Merge PR #65: soul: OpenAI-compatible provider path for chat (Ollama/OpenAI/Grok/Gemini) v1
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Adds llm_base_url()/llm_wire_format() env-var readers and
openai_chat_complete() for basic (non-agentic) chat via any
OpenAI-compatible endpoint. Activated when NEURON_LLM_0_FORMAT=openai
and NEURON_LLM_0_URL is set; Anthropic path is untouched and remains
default. Agentic tool loop support deferred to a follow-up PR.
This commit is contained in:
2026-07-01 11:35:02 -05:00
+88 -1
View File
@@ -1276,6 +1276,86 @@ fn agentic_api_key() -> String {
return env("NEURON_LLM_0_KEY")
}
// OpenAI-compatible providers (Ollama / OpenAI / Grok / Gemini)
// The brain speaks Anthropic's Messages format by default. When the active provider uses the
// OpenAI-compatible wire format (NEURON_LLM_0_FORMAT=openai) with a configured base URL
// (NEURON_LLM_0_URL, e.g. http://localhost:11434/v1 for local Ollama), basic chat turns are served
// here instead of the Anthropic agentic loop.
// v1 SCOPE: plain chat completion only NO tools / agentic loop yet (that is a follow-up port).
// This block is ADDITIVE: the Anthropic path is untouched and stays the default.
fn llm_base_url() -> String {
return env("NEURON_LLM_0_URL")
}
fn llm_wire_format() -> String {
let f: String = env("NEURON_LLM_0_FORMAT")
if str_eq(f, "") {
return "anthropic"
}
return f
}
// Escape a decoded string so it can be embedded back into a JSON string literal.
fn json_escape(s: String) -> String {
let a: String = str_replace(s, "\\", "\\\\")
let b: String = str_replace(a, "\"", "\\\"")
let c: String = str_replace(b, "\n", "\\n")
let d: String = str_replace(c, "\r", "\\r")
return d
}
// Basic (non-agentic) chat completion against an OpenAI-compatible endpoint.
// [safe_sys] is already JSON-escaped; [messages_json] is the same JSON array the Anthropic path
// builds (e.g. [{"role":"user","content":"..."}]). Returns the soul's standard {"reply":"..."}.
fn openai_chat_complete(model: String, base_url: String, api_key: String, safe_sys: String, messages_json: String) -> String {
// Prepend the system prompt as an OpenAI "system" message, then the existing turn array.
let inner: String = if json_array_len(messages_json) > 0 {
str_slice(messages_json, 1, str_len(messages_json) - 1)
} else {
""
}
let msgs: String = if str_eq(inner, "") {
"[{\"role\":\"system\",\"content\":\"" + safe_sys + "\"}]"
} else {
"[{\"role\":\"system\",\"content\":\"" + safe_sys + "\"}," + inner + "]"
}
let req_body: String = "{\"model\":\"" + model + "\""
+ ",\"max_tokens\":4096"
+ ",\"messages\":" + msgs
+ "}"
let h: Map = {}
map_set(h, "content-type", "application/json")
// Ollama needs no key; OpenAI / Grok / Gemini use a Bearer token.
if !str_eq(api_key, "") {
map_set(h, "Authorization", "Bearer " + api_key)
}
let url: String = base_url + "/chat/completions"
let raw_resp: String = http_post_with_headers(url, req_body, h)
let is_error: Bool = str_starts_with(raw_resp, "{\"error\"") || str_contains(raw_resp, "\"error\":")
if is_error {
return "{\"error\":\"llm unavailable\",\"reply\":\"\"}"
}
// Parse OpenAI response shape: choices[0].message.content
let choices: String = json_get_raw(raw_resp, "choices")
let eff_choices: String = if str_eq(choices, "") {
"[]"
} else {
choices
}
if json_array_len(eff_choices) < 1 {
return "{\"error\":\"empty response\",\"reply\":\"\"}"
}
let first: String = json_array_get(eff_choices, 0)
let message: String = json_get_raw(first, "message")
let content: String = json_get(message, "content")
return "{\"reply\":\"" + json_escape(content) + "\",\"tools_used\":[]}"
}
fn agentic_tools_literal() -> String {
return "[" +
"{\"name\":\"read_file\",\"description\":\"Read contents of a file from disk.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\",\"description\":\"Absolute file path\"}},\"required\":[\"path\"]}}," +
@@ -1840,7 +1920,14 @@ fn handle_chat_agentic(body: String) -> String {
// Use caller-supplied session_id if provided, otherwise generate a bridge id.
let session_id: String = if str_eq(req_session, "") { next_bridge_id() } else { req_session }
let result: String = agentic_loop(session_id, model, safe_sys, tools_json, messages, h, "")
// Provider fork: OpenAI-compatible providers (Ollama/OpenAI/Grok/Gemini) take the plain-completion
// path (v1, no tools); everything else stays on the Anthropic agentic loop (the default).
let use_openai: Bool = !str_eq(llm_base_url(), "") && str_eq(llm_wire_format(), "openai")
let result: String = if use_openai {
openai_chat_complete(model, llm_base_url(), agentic_api_key(), safe_sys, messages)
} else {
agentic_loop(session_id, model, safe_sys, tools_json, messages, h, "")
}
// Persist the exchange to session/global history for thread continuity on next turn.
// Only save when the loop completed (reply present), not when tool_pending.