DSPy : change the model from llama to anthropic

[Josephrp]

Issue

DSPy logic uses incommensurate models

https://github.com/Josephrp/adapt-a-rag/blob/20df2e6a8c36f8ce816790c455234cf736d7d580/app.py#L135

Task

use anthropic client in DSPy :

• https://github.com/stanfordnlp/dspy/blob/65551efc41739528ab9c48293c2bb511a14a0903/dsp/modules/anthropic.py#L37

[Mind-Interfaces]

Issue Description

The current DSPy logic utilizes incommensurate models, specifically relying on the Llama model. The goal is to update the code to use the Anthropic client instead of the Llama model.

Modify Code

In the adapt-a-rag/app.py file, replace the initialization of the Llama model with the Anthropic client. Update the relevant code section as follows:

from dspy.modules.anthropic import AnthropicClient

# Replace the initialization of the Llama model with AnthropicClient
anthropicChat = AnthropicClient(model="claude-v1.3", port=ports, max_tokens=150)

Ensure to replace ports with the appropriate port configuration used in your application.

3. API Key

Make sure you have a valid API key for Anthropic and set it up in your environment or configuration file as required by Anthropic's documentation.

4. Additional Considerations

Review and update any other parts of the code that may depend on the Llama model. This includes any references to the llamaChat variable or any Llama-specific configurations.

Example

Here's an example of how the updated code snippet might look:

from dspy.modules.anthropic import AnthropicClient

# Replace the initialization of the Llama model with AnthropicClient
anthropicChat = AnthropicClient(model="claude-v1.3", port=ports, max_tokens=150)

# Update any other relevant parts of the code to use anthropicChat instead of llamaChat

[Mind-Interfaces]

The provided script in dspy/dsp/modules/anthropic.py appears to be compatible with the requirements outlined in the summary. Here's a review of the script and confirmation of its compatibility:

1. Imports: The script imports necessary modules such as logging, os, backoff, and the LM class from dsp.modules.lm. It also imports the anthropic module if available, handling the case where the module is not found with an ImportError.

2. Constants: It defines a base URL for the Anthropic API (BASE_URL) and sets up a rate limit error exception (anthropic_rate_limit). This allows for easy configuration and handling of API requests.

3. Claude Class: The main class defined in the script is Claude, which serves as a wrapper around the Anthropic API. It inherits from the LM class, indicating its specific use case related to language modeling within the DSPy framework.

4. Initialization: The __init__ method initializes the Claude class, setting up parameters such as the model name, API key, API base URL, and other keyword arguments. It also sets up the Anthropic client.

5. Request Handling: The request method handles retrieval of completions from Anthropic while handling API errors using backoff for retrying API requests.

6. Usage Logging: The log_usage method logs the total tokens from the Anthropic API response, providing insights into API usage.

7. Backoff Handling: The script utilizes the backoff library to handle backoff strategies for retrying API requests, specifically when encountering rate limit errors. This ensures robustness and reliability in handling API interactions.

8. Call Method: The __call__ method retrieves completions from Anthropic based on the provided prompt, with options to return only completed responses and sort completion choices.

Overall, the script is well-structured, follows best practices for error handling and logging, and provides a comprehensive interface for interacting with the Anthropic API within the DSPy framework. It aligns with the requirements outlined in the summary, making it compatible with the intended use case of generating a Rag app using Anthropics Opus.

https://github.com/stanfordnlp/dspy/blob/main/dsp/modules/anthropic.py

[Mind-Interfaces]

The provided code snippet attempts to import AnthropicClient from dspy.modules.anthropic and initialize it with specific parameters. However, there are a couple of issues with this code:

Port Argument: The AnthropicClient initialization includes a port argument, but it's unclear what this port refers to. Typically, when initializing an API client like AnthropicClient, you would specify parameters such as the API key, model name, and other configuration options, but not a port. If the Anthropic API requires a port for connection, it should be specified in a different way.

Unknown Variable: The variable ports used in the AnthropicClient initialization is not defined in the provided code snippet. This would result in a NameError unless ports is defined elsewhere in the code.

To make the code work, you should ensure the following:

Use the correct parameters for initializing AnthropicClient, such as the API key and model name. Ensure that any variables used in the initialization (such as ports) are properly defined and appropriate for the context. Here's a revised example assuming you have the necessary API key:

from dspy.modules.anthropic import AnthropicClient

# Replace "YOUR_API_KEY" with your actual Anthropic API key
api_key = "YOUR_API_KEY"

# Initialize AnthropicClient with the appropriate model and API key
anthropicChat = AnthropicClient(model="claude-v1.3", api_key=api_key, max_tokens=150)

In this example, api_key is used to authenticate with the Anthropic API, and max_tokens specifies the maximum number of tokens allowed for each response. Adjust the parameters as needed based on your specific requirements and the documentation of the AnthropicClient class.

[Mind-Interfaces]

The code you provided will not work as-is because there is no AnthropicClient class in the dspy.modules.anthropic module based on the script provided earlier. Instead, the script defines a Claude class to interact with the Anthropic API.

To correctly initialize the Anthropic client using the Claude class, you would use the following code:

from dspy.modules.anthropic import Claude

# Replace the initialization of the Llama model with Claude
anthropicChat = Claude(model="claude-v1.3", port=ports, max_tokens=150)

This code will create an instance of the Claude class with the specified parameters, allowing you to interact with the Anthropic API as intended. Make sure to replace ports with the appropriate port configuration used in your application.

[Josephrp]

yeah that's much better looking to me :-) we have time to make a PR but if we instantiate it early we can use it even "before" synthetic data generation

[Ariankhalfani]

all completed