File size: 4,316 Bytes
4412065 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 | """Chat helper functions — history conversion, prompt building, iteration context."""
from __future__ import annotations
from typing import Any
from code.config.constants import SYSTEM_PROMPT
from code.execution.code_extractor import strip_thinking_blocks
def chat_history_to_messages(history: list[dict[str, str]]) -> list[dict[str, Any]]:
"""Convert chat history list to messages format for the model.
Prepends the system prompt and strips thinking blocks from
assistant messages.
"""
messages: list[dict[str, Any]] = [{"role": "system", "content": SYSTEM_PROMPT}]
for item in history:
role = item.get("role")
content = str(item.get("content") or "").strip()
if role not in {"user", "assistant"} or not content:
continue
if role == "assistant":
content = strip_thinking_blocks(content)
messages.append({"role": role, "content": content})
return messages
def clip_context(text: str, limit: int = 4_000) -> str:
"""Truncate text to a character limit with a note."""
if len(text) <= limit:
return text
return text[:limit] + f"\n... truncated {len(text) - limit} characters ..."
def iteration_context(execution_context: dict[str, Any] | None) -> str:
"""Build a context string from previous execution results.
This allows the model to reference prior code, stdout, and stderr
when the user asks to iterate or debug.
"""
if not execution_context or not execution_context.get("code"):
return ""
code = clip_context(str(execution_context.get("code") or ""), 6_000)
target = str(execution_context.get("target") or "code")
fence_lang = str(execution_context.get("fence_lang") or target)
status = str(execution_context.get("status") or "")
stdout = clip_context(str(execution_context.get("stdout") or ""), 2_000)
stderr = clip_context(str(execution_context.get("stderr") or ""), 2_000)
parts = [
"Previous generated code and run result are available for iteration.",
f"Previous target: {target}",
f"Previous status: {status}",
f"Previous code:\n```{fence_lang}\n{code}\n```",
]
if stdout:
parts.append(f"Previous stdout:\n{stdout}")
if stderr:
parts.append(f"Previous stderr / traceback:\n{stderr}")
parts.append(
"If the user asks to revise, debug, extend, or explain the prior code, use this context."
)
return "\n\n".join(parts)
def targeted_prompt(
prompt: str,
target_language: str,
target_framework: str = "",
execution_context: dict[str, Any] | None = None,
search_context: str = "",
) -> str:
"""Build the full user prompt with language, framework, search, and iteration context."""
iter_ctx = iteration_context(execution_context)
context_block = f"\n\n{iter_ctx}" if iter_ctx else ""
search_block = ""
if search_context:
search_block = (
f"\n\n{search_context}\n\n"
"Use the above search results to inform your code generation if relevant."
)
framework_hint = f" using {target_framework}" if target_framework else ""
gradio_hint = ""
if target_framework == "Gradio":
gradio_hint = (
"\n\nIMPORTANT: This is a Gradio app. Create a complete Python script that:\n"
"- Imports gradio as gr\n"
"- Defines the UI using gr.Interface() or gr.Blocks()\n"
"- Includes all processing logic inline\n"
"- Calls .launch(server_name='0.0.0.0', server_port=7860) at the end\n"
"- Uses only standard library + gradio + common packages (PIL, matplotlib, numpy)\n"
"- Make the UI clean, modern, and functional"
)
return (
f"Target: {target_language}{framework_hint}. Generate a complete, runnable application. "
"If the user asks for a web app, include all HTML/CSS/JS. "
"If they ask for a backend, include the server code and any API definitions. "
"For single-file apps, use a single code block. For multi-file projects, use the @@FILE: format. "
"Make the code complete, working, and well-structured."
f"{gradio_hint}"
f"{search_block}"
f"{context_block}\n\n"
f"User request:\n{prompt}"
)
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