From 8453ea7bbc197a8312a0f0c45776246552f72015 Mon Sep 17 00:00:00 2001
From: mmorge <maxime.morge@univ-lyon1.fr>
Date: Mon, 31 Mar 2025 22:46:57 +0200
Subject: [PATCH] Ivestment XP with Pagoda
---
.idea/PyGAAMAS.iml | 6 +-
.idea/misc.xml | 2 +-
data/investment/investment.csv | 116 +
figures/investment/investment_violin.svg | 2741 +++++++++++++---------
src/investment/investment.py | 185 +-
src/investment/investment_draw_violin.py | 25 +-
src/investment/investment_experiments.py | 4 +-
7 files changed, 1887 insertions(+), 1192 deletions(-)
diff --git a/.idea/PyGAAMAS.iml b/.idea/PyGAAMAS.iml
index ec63674..7c20165 100644
--- a/.idea/PyGAAMAS.iml
+++ b/.idea/PyGAAMAS.iml
@@ -1,7 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<module version="4">
- <component name="PyDocumentationSettings">
- <option name="format" value="PLAIN" />
- <option name="myDocStringFormat" value="Plain" />
+ <component name="NewModuleRootManager">
+ <orderEntry type="jdk" jdkName="Python 3.13" jdkType="Python SDK" />
+ <orderEntry type="sourceFolder" forTests="false" />
</component>
</module>
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
index db8786c..977706b 100644
--- a/.idea/misc.xml
+++ b/.idea/misc.xml
@@ -3,5 +3,5 @@
<component name="Black">
<option name="sdkName" value="Python 3.12" />
</component>
- <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.12" project-jdk-type="Python SDK" />
+ <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.13" project-jdk-type="Python SDK" />
</project>
\ No newline at end of file
diff --git a/data/investment/investment.csv b/data/investment/investment.csv
index c7d1789..99035a3 100644
--- a/data/investment/investment.csv
+++ b/data/investment/investment.csv
@@ -119,3 +119,119 @@ iteration,model,temperature,ccei
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29,deepseek-r1,0.0,0.2575
30,deepseek-r1,0.0,0.1514285714285714
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diff --git a/figures/investment/investment_violin.svg b/figures/investment/investment_violin.svg
index 44d5264..052091a 100644
--- a/figures/investment/investment_violin.svg
+++ b/figures/investment/investment_violin.svg
@@ -6,11 +6,11 @@
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<cc:Work>
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/>
- <dc:date>2025-03-26T17:38:14.450542</dc:date>
+ <dc:date>2025-03-31T18:45:53.412689</dc:date>
<dc:format>image/svg+xml</dc:format>
<dc:creator>
<cc:Agent>
- <dc:title>Matplotlib v3.10.0, https://matplotlib.org/</dc:title>
+ <dc:title>Matplotlib v3.10.1, https://matplotlib.org/</dc:title>
</cc:Agent>
</dc:creator>
</cc:Work>
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diff --git a/src/investment/investment.py b/src/investment/investment.py
index e1104bd..90ad7dd 100644
--- a/src/investment/investment.py
+++ b/src/investment/investment.py
@@ -9,31 +9,47 @@ from autogen_core import CancellationToken
from autogen_ext.models.openai import OpenAIChatCompletionClient
from pydantic import BaseModel
from scipy.optimize import linprog
+import requests
+import json
+import httpx
+import re
-# Load API key from environment variable
+# Load API key from environment variables
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
if not OPENAI_API_KEY:
raise ValueError("Missing OPENAI_API_KEY. Set it as an environment variable.")
+PAGODA_API_KEY = os.getenv("PAGODA_API_KEY")
+if not PAGODA_API_KEY:
+ raise ValueError("Missing PAGODA_API_KEY. Set it as an environment variable.")
