diff --git a/_sources/examples/game/battleship.ipynb b/_sources/examples/game/battleship.ipynb index c9f5ece..cad342a 100644 --- a/_sources/examples/game/battleship.ipynb +++ b/_sources/examples/game/battleship.ipynb @@ -41,6 +41,59 @@ "from autogen import config_list_from_json" ] }, + { + "metadata": {"tags": ["hide-input"]}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "import os\n", + "import ipywidgets as widgets\n", + "from IPython.display import display\n", + "\n", + "# Function to save the environment variable and API key\n", + "def save_env_variable(env_name, api_key):\n", + " # Validate inputs\n", + " if not env_name.strip():\n", + " print(\"⚠️ Environment variable name cannot be empty.\")\n", + " return\n", + " if not api_key.strip():\n", + " print(\"⚠️ API key cannot be empty.\")\n", + " return\n", + " \n", + " # Store the API key as an environment variable\n", + " os.environ[env_name] = api_key\n", + " globals()[env_name] = api_key # Set it as a global variable\n", + " print(f\"✅ API key has been set for environment variable: {env_name}\")\n", + "\n", + "# Create the input widgets\n", + "env_name_input = widgets.Text(\n", + " value=\"OPENAI_API_KEY\", # Default value\n", + " description=\"Env Name:\",\n", + " placeholder=\"Enter env variable name (e.g., MY_API_KEY)\",\n", + ")\n", + "\n", + "api_key_input = widgets.Password(\n", + " description=\"API Key:\",\n", + " placeholder=\"Enter your API key\",\n", + ")\n", + "\n", + "# Create the button to submit the inputs\n", + "submit_button = widgets.Button(description=\"Set API Key\")\n", + "\n", + "# Display the widgets\n", + "display(env_name_input, api_key_input, submit_button)\n", + "\n", + "# Callback function for the button click\n", + "def on_button_click(b):\n", + " env_name = env_name_input.value\n", + " api_key = api_key_input.value\n", + " save_env_variable(env_name, api_key)\n", + "\n", + "# Attach the callback to the button\n", + "submit_button.on_click(on_button_click)" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/_sources/examples/nlp/bigbench_hard.ipynb b/_sources/examples/nlp/bigbench_hard.ipynb index 533e0ae..4f1542e 100644 --- a/_sources/examples/nlp/bigbench_hard.ipynb +++ b/_sources/examples/nlp/bigbench_hard.ipynb @@ -66,6 +66,59 @@ "import re" ] }, + { + "metadata": {"tags": ["hide-input"]}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "import os\n", + "import ipywidgets as widgets\n", + "from IPython.display import display\n", + "\n", + "# Function to save the environment variable and API key\n", + "def save_env_variable(env_name, api_key):\n", + " # Validate inputs\n", + " if not env_name.strip():\n", + " print(\"⚠️ Environment variable name cannot be empty.\")\n", + " return\n", + " if not api_key.strip():\n", + " print(\"⚠️ API key cannot be empty.\")\n", + " return\n", + " \n", + " # Store the API key as an environment variable\n", + " os.environ[env_name] = api_key\n", + " globals()[env_name] = api_key # Set it as a global variable\n", + " print(f\"✅ API key has been set for environment variable: {env_name}\")\n", + "\n", + "# Create the input widgets\n", + "env_name_input = widgets.Text(\n", + " value=\"OPENAI_API_KEY\", # Default value\n", + " description=\"Env Name:\",\n", + " placeholder=\"Enter env variable name (e.g., MY_API_KEY)\",\n", + ")\n", + "\n", + "api_key_input = widgets.Password(\n", + " description=\"API Key:\",\n", + " placeholder=\"Enter your API key\",\n", + ")\n", + "\n", + "# Create the button to submit the inputs\n", + "submit_button = widgets.Button(description=\"Set API Key\")\n", + "\n", + "# Display the widgets\n", + "display(env_name_input, api_key_input, submit_button)\n", + "\n", + "# Callback function for the button click\n", + "def on_button_click(b):\n", + " env_name = env_name_input.value\n", + " api_key = api_key_input.value\n", + " save_env_variable(env_name, api_key)\n", + "\n", + "# Attach the callback to the button\n", + "submit_button.on_click(on_button_click)" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/_sources/examples/robotics/metaworld.ipynb b/_sources/examples/robotics/metaworld.ipynb index 0877522..74705d4 100644 --- a/_sources/examples/robotics/metaworld.ipynb +++ b/_sources/examples/robotics/metaworld.ipynb @@ -48,6 +48,59 @@ "from opto.trace.errors import ExecutionError\n" ] }, + { + "metadata": {"tags": ["hide-input"]}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "import os\n", + "import ipywidgets as widgets\n", + "from IPython.display import display\n", + "\n", + "# Function to save the environment variable and API key\n", + "def save_env_variable(env_name, api_key):\n", + " # Validate inputs\n", + " if not env_name.strip():\n", + " print(\"⚠️ Environment variable name cannot be empty.