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  1. __pycache__/server.cpython-312.pyc +0 -0
  2. app.py +21 -0
  3. client.py +39 -0
  4. pyproject.toml +3 -0
  5. server.py +74 -0
  6. uv.lock +175 -0
__pycache__/server.cpython-312.pyc ADDED
Binary file (3.17 kB). View file
 
app.py CHANGED
@@ -20,6 +20,27 @@ def sentiment_analysis(text: str) -> dict:
20
  "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
21
  }
22
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
23
  # Create the Gradio interface
24
  demo = gr.Interface(
25
  fn=sentiment_analysis,
 
20
  "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
21
  }
22
 
23
+ def prime_factors(n: int) -> list[int]:
24
+ """
25
+ Find all prime factors of input integer n
26
+
27
+ Args:
28
+ n (int): The integer to find all prime factors for
29
+
30
+ Returns:
31
+ list[int]: list of all integer prime factors of n
32
+ """
33
+ factors = []
34
+ d = 2
35
+ while d * d <= n:
36
+ while n % d == 0:
37
+ factors.append(d)
38
+ n //= d
39
+ d += 1
40
+ if n > 1:
41
+ factors.append(n)
42
+ return factors
43
+
44
  # Create the Gradio interface
45
  demo = gr.Interface(
46
  fn=sentiment_analysis,
client.py ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import gradio as gr
2
+
3
+ from mcp.client.stdio import StdioServerParameters
4
+ from smolagents import InferenceClientModel, CodeAgent, ToolCollection, OpenAIServerModel
5
+ from smolagents.mcp_client import MCPClient
6
+
7
+
8
+ try:
9
+ mcp_client = MCPClient(
10
+ ## Try this working example on the hub:
11
+ # {"url": "https://abidlabs-mcp-tools.hf.space/gradio_api/mcp/sse"}
12
+ {"url": "http://localhost:8000/sse", "transport": "sse"}
13
+ )
14
+ tools = mcp_client.get_tools()
15
+
16
+ model = OpenAIServerModel(
17
+ model_id="deepseek/deepseek-r1-0528:free",
18
+ api_base="https://openrouter.ai/api/v1", # Leave this blank to query OpenAI servers.
19
+ api_key="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"
20
+ )
21
+ agent = CodeAgent(tools=[*tools], model=model)
22
+
23
+ demo = gr.ChatInterface(
24
+ fn=lambda message, history: str(agent.run(message)),
25
+ type="messages",
26
+ examples=["What is the weather in Singapore?", "What is the prime factors of 58?", "analyze sentiment of this sentence: this product is great!"],
27
+ title="Agent with MCP Tools",
28
+ description="This is a simple agent that uses MCP tools to answer questions.",
29
+ )
30
+
31
+ demo.launch()
32
+ finally:
33
+ mcp_client.disconnect()
34
+
35
+ from openai import OpenAI
36
+
37
+ client = OpenAI()
38
+
39
+ response = client.chat.completions.create(messages=[], stream=False)
pyproject.toml CHANGED
@@ -6,8 +6,11 @@ readme = "README.md"
6
  requires-python = ">=3.12"
7
  dependencies = [
8
  "fastapi>=0.115.12",
 
9
  "gradio[mcp]>=5.32.0",
10
  "httpx>=0.28.1",
 
 
11
  "textblob>=0.19.0",
12
  ]
13
 
 
6
  requires-python = ">=3.12"
7
  dependencies = [
8
  "fastapi>=0.115.12",
9
+ "fastmcp>=2.5.2",
10
  "gradio[mcp]>=5.32.0",
11
  "httpx>=0.28.1",
12
+ "mcp>=1.9.0",
13
+ "smolagents[mcp,openai]>=1.17.0",
14
  "textblob>=0.19.0",
15
  ]
16
 
