Merge pull request #1 from NERVsystems/claude/local-llm-feasibility-gVLhq

Add OpenAI-compatible local LLM backend support

Add OpenAI-compatible backend for local LLM support (GPT-OSS)

Implement OpenAIClient backend that speaks the OpenAI Chat Completions
API (/v1/chat/completions), enabling llm9p to work with any local model
server: Ollama, vLLM, llama-server, LocalAI, or LM Studio.

Primary target is GPT-OSS (OpenAI's open-weight MoE models), but any
model served via these platforms works. The backend supports:
- Blocking and streaming chat completions
- Tool/function calling with STOP:/TOOL: formatting
- Token counting from API usage (with estimation fallback)
- Conversation history, system prompts, temperature control
- Stateless AskWithRequest for session isolation

Usage:
  ./llm9p -backend openai -openai-url http://localhost:11434/v1 -model gpt-oss:20b

Also fixes pre-existing stale mock backends in test files (AskWithRequest
signature was out of date with the Backend interface).

https://claude.ai/code/session_017qVVZUUhfCCvNkMYmXDZAa

feat(llmfs): native Anthropic tool_use protocol support

Add structured tool_use protocol to llm9p, enabling Veltro to use
Claude's native JSON tool invocation instead of text-based parsing.

New types (backend.go):
- AskResponse: carries Response, StructuredJSON, and Tokens — replaces
  the old (string, int, error) return from AskWithRequest
- ToolDef: tool definition passed to Anthropic tools API
- ToolResult: tool execution result for submission to the LLM
- Backend.AskWithRequest() now returns (AskResponse, error)

client.go:
- Message.StructuredContent: stores JSON content blocks for correct
  history replay of tool_use and tool_result turns
- AskWithRequest(): when ToolDefs non-nil, passes tools to API and
  returns STOP:/TOOL: formatted response for Limbo parsing
  Format: "STOP:tool_use\nTOOL:<id>:<name>:<args>\n<text>" or
          "STOP:end_turn\n<text>" or plain text (no tools)
- AskWithToolResults(): submits tool results as a new user turn
- Helpers: buildMessageParam(), buildToolParams(), extractToolArgs(),
  jsonEscapeString()

session.go:
- Session.tools field + SetTools/Tools methods
- Session.AddStructuredMessage() for storing structured content blocks
- AskRequest extended with ToolDefs and ToolResults fields
- SessionManager.Ask(): includes tools, stores structured JSON in history
- SessionManager.AskWithToolResults(): new method for tool result turns
- Fix Compact() for new AskResponse return type
- Helpers: extractTextContent(), buildToolResultsJSON()

cli_client.go: update AskWithRequest() to return AskResponse (no tools
support; StructuredJSON always empty)

session_tools.go (new): /n/llm/{id}/tools write-only file
- Write JSON array of ToolDef to enable native tool_use protocol
- Empty write clears tools (returns session to text-only mode)

session_ask.go:
- Detect TOOL_RESULTS\n prefix in Write() → parseToolResults() → AskWithToolResults()
- TOOL_RESULTS format: "TOOL_RESULTS\n<id>\n<content>\n---\n..."

session_dir.go: add tools file to Children() and Lookup()

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

feat(llm9p): Implement clone-based session architecture

Replace per-fid session model with Plan 9 clone pattern:
- Reading /n/llm/new creates a session and returns its ID
- Each session gets its own directory: /n/llm/<id>/
- Per-session files: ask, ctl, model, system, thinking, context, metrics
- AskWithRequest method for stateless CSP-style LLM calls
- Session settings (model, temperature, thinking) are per-session
- Remove old ask.go, context.go in favor of session-scoped files

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

feat(llm9p): Add per-fid session isolation and prefill support

- Add SessionManager for per-fid conversation isolation
- Each 9P fid now gets its own conversation history
- Add FidAwareFile interface for files needing fid context
- Add /n/llm/prefill file for assistant response prefill
- Prefill helps keep model in character (e.g., "[Veltro]")
- Update ask, new, context files to use session manager
- Fix context contamination between parent and subagent

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

feat(llm): Add extended thinking support and usage tracking

- Add thinking token control via /n/llm/thinking file (max/off/number)
- CLI backend sets MAX_THINKING_TOKENS env var for Claude CLI
- Default to max thinking (31999 tokens) for CLI backend
- Add /n/llm/usage file for token usage monitoring
- Add /n/llm/compact file for conversation summarization
- Extend Backend interface with ThinkingTokens, TotalTokens, ContextLimit, Compact
- Add true streaming support for CLI backend with line-by-line output
- Update example file with thinking documentation

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

feat: Add system prompt file for persistent persona configuration

- Add system file (read/write) to set system prompt
- System prompt persists across conversation resets
- Add SystemPrompt() and SetSystemPrompt() to Backend interface
- Update both API and CLI clients to support dedicated system prompt
- Update documentation and examples

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

feat: Add CLI backend for Claude Max subscription

Add support for using Claude Code CLI as an alternative backend,
allowing users with Claude Max subscriptions to use llm9p without
API tokens.

New files:
- internal/llm/backend.go: Backend interface for swappable LLM providers
- internal/llm/cli_client.go: CLI-based client using `claude` command

Changes:
- Add -backend flag: 'api' (default) or 'cli'
- Refactor llmfs to use Backend interface instead of concrete Client
- Model names normalized for CLI (opus, sonnet, haiku)

Usage:
  ./llm9p -backend cli  # Uses Claude Max subscription
  ./llm9p -backend api  # Uses Anthropic API (default)

Limitations of CLI backend:
- Token counting not available (always 0)
- Streaming is simulated (full response as single chunk)
- Uses short model names (opus, sonnet, haiku)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>