Spaces:
Sleeping
Sleeping
File size: 37,844 Bytes
81cf53b |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 |
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "EGTI9yHm74B0"
},
"outputs": [],
"source": [
"%%capture\n",
"!pip install huggingface-hub hf-transfer langchain llama-cpp-python"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "ao6p6SSd5VvW"
},
"outputs": [],
"source": [
"%%capture\n",
"# !CMAKE_ARGS=\"-DLLAMA_CUBLAS=on\" FORCE_CMAKE=1 pip install llama-cpp-python"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"id": "AOmrozm5GoZZ"
},
"outputs": [],
"source": [
"# !wget https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF/resolve/main/llama-2-7b-chat.Q3_K_M.gguf"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "FoxgM851hI5F",
"outputId": "fcc7276e-3d87-4e8a-cd10-ff533074d12b"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"downloading https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF/resolve/main/llama-2-7b-chat.Q2_K.gguf to /root/.cache/huggingface/hub/tmp02ipqll0\n",
"llama-2-7b-chat.Q2_K.gguf: 100% 2.83G/2.83G [00:26<00:00, 107MB/s]\n",
"./llama-2-7b-chat.Q2_K.gguf\n"
]
}
],
"source": [
"import os\n",
"os.environ[\"HF_HUB_ENABLE_HF_TRANSFER\"] = \"1\"\n",
"\n",
"# !huggingface-cli download \\\n",
"# Deci/DeciLM-7B-instruct-GGUF \\\n",
"# decilm-7b-uniform-gqa-q8_0.gguf \\\n",
"# --local-dir . \\\n",
"# --local-dir-use-symlinks False\n",
"\n",
"!huggingface-cli download \\\n",
" TheBloke/Llama-2-7B-Chat-GGUF \\\n",
" llama-2-7b-chat.Q2_K.gguf \\\n",
" --local-dir . \\\n",
" --local-dir-use-symlinks False"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"id": "176a5LS68sBI"
},
"outputs": [],
"source": [
"from langchain.callbacks.manager import CallbackManager\n",
"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.llms import LlamaCpp"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"id": "E0nySsfAHmu_"
},
"outputs": [],
"source": [
"MODEL_PATH = \"llama-2-7b-chat.Q2_K.gguf\""
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"id": "r_rEfQFfBYOb"
},
"outputs": [],
"source": [
"template = \"\"\"Question: {question}\n",
"\n",
"Answer: Let's work this out in a step by step way to be sure we have the right answer.\"\"\"\n",
"\n",
"prompt = PromptTemplate.from_template(template)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"id": "VR2kLDqLBY1A"
},
"outputs": [],
"source": [
"# Callbacks support token-wise streaming\n",
"callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "L_KBhPNmBbCV",
"outputId": "ed5292d0-67e6-4b91-b8e0-418dd92d2572"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"llama_model_loader: loaded meta data with 19 key-value pairs and 291 tensors from llama-2-7b-chat.Q2_K.gguf (version GGUF V2)\n",
"llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.\n",
"llama_model_loader: - kv 0: general.architecture str = llama\n",
"llama_model_loader: - kv 1: general.name str = LLaMA v2\n",
"llama_model_loader: - kv 2: llama.context_length u32 = 4096\n",
"llama_model_loader: - kv 3: llama.embedding_length u32 = 4096\n",
"llama_model_loader: - kv 4: llama.block_count u32 = 32\n",
"llama_model_loader: - kv 5: llama.feed_forward_length u32 = 11008\n",
"llama_model_loader: - kv 6: llama.rope.dimension_count u32 = 128\n",
"llama_model_loader: - kv 7: llama.attention.head_count u32 = 32\n",
"llama_model_loader: - kv 8: llama.attention.head_count_kv u32 = 32\n",
"llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000001\n",
"llama_model_loader: - kv 10: general.file_type u32 = 10\n",
"llama_model_loader: - kv 11: tokenizer.ggml.model str = llama\n",
"llama_model_loader: - kv 12: tokenizer.ggml.tokens arr[str,32000] = [\"<unk>\", \"<s>\", \"</s>\", \"<0x00>\", \"<...\n",
"llama_model_loader: - kv 13: tokenizer.ggml.scores arr[f32,32000] = [0.000000, 0.000000, 0.000000, 0.0000...\n",
"llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,32000] = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...\n",
"llama_model_loader: - kv 15: tokenizer.ggml.bos_token_id u32 = 1\n",
"llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 2\n",
"llama_model_loader: - kv 17: tokenizer.ggml.unknown_token_id u32 = 0\n",
"llama_model_loader: - kv 18: general.quantization_version u32 = 2\n",
"llama_model_loader: - type f32: 65 tensors\n",
"llama_model_loader: - type q2_K: 65 tensors\n",
"llama_model_loader: - type q3_K: 160 tensors\n",
"llama_model_loader: - type q6_K: 1 tensors\n",
"llm_load_vocab: special tokens definition check successful ( 259/32000 ).\n",
"llm_load_print_meta: format = GGUF V2\n",
"llm_load_print_meta: arch = llama\n",
"llm_load_print_meta: vocab type = SPM\n",