\")\n", + " return\n", + " if not api_key.strip():\n", + " print(\"⚠️ API key cannot be empty.\")\n", + " return\n", + " \n", + " # Store the API key as an environment variable\n", + " os.environ[env_name] = api_key\n", + " globals()[env_name] = api_key # Set it as a global variable\n", + " print(f\"✅ API key has been set for environment variable: {env_name}\")\n", + "\n", + "# Create the input widgets\n", + "env_name_input = widgets.Text(\n", + " value=\"OPENAI_API_KEY\", # Default value\n", + " description=\"Env Name:\",\n", + " placeholder=\"Enter env variable name (e.g., MY_API_KEY)\",\n", + ")\n", + "\n", + "api_key_input = widgets.Password(\n", + " description=\"API Key:\",\n", + " placeholder=\"Enter your API key\",\n", + ")\n", + "\n", + "# Create the button to submit the inputs\n", + "submit_button = widgets.Button(description=\"Set API Key\")\n", + "\n", + "# Display the widgets\n", + "display(env_name_input, api_key_input, submit_button)\n", + "\n", + "# Callback function for the button click\n", + "def on_button_click(b):\n", + " env_name = env_name_input.value\n", + " api_key = api_key_input.value\n", + " save_env_variable(env_name, api_key)\n", + "\n", + "# Attach the callback to the button\n", + "submit_button.on_click(on_button_click)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -279,15 +332,15 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:32: UserWarning: \u001b[33mWARN: A Box observation space maximum and minimum values are equal. Actual equal coordinates: [(36,), (37,), (38,)]\u001b[0m\n", + "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:32: UserWarning: \u001B[33mWARN: A Box observation space maximum and minimum values are equal. Actual equal coordinates: [(36,), (37,), (38,)]\u001B[0m\n", " logger.warn(\n", - "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:159: UserWarning: \u001b[33mWARN: The obs returned by the `reset()` method is not within the observation space.\u001b[0m\n", + "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:159: UserWarning: \u001B[33mWARN: The obs returned by the `reset()` method is not within the observation space.\u001B[0m\n", " logger.warn(f\"{pre} is not within the observation space.\")\n", - "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:131: UserWarning: \u001b[33mWARN: The obs returned by the `reset()` method was expecting a numpy array, actual type: \u001b[0m\n", + "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:131: UserWarning: \u001B[33mWARN: The obs returned by the `reset()` method was expecting a numpy array, actual type: \u001B[0m\n", " logger.warn(\n", - "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/spaces/box.py:240: UserWarning: \u001b[33mWARN: Casting input x to numpy array.\u001b[0m\n", + "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/spaces/box.py:240: UserWarning: \u001B[33mWARN: Casting input x to numpy array.\u001B[0m\n", " gym.logger.warn(\"Casting input x to numpy array.\")\n", - "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/core.py:311: UserWarning: \u001b[33mWARN: env.control_mode to get variables from other wrappers is deprecated and will be removed in v1.0, to get this variable you can do `env.unwrapped.control_mode` for environment variables or `env.get_wrapper_attr('control_mode')` that will search the reminding wrappers.\u001b[0m\n", + "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/core.py:311: UserWarning: \u001B[33mWARN: env.control_mode to get variables from other wrappers is deprecated and will be removed in v1.0, to get this variable you can do `env.unwrapped.control_mode` for environment variables or `env.get_wrapper_attr('control_mode')` that will search the reminding wrappers.\u001B[0m\n", " logger.warn(\n" ] }, @@ -302,9 +355,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:159: UserWarning: \u001b[33mWARN: The obs returned by the `step()` method is not within the observation space.\u001b[0m\n", + "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:159: UserWarning: \u001B[33mWARN: The obs returned by the `step()` method is not within the observation space.\u001B[0m\n", " logger.warn(f\"{pre} is not within the observation space.