# Define the expected response format as a Pydantic model
class AgentResponse(BaseModel):
- assetA: int
- assetB: int
+ assetA: float
+ assetB: float
reasoning: str
# The investment game simulation class
class Investment:
def __init__(self, model: str, temperature: float, max_retries: int = 3):
- self.debug = False
+ self.debug = True
self.model = model
self.temperature = temperature
self.strategy = random
self.max_retries = max_retries # Maximum retry attempts in case of hallucinations
- if not model == "random" and not model == "optimal":
- is_openai_model = model.startswith("gpt")
- base_url = "https://api.openai.com/v1" if is_openai_model else "http://localhost:11434/v1"
+ is_openai_model = model.startswith("gpt")
+ is_pagoda_model = ":" in model
+ base_url = (
+ "https://api.openai.com/v1" if is_openai_model else
+ "https://ollama-ui.pagoda.liris.cnrs.fr/ollama/api/generate" if is_pagoda_model else
+ "http://localhost:11434/v1"
+ )
+ self.base_url = base_url
+
+ key = OPENAI_API_KEY if is_openai_model else PAGODA_API_KEY
+
+ if not model in ["random", "optimal"]:
model_info = {
"temperature": self.temperature,
"function_calling": True,
@@ -46,13 +62,12 @@ class Investment:
self.model_client = OpenAIChatCompletionClient(
model=self.model,
base_url=base_url,
- api_key=OPENAI_API_KEY,
+ api_key=key,
model_info=model_info,
response_format=AgentResponse
)
async def run(self, m: float, n: float) -> Dict:
- """Runs the model if strategy is False, otherwise uses a classical method."""
if self.model == "random":
return self.apply_random(m, n)
if self.model == "optimal":
@@ -66,11 +81,15 @@ class Investment:
Your response should be in JSON format with `assetA`, `assetB`, and `reasoning`.
"""
+ is_pagoda_model = ":" in self.model
+ if is_pagoda_model:
+ return await self.run_pagoda(instruction)
+
for attempt in range(self.max_retries):
agent = AssistantAgent(
name="Investor",
model_client=self.model_client,
- system_message="You are a helpful assistant. You will be given 25 rounds of decision-making tasks and will be responsible for making decisions. You should use your best judgment to come up with solutions that you like most."
+ system_message="You are a helpful assistant."
)
response = await agent.on_messages(
@@ -80,50 +99,110 @@ class Investment:
try:
response_data = response.chat_message.content
- agent_response = AgentResponse.model_validate_json(response_data) # Parse JSON
+ agent_response = AgentResponse.model_validate_json(response_data)
assetA, assetB = agent_response.assetA, agent_response.assetB
if self.debug:
print(f"Response (Attempt {attempt+1}): {response_data}")
- # Validate values: ensure they sum to $100 considering the values M and N
- if 0 <= assetA and assetA <= 100 and 0 <= assetB and assetB <= 100 and assetA + assetB == 100:
+ if 0 <= assetA <= 100 and 0 <= assetB <= 100 and assetA + assetB == 100:
return agent_response.model_dump()
- else:
- if self.debug:
- print(f"Invalid response detected (Attempt {attempt+1}): {response_data}")
except Exception as e:
print(f"Error parsing response (Attempt {attempt+1}): {e}")
raise ValueError("Model failed to provide a valid response after multiple attempts.")
- def apply_random(self, m: int, n: int) -> Dict:
- """Generates a response."""
- assetA = random.randint(0, 100)
- assetB = 100 - assetA
- return {
- "assetA": assetA,
- "assetB": assetB,
- "reasoning": "Random choice"
+ async def run_pagoda(self, instruction: str) -> Dict:
+ """Runs the Pagoda model using a direct request with improved response parsing."""
+ url = self.base_url
+ headers = {
+ "Authorization": f"Bearer {PAGODA_API_KEY}",
+ "Content-Type": "application/json"
}
-
- def apply_optimal(self, m: int, n: int) -> Dict:
- """Generates a response."""