"llm_load_print_meta: n_vocab = 32000\n",
"llm_load_print_meta: n_merges = 0\n",
"llm_load_print_meta: n_ctx_train = 4096\n",
"llm_load_print_meta: n_embd = 4096\n",
"llm_load_print_meta: n_head = 32\n",
"llm_load_print_meta: n_head_kv = 32\n",
"llm_load_print_meta: n_layer = 32\n",
"llm_load_print_meta: n_rot = 128\n",
"llm_load_print_meta: n_embd_head_k = 128\n",
"llm_load_print_meta: n_embd_head_v = 128\n",
"llm_load_print_meta: n_gqa = 1\n",
"llm_load_print_meta: n_embd_k_gqa = 4096\n",
"llm_load_print_meta: n_embd_v_gqa = 4096\n",
"llm_load_print_meta: f_norm_eps = 0.0e+00\n",
"llm_load_print_meta: f_norm_rms_eps = 1.0e-06\n",
"llm_load_print_meta: f_clamp_kqv = 0.0e+00\n",
"llm_load_print_meta: f_max_alibi_bias = 0.0e+00\n",
"llm_load_print_meta: n_ff = 11008\n",
"llm_load_print_meta: n_expert = 0\n",
"llm_load_print_meta: n_expert_used = 0\n",
"llm_load_print_meta: rope scaling = linear\n",
"llm_load_print_meta: freq_base_train = 10000.0\n",
"llm_load_print_meta: freq_scale_train = 1\n",
"llm_load_print_meta: n_yarn_orig_ctx = 4096\n",
"llm_load_print_meta: rope_finetuned = unknown\n",
"llm_load_print_meta: model type = 7B\n",
"llm_load_print_meta: model ftype = Q2_K - Medium\n",
"llm_load_print_meta: model params = 6.74 B\n",
"llm_load_print_meta: model size = 2.63 GiB (3.35 BPW) \n",
"llm_load_print_meta: general.name = LLaMA v2\n",
"llm_load_print_meta: BOS token = 1 '<s>'\n",
"llm_load_print_meta: EOS token = 2 '</s>'\n",
"llm_load_print_meta: UNK token = 0 '<unk>'\n",
"llm_load_print_meta: LF token = 13 '<0x0A>'\n",
"llm_load_tensors: ggml ctx size = 0.11 MiB\n",
"llm_load_tensors: CPU buffer size = 2694.32 MiB\n",
".................................................................................................\n",
"llama_new_context_with_model: n_ctx = 512\n",
"llama_new_context_with_model: freq_base = 10000.0\n",
"llama_new_context_with_model: freq_scale = 1\n",
"llama_kv_cache_init: CPU KV buffer size = 256.00 MiB\n",
"llama_new_context_with_model: KV self size = 256.00 MiB, K (f16): 128.00 MiB, V (f16): 128.00 MiB\n",
"llama_new_context_with_model: CPU input buffer size = 0.14 MiB\n",
"llama_new_context_with_model: CPU compute buffer size = 1.10 MiB\n",
"llama_new_context_with_model: graph splits (measure): 1\n",
"AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | \n",
"Model metadata: {'tokenizer.ggml.unknown_token_id': '0', 'tokenizer.ggml.eos_token_id': '2', 'general.architecture': 'llama', 'llama.context_length': '4096', 'general.name': 'LLaMA v2', 'llama.embedding_length': '4096', 'llama.feed_forward_length': '11008', 'llama.attention.layer_norm_rms_epsilon': '0.000001', 'llama.rope.dimension_count': '128', 'llama.attention.head_count': '32', 'tokenizer.ggml.bos_token_id': '1', 'llama.block_count': '32', 'llama.attention.head_count_kv': '32', 'general.quantization_version': '2', 'tokenizer.ggml.model': 'llama', 'general.file_type': '10'}\n"
]
}
],
"source": [
"# Make sure the model path is correct for your system!\n",
"llm = LlamaCpp(\n",
" model_path=MODEL_PATH,\n",
" temperature=0.75,\n",
" max_tokens=2000,\n",
" top_p=1,\n",
" callback_manager=callback_manager,\n",
" verbose=True, # Verbose is required to pass to the callback manager\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "crv_Wu52Bdz_",
"outputId": "4b45a176-4503-4bf7-8fb7-0bc949eed169"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Stephen Colbert:"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"ERROR:root:Internal Python error in the inspect module.\n",
"Below is the traceback from this internal error.\n",
"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3553, in run_code\n",
" exec(code_obj, self.user_global_ns, self.user_ns)\n",
" File \"<ipython-input-10-a402e682f208>\", line 4, in <cell line: 4>\n",
" llm.invoke(prompt)\n",
" File \"/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\", line 273, in invoke\n",
" self.generate_prompt(\n",
" File \"/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\", line 568, in generate_prompt\n",
" return self.generate(prompt_strings, stop=stop, callbacks=callbacks, **kwargs)\n",
" File \"/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\", line 741, in generate\n",
" output = self._generate_helper(\n",
" File \"/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\", line 605, in _generate_helper\n",
" raise e\n",
" File \"/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\", line 592, in _generate_helper\n",
" self._generate(\n",
" File \"/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\", line 1177, in _generate\n",
" self._call(prompt, stop=stop, run_manager=run_manager, **kwargs)\n",