\")\n", - "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:131: UserWarning: \u001b[33mWARN: The obs returned by the `step()` method was expecting a numpy array, actual type: \u001b[0m\n", + "/home/chinganc/miniconda3/envs/trace/lib/python3.8/site-packages/gymnasium/utils/passive_env_checker.py:131: UserWarning: \u001B[33mWARN: The obs returned by the `step()` method was expecting a numpy array, actual type: \u001B[0m\n", " logger.warn(\n" ] }, diff --git a/_sources/quickstart/quick_start.ipynb b/_sources/quickstart/quick_start.ipynb index 853958d..b72d09d 100644 --- a/_sources/quickstart/quick_start.ipynb +++ b/_sources/quickstart/quick_start.ipynb @@ -31,6 +31,60 @@ "%pip install trace-opt" ] }, + { + "metadata": {"tags": ["hide-input"]}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "import os\n", + "import ipywidgets as widgets\n", + "from IPython.display import display\n", + "\n", + "# Function to save the environment variable and API key\n", + "def save_env_variable(env_name, api_key):\n", + " # Validate inputs\n", + " if not env_name.strip():\n", + " print(\"⚠️ Environment variable name cannot be empty.\")\n", + " return\n", + " if not api_key.strip():\n", + " print(\"⚠️ API key cannot be empty.\")\n", + " return\n", + " \n", + " # Store the API key as an environment variable\n", + " os.environ[env_name] = api_key\n", + " globals()[env_name] = api_key # Set it as a global variable\n", + " print(f\"✅ API key has been set for environment variable: {env_name}\")\n", + "\n", + "# Create the input widgets\n", + "env_name_input = widgets.Text(\n", + " value=\"OPENAI_API_KEY\", # Default value\n", + " description=\"Env Name:\",\n", + " placeholder=\"Enter env variable name (e.g., MY_API_KEY)\",\n", + ")\n", + "\n", + "api_key_input = widgets.Password(\n", + " description=\"API Key:\",\n", + " placeholder=\"Enter your API key\",\n", + ")\n", + "\n", + "# Create the button to submit the inputs\n", + "submit_button = widgets.Button(description=\"Set API Key\")\n", + "\n", + "# Display the widgets\n", + "display(env_name_input, api_key_input, submit_button)\n", + "\n", + "# Callback function for the button click\n", + "def on_button_click(b):\n", + " env_name = env_name_input.value\n", + " api_key = api_key_input.value\n", + " save_env_variable(env_name, api_key)\n", + "\n", + "# Attach the callback to the button\n", + "submit_button.on_click(on_button_click)" + ], + "id": "150ebe0c019eb767" + }, { "cell_type": "markdown", "id": "1c6eec8b500e7966", diff --git a/_sources/quickstart/quick_start_2.ipynb b/_sources/quickstart/quick_start_2.ipynb index d16fcf1..e13d779 100644 --- a/_sources/quickstart/quick_start_2.ipynb +++ b/_sources/quickstart/quick_start_2.ipynb @@ -44,6 +44,60 @@ "from opto.optimizers import OptoPrime" ] }, + { + "metadata": {"tags": ["hide-input"]}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "import os\n", + "import ipywidgets as widgets\n", + "from IPython.display import display\n", + "\n", + "# Function to save the environment variable and API key\n", + "def save_env_variable(env_name, api_key):\n", + " # Validate inputs\n", + " if not env_name.strip():\n", + " print(\"⚠️ Environment variable name cannot be empty.\")\n", + " return\n", + " if not api_key.strip():\n", + " print(\"⚠️ API key cannot be empty.\")\n", + " return\n", + " \n", + " # Store the API key as an environment variable\n", + " os.environ[env_name] = api_key\n", + " globals()[env_name] = api_key # Set it as a global variable\n", + " print(f\"✅ API key has been set for environment variable: {env_name}\")\n", + "\n", + "# Create the input widgets\n", + "env_name_input = widgets.Text(\n", + " value=\"OPENAI_API_KEY\", # Default value\n", + " description=\"Env Name:\",\n", + " placeholder=\"Enter env variable name (e.g., MY_API_KEY)\",\n", + ")\n", + "\n", + "api_key_input = widgets.Password(\n", + " description=\"API Key:\",\n", + " placeholder=\"Enter your API key\",\n", + ")\n", + "\n", + "# Create the button to submit the inputs\n", + "submit_button = widgets.Button(description=\"Set API Key\")\n", + "\n", + "# Display the widgets\n", + "display(env_name_input, api_key_input, submit_button)\n", + "\n", + "# Callback function for the button click\n", + "def on_button_click(b):\n", + " env_name = env_name_input.value\n", + " api_key = api_key_input.value\n", + " save_env_variable(env_name, api_key)\n", + "\n", + "# Attach the callback to the button\n", + "submit_button.on_click(on_button_click)" + ], + "id": "dea338357fc76304" + }, { "cell_type": "markdown", "id": "fa000905-9028-4f6b-b42a-5a421ebf31c6", diff --git a/examples/game/battleship.html b/examples/game/battleship.html index d214808..3972e1a 100644 --- a/examples/game/battleship.html +++ b/examples/game/battleship.html @@ -516,6 +516,63 @@