- if m > n:
- assetA = 100
- assetB = 0
- else:
- assetA = 0
- assetB = 100
- return {
- "assetA": assetA,
- "assetB": assetB,
- "reasoning": "Optimal choice"
+ payload = {
+ "model": self.model,
+ "temperature": self.temperature,
+ "prompt": instruction,
+ "stream": False,
+ "response_format": "json"
}
- def generate_M_N(self):
- while True:
- M = random.uniform(0.1, 1) # Random value in [0.1, 1]
- N = random.uniform(0.1, 1) # Random value in [0.1, 1]
- if max(M, N) >= 0.5: # Ensure max(M, N) is at least 0.5
- return round(M, 1), round(N, 1)
+ # Print equivalent cURL command for debugging
+ curl_cmd = f"""
+ curl -X POST {url} \\
+ -H "Authorization: Bearer {PAGODA_API_KEY}" \\
+ -H "Content-Type: application/json" \\
+ -d '{json.dumps(payload, indent=2)}'
+ """
+ print("Run this cURL command in your terminal to manually test the request:\n")
+ print(curl_cmd)
+
+ for attempt in range(self.max_retries):
+ try:
+ async with httpx.AsyncClient(verify=False, timeout=30) as client:
+ response = await client.post(url, headers=headers, json=payload)
+ response.raise_for_status() # Raise an error for HTTP status codes 4xx/5xx
+ response_data = response.json()
+
+ if self.debug:
+ print(f"Raw response (Attempt {attempt + 1}): {response_data}")
+
+ response_json = response_data.get("response")
+ if not response_json:
+ raise ValueError(f"Missing 'response' field (Attempt {attempt + 1})")
+
+ # Print full response for debugging
+ if self.debug:
+ print(f"Full response content (Attempt {attempt + 1}): {response_data}")
+
+ # Clean and parse JSON
+ if isinstance(response_json, str):
+ response_json = response_json.strip()
+ match = re.search(r'```json\n(.*?)\n```', response_json, re.DOTALL)
+ if match:
+ response_json = match.group(1)
+
+ response_json = response_json.replace("\n", "").replace("\\", "")
+
+ try:
+ response_dict = json.loads(response_json)
+ except json.JSONDecodeError:
+ print(f"Failed JSON: {response_json}")
+ raise ValueError(f"Failed to parse JSON (Attempt {attempt + 1})")
+
+ elif isinstance(response_json, dict):
+ response_dict = response_json
+ else:
+ raise TypeError(f"Unexpected response type: {type(response_json)}")
+
+ # Validate and adjust asset allocation
+ agent_response = AgentResponse(**response_dict)
+ assetA, assetB = round(agent_response.assetA), round(agent_response.assetB)
+ difference = 100 - (assetA + assetB)
+ if assetA >= assetB:
+ assetA += difference
+ else:
+ assetB += difference
+
+ if assetA + assetB != 100:
+ raise ValueError(f"Invalid allocation sum: {assetA}, {assetB}")
+
+ if not (0 <= assetA <= 100 and 0 <= assetB <= 100):
+ raise ValueError(f"Invalid asset allocation: {assetA}, {assetB}")
+
+ return agent_response.dict()
+
+ except httpx.HTTPStatusError as e:
+ print(
+ f"HTTP error from Pagoda API (Attempt {attempt + 1}): {e.response.status_code} - {e.response.text}")
+ except httpx.RequestError as e:
+ print(f"Request error in Pagoda API (Attempt {attempt + 1}): {e}")
+ except json.JSONDecodeError as e:
+ print(f"JSON parsing error (Attempt {attempt + 1}): {e}")
+ except ValueError as e:
+ print(f"Value error (Attempt {attempt + 1}): {e}")
+ except Exception as e:
+ print(f"Unexpected error (Attempt {attempt + 1}): {e}")
+
+ raise ValueError("Pagoda model failed to provide a valid response after multiple attempts.")
+
async def run_rounds(self, nb_rounds: int) -> float:
"""Runs the investment game for n rounds and computes the CCEI."""