" File \"/usr/local/lib/python3.10/dist-packages/langchain_community/llms/llamacpp.py\", line 288, in _call\n",
" for chunk in self._stream(\n",
" File \"/usr/local/lib/python3.10/dist-packages/langchain_community/llms/llamacpp.py\", line 341, in _stream\n",
" for part in result:\n",
" File \"/usr/local/lib/python3.10/dist-packages/llama_cpp/llama.py\", line 978, in _create_completion\n",
" for token in self.generate(\n",
" File \"/usr/local/lib/python3.10/dist-packages/llama_cpp/llama.py\", line 663, in generate\n",
" self.eval(tokens)\n",
" File \"/usr/local/lib/python3.10/dist-packages/llama_cpp/llama.py\", line 503, in eval\n",
" self._ctx.decode(self._batch)\n",
" File \"/usr/local/lib/python3.10/dist-packages/llama_cpp/_internals.py\", line 305, in decode\n",
" return_code = llama_cpp.llama_decode(\n",
" File \"/usr/local/lib/python3.10/dist-packages/llama_cpp/llama_cpp.py\", line 1636, in llama_decode\n",
" return _lib.llama_decode(ctx, batch)\n",
"KeyboardInterrupt\n",
"\n",
"During handling of the above exception, another exception occurred:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 2099, in showtraceback\n",
" stb = value._render_traceback_()\n",
"AttributeError: 'KeyboardInterrupt' object has no attribute '_render_traceback_'\n",
"\n",
"During handling of the above exception, another exception occurred:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 1101, in get_records\n",
" return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
" File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 248, in wrapped\n",
" return f(*args, **kwargs)\n",
" File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 281, in _fixed_getinnerframes\n",
" records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
" File \"/usr/lib/python3.10/inspect.py\", line 1662, in getinnerframes\n",
" frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
" File \"/usr/lib/python3.10/inspect.py\", line 1620, in getframeinfo\n",
" filename = getsourcefile(frame) or getfile(frame)\n",
" File \"/usr/lib/python3.10/inspect.py\", line 829, in getsourcefile\n",
" module = getmodule(object, filename)\n",
" File \"/usr/lib/python3.10/inspect.py\", line 878, in getmodule\n",
" os.path.realpath(f)] = module.__name__\n",
" File \"/usr/lib/python3.10/posixpath.py\", line 396, in realpath\n",
" path, ok = _joinrealpath(filename[:0], filename, strict, {})\n",
" File \"/usr/lib/python3.10/posixpath.py\", line 429, in _joinrealpath\n",
" newpath = join(path, name)\n",
" File \"/usr/lib/python3.10/posixpath.py\", line 71, in join\n",
" def join(a, *p):\n",
"KeyboardInterrupt\n"
]
},
{
"ename": "TypeError",
"evalue": "object of type 'NoneType' has no len()",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
" \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
"\u001b[0;32m<ipython-input-10-a402e682f208>\u001b[0m in \u001b[0;36m<cell line: 4>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 3\u001b[0m \"\"\"\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mllm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minvoke\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\u001b[0m in \u001b[0;36minvoke\u001b[0;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[1;32m 272\u001b[0m return (\n\u001b[0;32m--> 273\u001b[0;31m self.generate_prompt(\n\u001b[0m\u001b[1;32m 274\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_convert_input\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\u001b[0m in \u001b[0;36mgenerate_prompt\u001b[0;34m(self, prompts, stop, callbacks, **kwargs)\u001b[0m\n\u001b[1;32m 567\u001b[0m \u001b[0mprompt_strings\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_string\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mprompts\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 568\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompt_strings\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallbacks\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcallbacks\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 569\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self, prompts, stop, callbacks, tags, metadata, run_name, **kwargs)\u001b[0m\n\u001b[1;32m 740\u001b[0m ]\n\u001b[0;32m--> 741\u001b[0;31m output = self._generate_helper(\n\u001b[0m\u001b[1;32m 742\u001b[0m \u001b[0mprompts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_managers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbool\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_arg_supported\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\u001b[0m in \u001b[0;36m_generate_helper\u001b[0;34m(self, prompts, stop, run_managers, new_arg_supported, **kwargs)\u001b[0m\n\u001b[1;32m 