Setup and Installation +
+
+ + +Hide code cell source + +
+
import os
+import ipywidgets as widgets
+from IPython.display import display
+
+# Function to save the environment variable and API key
+def save_env_variable(env_name, api_key):
+    # Validate inputs
+    if not env_name.strip():
+        print("⚠️ Environment variable name cannot be empty.")
+        return
+    if not api_key.strip():
+        print("⚠️ API key cannot be empty.")
+        return
+    
+    # Store the API key as an environment variable
+    os.environ[env_name] = api_key
+    globals()[env_name] = api_key  # Set it as a global variable
+    print(f"✅ API key has been set for environment variable: {env_name}")
+
+# Create the input widgets
+env_name_input = widgets.Text(
+    value="OPENAI_API_KEY",  # Default value
+    description="Env Name:",
+    placeholder="Enter env variable name (e.g., MY_API_KEY)",
+)
+
+api_key_input = widgets.Password(
+    description="API Key:",
+    placeholder="Enter your API key",
+)
+
+# Create the button to submit the inputs
+submit_button = widgets.Button(description="Set API Key")
+
+# Display the widgets
+display(env_name_input, api_key_input, submit_button)
+
+# Callback function for the button click
+def on_button_click(b):
+    env_name = env_name_input.value
+    api_key = api_key_input.value
+    save_env_variable(env_name, api_key)
+
+# Attach the callback to the button
+submit_button.on_click(on_button_click)
+
+
+
+
+

