Add direct API backend for agent execution

When api_base_url is configured, agents call the LLM directly via
OpenAI-compatible API (vllm, llama.cpp, etc.) instead of shelling
out to claude CLI. Implements the full tool loop: send prompt, if
tool_calls execute them and send results back, repeat until text.

This enables running agents against local/remote models like
Qwen-27B on a RunPod B200, with no dependency on claude CLI.

Config fields: api_base_url, api_key, api_model.
Falls back to claude CLI when api_base_url is not set.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Kent Overstreet 2026-03-18 23:05:14 -04:00
parent 1b48e57f34
commit a29b6d4c5d
6 changed files with 145 additions and 1 deletions

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@ -0,0 +1,115 @@
// agents/api.rs — Direct API backend for agent execution
//
// Uses poc-agent's OpenAI-compatible API client to call models directly
// (vllm, llama.cpp, OpenRouter, etc.) instead of shelling out to claude CLI.
// Implements the tool loop: send prompt → if tool_calls, execute them →
// send results back → repeat until text response.
//
// Activated when config has api_base_url set.
use poc_agent::api::ApiClient;
use poc_agent::types::*;
use poc_agent::tools::{self, ProcessTracker};
use poc_agent::ui_channel::StreamTarget;
/// Run an agent prompt through the direct API with tool support.
/// Returns the final text response after all tool calls are resolved.
pub async fn call_api_with_tools(
agent: &str,
prompt: &str,
log: &dyn Fn(&str),
) -> Result<String, String> {
let config = crate::config::get();
let base_url = config.api_base_url.as_deref()
.ok_or("api_base_url not configured")?;
let api_key = config.api_key.as_deref().unwrap_or("");
let model = config.api_model.as_deref().unwrap_or("qwen-2.5-27b");
let client = ApiClient::new(base_url, api_key, model);
// Set up a minimal UI channel (we just collect messages, no TUI)
let (ui_tx, _ui_rx) = poc_agent::ui_channel::channel();
// Build tool definitions — just bash for poc-memory commands
let all_defs = tools::definitions();
let tool_defs: Vec<ToolDef> = all_defs.into_iter()
.filter(|d| d.function.name == "bash")
.collect();
let tracker = ProcessTracker::new();
// Start with the prompt as a user message
let mut messages = vec![Message::user(prompt)];
let max_turns = 50;
for turn in 0..max_turns {
log(&format!("API turn {} ({} messages)", turn, messages.len()));
let (msg, usage) = client.chat_completion_stream(
&messages,
Some(&tool_defs),
&ui_tx,
StreamTarget::Autonomous,
"none",
).await.map_err(|e| format!("API error: {}", e))?;
if let Some(u) = &usage {
log(&format!("tokens: {} prompt + {} completion",
u.prompt_tokens, u.completion_tokens));
}
let has_content = msg.content.is_some();
let has_tools = msg.tool_calls.as_ref().is_some_and(|tc| !tc.is_empty());
if has_tools {
// Push the assistant message with tool calls
messages.push(msg.clone());
// Execute each tool call
for call in msg.tool_calls.as_ref().unwrap() {
log(&format!("tool: {}({})",
call.function.name,
crate::util::first_n_chars(&call.function.arguments, 80)));
let args: serde_json::Value = serde_json::from_str(&call.function.arguments)
.unwrap_or_default();
let output = tools::dispatch(&call.function.name, &args, &tracker).await;
log(&format!("tool result: {} chars", output.text.len()));
messages.push(Message::tool_result(&call.id, &output.text));
}
continue;
}
// Text-only response — we're done
let text = msg.content_text().to_string();
if text.is_empty() && !has_content {
log("empty response, retrying");
messages.push(Message::user(
"[system] Your previous response was empty. Please respond with text or use a tool."
));
continue;
}
return Ok(text);
}
Err(format!("agent exceeded {} tool turns", max_turns))
}
/// Synchronous wrapper — creates a tokio runtime and blocks.
/// Used by the existing sync call path in knowledge.rs.
pub fn call_api_with_tools_sync(
agent: &str,
prompt: &str,
log: &dyn Fn(&str),
) -> Result<String, String> {
let rt = tokio::runtime::Builder::new_current_thread()
.enable_all()
.build()
.map_err(|e| format!("tokio runtime: {}", e))?;
rt.block_on(call_api_with_tools(agent, prompt, log))
}

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@ -184,8 +184,15 @@ pub(crate) fn call_haiku(agent: &str, prompt: &str) -> Result<String, String> {
}
/// Call a model using an agent definition's model and tool configuration.
/// Uses the direct API backend when api_base_url is configured,
/// otherwise falls back to claude CLI subprocess.
pub(crate) fn call_for_def(def: &super::defs::AgentDef, prompt: &str) -> Result<String, String> {
call_model_with_tools(&def.agent, &def.model, prompt, &def.tools)
if crate::config::get().api_base_url.is_some() && !def.tools.is_empty() {
let log = |msg: &str| eprintln!("[{}] {}", def.agent, msg);
super::api::call_api_with_tools_sync(&def.agent, prompt, &log)
} else {
call_model_with_tools(&def.agent, &def.model, prompt, &def.tools)
}
}
/// Parse a JSON response, handling markdown fences.

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@ -16,6 +16,7 @@
// transcript — shared JSONL transcript parsing
pub mod transcript;
pub mod api;
pub mod llm;
pub mod prompts;
pub mod defs;