feat: add AnthropicClient as drop-in replacement for PerplexityClient (closes #105 phase 1)

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KoalaTrapLord authored and GitHub committed 2026-03-25 12:16:14 -04:00
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"""
Commander AI Lab — Anthropic Claude Structured Output Client
════════════════════════════════════════════════════════════
Uses the anthropic SDK to call Claude's messages endpoint
with structured JSON output enforced via system prompt.
Supports both sync and native async operation.
"""
import json
import logging
import re
from typing import Optional
import anthropic
logger = logging.getLogger("coach.anthropic")
# ── Anthropic Models ───────────────────────────────────────────
CLAUDE_OPUS = "claude-opus-4-0-20250514"
CLAUDE_SONNET = "claude-sonnet-4-5"
CLAUDE_HAIKU = "claude-haiku-4-5"
class AnthropicResponse:
"""Parsed response container from Anthropic API.
Drop-in replacement for PerplexityResponse — same attribute shape
so all existing call-sites work without changes.
"""
def __init__(
self,
content: str,
parsed_json: Optional[dict],
prompt_tokens: int,
completion_tokens: int,
model: str,
citations: list[str] = None,
):
self.content = content
self.parsed_json = parsed_json
self.prompt_tokens = prompt_tokens
self.completion_tokens = completion_tokens
self.model = model
self.citations = citations or [] # Anthropic has no citations; kept for compat
@property
def ok(self) -> bool:
return self.parsed_json is not None
class AnthropicClient:
"""
Anthropic Claude API client.
Drop-in replacement for PerplexityClient.
Usage:
client = AnthropicClient(api_key="sk-ant-...")
resp = client.chat_structured(
system_prompt="You are a deck builder.",
user_prompt="Build a deck for...",
json_schema=deck_schema,
schema_name="DeckList",
)
if resp.ok:
deck = resp.parsed_json
"""
def __init__(
self,
api_key: str,
model: str = CLAUDE_OPUS,
timeout: int = 120,
base_url: str = None,
):
if not api_key:
raise ValueError("Anthropic API key is required")
self.api_key = api_key
self.model = model
self.timeout = timeout
self._client = anthropic.Anthropic(
api_key=api_key,
base_url=base_url,
timeout=float(timeout),
)
self._async_client = anthropic.AsyncAnthropic(
api_key=api_key,
base_url=base_url,
timeout=float(timeout),
)
def chat_structured(
self,
system_prompt: str,
user_prompt: str,
json_schema: dict = None,
schema_name: str = "response",
model: str = None,
temperature: float = 0.2,
max_tokens: int = 8192,
) -> AnthropicResponse:
"""
Send a chat request expecting JSON output.
The system_prompt should instruct the model to return JSON matching
the expected schema. Claude Opus follows JSON instructions reliably.
Args:
system_prompt: System message (should instruct JSON output)
user_prompt: User message
json_schema: (optional) Kept for call-site compatibility; appended
as a schema hint in the system prompt when provided
schema_name: (optional) Label used in the schema hint
model: Override model
temperature: Sampling temperature (0.0-1.0)
max_tokens: Max output tokens
Returns:
AnthropicResponse with parsed_json extracted from model output
"""
use_model = model or self.model
effective_system = self._build_system(system_prompt, json_schema, schema_name)
try:
response = self._client.messages.create(
model=use_model,
system=effective_system,
messages=[{"role": "user", "content": user_prompt}],
temperature=temperature,
max_tokens=max_tokens,
)
return self._parse_response(response, use_model)
except Exception as e:
logger.error("[anthropic] API call failed: %s", e)
raise
def chat_plain(
self,
system_prompt: str,
user_prompt: str,
model: str = None,
temperature: float = 0.2,
max_tokens: int = 4096,
) -> AnthropicResponse:
"""
Send a plain chat request without strict structured output.
Used for substitution fallback queries.
"""
use_model = model or self.model
try:
response = self._client.messages.create(
model=use_model,
system=system_prompt,
messages=[{"role": "user", "content": user_prompt}],
temperature=temperature,
max_tokens=max_tokens,
)
return self._parse_response(response, use_model)
except Exception as e:
logger.error("[anthropic] Plain chat failed: %s", e)
raise
async def achat_structured(
self,
system_prompt: str,
user_prompt: str,
json_schema: dict = None,
schema_name: str = "response",
model: str = None,
temperature: float = 0.2,
max_tokens: int = 8192,
) -> AnthropicResponse:
"""Native async structured chat — no run_in_executor needed."""
use_model = model or self.model
effective_system = self._build_system(system_prompt, json_schema, schema_name)
try:
response = await self._async_client.messages.create(
model=use_model,
system=effective_system,
messages=[{"role": "user", "content": user_prompt}],
temperature=temperature,
max_tokens=max_tokens,
)
return self._parse_response(response, use_model)
except Exception as e:
logger.error("[anthropic] Async structured chat failed: %s", e)
raise
async def achat_plain(
self,
system_prompt: str,
user_prompt: str,
model: str = None,
temperature: float = 0.2,
max_tokens: int = 4096,
) -> AnthropicResponse:
"""Native async plain chat."""