Environment Setup#

diff --git a/examples/nlp/bigbench_hard.html b/examples/nlp/bigbench_hard.html index 4db944c..9ba6197 100644 --- a/examples/nlp/bigbench_hard.html +++ b/examples/nlp/bigbench_hard.html @@ -528,6 +528,63 @@

Setup#< +
+
+ + +Hide code cell source + +
+
import os
+import ipywidgets as widgets
+from IPython.display import display
+
+# Function to save the environment variable and API key
+def save_env_variable(env_name, api_key):
+    # Validate inputs
+    if not env_name.strip():
+        print("⚠️ Environment variable name cannot be empty.")
+        return
+    if not api_key.strip():
+        print("⚠️ API key cannot be empty.")
+        return
+    
+    # Store the API key as an environment variable
+    os.environ[env_name] = api_key
+    globals()[env_name] = api_key  # Set it as a global variable
+    print(f"✅ API key has been set for environment variable: {env_name}")
+
+# Create the input widgets
+env_name_input = widgets.Text(
+    value="OPENAI_API_KEY",  # Default value
+    description="Env Name:",
+    placeholder="Enter env variable name (e.g., MY_API_KEY)",
+)
+
+api_key_input = widgets.Password(
+    description="API Key:",
+    placeholder="Enter your API key",
+)
+
+# Create the button to submit the inputs
+submit_button = widgets.Button(description="Set API Key")
+
+# Display the widgets
+display(env_name_input, api_key_input, submit_button)
+
+# Callback function for the button click
+def on_button_click(b):
+    env_name = env_name_input.value
+    api_key = api_key_input.value
+    save_env_variable(env_name, api_key)
+
+# Attach the callback to the button
+submit_button.on_click(on_button_click)
+
+
+
+
+

Define the Evaluation Function#

diff --git a/examples/robotics/metaworld.html b/examples/robotics/metaworld.html index 07ab8aa..af1f69c 100644 --- a/examples/robotics/metaworld.html +++ b/examples/robotics/metaworld.html @@ -517,6 +517,63 @@

Setup and Installation +
+
+ + +Hide code cell source + +
+
import os
+import ipywidgets as widgets
+from IPython.display import display
+
+# Function to save the environment variable and API key
+def save_env_variable(env_name, api_key):
+    # Validate inputs
+    if not env_name.strip():
+        print("⚠️ Environment variable name cannot be empty.")
+        return
+    if not api_key.strip():
+        print("⚠️ API key cannot be empty.")
+        return
+    
+    # Store the API key as an environment variable
+    os.environ[env_name] = api_key
+    globals()[env_name] = api_key  # Set it as a global variable
+    print(f"✅ API key has been set for environment variable: {env_name}")
+
+# Create the input widgets
+env_name_input = widgets.Text(
+    value="OPENAI_API_KEY",  # Default value
+    description="Env Name:",
+    placeholder="Enter env variable name (e.g., MY_API_KEY)",
+)
+
+api_key_input = widgets.Password(
+    description="API Key:",
+    placeholder="Enter your API key",
+)
+
+# Create the button to submit the inputs
+submit_button = widgets.Button(description="Set API Key")
+
+# Display the widgets
+display(env_name_input, api_key_input, submit_button)
+
+# Callback function for the button click
+def on_button_click(b):
+    env_name = env_name_input.value
+    api_key = api_key_input.value
+    save_env_variable(env_name, api_key)
+
+# Attach the callback to the button
+submit_button.on_click(on_button_click)
+
+
+
+
+

Environment Setup#

diff --git a/quickstart/quick_start.html b/quickstart/quick_start.html index f536cd0..b38e741 100644 --- a/quickstart/quick_start.html +++ b/quickstart/quick_start.html @@ -499,6 +499,63 @@