@@ -151,10 +230,26 @@ class Investment:
print(f"choices: {choices}")
print(f"budgets: {budgets}")
print(f"CCEI: {ccei_value}")
-
return ccei_value
+ def apply_random(self, m: int, n: int) -> Dict:
+ assetA = random.randint(0, 100)
+ assetB = 100 - assetA
+ return {"assetA": assetA, "assetB": assetB, "reasoning": "Random choice"}
+
+ def apply_optimal(self, m: int, n: int) -> Dict:
+ assetA = 100 if m > n else 0
+ assetB = 100 - assetA
+ return {"assetA": assetA, "assetB": assetB, "reasoning": "Optimal choice"}
+
+ def generate_M_N(self):
+ while True:
+ M = random.uniform(0.1, 1)
+ N = random.uniform(0.1, 1)
+ if max(M, N) >= 0.5:
+ return round(M, 1), round(N, 1)
+
def compute_ccei(self, prices, choices, budgets):
"""
Computes the Critical Cost Efficiency Index (CCEI).
@@ -186,6 +281,6 @@ class Investment:
# Run the async function and return the response
if __name__ == "__main__":
- game_agent = Investment(model="mistral-small", temperature=0.0) # Toggle strategy here
+ game_agent = Investment(model="mistral-small", temperature=0.0)
response = asyncio.run(game_agent.run_rounds(30))
print(response)
diff --git a/src/investment/investment_draw_violin.py b/src/investment/investment_draw_violin.py
index a05303d..ffcc6fd 100644
--- a/src/investment/investment_draw_violin.py
+++ b/src/investment/investment_draw_violin.py
@@ -4,13 +4,26 @@ import matplotlib.pyplot as plt
# Custom color palette
color_palette = {
- 'random' : '#333333', # Black
- 'gpt-4.5-preview-2025-02-27': '#7abaff', # Blue
- 'llama3': '#32a68c', # Green
- 'mistral-small': '#ff6941', # Orange
- 'deepseek-r1': '#5862ed' # Indigo
+ 'random': '#333333', # Black
+ 'gpt-4.5-preview-2025-02-27': '#7abaff', # BlueEscape
+ 'llama3': '#32a68c', # GreenFuture
+ 'llama3.3:latest': '#4b9f7d', # GreenLlama3.3
+ 'mistral-small': '#ff6941', # WarmOrange
+ 'mixtral:8x7b': '#f1a61a', # YellowMixtral
+ 'deepseek-r1': '#5862ed', # InclusiveIndigo
+ 'deepseek-r1:7b': '#9a7bff' # PurpleDeepseek-r1:7b
}
+# Specify the order of models for the x-axis
+model_order = [
+ 'random',
+ 'gpt-4.5-preview-2025-02-27',
+ 'llama3', 'llama3.3:latest', # Place llama3 and llama3.3:latest together
+ 'mistral-small', 'mixtral:8x7b', # Bring mistral-small and mixtral:8x7b closer
+ 'deepseek-r1', 'deepseek-r1:7b'
+]
+
+
# Load CSV file
file_path = "../../data/investment/investment.csv" # Update path
df = pd.read_csv(file_path)
@@ -29,7 +42,7 @@ sns.set(style="whitegrid")
plt.figure(figsize=(10, 6))
# Draw violin plot (replacing boxplot with violinplot)
-sns.violinplot(data=df, x="model", y="ccei", palette=color_palette)
+sns.violinplot(data=df, x="model", y="ccei", palette=color_palette, order=model_order)
# Add plot labels
plt.title("CCEI Distribution by Model", fontsize=14)
diff --git a/src/investment/investment_experiments.py b/src/investment/investment_experiments.py
index a51056a..4348dc3 100644
--- a/src/investment/investment_experiments.py
+++ b/src/investment/investment_experiments.py
@@ -1,9 +1,9 @@
import asyncio
import csv
-from investment import Investment # Assuming this is in a separate file
+from investment import Investment
# Define models, temperature, and iterations
-models = ["optimal", "random", "llama3", "mistral-small", "deepseek-r1"] # "gpt-4.5-preview-2025-02-27", "optimal", "random", "llama3", "mistral-small", "deepseek-r1"
+models = ["deepseek-r1:7b"] # "gpt-4.5-preview-2025-02-27", "optimal", "random", "llama3", "mistral-small", "deepseek-r1", "mixtral:8x7b", "llama3.3:latest",
temperature = 0.0
iterations = 30
output_file = "../../data/investment/investment.csv"
--
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