server.py ADDED
@@ -0,0 +1,74 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from fastmcp import FastMCP
2
+ from textblob import TextBlob
3
+
4
+ # Create an MCP server
5
+ mcp = FastMCP("Weather Service")
6
+
7
+
8
+ @mcp.tool()
9
+ def get_weather(location: str) -> str:
10
+ """Get the current weather for a specified location."""
11
+ return f"Weather in {location}: Sunny, 72°F"
12
+
13
+ @mcp.tool()
14
+ def sentiment_analysis(text: str) -> dict:
15
+ """
16
+ Analyze the sentiment of the given text.
17
+
18
+ Args:
19
+ text (str): The text to analyze
20
+
21
+ Returns:
22
+ dict: A dictionary containing polarity, subjectivity, and assessment
23
+ """
24
+ blob = TextBlob(text)
25
+ sentiment = blob.sentiment
26
+
27
+ return {
28
+ "polarity": round(sentiment.polarity, 2), # -1 (negative) to 1 (positive)
29
+ "subjectivity": round(sentiment.subjectivity, 2), # 0 (objective) to 1 (subjective)
30
+ "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
31
+ }
32
+
33
+ @mcp.tool()
34
+ def prime_factors(n: int) -> list[int]:
35
+ """
36
+ Find all prime factors of input integer n
37
+
38
+ Args:
39
+ n (int): The integer to find all prime factors for
40
+
41
+ Returns:
42
+ list[int]: list of all integer prime factors of n
43
+ """
44
+ factors = []
45
+ d = 2
46
+ while d * d <= n:
47
+ while n % d == 0:
48
+ factors.append(d)
49
+ n //= d
50
+ d += 1
51
+ if n > 1:
52
+ factors.append(n)
53
+ return factors
54
+
55
+ @mcp.resource("resource://greeting")
56
+ def greeting() -> str:
57
+ """Provide weather data as a resource."""
58
+ return "hello world"
59
+
60
+ @mcp.resource("weather://{location}")
61
+ def weather_resource(location: str) -> str:
62
+ """Provide weather data as a resource."""
63
+ return f"Weather data for {location}: Sunny, 72°F"
64
+
65
+
66
+ @mcp.prompt()
67
+ def weather_report(location: str) -> str:
68
+ """Create a weather report prompt."""
69
+ return f"""You are a weather reporter. Weather report for {location}?"""
70
+
71
+
72
+ # Run the server
73
+ if __name__ == "__main__":
74
+ mcp.run()
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@@ -357,6 +397,54 @@ wheels = [
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360
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361
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362
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369
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@@ -442,19 +539,40 @@ version = "0.1.0"
442
  source = { virtual = "." }
443
  dependencies = [
444
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445
  { name = "gradio", extra = ["mcp"] },
446
  { name = "httpx" },
 
 
447
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448
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449
 
450
  [package.metadata]
451
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453
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454
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455
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456
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457
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
458
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459
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460
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520
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521
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926
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927
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146
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181
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1072
  { url = "https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274", size = 11050, upload-time = "2024-12-04T17:35:26.475Z" },
1073
  ]
1074
 
1075
+ [[package]]
1076
+ name = "smolagents"
1077
+ version = "1.17.0"
1078
+ source = { registry = "https://pypi.org/simple" }
1079
+ dependencies = [
1080
+ { name = "huggingface-hub" },
1081
+ { name = "jinja2" },
1082
+ { name = "pillow" },
1083
+ { name = "python-dotenv" },
1084
+ { name = "requests" },
1085
+ { name = "rich" },
1086
+ ]
1087
+ sdist = { url = "https://files.pythonhosted.org/packages/b3/f3/1572c767e40353409c3b7d002a009b978013bd74c63d93fc96650eee3d49/smolagents-1.17.0.tar.gz", hash = "sha256:8d4ec4ccb759986560299e5489eab530282c68a4110820919d13a69e642f2b5b", size = 177215, upload-time = "2025-05-27T11:24:16.931Z" }
1088
+ wheels = [
1089
+ { url = "https://files.pythonhosted.org/packages/c0/c0/43c4cd2a98943992dbee705cbcfc57d6da89e4d75860bb379dc1e2fa1f33/smolagents-1.17.0-py3-none-any.whl", hash = "sha256:b6b7853d454c24c949cb306858523e97792310b9ab422a61cba5ccbab48f01c1", size = 133973, upload-time = "2025-05-27T11:24:15.025Z" },
1090
+ ]
1091
+
1092
+ [package.optional-dependencies]
1093
+ mcp = [
1094
+ { name = "mcp" },
1095
+ { name = "mcpadapt" },
1096
+ ]
1097
+ openai = [
1098
+ { name = "openai" },
1099
+ ]
1100
+
1101
  [[package]]
1102
  name = "sniffio"
1103
  version = "1.3.1"