⚡️ First: 5-Minute Basics +
+ + +Hide code cell source + +
+
import os
+import ipywidgets as widgets
+from IPython.display import display
+
+# Function to save the environment variable and API key
+def save_env_variable(env_name, api_key):
+    # Validate inputs
+    if not env_name.strip():
+        print("⚠️ Environment variable name cannot be empty.")
+        return
+    if not api_key.strip():
+        print("⚠️ API key cannot be empty.")
+        return
+    
+    # Store the API key as an environment variable
+    os.environ[env_name] = api_key
+    globals()[env_name] = api_key  # Set it as a global variable
+    print(f"✅ API key has been set for environment variable: {env_name}")
+
+# Create the input widgets
+env_name_input = widgets.Text(
+    value="OPENAI_API_KEY",  # Default value
+    description="Env Name:",
+    placeholder="Enter env variable name (e.g., MY_API_KEY)",
+)
+
+api_key_input = widgets.Password(
+    description="API Key:",
+    placeholder="Enter your API key",
+)
+
+# Create the button to submit the inputs
+submit_button = widgets.Button(description="Set API Key")
+
+# Display the widgets
+display(env_name_input, api_key_input, submit_button)
+
+# Callback function for the button click
+def on_button_click(b):
+    env_name = env_name_input.value
+    api_key = api_key_input.value
+    save_env_variable(env_name, api_key)
+
+# Attach the callback to the button
+submit_button.on_click(on_button_click)
+
+
+
+
+

Start with a Normal Python Program#

To illustrate the fundamental difference between Trace and many other LLM libraries, we can look at a coding problem from OpenAI’s Human-Eval dataset.

diff --git a/quickstart/quick_start_2.html b/quickstart/quick_start_2.html index 49fa1c1..0d840bd 100644 --- a/quickstart/quick_start_2.html +++ b/quickstart/quick_start_2.html @@ -504,6 +504,63 @@

A Reinforcement Learning Agent +
+ + +Hide code cell source + +
+
import os
+import ipywidgets as widgets
+from IPython.display import display
+
+# Function to save the environment variable and API key
+def save_env_variable(env_name, api_key):
+    # Validate inputs
+    if not env_name.strip():
+        print("⚠️ Environment variable name cannot be empty.")
+        return
+    if not api_key.strip():
+        print("⚠️ API key cannot be empty.")
+        return
+    
+    # Store the API key as an environment variable
+    os.environ[env_name] = api_key
+    globals()[env_name] = api_key  # Set it as a global variable
+    print(f"✅ API key has been set for environment variable: {env_name}")
+
+# Create the input widgets
+env_name_input = widgets.Text(
+    value="OPENAI_API_KEY",  # Default value
+    description="Env Name:",
+    placeholder="Enter env variable name (e.g., MY_API_KEY)",
+)
+
+api_key_input = widgets.Password(
+    description="API Key:",
+    placeholder="Enter your API key",
+)
+
+# Create the button to submit the inputs
+submit_button = widgets.Button(description="Set API Key")
+
+# Display the widgets
+display(env_name_input, api_key_input, submit_button)
+
+# Callback function for the button click
+def on_button_click(b):
+    env_name = env_name_input.value
+    api_key = api_key_input.value
+    save_env_variable(env_name, api_key)
+
+# Attach the callback to the button
+submit_button.on_click(on_button_click)
+
+
+
+
+

Trace uses decorators like @bundle and data wrappers like node to expose different parts of these programs to an LLM. An LLM can rewrite the entire or only parts of system based on the user’s specification. An LLM can change various parts of this system, with feedback they receive from the environment. Trace allows users to exert control over the LLM code-generation process.