604\u001b[0m \u001b[0mrun_manager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_llm_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mLLMResult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgenerations\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 605\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 606\u001b[0m \u001b[0mflattened_outputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mflatten\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\u001b[0m in \u001b[0;36m_generate_helper\u001b[0;34m(self, prompts, stop, run_managers, new_arg_supported, **kwargs)\u001b[0m\n\u001b[1;32m 591\u001b[0m output = (\n\u001b[0;32m--> 592\u001b[0;31m self._generate(\n\u001b[0m\u001b[1;32m 593\u001b[0m \u001b[0mprompts\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/llms.py\u001b[0m in \u001b[0;36m_generate\u001b[0;34m(self, prompts, stop, run_manager, **kwargs)\u001b[0m\n\u001b[1;32m 1176\u001b[0m text = (\n\u001b[0;32m-> 1177\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_manager\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrun_manager\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1178\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnew_arg_supported\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_community/llms/llamacpp.py\u001b[0m in \u001b[0;36m_call\u001b[0;34m(self, prompt, stop, run_manager, **kwargs)\u001b[0m\n\u001b[1;32m 287\u001b[0m \u001b[0mcombined_text_output\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 288\u001b[0;31m for chunk in self._stream(\n\u001b[0m\u001b[1;32m 289\u001b[0m \u001b[0mprompt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_community/llms/llamacpp.py\u001b[0m in \u001b[0;36m_stream\u001b[0;34m(self, prompt, stop, run_manager, **kwargs)\u001b[0m\n\u001b[1;32m 340\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclient\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 341\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mpart\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 342\u001b[0m \u001b[0mlogprobs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpart\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"choices\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"logprobs\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/llama_cpp/llama.py\u001b[0m in \u001b[0;36m_create_completion\u001b[0;34m(self, prompt, suffix, max_tokens, temperature, top_p, min_p, typical_p, logprobs, echo, stop, frequency_penalty, presence_penalty, repeat_penalty, top_k, stream, seed, tfs_z, mirostat_mode, mirostat_tau, mirostat_eta, model, stopping_criteria, logits_processor, grammar, logit_bias)\u001b[0m\n\u001b[1;32m 977\u001b[0m \u001b[0mmultibyte_fix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 978\u001b[0;31m for token in self.generate(\n\u001b[0m\u001b[1;32m 979\u001b[0m \u001b[0mprompt_tokens\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/llama_cpp/llama.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self, tokens, top_k, top_p, min_p, typical_p, temp, repeat_penalty, reset, frequency_penalty, presence_penalty, tfs_z, mirostat_mode, mirostat_tau, mirostat_eta, penalize_nl, logits_processor, stopping_criteria, grammar)\u001b[0m\n\u001b[1;32m 662\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 663\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtokens\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 664\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0msample_idx\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mn_tokens\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/llama_cpp/llama.py\u001b[0m in \u001b[0;36meval\u001b[0;34m(self, tokens)\u001b[0m\n\u001b[1;32m 502\u001b[0m )\n\u001b[0;32m--> 503\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_ctx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_batch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 504\u001b[0m \u001b[0;31m# Save tokens\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/llama_cpp/_internals.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m 304\u001b[0m \u001b[0;32massert\u001b[0m \u001b[0mbatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbatch\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 305\u001b[0;31m return_code = llama_cpp.llama_decode(\n\u001b[0m\u001b[1;32m 306\u001b[0m \u001b[0mctx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mctx\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/llama_cpp/llama_cpp.py\u001b[0m in \u001b[0;36mllama_decode\u001b[0;34m(ctx, batch)\u001b[0m\n\u001b[1;32m 1635\u001b[0m < 0 - error\"\"\"\n\u001b[0;32m-> 1636\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_lib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mllama_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mctx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1637\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyboardInterrupt\u001b[0m: ",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m 2098\u001b[0m \u001b[0;31m# in the engines. This should return a list of strings.