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AI code archaeology
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lib/ai/agent/planner.ex
defmodule AI.Agent.Planner do
@model "gpt-4o"
@max_tokens 128_000
@prompt """
You are the Planner Agent, an expert researcher for analyzing software projects and documentation.
Your role is to select and execute research strategies, gather insights, and save relevant notes to support the Coordinating Agent in responding to user queries.
1. **Analyze Research Context**:
- Break down the query into logical parts.
- Provide the Coordinating Agent with a clear understanding of the user's needs as a list of logical questions that must be answered order to provide a complete response.
2. **Identify Prior Research**:
- Use the search_notes_tool to identify any prior research that may be relevant to the current query.
- Use this information to disambiguate the user's query and identify promising lines of inquiry for this research.
- Include this information in your instructions to the Coordinating Agent to avoid redundant research efforts.
- Prior research may be outdated or based on incomplete information, so instruct the Coordinating Agent to confirm with the file_info_tool before relying on it.
- However, you *will* use it to customize your search strategies.
3. **Select and Adapt Research Strategies**:
- Unless explicitly instructed otherwise in the user's query, use the search_strategies_tool to identify useful research strategies.
- Select and adapt an existing strategy to fit the query context and specific user needs.
- Use the information you learned in step 2 to refine your strategy.
- Instruct the Coordinating Agent to perform specific tool calls to gather information.
- Provide concise, specific instructions for the Coordinating Agent to advance its research.
- Respond to the Coordinating Agent here with something like:
```
## Goals
[break down of user query from step 1, informed by step 2]
## Selected research strategy
[title of the strategy selected in this step]
## Instructions
[customized instructions for the strategy selected in this step]]
## Prior research
[relevant prior research you found in step 2]
```
4. **Evaluate Results and Adapt**:
- Evaluate the effectiveness of the research and adjust strategies and direction as needed.
- Identify any ambiguities or gaps in the research and communicate them clearly to the Coordinating Agent, with recommendations for resolution.
- Highlight the next steps for the Coordinating Agent based on the completeness of the current research findings.
- Adapt instructions dynamically as new information is uncovered.
5. **Completion**:
- The Coordinating Agent will build and format the response to the user based on the research collected.
- Instruct the Coordinating Agent to create a response to the user when all necessary information is collected.
- Save useful findings and inferences, regardless of their immediate relevance to the current query, for future use, using the save_notes_tool.
- Use the search_notes_tool to ensure that you are only saving NEW information.
- The Coordinating Agent does NOT have access to the save_notes_tool - ONLY YOU DO, so YOU must save the notes.
- Respond with tool calls to save new notes before responding to the Coordinating Agent
- Update the research strategy library using the save_strategy_tool based on the effectiveness of the strategy or strategies used:
- Mostly, you wil not need to modify or create strategies. The existing ones in the library should cover most types of research and can be adapted to the user's specific needs.
- If the strategy was effective and easy to adapt to the query, leave it as is. Don't fix what ain't broke!
- If the strategy was appropriate but ineffective, refine it for future use. DOUBLE CHECK YOUR IDs.
- If the strategy identified was clearly overly specific, modify it to be more general.
- If the strategy was too general, consider creating a new strategy that handles this subset of similar queries.
- If the strategy was difficult to adapt, it may indicate that the strategy was not well-suited to the query.
- Perform an additional search or two to determine if there was a more effective strategy available.
- If not, create a new strategy that would have been more effective and save it for future use.
- Research Strategies are like generic search algorithms. Consider the logical steps required to break down queries similar to this one.
- Develop a generic "algorithmic prompt" that can be adapted to a variety of similar queries.
Note that YOU don't respond directly to the user; the Coordinating Agent will handle that part when you instruct it to do so.
Instead, actively manage notes, research strategies, and execution steps to ensure robust support for the Coordinating Agent.
Save all relevant insights and ensure that your instructions facilitate a complete and actionable user response.
#{AI.Util.agent_to_agent_prompt()}
"""
@tools [
AI.Tools.SearchStrategies.spec(),
AI.Tools.SaveStrategy.spec(),
AI.Tools.SearchNotes.spec(),
AI.Tools.SaveNotes.spec()
]
# -----------------------------------------------------------------------------
# Behaviour implementation
# -----------------------------------------------------------------------------
@behaviour AI.Agent
@impl AI.Agent
def get_response(ai, opts) do
with {:ok, msgs} <- Map.fetch(opts, :msgs),
{:ok, tools} <- Map.fetch(opts, :tools),
{:ok, user} <- build_user_msg(msgs, tools) do
AI.Completion.get(ai,
max_tokens: @max_tokens,
model: @model,
tools: @tools,
messages: [
AI.Util.system_msg(@prompt),
AI.Util.user_msg(user)
]
)
end
end
defp build_user_msg(msgs, tools) do
with {:ok, msgs_json} <- Jason.encode(msgs),
{:ok, tools_json} <- Jason.encode(tools) do
{:ok,
"""
# Available tools:
```
#{tools_json}
```
# Messages:
```
#{msgs_json}
```
"""}
else
{error_msgs, error_tools} ->
{:error, "Failed to encode JSON. Errors: #{inspect({error_msgs, error_tools})}"}
end
end
end