use_model = model or self.model
try:
response = await self._async_client.messages.create(
model=use_model,
system=system_prompt,
messages=[{"role": "user", "content": user_prompt}],
temperature=temperature,
max_tokens=max_tokens,
)
return self._parse_response(response, use_model)
except Exception as e:
logger.error("[anthropic] Async plain chat failed: %s", e)
raise
def check_status(self) -> dict:
"""Quick health check — try a minimal API call."""
try:
response = self._client.messages.create(
model=self.model,
system="Reply with the word OK.",
messages=[{"role": "user", "content": "Status check."}],
max_tokens=10,
)
content = response.content[0].text if response.content else ""
return {
"connected": True,
"model": self.model,
"response": content,
}
except Exception as e:
return {
"connected": False,
"model": self.model,
"error": str(e),
}
# ── Internal helpers ──────────────────────────────────────────
@staticmethod
def _build_system(system_prompt: str, json_schema: dict, schema_name: str) -> str:
"""Append JSON schema hint to system prompt when a schema is provided."""
if not json_schema:
return system_prompt
schema_str = json.dumps(json_schema, indent=2)
return (
f"{system_prompt}\n\n"
f"You MUST respond with valid JSON only — no markdown fences, no prose.\n"
f"The response must conform to the following JSON schema ({schema_name}):\n"
f"{schema_str}"
)
def _parse_response(self, response, use_model: str) -> AnthropicResponse:
"""Extract content and attempt JSON parsing from an Anthropic response."""
content = ""
if response.content:
content = response.content[0].text or ""
usage = response.usage
prompt_tokens = usage.input_tokens if usage else 0
completion_tokens = usage.output_tokens if usage else 0
parsed = None
try:
parsed = json.loads(content)
except (json.JSONDecodeError, TypeError):
parsed = self._extract_json(content)
logger.info(
"[anthropic] model=%s tokens=(%d in, %d out) parsed=%s",
use_model,
prompt_tokens,
completion_tokens,
"yes" if parsed else "no",
)
return AnthropicResponse(
content=content,
parsed_json=parsed,
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
model=use_model,
citations=[],
)
@staticmethod
def _extract_json(text: str) -> Optional[dict]:
"""Best-effort JSON extraction from possibly noisy text."""
try:
return json.loads(text.strip())
except (json.JSONDecodeError, TypeError):
pass
# Markdown fences
fence_match = re.search(r'```(?:json)?\s*([\s\S]*?)```', text)
if fence_match:
try:
return json.loads(fence_match.group(1).strip())
except (json.JSONDecodeError, TypeError):
pass
# Brace counting
start = text.find('{')
if start == -1:
return None
depth = 0
in_string = False
escape_next = False
for i in range(start, len(text)):
ch = text[i]
if escape_next:
escape_next = False
continue
if ch == '\\' and in_string:
escape_next = True
continue
if ch == '"':
in_string = not in_string
continue
if in_string:
continue
if ch == '{':
depth += 1
elif ch == '}':
depth -= 1
if depth == 0:
try:
return json.loads(text[start:i + 1])
except (json.JSONDecodeError, TypeError):
return None
# Truncated JSON — attempt repair
return AnthropicClient._repair_truncated_json(text[start:])
@staticmethod
def _repair_truncated_json(text: str) -> Optional[dict]:
"""
Attempt to repair truncated JSON from max_tokens cutoff.
Strategy: find the last complete nested object, then close
all open brackets/braces.
"""
logger.info("Attempting truncated JSON repair (%d chars)...", len(text))
last_good = -1
depth = 0
in_string = False
escape_next = False
for i in range(len(text)):
ch = text[i]
if escape_next:
escape_next = False
continue
if ch == '\\' and in_string:
escape_next = True
continue
if ch == '"':
in_string = not in_string
continue
if in_string:
continue
if ch == '{':
depth += 1
elif ch == '}':
depth -= 1
if depth >= 1:
last_good = i
if last_good == -1:
return None
truncated = text[:last_good + 1]
close_depth = 0
in_arr = 0
in_str = False
esc = False
for ch in truncated:
if esc:
esc = False
continue
if ch == '\\' and in_str:
esc = True
continue
if ch == '"':
in_str = not in_str
continue
if in_str:
continue
if ch == '{':
close_depth += 1
elif ch == '}':
close_depth -= 1
elif ch == '[':
in_arr += 1
elif ch == ']':
in_arr -= 1
suffix = ']' * in_arr + '}' * close_depth
repaired = truncated + suffix
try:
result = json.loads(repaired)
card_count = len(result.get('cards', []))
logger.info("JSON repair succeeded: recovered %d cards", card_count)
return result
except (json.JSONDecodeError, TypeError) as e:
logger.warning("JSON repair failed: %s", e)
return None