 3. Additional context (if relevant):
|
299 |
|
300 |
+
Be careful to follow the exact submission format and instruction.
|
301 |
+
|
302 |
+
Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
|
303 |
+
|
304 |
Put all these in your final_answer tool, everything that you do not pass as an argument to final_answer will be lost.
|
305 |
And even if your task resolution is not successful, please return as much context as possible, so that your manager can act upon this feedback.
|
306 |
report: |-
|
|
|
310 |
pre_messages: |-
|
311 |
An agent tried to answer a user query but it got stuck and failed to do so. You are tasked with providing an answer instead. Here is the agent's memory:
|
312 |
post_messages: |-
|
313 |
+
Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
|
314 |
+
|
315 |
Based on the above, please provide an answer to the following user task:
|
316 |
{{task}}
|
|
|
|
requirements.txt
CHANGED
@@ -3,10 +3,29 @@ gradio[oauth]
|
|
3 |
requests
|
4 |
duckduckgo-search
|
5 |
smolagents
|
|
|
6 |
markdownify
|
7 |
typing
|
8 |
numpy
|
9 |
pandas
|
10 |
-
smolagents[litellm]
|
11 |
numpy
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
12 |
qwen_vl_utils
|
|
|
|
|
|
|
|
|
|
3 |
requests
|
4 |
duckduckgo-search
|
5 |
smolagents
|
6 |
+
smolagents[litellm]
|
7 |
markdownify
|
8 |
typing
|
9 |
numpy
|
10 |
pandas
|
|
|
11 |
numpy
|
12 |
+
wikipedia-api
|
13 |
+
openpyxl
|
14 |
+
openai
|
15 |
+
yfinance
|
16 |
+
lancedb
|
17 |
+
tantivy
|
18 |
+
pypdf
|
19 |
+
exa-py
|
20 |
+
newspaper4k
|
21 |
+
lxml_html_clean
|
22 |
+
sqlalchemy
|
23 |
+
agno
|
24 |
+
beautifulsoup4
|
25 |
+
wikipedia
|
26 |
+
langchain-community
|
27 |
qwen_vl_utils
|
28 |
+
langgraph
|
29 |
+
langchain[openai]
|
30 |
+
rizaio
|
31 |
+
google-search-results
|