diff --git a/searchindex.js b/searchindex.js index b2fa217..a001989 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"A Reinforcement Learning Agent": [[33, "a-reinforcement-learning-agent"]], "API": [[1, "api"], [2, "api"], [3, "api"], [4, "api"], [5, "api"], [6, "api"], [7, "api"], [8, "api"], [9, "api"], [10, "api"], [11, "api"], [12, "api"], [13, "api"], [14, "api"], [15, "api"], [16, "api"], [18, "api"], [19, "api"], [20, "api"], [22, "api"], [23, "api"]], "Adding constraints": [[39, "adding-constraints"]], "Agent Architecture": [[34, "agent-architecture"]], "Backpropagation": [[39, "backpropagation"]], "Basic back-propagation and gradient descent with PyTorch": [[36, "basic-back-propagation-and-gradient-descent-with-pytorch"]], "Basics": [[35, "basics"]], "Batch Optimization": [[38, "batch-optimization"]], "Batching Non-Commutative Feedbacks": [[38, "batching-non-commutative-feedbacks"]], "BigBench-Hard": [[27, "bigbench-hard"]], "Broadcasting": [[35, "broadcasting"]], "Building Custom Optimizer": [[36, "building-custom-optimizer"]], "Classes": [[1, "classes"], [2, "classes"], [3, "classes"], [4, "classes"], [5, "classes"], [6, "classes"], [8, "classes"], [10, "classes"], [11, "classes"], [13, "classes"], [14, "classes"], [15, "classes"], [18, "classes"], [19, "classes"], [22, "classes"], [23, "classes"]], "Coder-Verifier Framework using Trace": [[32, "coder-verifier-framework-using-trace"]], "Creating the initial policy": [[25, "creating-the-initial-policy"]], "Data": [[6, "data"], [8, "data"], [15, "data"], [20, "data"]], "Define An Agent Using Trace": [[33, "define-an-agent-using-trace"]], "Define Chat Function": [[26, "define-chat-function"]], "Define Game Components": [[26, "define-game-components"]], "Define a Policy class with multiple trainable functions": [[25, "define-a-policy-class-with-multiple-trainable-functions"]], "Define a Traced Class": [[27, "define-a-traced-class"]], "Define the Evaluation Function": [[27, "define-the-evaluation-function"]], "Define the Optimization Process": [[33, "define-the-optimization-process"]], "Define the end_game function": [[26, "define-the-end-game-function"]], "Define the optimizer": [[27, "define-the-optimizer"]], "Developer Installation": [[31, "developer-installation"]], "Difference to Libraries like AutoGen, AG2, OpenAI Swarm, Llama Stack": [[29, "difference-to-libraries-like-autogen-ag2-openai-swarm-llama-stack"]], "Difference to Libraries like TextGrad": [[29, "difference-to-libraries-like-textgrad"]], "Emergent Pro-Social Behaviors": [[34, "emergent-pro-social-behaviors"]], "Environment Setup": [[25, "environment-setup"], [28, "environment-setup"]], "Error Handling": [[37, "error-handling"]], "Example of Full Optimization Loop": [[39, "example-of-full-optimization-loop"]], "Example of hyper-parameter optimization for ML models": [[39, "example-of-hyper-parameter-optimization-for-ml-models"]], "Example of optimizing functions": [[39, "example-of-optimizing-functions"]], "Example of optimizing strings": [[39, "example-of-optimizing-strings"]], "Execute the Optimization Process": [[28, "execute-the-optimization-process"]], "FAQ": [[29, "faq"]], "Functions": [[5, "functions"], [6, "functions"], [7, "functions"], [8, "functions"], [9, "functions"], [10, "functions"], [11, "functions"], [13, "functions"], [14, "functions"], [15, "functions"], [16, "functions"], [20, "functions"]], "Helper Function": [[27, "helper-function"]], "Helper Functions to rollout and evaluate the policy": [[25, "helper-functions-to-rollout-and-evaluate-the-policy"]], "Installation Command": [[31, null]], "Introduction": [[25, "introduction"], [26, "introduction"], [27, "introduction"], [28, "introduction"]], "Meta-World": [[28, "meta-world"]], "Module