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2099\u001b[0;31m \u001b[0mstb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_render_traceback_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2100\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mAttributeError\u001b[0m: 'KeyboardInterrupt' object has no attribute '_render_traceback_'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
" \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m 2099\u001b[0m \u001b[0mstb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_render_traceback_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2100\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2101\u001b[0;31m stb = self.InteractiveTB.structured_traceback(etype,\n\u001b[0m\u001b[1;32m 2102\u001b[0m value, tb, tb_offset=tb_offset)\n\u001b[1;32m 2103\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1365\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1366\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1367\u001b[0;31m return FormattedTB.structured_traceback(\n\u001b[0m\u001b[1;32m 1368\u001b[0m self, etype, value, tb, tb_offset, number_of_lines_of_context)\n\u001b[1;32m 1369\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1265\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mverbose_modes\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1266\u001b[0m \u001b[0;31m# Verbose modes need a full traceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1267\u001b[0;31m return VerboseTB.structured_traceback(\n\u001b[0m\u001b[1;32m 1268\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb_offset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumber_of_lines_of_context\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1269\u001b[0m )\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1122\u001b[0m \u001b[0;34m\"\"\"Return a nice text document describing the traceback.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1124\u001b[0;31m formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,\n\u001b[0m\u001b[1;32m 1125\u001b[0m tb_offset)\n\u001b[1;32m 1126\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mformat_exception_as_a_whole\u001b[0;34m(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m 1080\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1081\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1082\u001b[0;31m \u001b[0mlast_unique\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecursion_repeat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfind_recursion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_etype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1083\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1084\u001b[0m \u001b[0mframes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat_records\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecords\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlast_unique\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecursion_repeat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mfind_recursion\u001b[0;34m(etype, value, records)\u001b[0m\n\u001b[1;32m 380\u001b[0m \u001b[0;31m# first frame (from in to out) that looks different.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 381\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_recursion_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 382\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 383\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 384\u001b[0m \u001b[0;31m# Select filename, lineno, func_name to track frames with\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: object of type 'NoneType' has no len()"
]
}
],
"source": [
"prompt = \"\"\"\n",
"Question: A rap battle between Stephen Colbert and John Oliver\n",
"\"\"\"\n",
"llm.invoke(prompt)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Bdpj6esPBs4q"
},
"outputs": [],
"source": [
"llm_chain = LLMChain(prompt=prompt, llm=llm)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Ex8ZzlTKBtlm"
},
"outputs": [],
"source": [
"question = \"What NFL team won the Super Bowl in the year Justin Bieber was born?\"\n",
"llm_chain.run(question)"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
|