Contents": [[2, "module-contents"], [3, "module-contents"], [4, "module-contents"], [5, "module-contents"], [6, "module-contents"], [7, "module-contents"], [9, "module-contents"], [10, "module-contents"], [11, "module-contents"], [12, "module-contents"], [13, "module-contents"], [14, "module-contents"], [15, "module-contents"], [16, "module-contents"], [18, "module-contents"], [19, "module-contents"], [20, "module-contents"], [22, "module-contents"], [23, "module-contents"]], "Multi-Agent Synchronous Optimization": [[34, "multi-agent-synchronous-optimization"]], "Multi-Agent: Negotiation Arena": [[26, "multi-agent-negotiation-arena"]], "Node and MessageNode": [[35, "node-and-messagenode"]], "Nodes and Python Data Structure": [[35, "nodes-and-python-data-structure"]], "Operations on Nodes": [[35, "operations-on-nodes"]], "Optimization": [[39, "optimization"]], "Optimize Prompts": [[26, "optimize-prompts"]], "Optimize using Trace": [[28, "optimize-using-trace"]], "Optimize with Feedback": [[32, "optimize-with-feedback"]], "Package Contents": [[1, "package-contents"], [8, "package-contents"]], "Putting it all together": [[25, "putting-it-all-together"], [27, "putting-it-all-together"]], "Recording of Agent Behavior": [[34, "recording-of-agent-behavior"]], "Results": [[34, "results"]], "Rollout Function": [[28, "rollout-function"]], "Save and Load the Optimized Function": [[32, "save-and-load-the-optimized-function"]], "Set up the objective in Trace": [[36, "set-up-the-objective-in-trace"]], "Setup": [[26, "setup"], [27, "setup"]], "Setup and Installation": [[25, "setup-and-installation"], [28, "setup-and-installation"]], "Single Agent: Battleship": [[25, "single-agent-battleship"]], "Start with a Normal Python Program": [[32, "start-with-a-normal-python-program"]], "Submodules": [[0, "submodules"], [17, "submodules"], [21, "submodules"]], "Subpackages": [[0, "subpackages"], [8, "subpackages"]], "The Game of BattleShip": [[33, "the-game-of-battleship"]], "The Optimized Function is Runnable": [[32, "the-optimized-function-is-runnable"]], "Trace this Program": [[32, "trace-this-program"]], "Use Bundle to Writing Custom Node Operators": [[35, "use-bundle-to-writing-custom-node-operators"]], "Using bundle to wrap helper functions": [[26, "using-bundle-to-wrap-helper-functions"]], "Version 1 Trace Implementation based on Optimizer": [[36, "version-1-trace-implementation-based-on-optimizer"]], "Version 2 Trace Implementation based on Propagator + Optimizer": [[36, "version-2-trace-implementation-based-on-propagator-optimizer"]], "Visualize Graph": [[35, "visualize-graph"]], "Visualize Trace Graph of an Action": [[33, "visualize-trace-graph-of-an-action"]], "What Did the Agent Learn?": [[33, "what-did-the-agent-learn"]], "What\u2019s Next?": [[32, "what-s-next"], [34, "what-s-next"]], "Wrap the environment into a BattleshipBoard class": [[25, "wrap-the-environment-into-a-battleshipboard-class"]], "opto": [[0, "module-opto"]], "opto.optimizers": [[1, "module-opto.optimizers"]], "opto.optimizers.buffers": [[2, "module-opto.optimizers.buffers"]], "opto.optimizers.opro": [[3, "module-opto.optimizers.opro"]], 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"opto.trace.propagators.propagators": [[19, "module-opto.trace.propagators.propagators"]], "opto.trace.utils": [[20, "module-opto.trace.utils"]], "opto.utils": [[21, "module-opto.utils"]], "opto.utils.llm": [[22, "module-opto.utils.llm"]], "opto.utils.trainer": [[23, "module-opto.utils.trainer"]], "opto.version": [[24, "module-opto.version"]], "\u26a1\ufe0f First: 5-Minute Basics": [[32, "first-5-minute-basics"]], "\ud83c\udf10 Installation": [[31, "installation"]], "\ud83c\udfaf Trace": [[30, "trace"]], "\ud83c\udfe0 VirtualHome": [[34, "virtualhome"]], "\ud83d\ude80 Next: Adaptive Agent": [[33, "next-adaptive-agent"]], "\ud83e\udd2f Finally: Emergent Behaviors": [[34, "finally-emergent-behaviors"]]}, "docnames": ["api/opto/opto", "api/opto/opto.optimizers", "api/opto/opto.optimizers.buffers", "api/opto/opto.optimizers.opro", "api/opto/opto.optimizers.optimizer", "api/opto/opto.optimizers.optoprime", "api/opto/opto.optimizers.textgrad", "api/opto/opto.optimizers.utils", 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